Structure of Unemployment and Structural Unemployment in … · 2017. 1. 18. · 6 Detection of the...

Structure of Unemploymentand Structural Unemploymentin Georgia

2016

Structure of Unemployment and Structural Unemployment in Georgia

2016

The study is implemented by Georgian Foundation for Strategic and International Studies(Rondeli Foundation) under the support of Friedrich-Ebert-Stiftung (FES).

Project coordinator, Team leader: Professor Merab Kakulia Senior researcher: Nodar Kapanadze Researchers: Vakhtang Lomjaria, Lali Kurkhuli

Editor: Professor Joseph Archvadze

The publication represents personal opinions of the authors.

The use of the materials published by Friedrich-Ebert-Stiftung (FES) for commercial purposes is inadmissible without the foundation’s consent.

© Friedrich-Ebert-Stiftung (FES), 2016

ISBN 978-9941-0-9431-6

Contents

1. Introduction ................................................................................................................. 51.1 Unemployment statistics in Georgia ...........................................................................................................51.2 Goal and objectives of the study .................................................................................................................61.3 Sources of information ...............................................................................................................................61.4 Research methodology ................................................................................................................................7

2. Structure of Unemployment ....................................................................................... 92.1 Assessment of aggregated level of unemployment .....................................................................................92.2 Consistence of structure of employment and unemployment by qualifi cation ......................................... 112.5 Dynamics of unemployment by qualifi cation ...........................................................................................152.4 Unemployment structure by duration .......................................................................................................172.5 Unemployment structure by achieved education level .............................................................................20

3. The Employment Structure ...................................................................................... 223.1 Sectoral structure of employment .............................................................................................................223.2 Sources for job generation .........................................................................................................................28

4. Structural Unemployment ........................................................................................ 314.1 Structural unemployment: methodological aspect .....................................................................................314.2 Long-term unemployment and de-qualifi cation as a manifestation of structural unemployment .............324.3 “Unsatisfi ed” workers or hidden structural unemployment .......................................................................344.4 Structural compatibility of labor market demand and supply ..................................................................384.5 Effectiveness of the educational system in the context of structural unemployment ................................45

5. Institutional Weaknesses of the Labor Market ...................................................... 51

6. Key Findings ............................................................................................................... 536.1 Empirical fi ndings ......................................................................................................................................536.2 Qualitative fi ndings ....................................................................................................................................54

7. Recommendations ...................................................................................................... 56

8. Scenarios for Development of the Labor Market ................................................... 58

9. Sources ........................................................................................................................ 62

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1. Introduction

1.1 Unemployment statistics in Georgia

In Georgia, the National Statistics Office of Georgia (Geostat) is responsible for production of labor statistics. The main source of information comes from the Integrated Household Survey (IHS) of Geor-gia.

In 1996-2001 the economic status of the population was assessed by just a small questionnaire which never allowed for deep analyses of the issue. In 2000-2001 the Integrated Household Survey was quali-tatively improved; following which, within the frame of the survey, a detailed study of employment and unemployment was introduced. For this purpose, an integrated research tool – “Shinda 05_1”1 is used; with the help of which each member of 15 years and older of the sampled household are interviewed.

The unemployment rate has been the subject of high interest and regular discussion in Georgian society throughout the last 20 years. Concerns are often voiced that the indicator is reduced artificially. However, going deeper into this issue, one can realise that even a reduced unemployment rate determined in accordance with ILO criteria, is not low at all, as is revealed below.

Despite this, the unemployment rate indicator defined by ILO criteria does not allow for complex assessment of this acute social and economic problem: it does not cover under-employment and hidden unemployment – vents widely distributed in the countries with transitional economies such as Georgia. The database of the IHS does offer the possibility for analyses of under-employment and hidden unem-ployment.

The database of integrated household survey also contains information regarding structure by quali-fication of unemployment, its differentiation by duration, sources for job creation and structural unem-ployment (Skills Gap), the regular processing of which is not normally carried out. Analyses of the data of different structural aspects of unemployment and structural unemployment provide the opportunity for significant conclusions to be made in order to improve the effectiveness of the employment policy and economic policy in general.

Chart N1

13%2% 4% 3% 3%

10%

73% 95% 92% 94% 93%87%

15%3% 4% 3% 4% 3%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1997 1998 1999 2000 2001 2002

Distribution of unemployed by registration

Registered unemployed Not registered unemployed

Status is not clear

Source: Geostat. Statistical Yearbook, 2004.

1 http://www.geostat.ge/cms/site_images/_files/georgian/kitxvarebi/shinda/Shinda05-1_2015_Geo.pdf

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Detection of the tendencies of the unemployment structure and structural unemployment much de-pends on the correct operation of the system for current registration of unemployed persons. Although a service for registration of unemployment existed in Georgia until 2004, it never operated properly- citi-zens could register there as unemployed but the number of job seekers covered by the system was insuf-ficient (see Chart N1).

The inefficiency of the system for current registration of unemployed persons was logical, since in fact registration as unemployed did not contain any prospective for employment, and unemployment benefits were too low. This clearly reflected a complex and unfortunate situation existing in the economy of Georgia at the turn of the century. No system for registration of vacancies was available, which made registration of unemployment irrational. Vacancies are still not registered and it is still impossible to obtain such information.

Deep analysis of the structure of unemployment is possible only in conditions of proper functioning of the system for current registration of unemployed people. Since such a system is unavailable in Geor-gia, we are limited with the assessments of sampling surveys, and must still depend on the databases of the Integrated Household Survey. Although, these are data of another registry and cannot function as the current registration system, on their basis are created particular time series of homogenous information, providing the opportunity for research of developed tendencies.

1.2 Goal and objectives of the study

The main goal of the present study is the research of structural aspects of unemployment and struc-tural unemployment in Georgia, which goes beyond the framework for assessment of the unemployment rate by ILO criteria and aims at the following:

Assessment of aggregated unemployment level and its structure. 1. Analyses of the structure of unemployment, including: 2.

By qualification,• By duration,• By achieved level of education.•

Identification of the structure of the sources for job generation. 3. Analyses of structural unemployment (Skills Gap), including:4.

Study of long-term unemployment and de-qualification;• Study of “unsatisfied” employees and hidden structural unemployment;• Study of structural consistence of the demand and supply of the labor market;• Analyses of the effectiveness of the education system, in the aspect of structural unemployment. •

Identification of institutional weaknesses of the labor market. 5. Scenarios for development of the labor market. 6.

1.3 Sources of information

In order to achieve the above-stated objectives, several sources were used in the study, of which the most important is the Integrated Household Survey.

IHS has been carried out continuously since 1996. Consequently, a pretty long-term time series was developed, providing broad opportunities for in-depth analyses of unemployment and employment. Pri-mary databases of the survey are accessible on the website of Geostat.2 The questions of the survey are also presented.3 Although the database provides a lot of information regarding the structural and systemic peculiarities of unemployment, this is still insufficient. Consequently, additional information is required in order to develop a full scale picture of the demand - supply of the labor market.

The report of the research of employers’ attitudes towards vocational education, ordered by the Min-istry of Education and Science of Georgia4 and carried out by the company ACT in 2015, was used for 2 http://www.geostat.ge/?action=meurneoba_archive&lang=geo3 http://www.geostat.ge/?action=page&p_id=697&lang=geo4 http://www.mes.gov.ge/content.php?id=5962&lang=geo

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analyses of the labor market. The Survey Report of Labour Market Demand Component conducted by the company BCG in 2015 under the order of the Ministry of Labor, Health and Social Affairs of Georgia was used as well.5

For the purpose of a more complete assessment of the current demand – supply condition on the labor market, systematization of the offers, provided in more or less institutionalized information sources of employment, and formation and analyses of the database were planned within the frame of the project.

The following were considered as such information sources: Newspaper “Sitkva da Saqme”, a weekly newspaper with the highest print run in Georgia. It is a.

the only source in print media in which job advertisements are published. Similar information is published in other newspapers, but their print run and coverage are limited, and the number of ad-vertisements low;

Web-resource - jobs.ge, a key electronic information source of employment. Web resource HR.ge, b. providing information on vacancies in public sector, can be considered as an information source of similar co-measurable scale; but due to the specific character of the study, the main focus was on the data of the relatively universal source - jobs.ge.

Within the frame of the project, 10 in depth interviews were carried out with large employers in dif-ferent sectors, based on the objectives of the study.

1.4 Research methodology

The level of institutionalization of the labor market is very low in Georgia. According to the latest data of Geostat, the share of hired employment in the economically active population stands at just 37.3 percent, almost half of which are employed in the public sector. As mentioned above, the quality of the current statistical recording of unemployment is also very low. The only information array complying with international standards is the database of the Integrated Household Survey. For the purposes of the present survey, additional processing of the mentioned database became essential, based on which versatile analy-ses of time series of 2009 – 2015 was carried out.

Analyses were conducted for the quantitative assessment of social layers such as under-employment and hidden employment which made the possible calculation of aggregated indicator of unemployment and identification of its dynamics and structure.

Based on additional analyses of the IHS database, the question: what could unemployed people offer potential employers? - was answered. With this, the professional and qualification structure of unemployed people, identified by ILO criteria, was studied. The survey questionnaire envisages indication of the basic profession of the respondent according to diplomas or other certificates. Consequently, the assumption was made that unemployed people seek jobs in accordance with their profession.

The Integrated Household Survey questionnaire allows the analysis of job seeking in different forms. Thus, the question regarding how an unemployed individual looks for work was answered. Whether job-seekers prefer hired employment or self-employment could also be determined with the help of the ques-tionnaire.

The extent to which the job seeking process is within an institutional framework, or distribution of institutional resources and social capital (relatives, friends) in this process, or the duration of job seeking and so on, could also be assessed based on the same source.

In the process of implementation of the given research project, the biggest challenge was quantitative assessment of the inconsistence of the demand for a labor force and structure by qualification of supply (Skills Gap), standard methodology for which is unavailable. According to information obtained on the ILO website, the concept of structural unemployment is limited by a detailed explanation of unemploy-ment of this type.6 Study of the examples of calculation of structural unemployment demonstrated that quantitative assessment of this event means a high level of institutionalization of the labor market when detailed information regarding appointment and dismissal of employees from companies is accumulated in one agency. 5 http://moh.gov.ge/files/2015/Failebi/29.12.15.pdf6 http://www.ilo.org/wcmsp5/groups/public/---dgreports/---stat/documents/publication/wcms_166604.pdf

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Quantitative assessment of single aspects of structural unemployment is possible according to the IHS data, which of course does not show the full picture. For example: the analyses of duration of un-employment give an impression about the extent of structural employment. In this regard, comparative analyses of actual professions and those by diploma are interesting, based on which the employment rate indicator according to qualification can be calculated, which, in context, is close to the structural unem-ployment indicator. Despite this, the indicators obtained as a result of additional analyses of the Integrated Household Survey cannot substitute the importance of the level of institutionalization of the labor market in the comprehensive assessment of structural unemployment.

The job seeking process is just partially institutionalized in Georgia, providing minimal opportunities for qualitative and quantitative analyses. In particular, vacancies offered are not classified. Thus, at the first stage, the systematization of information given in the advertisements published in “Sitkva da Saqme” and jobs.ge became essential. The question was answered based on the information provided in each ad-vertisement. Completed questionnaires were entered into the database with the help of which it is possible to determine the structure of the vacancies available on the labor market.

At the beginning, the intention was to generate a time series from both sources of information to cover the period 2009-2015. In the case of newspaper “Sitkva da Saqme”, this was possible: figures from 2009 to 2015 were collected, from which numbers published in May and late December of each year were se-lected. The database was formed based on these data and the above mentioned questionnaire. Regrettably, the administration of internet resource Jobs.ge was not similarly ready for cooperation, and did not give the researchers access to the archive of the site. Consequently, the analyses of the structure of vacancies were possible only for late May, 2016. Due to this, making quantitative assessments based on historical data was not possible.

Within the frame of the project, in depth interviews were also conducted with 10 large employers of different sectors. For this purpose, a special questionnaire was created. The scope of the institutional problem for finding potential employees and their professional consistence was assessed based on content analyses of said interviews.

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2. Structure of Unemployment

2.1 Assessment of aggregated level of unemployment

As mentioned above, the official unemployment rate indicator is based on ILO criteria according to which the unemployment rate in Georgia was decreasing in 2009 – 2015, particularly in 2014 – 2015.

A 12 percent unemployment rate means that 12 percent of the economically active population did not work for cash or in-kind income for even one hour during the seven days prior to the interview. It must be taken into consideration that the economically active population does not include those individuals who do not work (students, housewives and so on) or are not actively seeking work. The economic activeness indicator was 68 percent in 2015, i.e. 32 percent of the population was not economically active for various reasons.

Chart N2

15.2%16.0%

15.1% 15.0% 14.6%

12.4% 12.0%

27.7% 27.6%26.4% 26.2% 25.6%

22.1% 21.5%

6.1%7.2% 6.5% 7.0% 6.5%

5.4% 4.8%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

2009 2010 2011 2012 2013 2014 2015

Unemployment rate by ILO criteriaCountry total Urban Rural

Source: IHS database processed by the group of authors

As demonstrated by the above chart the difference between the unemployment rates in urban and ru-ral areas is great: in 2015, the unemployment rate in urban areas was almost 5 times more than that in rural areas. The low unemployment rate in rural areas is obviously a result of self-employment, which brings the rural unemployment rate to minimal values. In 2009 – 2015, unemployment decreased in both urban and rural areas; however, the tendency was relatively high in urban areas, especially in 2014 – 2015.

Although the unemployment rate calculated by ILO criteria is pretty informative, the picture of un-employment would never be complete without taking into consideration under-employment and hidden employment. IHS allows for analyses of both.

To assess under-employment and hidden employment in the present study, we decided to use the fol-lowing criteria, which are actively used in similar international studies:7

The worker shall be considered as under-employed if: 1. They performed more than one job during the seven days prior to the interview. This is mainly due •

to the fact that the income from one job is not enough and one is forced to take multiple jobs; They were forced to work part time during the seven days prior to the interview and were willing •

to work full time, being ready to start immediately if there was an opportunity.7 Presented criteria envisage the methodology recommended by ILO

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The worker shall be considered as hidden unemployed, if: 2. They worked full time during the seven days prior to the interview, but were not satisfied with the •

job; They were seeking other job;• In the event of finding a job, they were ready to change the job immediately. •

Using the mentioned criteria, it is possible to calculate the aggregated unemployment rate, which includes unemployed people identified by ILO criteria, under-employed and hidden unemployed workers. The dynamics of this indicator on a countrywide level and by urban rural areas are given below.

Chart N3

39.1%38.4% 37.2% 36.2% 35.7%

31.7%29.6%

26.7%28.3% 28.1%

29.5% 27.0%24.4%

23.1%

31.9% 32.6% 32.0% 32.3%30.7%

27.4%25.9%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

2009 2010 2011 2012 2013 2014 2015

Aggregated level of Unemployment

Country totalUrban Rural


It is clear that the aggregated unemployment indicators calculated by urban rural area are not that significantly different from those of the indicators calculated by ILO criteria. The main reason for this is self-employment in agriculture: quite a significant part of self-employed people are under-employed or hidden unemployed.

Aggregated indicators of unemployment, as well as unemployment rate indicators according to ILO criteria, show a decreasing tendency, but the reduction trend in this case is relatively linear compared to the unemployment rate trend according to ILO criteria.

43 percent of the aggregated level of unemployment consists of unemployment by ILO criteria, al-most one third – 32 percent under-employment, and 25 percent hidden unemployment. (See Chart N4)

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Chart N4

44% 44% 42% 42% 43% 41% 43%

29% 28% 29% 27% 27% 30%32%

28% 28% 30% 31% 30% 29% 25%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Structure of aggregated unemployment

Unemployment by ILO criteria Under-employment Hidden unemployment


It is interesting that in 2009-2015 the structure of aggregated unemployment level did not change substantially. The weight of under-employment rose slightly, while hidden unemployment reduces. The change in weight in the components of the aggregated unemployment rate falls within the frame of statisti-cal errors and is not substantial.

2.2 Consistence of structure of employment and unemployment by qualifi cation

In 2015, 38 percent of unemployed people identified by ILO criteria, according to certified profes-sion, were high qualification specialists; 17 percent of unemployed people were medium level specialists, and 4 percent of lower than medium qualification (the latter includes groups 4-9).8

The biggest group of unemployed people includes those who do not have a certified profession i.e. people without a profession.

In the groups aggregated according to the level of qualification (see the table below), distribution of unemployed people does not change significantly between 2009 and 2015. A relatively clear tendency is an insignificant increase in the number of individuals not having a profession, which is quite low. General changes are statistically insufficient.

In the groups aggregated by level of qualification, 31 percent are highly qualified specialists by di-ploma, 17 percent are mid level specialists, 8 percent are lower-than-mid level specialists, and 45 percent of employed individuals do not have a speciality. Among identified trends slight increase in the weight of the highly qualified specialists is remarkable. On the other hand, no other trend is characteristic to the distribution of the employed people in aggregated groups of professions. It is important to view the em-8 Distribution of employed and unemployed people in groups aggregated by profession was implemented on the basis of ISCO classificatory, which on the level of one digit codes includes 9 main groups: Group 1. Leadership of all levels of government and governance bodies, including the heads of agencies, organizations and enterprises; Group 2. Highly qualified specialists; Group 3. Mid-level specialists; Group 4. Office workers;Group 5. Services and sales workers;Group 6. Qualified agricultural, forestry, hunting and fishery workers; Group 7. Qualified workers in industrial enterprises, artistic handicrafts, construction, transport, communications, geology and mineral exploration sectors; Group 8. Plant and machine operators, machinists, assemblers and metal craftsmen; Group 9. Non-qualified workers

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ployment structure without rural self-employment, since this is such a large and amorphous group that it covers the tendencies ongoing in other sectors.

Without rural self-employment, 50 percent of total employment included highly qualified specialists in 2015, 16 percent – mid level specialists, and 9 percent lower-than-mid level specialists. Discluding rural self-employment, 25 percent of employed people do not have a profession.

Table N1: Distribution of employed and unemployed people in aggregated groups of professions (Percent)

2009 2010 2011 2012 2013 2014 2015

Distribution of unemployed in aggregated groups of certified professions

High level specialists 37 39 41 39 40 39 38

Mid - level specialists 18 18 17 18 15 15 17

Rest of specialists 8 7 5 5 7 5 4

Without profession 37 36 37 38 39 41 41

Total 100 100 100 100 100 100 100

Distribution of employed in aggregated groups of certified professions





Total 100 100 100 100 100 100 100

Distribution of employed in aggregated groups of certified professions(without agro self-employment)





Total 100 100 100 100 100 100 100Source: IHS database processed by the group of authors

The employment structure without rural employment varies significantly from the total employment structure (see Table N1), which is reflected in a substantial decrease in the number of people not having a profession and an increase in the number of high level specialists. The decrease of specialists with mid and low level are also distinguished among the identified trends.

For purpose of comparison of the structures of employed and unemployed people by the level of qualification, a method of correlation analyses is used in the survey. The correlation coefficient quite pre-cisely indicates the degree and direction of similarity of the structures. Factor analyses are recommended for deeper analyses.

As demonstrated by comparative analyses of the aggregated groups, distribution of unemployed peo-ple in said groups of certified professions is similar to the structure of total distribution of employed peo-ple in the same groups. Correlation coefficient equals almost -1, which means that both structures are in fact identical.

Without rural self-employment, the structure of employed people is less identical with a correlation coefficient of - 0.9091.

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Chart N5

0.95670.9610

0.9454

0.96120.9663

0.9738

0.9852

0.9246 0.92070.9299 0.9272

0.92170.9130 0.9091

0.860

0.880

0.900

0.920

0.940

0.960

0.980

1.000

2009 2010 2011 2012 2013 2014 2015

Correlation of the structure of unemployed by certified professions with thestructure of employed by certified professions on one digit ISCO codes level

With total employment structure With employment structure without agro self-employment


The correlation coefficient of structures of total employment and unemployment was characterized by a clear increasing trend in 2009 – 2015, while the non-agricultural employment and unemployment structure correlation coefficient saw a decreasing trend. The unemployment structure is the same in both cases. Thus, the change is preconditioned by the difference between the employment structures, which is increasing, as shown by the trend of correlation coefficients. The main reason for the difference is the indicator of the number of individuals not having a profession, which is a significant component of rural self-employment.

Thus, rural self-employment is an amorphous large field with low effectiveness which impacts on the absorption of the labor force without profession and improves the statistical picture of employment. This became clear while comparing the same differences between the urban and rural unemployment indicators developed by ILO criteria and the same differences in aggregated unemployment indicators.

Consequently, an essential precondition for systemic improvement of the employment structure is the introduction of a special education program for groups of individuals not having a profession.

The correlation of the distribution of employment and unemployment by qualification level in groups aggregated on the level of one digit ISCO codes, leading to less homogeneity of identified groups, was discussed above.

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Employment and unemployment structure viewed on the level of two digit ISCO codes9 identifies relatively more homogeneous groups. Thus, the correlation degree in this area is more telling than in the case of aggregated groups.

Chart N6

0.9651 0.9673

0.9590

0.9709 0.9719 0.9717

0.9813

0.9383

0.93060.9360 0.9356 0.9381

0.9347 0.9366

0.9

0.91

0.92

0.93

0.94

0.95

0.96

0.97

0.98

0.99

2009 2010 2011 2012 2013 2014 2015

Correlation of the structure of employed by certified professionswith the structure of unemployed by certified professions on two digit ISCO codes level

Including agro self-employment Without agro self-employment


According to two digit ISCO codes, structure by qualification of employment and unemployment is also identical: the correlation coefficient equals almost 1, i.e. employment and unemployment structures are similar in this case also. In 2009-2015, the correlation coefficient displayed an increasing trend, i.e. the employment and unemployment structures became more and more alike. 9 The list of two digit ISCO codes: 11 – Leadership (representatives) of the government and governance bodies;12 – Managerial staff of agencies, organizations, enterprises and their structural subdivision; 13 – Managerial staff of small agencies, organizations and enterprises;21 – Specialists in natural and engineering science sectors;22 – Biology and agricultural science and health care sector specialists; 23 – Education sector specialists;24 – Other highly qualified specialists; 31 – Mid level specialists in physical and technical sciences; 32 – Mid level specialists in natural science and health care sector and support stuff; 33 – Mid level specialists in education sector;34 – Mid level specialists in financial, administrative and social fields;41 – Workers preparing and processing information;42 – Service workers;51 – Individual service and property protective services workers;52 – Salespersons, demonstrators and models;53 – Utility workers;54 – Film and TV workers;55 – Advertising - decoration and restoration workers;61 – Market-oriented qualified agricultural, forestry, hunting, fishing and fishery workers;62 – Qualified agricultural, forestry, hunting, fishing and fishery workers;71 – Extraction and construction sectors workers;72 – Metal processing industry, machinery and associate trades workers;73 – Precision instruments and devices manufacturing, printing and related trades workers; 74 – Other qualified workers of manufacturing and related professions;75 – Transport and communication workers; 76 – Geology and mining professions; 81 – Stationary plant operators and machinists; 82 – Metalworking and mineral raw material processing machine operators and machinists; 83 – Moving apparatus drivers, operators and machinists; 91 – Unqualified workers in trade and services sectors;92– Unqualified workers in agriculture, forestry, hunting, fishing and fishery;93– Unqualified workers in manufacturing, construction, transport, communication, geology and mineral exploration;94 – Unqualified workers in all other fields.

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Without agriculture self-employment, the correlation coefficient, despite a decrease, is still quite high - 0.9366. The trend of this indicator in fact was immovable during the research period.

Chart N7

0.9648 0.9637

0.9559

0.9655

0.9532

0.9394

0.9677

0.9711

0.99060.9865

0.9810

0.9881

0.96980.9756

0.91

0.92

0.93

0.94

0.95

0.96

0.97

0.98

0.99

1.00

2009 2010 2011 2012 2013 2014 2015

Correlation of the structure of employed by certified professions withthe structure of unemployed by certified professions on two digit ISCO codes level

excluding individuals not having professions



If we view the structure excluding people not having a profession (see Chart N7), the structures of employment by certified professions and of unemployment are still identical, but there is one not ever so large but important difference: excluding people not having a profession, the structures of employment and unemployment according to ISCO two digit codes correlate less than when not taking into considera-tion rural self-employment. Otherwise, the factor of rural self-employment in this case reduces correla-tion, which is due to the fact that the main shelter for those not having a profession is self-employment in agriculture.

2.5 Dynamics of unemployment by qualifi cation

According to ILO criteria, in 2009-2015 the unemployment rate in the 2nd group of ISCO profes-sions, i.e. among highly qualified specialists, was higher than the average unemployment rate, despite pretty solid decreasing trends.

The unemployment rate in this group at 20.8 percent exceeded the average unemployment rate in 2015. As demonstrated by the Integrated Household Survey, this category of the professionals conveys a high risk of unemployment. The unemployment rate is lower than average in all other groups.

The unemployment rate is slightly lower than average among the professionals of mid-level qualifica-tion, and even demonstrates a decreasing trend.

The two times lower-than-average unemployment rate among low qualified professionals deserves special attention. This indicator was consistently lower than average in 2009 – 2015, and went even lower during the last three years.

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Chart N8

19.3%20.4% 20.5%

19.5%18.6%

15.8%

14.4%

16.4%

15.2% 13.7% 14.3%

12.0%

10.7%11.7%12.8% 12.8%

9.9%10.4%

12.2%

7.8% 6.5%

12.5%13.7%

12.7% 13.0%13.1%

11.4%11.2%

15.2%

16.0%15.0% 15.0% 14.6%

12.4%12.0%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

2009 2010 2011 2012 2013 2014 2015

Unemployment rate according to ILO criteria in the groups of certified professions

Group 2 Group 3 Group 4-9 Not having profession Total


The unemployment rate, according to ILO criteria, in the group of not having a profession is 6.2 percent lower than the average unemployment rate. The main pre-requisite for this is mass employment in agriculture. It is also noteworthy that the unemployment rate in the given group was lower than aver-age throughout the study period, however, this difference was not as large as in the case of low qualified professionals.

Chart N9

27.3% 28.0%

36.5%29.8% 28.0% 27.7%

20.8%

8.0%

-4.7%-9.1%

-5.0%

-17.4%

-13.3%

-2.3%

-15.8%-19.5%

-34.4%-30.9%

-16.0%

-36.8%

-45.7%

-17.5%-14.1% -15.3% -13.4%

-9.9%-7.4% -6.2%

-50.0%

-40.0%

-30.0%

-20.0%

-10.0%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

2009 2010 2011 2012 2013 2014 2015

Difference between the unemployment rates by ILO criteria in the groupsof certified professions and total unemployment rate

Group 2 Group 3 Group 4-9 Not having profession


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The above-mentioned demonstrates that the majority of jobs generated on the labor market do not require high qualification.

As for rural self-employment, it may require quite high qualification, but in Georgia’s case it is still based on traditions. A person of working age living in Georgia might not have a winemaker’s certificate, but planting a vineyard and winemaking is part of his/her life, transferred from generation to generation. The same could be said, for example, about a Tushetian shepherd lacking a cheese maker’s certificate (which means quite high qualification), however, he is still a high-skilled professional, with experience accumulated by generations, but uncertified.

2.4 Unemployment structure by duration

One of the key aspects of the assessment of unemployment is analyses of duration of unemployment. The grounds for this are provided by certain important aspects, of which two are most important:

Long-term unemployment results in de-qualification; 1. Highly qualified unemployed professionals might be more vulnerable to long-term unemployment, 2. since finding a job respective to their qualification is relatively difficult.

As demonstrated by the data of the IHS, the weight of unemployment up to 1 month, and 1-3 months unemployed by ILO criteria, is stable – around 6-8 percent during the research period and not showing any clear trend.

Unemployment from 3 to 12 months made up 18 percent of total unemployment in 2015. The weight of unemployment of this term had a growing tendency in 2009 – 2015.

From the unemployment structure by duration, most distinguished are an increase of the number of unemployed over three years and more, and the decrease of those unemployed lacking work experience.

The number of unemployed, who have never worked despite a decreasing tendency, was still on the 25 percent mark in 2015, i.e. 25 percent of those unemployed by ILO criteria have never worked. This is a pretty high indicator.

Chart N10

4% 4% 4% 5% 4% 5% 6%9% 9% 10% 9% 8% 9% 8%

13% 14% 14% 16% 16% 16% 18%

13% 11% 10% 10% 9% 11% 11%6% 7% 6% 7% 6% 5% 5%

24% 26% 24% 26% 27% 27% 27%

31% 30% 31% 28% 29% 27% 25%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Distribution of unemployed by ILO criteria by duration of unemployment

Up to 1 month From1 to 3 months From 3 to 12 months

From 1 to 2 years From 2 to 3 years More than 3 years

Never worked


Age can be considered as one of possible reasons for the high number of individuals lacking working experience. The working age starts at 15 and even if the ILO criteria excludes students from unemployed people (59.6 percent of the population under 25 years old do not belong to an economically active popula-

18

tion, while the unemployment rate is 30.8 percent in the economically active population of this age, i.e. 2.5 times higher than the average unemployment rate), there is still a high chance that an individual employed by ILO criteria has no working experience due to age.

Taking into consideration the age factors, the unemployment duration structure among the popula-tion older than 25 is informative. Not having working experience is the factor of different grades- for the unemployed over-25s, than those 25 or younger.

The structure of unemployed over-25s is similar to the distribution of total unemployed population, however the differences between the proportions still exist and they are substantial. The number of indi-viduals not having working experience is 13 percent, which is almost half the indicator of total unemploy-ment distribution.

The weight of unemployed for more than three years is 33 percent among the unemployed over-25s years old, which is substantially more than the similar indicator of total unemployment distribution.

Thus, it can be categorically stated that the probability of long-term unemployment is being increased in parallel with getting older.

Chart N11

4% 5% 4% 5% 5% 5% 7%11% 10% 12% 10% 9% 10% 9%

15% 16% 16% 17% 19% 16% 20%

14% 12% 11% 11% 10% 13%12%

7% 8% 8% 8% 8% 6% 6%

30% 33% 31% 32% 35% 34% 33%

19% 17% 18% 16% 15% 15% 13%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Distribution of unemployed by ILO criteria older than 25 years old by duration of unemployment

Up to 1 month From1 to 3 months From 3 to 12 months

From 1 to 2 years From 2 to 3 years More than 3 years

Never worked


With the regard to the duration, unemployment up to 1 year can be viewed as short term unemploy-ment, while unemployment which continues for more than 1 year can be considered long-term unemploy-ment, which goes beyond the frictional unemployment, contains substantial threat of de-qualification and in fact goes to the dimension of structural unemployment.

Aggregation in big groups is preconditioned by substantially low reliability of assessment in small groups compared with aggregated groups. Further, homogeneous groups are developed by such aggrega-tion.

Individuals unemployed up to 1 year make up 32 percent of the total unemployed, while those un-employed for more than 1 year make up 43 percent. As we already mentioned, 25 percent of those unem-ployed have never worked.

19

Chart N12

26% 27% 29% 30% 29% 30% 32%

43% 43% 40% 42% 42% 43% 43%

31% 30% 31% 28% 29% 27% 25%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Distribution of unemployed by ILO criteria in aggregated groups by duration of unemployment

Unemployed up to 1 year Unemployed more than 1 year Never worked


Due to the above-mentioned distributions, we considered as long-term unemployed those individuals who met the following criteria:

Stated that they have been unemployed for more than 1 year; 1. Unemployed over 25 years old who have never worked. 2.

The latter assumption is preconditioned by the fact that not having any work experience due to lack of education is more or less explainable at a young age, but this argument loses strength with age.

Chart N13

45% 45% 49% 47% 48% 47% 48%

55% 55% 51% 53% 52% 53% 52%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Distribution of unemployed older than 25 years old by duration of unemployment

Short term unemployed Long-term unemployed


20

According to the calculations made on the basis of such assumptions, 48 percent of unemployed in-dividuals are short term unemployed, while 52 percent are long-term. The distribution of unemployment by duration saw no substantial change in 2009 – 2015. A slight decrease in long-term unemployment is identified which does not indicate substantial changes.

2.5 Unemployment structure by achieved education level

The Integrated Household Survey (IHS) allows for the calculation of various indicators according to achieved education level. For this purpose, an 11- step system for coding the achieved level of education is used. Due to the fact that data array broken down in 11 groups cannot ensure the generation of reliable assessments, it is reasonable to view each group in aggregated groups. The groups were aggregated ac-cording to the content and not mechanically, merged into four basic blocks:

The subjects with lower than secondary education included those whose achieved level of education 1. complied with the following code:

Illiterate;• Does not have primary education but can read and write; • Primary level of education;• General education, basic level.•

The subjects with secondary education included those whose achieved level of education complied 2. with the following code:

Full secondary education (secondary school). • The subjects with vocational education included those whose achieved level of education complied 3. with the following code:

Handicraft education certificate (diploma of primary vocational education); • Vocational education (secondary vocational) diploma. •

The subjects with high education included those whose achieved level of education complied with 4. the following code:

Diploma of high vocational education or equivalent education program; • Diploma of bachelor or professional health worker/veterinary or equivalent education program; • Diploma of master /graduate residency or equivalent high education program; • PhD or equivalent degree. •

The analyses demonstrated (see Chart N14), that 6 percent of the economically active population had lower than medium education; 41 percent – secondary education; 22 percent – secondary vocational, and 31 percent – higher education. In fact, the distribution saw no change in 2009- 2015, though an exception was seen in 2010 due to technical rather than content reasons10.

Unemployment rate by ILO criteria normally is higher among economically active people with high education, than average unemployment rate. It is to be mentioned that these two indicators manifested decreasing trend in the research period; special attention requires the fact that the trend of decreasing unemployment rate among the individuals with high education is stronger, in 2009 – 2015 it gradually reached average unemployment rate. Positive decreasing trend became especially stronger in 2014 – 2015. In all other groups of education level, the unemployment rate is low than average indicator. The group of individuals with lower than secondary education shall be distinguished especially, since the unemploy-ment rate is the lowest here.

10 The 7-step system for coding the achieved level of education was used in 2009, which is aggregated in the above-mentioned 4 groups. The coding system was changed in 2010. The problems associated with the transfer to a new coding system had an impact on the distribution of 2010. Further, the change was made between the 2nd and 3rd quarterly surveys and aggregation of the base of transition period appeared to be quite complex. Thus, the distribution of 2010 is somehow out of context.

21

Chart N14

9%17%

8% 8% 7% 7% 6%

40%32%

39% 39% 39% 40% 41%

21%26%

22% 23% 23% 23% 22%

30% 25%31% 30% 31% 31% 31%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Distribution of economically active population by achieved education level

Lower than secondary education Secondary educationVocational educaiton High education


In general, the trend of approximation of unemployment indicators in groups of different educational level are especially distinguished of the trends of 2009-2015: according to the 2015 data, the difference between the unemployment rates is not as substantial as in 2009 or 2011.

22

3. The Employment Structure

3.1 Sectoral structure of employment

The structure of employment by sectors outlines the balance between demand and supply on thee labor market. This is a result which covers all episodic, structural and systemic problems.

The employment structure in Georgia is quite specific (see Chart N15). Almost half of total employ-ment, 48.4 percent, falls on agriculture. The indicator of the weight of agriculture demonstrated a decreas-ing trend in 2009-2015 and for first time during the last 25 years went below 50 percent. This is undoubt-edly a positive sign, especially taking into consideration that the share of agriculture in the GDP was steadily decreasing and just in the last two years increasing. This trend gains especially positive meaning against the background of slight but still increase of the employment rate, which means that the number of employed in other sectors got increased. The weight of agriculture in total employment is so big that small percent decrease of self-employment does change substantially general level of effectiveness of the employment, but the decrease of agricultural self – employment is clearly positive event.

The next weighty component in the structure of employment is trade and consumer services, with major part of trade. The indicator of the weight of this sector was stably around 10 percent during whole research period and no clear trend was identified here. The same could be said about one more significant component of the employment structure – education sector.

Due to Georgian specifics of the employment structure, its review is reasonable without self -employ-ment, since its weight is so high that levels the processes and trends ongoing in all other sectors (see Chart N 16).

Exclusion of rural self -employment makes more visible the weights of other sectors. Despite of this the weight of the employed in mining and manufacturing, i.e. in real sector of economy, is very low. In 2009 – 2015 this indicator was near 11 percent.

In general, the structure of employment without agricultural self- employment was not substantially changed in the research period. This is not surprising, since such changes need decades in conditions of gravity flow, however in the event of development and implementation of effective industrial policy sig-nificant change of labor market structure is possible even during 3-4 years.

As the data provided on the charts N 15 and N 16 confirm, detailed sectoral distribution is less in-formative. The distribution in bigger groups – real sector and service sector, could be more important. Be-sides, it would be useful to take into consideration the sectoral specifics of the employment in Georgia and out of 16 viewed sectors identify 3 basic groups, significantly different form one another from economic point of view (see Chart N 17):

Agrarian sector, which includes the individuals employed in agriculture, forestry and fishery sectors. 1. In case of Georgia their absolute majority – more than 95 percent – are self-employed. Obviously, this is also real sector of economy, but in its content the mentioned form of employment has rather social meaning than economic. Due to that, we considered unreasonable the inclusion of agriculture in real sector of economy for purposes of our study; Real sector, which includes the individuals employed in mining industry, manufacturing, construc-2. tion and electricity, gas and water supply sectors; Service sector, which includes the representatives of other sectors, not producing natural – material 3. products.

23

Chart N15

53.8 52.3 52.4 52.0 51.2 50.4 48.4

0.5 0.7 0.8 0.8 0.8 0.9 1.2

4.5 4.8 4.7 4.5 4.8 4.6 4.7

1.1 1.2 1.3 1.2 1.3 1.0 0.9

3.6 3.4 3.7 3.6 3.4 3.9 3.9

9.9 9.7 9.7 10.1 10.1 9.7 10.5

1.1 1.2 1.1 1.3 1.4 1.1 1.5

4.84 4.36 3.86 4.29 4.67 5.27 4.95

1.0 1.2 1.0 1.1 1.6 1.6 1.81.8 1.6 1.6 1.5 1.7 1.8 2.0

4.0 4.3 4.7 4.7 4.8 4.8 5.7

7.6 7.7 7.5 7.0 7.8 8.2 7.6

2.66 3.35 3.07 2.97 2.87 3.06 3.142.4 2.9 3.1 3.4 2.6 2.8 3.21.1 1.1 1.3 1.3 0.8 0.7 0.60.1 0.1 0.1 0.2 0.1 0.1 0.1

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Distribution of employed by the sectors of employment including agro self-employment Agriculture Mining Processing industry Electrisity, gas and water supply Construction Trade and services Hotels and restaurants Transport and communicationOperations with real estate Financial intermediation Public administration EducationHealthcare Other services Hiring in households Exterritorial organizations


Chart N16

2.6 3.0 2.8 2.9 2.8 2.3 3.01.0 1.4 1.7 1.7 1.5 1.8 2.29.6 9.7 9.5 9.1 9.5 9.1 8.82.4 2.5 2.6 2.4 2.7 2.0 1.77.6 6.8 7.6 7.4 6.8 7.7 7.3

20.9 19.8 19.7 20.5 20.1 19.1 19.7

2.2 2.5 2.3 2.5 2.8 2.2 2.8

10.2 8.9 7.9 8.7 9.3 10.4 9.3

2.2 2.5 2.1 2.2 3.2 3.1 3.33.9 3.3 3.3 3.0 3.4 3.6 3.8

8.5 8.7 9.7 9.5 9.5 9.5 10.8

16.0 15.6 15.3 14.215.6 16.1 14.3

5.6 6.8 6.3 6.05.7 6.0 5.9

5.1 6.0 6.4 6.85.2 5.6 5.9

2.2 2.2 2.7 2.7 1.7 1.3 1.10.2 0.2 0.3 0.3 0.2 0.1 0.1

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Distribution of employed by the sectors of employment excluding agro self-employment Agriculture Mining Processing industry Electrisity, gas and water supplyConstruction Trade and services Hotels and restaurants Transport and communicationOperations with real estate Financial intermediation Public administration EducationHealthcare Other services Hiring in households Exterritorial organizations


We have already mentioned about amorphous high weight of employment in agrarian sector. This is key problem of Georgian economy; in this case the proportions of employment in real sector of economy and service field are more important.

24

Chart N17

53.8% 52.3% 52.4% 52.0% 51.2% 50.4% 48.4%

9.7% 10.1% 10.5% 10.2% 10.3% 10.5% 10.6%

36.5% 37.6% 37.2% 37.8% 38.5% 39.1% 41.0%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Distribution of employed in aggregated employement sectorsAgrarian sector Real sector Service sector


According to the data of Integrated Household Survey, the weight of employment in real sector of economy is 10.6 percent of total employment and this indicator remained unchangeable during 2009 – 2015.

The weight of employment in service sector was 41.0 percent in 2015 and had increasing tendency in 2009 – 2015.

It could be said to summarize, that positive movements developed in employment structure during last 6 years, reflected in the decrease of the weight of agrarian sector, basically was preconditioned by the increase of the weight of employment in the service sector. The mentioned positive in fact did not touch real sector of economy, the weight of which is unchangeable. The study of employment by professions in accordance with ISCO classificatory is important for the study of structural aspects of unemployment.

The biggest group of the structure of employment by professions is N 6, which includes skilled workers engaged in agriculture, forestry, hunting and fishery. This is the army of people self-employed in agriculture, who compiled 46, 7 percent of employed in 2015. It is to be mentioned that the weight of this group in 2009-2015 is distinguished by obviously positive, decreasing trend.

25

Chart N18

3.0% 3.1% 2.9% 2.9% 2.4% 2.0% 2.0%3.4% 3.4% 3.8% 3.9% 3.7% 3.6% 4.1%

11.8% 11.4% 11.1% 10.9% 11.1% 12.2% 11.8%

6.2% 7.3% 6.8% 6.8% 7.7% 7.8% 7.6%1.2% 1.5% 1.2% 1.8% 1.4% 1.5% 1.8%8.7% 9.6% 9.8% 8.9% 9.6% 9.4% 10.1%

52.2% 50.4% 50.7% 50.3% 49.7% 49.1% 46.7%

4.8% 4.2% 4.2% 4.5% 4.6% 4.6% 5.1%4.0% 4.0% 3.8% 4.3% 4.5% 5.0% 5.0%4.9% 5.1% 5.6% 5.7% 5.2% 4.9% 5.9%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Distribution of employed by professions including agro self-employment

NA Group 1 Group 2 Group 3 Group 4

Group 5 Group 6 Group 7 Group 8 Group 9


Distribution of the employed in basic sectors of employment to the groups by the level of qualifica-tion is crucial.

Chart N19

10% 10% 9% 10% 10% 10% 10%

16% 18% 18% 19% 19% 18% 18%

8% 9% 8% 7% 8% 7% 6%

67% 64% 66% 65% 63% 64% 66%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Distribution of employed in agriculture by certified professions



The individuals not having profession have advantage in distribution of employed in agriculture on these grounds: in 2015 their weight compiled 66 percent of employed in agriculture. This indicator was almost unchangeable in the research period.

26

The share of High level professionals employed in agriculture is stable – 10 percent, while of me-dium qualification specialists – 18 percent. Thus, pretty complex conditions for systemic change of the structure of employment are outlined, since ready for decrease of asymmetrically high weight of agrarian employment is ready just 34 percent of the individuals engaged in this field, and 66 percent is not ready for transition from this sector to another and the change of employment structure might require long-term, even decades without large scale vocational education.

31 percent of employed in industry and construction sectors are highly qualified professionals, while 36 percent do not have a profession. The weight of specialists with medium and high qualification shows a decreasing trend, while the weight of those not having a profession is increasing. The latter is very hard to explain, though in general weak but clearly negative trends of de-qualification of employment in this field can be observed.

Chart N20

36% 37% 38% 35% 33% 32% 31%

16% 18% 20% 20%19% 19% 16%

17% 15%14%

14%14% 14% 16%

30% 30% 28% 31% 35% 36% 36%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Distribution of employed in manufacturing and construction by certified professions



37 percent of those employed in trade and household services are highly qualified professionals by diploma. Almost the same number, 36 percent, do not have professions. 19 percent are mid-level special-ists by diploma. The weight indicators for the highly qualified specialists and those not having a profession show a weakly expressed increasing trend, while the number of mid-level specialists is decreasing.

27

Chart N21

32% 36% 33% 34% 38% 37% 37%

22%26%

25% 26% 21% 20% 19%

9%

8%8% 7% 8% 7% 8%

37%30% 33% 33% 34% 36% 36%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Distribution of employed in trade and household services by certified professions



Most interesting is the distribution by qualification of those employed in the education and healthcare sectors. The majority of people employed in these sectors are highly qualified professionals and the weight manifests a positive trend of increase. Further, the weight of mid-level specialists, which showed a de-creasing trend, is low. In the education sector, such trend can be assessed as positive, but in the healthcare sector it indicates an unfavorable condition.

Chart N22

70% 67% 70% 71% 73% 73% 74%

20% 23% 22% 20% 18% 18% 17%

2% 2% 2% 2% 2% 2% 2%8% 7% 7% 7% 7% 7% 8%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Distribution of employed in education and healthcare sectors by certified professions



28

Chart N23

52% 54% 54% 54% 53% 51% 54%

14% 16% 16% 14% 16% 15% 14%

14%12% 11% 11% 11% 12% 10%

20% 18% 19% 21% 20% 22% 21%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Distribution of employed in public administration, transport, communication, hotels and other service sectors by certified professions



The majority of those employed in a diverse group such as public governance agencies, transport, hotels and other services, is highly qualified professional (see Chart N23). An individual review of these groups does not give reliable assessments; however, the weight of highly qualified professionals in this amorphous group was the highest in 2015 compared with previous years, which could be considered as a sign of the beginning of a positive trend.

3.2 Sources for job generation

The distribution of jobs by the source of their generation is crucial for the study of the demand of the labor market. In this regard, we identified from the database of the Integrated Household Survey of four types of jobs:

Jobs created by the state – which include those employed in public institutions and governmental 1. organizations; Jobs created by the private sector, which include those employed in private enterprises and organiza-2. tions and entrepreneurs with hired employees; Jobs created based on own skills, which include non-agricultural self-employed who were employed 3. due to their own skills. Those are individual entrepreneurs, self-employed thanks to their profes-sional knowledge; Spontaneously created jobs, which include self-employed in agriculture, small traders, taxi drivers 4. and so on which does not require high qualification.

According to the data of 2015, 53 percent of workplaces were created spontaneously, 27 percent were generated by the private sector, and 4 percent – based on own skills.

29

Chart N24

17% 17% 16% 16% 14% 14% 15%

19% 22% 23% 23% 25% 26% 27%

5% 4% 4% 4% 4% 4% 4%

60% 57% 57% 57% 57% 56% 53%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Distribution of workplaces by the sources of their generation

Created by the state Created by the private sector

Created based on own skills Spontaneous jobs


The identified trends are important and demonstrate a broadening picture. In 2009 – 2015, the de-crease of the weight of spontaneously created workplaces and the increase of the weight of workplaces generated by the private sector were clearly identified. At the same time, a slight decrease in the weight of workplaces created by the state and the stability of the weight of workplaces created based on own skills are also clear.

Chart N25

35% 34% 33% 32% 29% 28% 29%

40% 44% 46% 47% 49% 51% 52%

10% 8% 8% 7% 8% 8% 8%

15% 14% 12% 13% 14% 13% 12%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Distribution of workplaces by the sources of their generation excluding agro self-employment

Created by the state Created by the private sector

Created based on own skills Spontaneous jobs


30

In general, the above-mentioned trends convey quite high positives, which are reflected in the in-crease of the influence of the private sector in job generation, basically to the extent that we see a decrease in the number of jobs created spontaneously. However, these positive trends are slow against the back-ground of the scale of the problem.

The present analyses once more demonstrate that in Georgia the most significant problem in the employment field is the hypertrophic high number of rural self-employment. Abstracting form rural self-employment, the above-mentioned trends look clearer and more positive (see Chart N25).

31

4. Structural Unemployment

4.1 Structural unemployment: methodological aspect

It is difficult to assess structural unemployment in more or less exact percentages, particularly in Georgia. To do this, it is necessary to study the existing vacancies in the labor market. Job-seekers in Georgia are not registered for a long time and the only source for professional assessment of the structure is the Integrated Household Survey.

The structural unemployment paradigm in Georgia can be illustrated as follows:The education system does not or cannot prepare staff with relevant (in demand on the labor mar-•

ket) specialties (qualifications). In other words, the education system and the labor market are not congruent. For example, there is a demand for zoo-technologists on the labor market yet the educa-tion system is preparing an inadequately excessive number of business administration specialists;

On the other hand, the education system - high as well as vocational - does not give the in-demand • knowledge (qualifications), which means that the educational qualification and actual knowledge and acquired skills do not match. For example, an engineering degree does not mean the graduated student has the real knowledge of a modern engineer. This can be called a professional inconsistency problem.

As a result, the country’s economy is unable to generate jobs respective to the labor force existing on the labor market. In this respect, it must be stressed that Georgia’s economy creates predominantly low-skilled jobs, the majority of which do not require special education.

As a result of long-term unemployment, the labor force prepared by the education system loses quali-fications or is forced to work in jobs with lower qualifications (and salary). De-qualification of the labor force is one of the main negative results of structural unemployment. However, it is noteworthy that this problem is diverse in its turn. With existing information arrays, it is possible to assess:

The weight of long-term unemployed individuals with high or mid-level qualifications among the • unemployed according to ILO criteria;

The weight of individuals employed inconsistent to their qualifications among the employed.• In many countries, there is no possibility for such assessments. In Georgia, information support is at

a reasonably high level; however, there is a very important condition for the assessment; in which equally successful can be people whose:

Actual qualification does not match the qualification received through education. They cannot find 1. a job appropriate to their education qualifications and/or are forced to agree to low-skilled jobs or wait for jobs that match their education qualifications.Education qualification matches their real skills, but because of the institutional weakness of the 2. labor market, they are unable to find a job with the relevant qualification and/or are forced to agree to low-skills jobs or wait for jobs which match their education qualification for a long time. They often do not have the informal links necessary to find a job.They got their diploma a long time ago and after that they were unable to follow technological devel-3. opments, because of which their knowledge is outdated in terms of practical use. They are forced to agree to low-qualification jobs or wait for jobs according to their relevant educational qualification for a long time.

It is very difficult to say which category, with which weight, determines the level of structural unem-ployment. For such assessments, in order to study the liquidity of education, it is necessary to conduct a large-scale research.

Studying the liquidity of education is an important issue which has central importance not only in terms of studying structural unemployment, but also because it is one of the decisive informational pillars for elaborating a strategy for further developing the education system. We will see below how impressive the part of the problem related to structural unemployment is, the evaluation of which is possible with the available information range.

32

4.2 Long-term unemployment and de-qualifi cation as a manifestation of structural unemployment

In terms of structural unemployment, it is particularly important to discuss long-term unemployment in professional dimension.

The majority of long-term unemployed surveyed during the study period consisted of highly qualified professionals and those with no profession. The weight of medium and low-skilled specialists among the long-term unemployed is relatively low. Among them, low-skilled specialists, whose number throughout the study period is in the range of 4-5 percent, should be especially underlined.

Chart N26

41% 41% 41% 43% 42% 43% 42%

19% 19% 20% 19% 16% 18% 17%

5% 6% 4% 3%5% 5% 4%

35% 34% 34% 35% 37% 35% 37%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

Distribution of long-term unemployed in aggregated groups of one digit ISCO codes

Highly qualified specialists Mid-level specialists

Low qualificaiton specialists Not having profession


It should be noted that in terms of structural unemployment, the distribution of long-term unemployed only according to professional characteristic, is not enough. Obviously, this distribution contains some information, but comparison of the distribution provided in the same context of this structure and the eco-nomically active population is more informative.

According to the comparison of structures, the weight of highly qualified professionals in long-term unemployment is 32 percent higher than the weight of professionals in a total economically active popula-tion. This difference manifests a decreasing trend in 2009-2015, but the 32 percent means that the highly qualified professional has a 1/3-higher than average chance of long-term unemployment and in case the subject is a low-skilled professional, this chance is 1.42 percent lower. The chance of long-term unem-ployment is also 16 percent lower in case the subject has no profession.

Therefore, we can say that the problem of de-qualification determined by long-term unemployment is very important. The following gives us a basis to conclude: almost 60 percent of the long-term unem-ployed are highly qualified professionals and medium-qualification specialists, from which the majority (43 percent) is highly qualified professional and long unemployment is almost half the total unemploy-ment. Thus, nearly 30 percent of the overall unemployed are de-qualified professionals. Such scale of de-qualification clearly proves the severity of structural unemployment in Georgia.

33

Chart N27

40% 36% 36%41%

34%40%

32%

10%0%

9%3%

-9%

1%

0%

-41%-31%

-44%

-58%

-43% -41% -43%

- 22% -20% -21% -20%-13%

-21%-16%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

2009 2010 2011 2012 2013 2014 2015

Difference between the shares of the aggregated groups ofone digit ISCO codes in long-term unemployed and the shares of the aggregated groups of

one digit ISCO codes in economically active population

Highly qualified specialists Mid-level specialists

Low qualificaiton specialists Not havingh profession


The long-term unemployment indicator in the years of 2009-2015 is characterized by a well-estab-lished trend of reduction. It should be noted that the long-term unemployment rate among medium-skilled specialists and highly qualified professionals, as a rule, is higher than among the low-skilled specialists or persons with no professions. The long-term unemployment rate, according to the data of 2015 was 9 percent, or not substantially lower than 12 percent, of the total unemployment level. This means that the friction unemployment rate is only 3 percent in Georgia, which is generally regarded as being in the nor-mal range.

Chart N28

15% 15%14% 14%

13% 13%

11%

8%10%

8% 8%9%

8% 7%

11%12%

11% 11% 11%10%

9%

0%

2%

4%

6%

8%

10%

12%

14%

16%

2009 2010 2011 2012 2013 2014 2015

Long-term unemployment level in aggregated groups of one digit ISCO codes

Highly qualified or mid-level specialists

Low qualified specialists or not having profession

In average


34

The unification of mid-level specialist and professionals into one group, and the comparison of these group’s indicators to the group of low-skilled specialists or persons with no profession is determined by the fact that the trends developed in both groups are more or less homogenic.

Chart N29

16%16%

15%16%

15% 14%

12%12% 12% 12%11%

10% 10%9%

7%

8%

6%

5%

6% 6%5%

9%10%

9% 9%9%

8% 8%

11%12%

11% 11%

11%10%

9%

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

2009 2010 2011 2012 2013 2014 2015

Long-term unemployment level in aggregated groups of one digit ISCO codes

Highly qualified specialists Mid-level specialistsLow qualification specialists Not having professionIn average


As for a relatively detailed review (See Chart N29), the trends are the same as in the case of aggregat-ed indicators in two groups, although the group of highly qualified professionals is clearly distinguished, where the long-term unemployment rate, in comparison with all other groups, is distinctly higher. While in 2009-2015 a clear trend of decrease is observed in this group, in 2015, too, the long-term unemployment rate is at quite a high benchmark - 12 percent.

4.3 “Unsatisfi ed” workers or hidden structural unemploymentIn the context of structural unemployment, the problem of “satisfied” employees is no less important

than the problem of long-term unemployment. These are the people who could not obtain a workplace according to their qualification and agreed to a job with other qualifications or lower-skills. Although they are formally employed, in fact they are not satisfied with the job. Therefore, this phenomenon can be called hidden structural unemployment. Here we can consider two cases:

When the labor force is employed, but is looking for another job, the reason of which, as a rule, is 1. professional mismatch;When the labor force is unable to find a job matching their qualifications and is forced to agree to a 2. job of lower qualifications.

For the second case, we took the main profession for each employment according to a diploma and compared it to its actual employment according to the diploma. We excluded those employees who, ac-cording to the actual employment, belong to the 1st ISCO group, i.e. leading positions, or professions which are not certified by diploma.

The calculations demonstrated that the number of job seekers due to professional inadequacy is within the margin of statistical error and is characterized with a trend of reduction. According to the data of 2015, such employees compile just 0.5 percent of the economically active population.

As for employees having diplomas working in lower-qualification jobs, for instance taxi drivers, sell-ers in kiosks or engineers working on their own land, their weight is 25 percent of the economically active population and the trend shows very mild, but some, growth.

35

Chart N30

22.6%

25.0% 24.7% 25.3% 25.9% 25.2% 25.8%

1.7% 1.2% 0.9% 0.9% 0.8% 0.7% 0.5%

22.8%25.1% 24.8% 25.4% 26.0% 25.3% 25.8%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

2009 2010 2011 2012 2013 2014 2015

The share of “unsatisfied” employed in economically active population

The level of employment by lower than certified qualification according to ISCO

The level of seeking additional job due to professional inconsistance

Share of “unsatisfied” employed, total


As the above analysis demonstrated, the problem of “unsatisfied” employees, as a manifestation of hidden structural unemployment, is mostly a result of low congruence of the education system and the labor market. The distribution of employees and unemployed in professional groups according to ISCO classification was discussed above according to both certified professions and actual employment by oc-cupation. The study showed that the structures, on the one hand according to certified professions and, on the other hand, actual employment, do not practically correlate with each other. Thus, it can be said that one of the important components of the problem of “unsatisfied” employees is exactly this circumstance.

Chart N31

6.9%

11.6%

7.1% 7.1%

10.7%

7.4% 7.0%

19.4%20.9% 20.5%

19.5%18.7%

15.8%14.4%15.2% 16.0%

15.9%14.5%

15.1%13.7%

12.9%

15.0%13.8%13.7%

14.6%13.3%

12.3%12.4%

11.7%10.4%

12.0%11.3%

11.0%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

2009 2010 2011 2012 2013 2014 2015

Unemployment rate by ILO criteria in the groups according to the achieved level of education

Lower than secondary education Secondary education

Vocational education High education

In average

15.1%14.0%


36

If the indicators of hidden structural unemployment are calculated according to our approach, the dif-ference between the groups is substantial and, one might say, even dramatic.

The hidden structural unemployment rate is the highest, as a rule, among the population with second-ary-special education. This indicator is also high among the population with high education, but it is still substantially lower than the rate of unemployment among the population with secondary-special educa-tion.

Chart N32

0.5% 3.4%0.2% 0.1% 0.2% 0.1% 0.0%

0.6%

8.4%

0.2% 0.2% 0.2% 0.1% 0.2%

53.9%

47.5%

58.1% 58.5% 57.2% 56.1% 58.2%

37.0% 38.9% 38.3% 39.6% 41.2% 40.6% 41.8%

22.8%25.1% 24.8% 25.4% 26.0% 25.3% 25.8%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

2009 2010 2011 2012 2013 2014 2015

Hidden structural unemployment level in the groups by achieved level of education



In average


It is a noteworthy trend and underlines the fact that the secondary-special education gives a very low chance of employment according to qualification.

Quite natural is the fact that the structural unemployment rate is actually zero among the population with secondary and lower than secondary education: This is a group of persons who does not have profes-sions and whose absorption takes place in mostly agricultural employment.

The aggregated level of unemployment in groups with different education levels is significant. If we consider the aggregate unemployment rate without the hidden structural unemployment, we will see that this indicator is characterized with a tendency of reduction in all groups. It is also significant that for al-most all groups it is in a rather narrow range, especially in the years 2014-2015.

A completely separate case can be found in the group of the population with an education level lower than medium, in which the aggregate unemployment rate is the lowest. A downward tendency is also re-vealed in this group, though at the expense of employment with the lowest qualification.

37

Chart N33

16.8%

26.2%

15.4%17.5%

19.5%17.8%

15.0%

29.2% 30.6% 31.2% 30.9%28.9%

26.2%24.8%

38.4%

34.1%

31.9%

38.0%

34.3%

32.6%

37.0%

32.5%

32.0%

36.1%34.5%

32.3%

34.7%

31.9%

30.7%

30.3%28.5%

27.4%

28.0%27.9%25.9%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

45.0%

2009 2010 2011 2012 2013 2014 2015

Aggregated level of unemployment excluding hidden structural unemployment in the groups by achieved level of education



In average


The difference becomes significant if we consider the aggregate unemployment rate including ob-servable structural unemployment. In this case, the unemployment rate in the population with secondary-special education already hits quite a high number. The aggregate unemployment rate in the population with high education is substantially lower, but generally still high.

Chart N34

17.0%

28.5%

15.4% 17.5% 19.6% 17.8% 15.0%

29.4%

37.2%31.4% 30.9% 28.9% 26.3% 24.9%

76.3%72.0%

77.7% 79.4%76.5% 73.8% 75.2%

65.6% 68.0% 66.9% 66.3% 66.9%62.9% 62.9%

49.1%52.2% 51.3% 51.7% 51.0%

47.7% 47.2%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

2009 2010 2011 2012 2013 2014 2015

Aggregated level of unemployment including hidden structural unemployment in the groups by achieved level of education



In average


The significantly lower level of the aggregate unemployment rate indicator for the population with secondary and lower than secondary education is determined by structural unemployment characteristic for this group.

38

Most important is that the aggregate unemployment rate indicator, including the hidden structural unemployment, stands out for the tendency of invariability in 2009 -2015.

4.4 Structural compatibility of labor market demand and supply

The distribution according to certified professions, or the component of workforce supply, is reviewed in the sectoral analysis part of the labor market. Here, we must question whether the supply structure is adequate in relation to the structure of demand.

For the review, the distribution according to ISCO double-digit codes was compared. As the com-parison demonstrates, the distribution of the employed, according to the certified and actual professions, practically does not correlate with each other: the correlation coefficient is -0.0792.

When discussing the employed without those self-employed in the agricultural field, the correlation coefficient increases significantly, but its absolute significance is still low at the 0.2085 benchmark. This means that these two structures are quite different when we review them without self-employment.

Including the self-employed in the agricultural sector, the correlation of distribution according to certified and actual professions was more or less similar during the research period. Even discussing the case without self-employment in the agricultural sector, the correlation of the structure is characterized by a certain tendency of reduction. The reduction rate is not high, but the tendency in itself is well-defined and confirms the low congruency of the education system towards the labor market.

Chart N35

-0.0764 -0.0812 -0.0833 -0.0831 -0.0791 -0.0760 -0.0792

0.2734

0.2319

0.2016 0.2118 0.21760.2471

0.2085

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

2009 2010 2011 2012 2013 2014 2015

Correlation of the structure of certified professions with the structure of actual professionson the level of two digit ISCO codes



While comparing the distribution of the employed according to certified and actual professions, the important factor that reduces the correlation is quite a large group of people who do not have a profes-sion- individuals who do not have any kind of certified profession, but actually do something, even a very low-skilled job, and so are still employed.

If we exclude the group without professions from the structure and compare the distribution accord-ing to actual and certified professions, the correlation of the structures including self-employment in agri-culture is still zero. The correlation coefficient of -0.0228, instead of -0.0972, does not reveal any essential difference and the correlation, as in the previous case, is actually zero here, too.

39

If we exclude self-employment in the agriculture sector from the structure, the correlation coefficient increases by almost 14 times - from 0.0288 to 0.4061. The latest in itself is not a high figure, but it is clear that by excluding those who are employed in the agricultural sector and do not have professions, the struc-ture of certified and actual professions is much more correlated.

Chart N36

-0.0394 -0.0470 -0.0488 -0.0466 -0.0339 -0.0246 -0.0228

0.4708

0.37440.3452

0.3852 0.3866

0.44520.4061

-0.1

0

0.1

0.2

0.3

0.4

0.5

2009 2010 2011 2012 2013 2014 2015

Correlation of the structure of certified professions with the structure of actual professionson the level of two digit ISCO codes excluding individuals not having profession

Including agro self-employment Excluding agro self-employment


The correlative analysis of the professional structures of employed and job-less persons demonstrated that the quality of the education system and its relevance to the labor market is very low in Georgia: the distribution of employed persons according to actual and certified professions is characterized with almost zero correlation.

The degree of correlation increases several times if we exclude such large components from the struc-ture as the group not having a profession. However, the correlation between the structures is less than 0.5 or lower. This means that a certified profession determines less the actual place of employment, or special-ists trained by the education system do not meet labor market needs.

The correlation of the employed and unemployed according to certified profession equals to almost 1, which means that the influence of certified professions on employment is very low. This also means that the weight of certified education received from the education system does not play a significant role in the job seeking process. In addition, the education system ensures the generation of a whole ‘army’ of those who do not have professions, and their competitiveness on the labor market is very low. The absolute majority will be self-employed in the agricultural area or in jobs with very low qualifications.

Thus, as noted above, one of the main problems for those who do not have certain professions is to develop and implement a vocational education program. This, of course, cannot be expected to solve the problem automatically.

It is interesting to illustrate the correlation among the structures according to actual profession of employed and certified profession for unemployed workers. Here, too, in the case of the distribution of the employed according to actual and certified professions, the correlation is zero, while the correlation with-out agricultural self-employment results in an increase. Yet the correlation is still zero. Moreover, even in these zero correlations show a declining tendency.

40

Chart N37

-0.0653-0.0743 -0.0768 -0.0752 -0.0733 -0.0726 -0.0707

0.1089

0.0823

0.06240.0740 0.0694

0.0579 0.0569

-0.1

-0.05

0

0.05

0.1

0.15

2009 2010 2011 2012 2013 2014 2015

Correlation of the structure of actual professions of employed with the structure of unemployedby certified professions on the level of two digit ISCO codes



The correlation substantially increases when excluding those who do not have professions from the structure, although it is still unable to be considered a high correlation.

Chart N38

-0.0238 -0.0378 -0.0398 -0.0345 -0.0284 -0.0246 -0.0130

0.4230

0.34430.3069

0.36610.3480 0.3484

0.3680

-0.1

0

0.1

0.2

0.3

0.4

0.5

2009 2010 2011 2012 2013 2014 2015

Correlation of the structure of actual professions of employed with the structureby the certified professions of unemployed on the level of two digit ISCO codes

excluding individuals not having profession

Including agro self-employment Excluding agro self-employment


The level of structural relevance of the education system and the labor market is very low. The degree of correlation somewhat increases if we exclude a large opponent from the structure, such as the group that does not have a profession, but despite this, the correlation between the structures is less than 0.5, or in low correlation with each other. This means that a certified profession determines less the actual place of employment and the output of the education system matches less with the demands of the labor market.

41

Among the employed, explaining the existence of the high number of those who do not have profes-sions is possible by age factor (See Chart N39). The potential labor force includes a population of 15 years plus, including school pupils and students, or the population in the early stages of education who have yet to receive any certification. The number of those who do not have professions until 25 years of age, situated among the economically active population, is 67 percent. This indicator revealed a less positive tendency of growth in the research period.

Futher, the number of those who do not have certified professions among the economically active over 25s is also very high. According to the data of 2015, it stood at 42 percent and remained virtually unchanged during the monitoring period - although with some growth likelihood, as the weight among the economically active population under 25 shows a tendency of increase.

Chart N39

62% 62% 62% 63%60%

67% 67%

43%40% 41% 41% 41% 42% 42%

45%42% 43% 44% 43% 44% 44%

0%

10%

20%

30%

40%

50%

60%

70%

80%

2009 2010 2011 2012 2013 2014 2015

The share of individuals not having profession in economically active population by age

under 25 years 25 years and older total


The large part of the population above 25, who do not have professions, with high probability will not begin education to receive an independent profession without a special offer- or the labor market will be saturated with low-skilled workers, which may become a prerequisite for the degradation of labor relations and the labor market in general.

To study the labor market supply structure, two sources were chosen - the website www.jobs.ge and the newspaper “Sitkva da Saqme” (Words and Deeds). Of course, these sources cannot completely cover vacancies existing on the labor market, but can serve to create a certain impression on the professional structure of the job supply. In order to generate a time series, we tried to obtain material for the identical period from both sources. However, because of the difficulties which we discussed above (P.1.4 - “Re-search Methodology”), making quantitative assessments based on combined historical data from both sources was not possible. As such, below, the analysis of only structures and not quantitative assessments are discussed.

The structure of vacancies according to the professions that were posted through both sources is substantially different in the same period. On vacancies uploaded on jobs.ge, the demand for senior-level workers and professionals with the highest level of qualification is predominant, while in announcements made through the newspaper “Sitkva da Saqme”, the proportion of workers in the service area and trade organizations is very high. The demand for the same group of specialists is also high on jobs.ge, but their share in the structure substantially lags behind the demand for the same group of specialists in “Sitkva da Saqme” while, on jobs.ge, the demand for such professions is insignificant. Thus, it can be said that these two sources focus on totally different segments.

42

While it is true that the two sources focus on different segments, they complement each other, and this is also confirmed by the results of the correlation analysis.

Table N2: The structure of vacancies published in the second half of May 2016 in the newspaper “Sitkva da Saqme” and the web-site jobs.ge in main ISCO groups (Percent)

“Sitkva da Saqme”/Words and Deeds Jobs.ge Total

Leaders of all levels 1 21 16Highly qualified specialists 2 25 20Specialists with med-level qualification 3 13 11Office workers 8 16 14Workers in the service and trade organizations 45 18 24Skilled workers in agriculture 1 0 0Qualified workers of industrial enterprises 16 3 6Plant and machine operators 2 1 2Unskilled workers 21 4 8Total 100 100 100

It is true that the mentioned two sources work on different segments, they complement each other, and this is also confirmed by results of the correlation analysis.

Including the self-employed in the agricultural sector, the correlation between the employment struc-ture and vacancy structure is negative, which can be explained by the fact that the scale of agricultural self-employment is in itself very big and amorphous. The demand for employment in the agricultural sector does not appear in the vacancies, while in the employment structure this sector has the greatest weight.

It is notable that the correlation coefficient of the vacancy structures announced separately for “Sitkva da Saqme” and separately for jobs.ge is essentially lower than the correlation of the united structure of vacancies announced on the basis of both sources with the actual employment structure.

Chart N40

0.389

0.562

0.661

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

“Sitkva da Saqme” Jobs.ge Total

Correlation of the structure of demand with the structure of actual employment without agro self-employment

The correlation between the demanded structure and employment structure when reviewed without agricultural self-employment is also noteworthy.

43

Chart N41

-0.193

-0.355

-0.395

-0.45

-0.4

-0.35

-0.3

-0.25

-0.2

-0.15

-0.1

-0.05

0

“Sitkva da Saqme” Jobs.ge Total

Correlation of the structure of demand with the strucutre of actual employmentwith agro self-employment

The change in the correlation is noteworthy - if the correlation between the demand and actual em-ployment including the agricultural self-employment was negative, the correlation without the agricultural self-employment is positive.

The vacancy structure of the newspaper “Sitkva da Saqme” correlates relatively less with the actual structure without agricultural self-employment - the correlation coefficient stands at 0.389, but, here, the correlation vectors are noteworthy and the correlation is positive. The structure of jobs.ge is in relatively high correlation - and the correlation coefficient here stands at 0.562.

It is noteworthy that the correlation coefficient following the unification of the data from “Sitkva da Saqme” and jobs.ge significantly increases to 0.661.

This confirms the necessity to solve the problem of structural unemployment and, in general, the implementation of the proper employment policy through the formation of a cumulative database of va-cancies.

As mentioned above, the generation of a time series became possible only for the data from “Sitkva da Saqme”. Of course, the data is incomplete and, as seen above, only works on certain segments. Yet it is still interesting to observe the dynamics of the announced vacancies through this source.

As seen from the data brought below (Chart N42), the reduction in the share of highly qualified professionals and medium-qualified workers is clear, as is the substantial increase in demand for workers from the service field and trade organizations. This tendency matches precisely the weight reduction of agricultural self-employment in the employment structure and the trend of growth of that number in the service field. Certain conformity can be seen but quantitative transformation does not reach such scale that could determine qualitative changes. Employment possibilities in real sector of the economy, and vacan-cies, have not changed.

44

Chart N42

2010

6 4 6 4 1

8

6 119

96

2

8

1711

7

10

8

4

4

26

22

9

916

5

38

23

30

4238

33

52

0

00

00

0 0

15 7 8

17 11

15 13

21 2 4

54

3

6 9 10 10 12 1620

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2010 2011 2012 2013 2014 2015 2016

The structure of vacancies published in the newspaper “Sitkva da Saqme” in May and Decemberof 2010 -2016 in main groups of ISCO professions

Managers of all levels

Highly qualified specialistsMid-level specialists

Office workers

Service and sales workersSklled workers in agriculture

Skilled workers in industry

Plant and machine operatorsUnskilled workers

Chart N43

60

830

9

9

13

1

37

16

0

0

12

35

3

4126

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Employer (demand) Unemployed (supply)

Overall strucutre of vacancies and job offers published in the newspaper “Sitkva da Saqme”in May and December of 2010 -2016 in main groups of ISCO profession Managers of all levels

Highly qualified specialistsMid-level specialists

Office workers

Service and sales workersSklled workers in agriculture

Skilled workers in industry

Plant and machine operatorsUnskilled workers

Newspaper “Sitkva da Saqme” published announcements not only about vacancies, but also job of-fers. Thus, this source enables us to simultaneously conduct correlative analyses for the demand and sup-ply. As can be seen from the cumulative structures of 2009-2015, the supply and demand have substan-tially different structures.

In response to 30 percent of offers in professions that require high qualifications, only 8 percent fall in the demand part (Chart N43).

A similar asymmetry is observed in the case of skilled workers in industrial enterprises, where only 12 percent is in response to 35 percent of offers. However, of 16 percent of the offers to workers in the

45

service field and trade organizations, the response in the demand part is 37 percent of vacancies.Overall, these two structures are in very weak correlation with each other, and the correlation coef-

ficient stands at only 0.2921.The above-mentioned structural analysis only reflects the percentage distribution. This in itself is

very important for the qualitative analysis of supply and demand. We should note that job offers from the unemployed in the database are 1.8 times higher than the demand by employers for work.

In-depth interviews with employers revealed that jobs.ge is the most important portal for them, ena-bling job seekers and employers too meet. During the in-depth interviews, 10 leading companies from 10 different sectors of the economy were interviewed. None of them mentioned the newspaper “Sitkva da Saqme” as a source of searching for a work force. This once again confirms the assumption that this resource focuses on a totally different segment.

All in-depth interview respondents named online resources as a means for searching for employees, which means that the universal internetisation project currently being implemented is also very important in the context of employment.

It should be noted that even large companies tend to look for desirable personnel through relatives and friends. The larger the company, the lower the likelihood of seeking employees through a non-insti-tutional search.

The main reason of staff turnover was named by almost all respondents as disciplinary. Only the wine producing respondent did not name this as a reason. In all other interviews, except for this respondent, tensions between the employee and the employer were clearly felt.

From the list of professions that are difficult and easy to find, an important circumstance emerges. As a rule, specialists from technical branches and fundamental science (physics, mathematics, chemistry) are difficult to find while it is easy to find competent staff in the social and humanitarian professions.

4.5 Effectiveness of the educational system in the context of structural unemployment

The relevance of employment and a profession received through education is the most important component of the employment and unemployment analysis. The Integrated Household Survey provides an opportunity for such analysis. In particular, the study toolkit envisages the classification of the profes-sion of respondent’s actual employment, as well as the profession confirmed by a diploma or other type of certification.

According to the survey data (see Chart N44), only 13.7 percent of the total number of employees is employed according to their certified professions at the level of the ISCO double-digit codes, which is exceptionally low.

As everywhere, here, too, the main determinant of the average rate is agricultural self-employment - almost half of the total employment. Among those who are employed this way, only a minority is em-ployed according to certified professions.

The highest level of unemployment according to profession is observed among the hired employees - 27.6 percent, which is generally very low. In 2009-2013, the rate was characterized with a decreasing trend. After the growth in 2014, it again declined in 2015. As for the same data among those who are self-employed in the agricultural sector, the share is insignificant- higher by only 3.5 percentage points than the average indicator (17.2 percent and 13.7 percent respectively).

46

Chart N44

33.19%

29.28%26.86% 26.95% 26.70%

29.31%27.64%

15.7% 16.7%15.6%

13.7%

17.3% 17.3% 17.2%

0.1% 0.1% 0.3% 0.2% 0.2% 0.1% 0.1%

13.7% 13.1% 12.1% 12.1% 12.4%13.6% 13.7%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

2009 2010 2011 2012 2013 2014 2015

The share of employed respective to professions on the level of two digit ISCO codesby the types of employment

Hired employed Non-agro self -employed

Agro self-employed Total


The not enviable tendency of the number of those who are employed according to their professions may indicate two facts:

The education system fails to provide knowledge which ensures employment in accordance with 1. profession;Education received during the Soviet period cannot meet the demands of the modern labor market. 2.

From these two conditions the first is more significant, as on the labor market, the weight of those who received their education during the Soviet period decreases in proportion as time passes.

Chart N45

34.3%

30.5%27.9% 28.0% 27.5%

30.2%28.4%

0%

5%

10%

15%

20%

25%

30%

35%

40%

2009 2010 2011 2012 2013 2014 2015

The share of employed respective to the professions ontwo digit ISCO codes level in hired employees


47

12 percent of those who are contracted are employed with a qualification higher than the qualifica-tion by diploma, while 35 percent have a lower level of qualification. 24 percent of employees do not have any certified profession. The number of this category of employees has somewhat increased in 2015 comparison to 2014.

The structure of relevance of the actual employment with the qualification according to the diploma shows that, according to the received qualification, it is difficult to find a job in Georgia. This can be de-termined by two main circumstances:

Educational qualification and real knowledge are not relevant to each other, and obtaining a di-• ploma does not equate to knowledge gain;

Either the structure of professions offered by educational facilities does not match the labor mar-• ket demand structure or the educational institutions are preparing educated personnel according to qualification, but with fewer employment prospects.

Most likely, these two reasons are proportional to force and demonstrate that the educational system is less oriented at the labor market. The distribution structure of the employees by contract according to the actual profession and the professions indicated in the diploma, which has not changed during the last eight years (2009-2015) also indicate the same.

Chart N46

3% 4% 4% 4% 3% 3% 1%

31% 34% 37% 35% 37% 35% 35%

33% 29% 27% 27% 27% 29% 28%

13% 14% 14% 14% 13% 12%12%

20% 19% 19% 21% 21% 21% 24%

0%

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70%

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2009 2010 2011 2012 2013 2014 2015

Distribution of hired employed by the consistence between actualprofession and certified profession

NA With lower qualification

With respective qualification With higher qualification

Not having profession


35 percent of those who are self-employed in non-agricultural sectors are employed with qualifica-tions that are lower than the profession according to their diploma, while 33 percent do not have a profes-sion. In the study period, the increase of the weight of those who do not have a profession shows a clear negative trend of growth. Only 13 percent of non-agricultural self-employed are employed with higher qualifications than the qualifications provided by their diplomas.

48

Chart N47

6% 6% 6% 6% 7% 5% 2%

32%40% 36% 37% 35%

33% 35%

16%17%

16% 14% 17%17% 17%

14%12% 15% 15% 13%

13% 13%

32% 26% 27% 28% 28% 32% 33%

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2009 2010 2011 2012 2013 2014 2015

Distribution of non-agro self-employed by consistence between actualprofession and certified profession





In terms of matching employment according to profession by diploma with the actual profession, the most severe situation, as expected, is regarding self-employment in rural areas. 66 percent of the agro self-employed do not have a profession and 29 percent are employed with a lower qualification. This group received a certain profession but was unable to find employment according to their professions, forced instead to become employed on their own farm (See Chart N48)

Chart N48

2% 2% 2% 2% 1% 1% 0%

28% 30% 28% 30% 31% 30% 29%

0% 0% 0% 0% 0% 0% 0%5% 6% 5% 5% 5% 5% 4%

65% 62% 65% 64% 62% 64% 66%

0%

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2009 2010 2011 2012 2013 2014 2015

Distribution of agro self-employed by the consistence between actualprofession and certified profession





49

The employment weight in accordance with qualification is in fact zero in the agricultural sector. The number of rural employed who are certified agronomists, veterinarians, machine-operators, meliora-tion specialists and persons with other agricultural professions is almost close to zero. Therefore, we can conclude that persons with certified agricultural professions almost never turn to agricultural self-employ-ment, but it does not mean that they have a real possibility to be employed by their profession.

From trends that were revealed in 2009-2015, the slight increase in the number of agro self-employed who do not have professions is noteworthy. As for the weight indicator of those who have lower certified qualification, it is stably in the range of 30 percent.

The share of those who are employed with higher qualifications is only 4-5 percent among the agro self-employed. This seems strange at first glance, but there are some professions that are considered to be lower-skilled than activities in the agricultural sector (for example, the 9th group - “Non-qualified work-ers”, 8th group - “Plant and machine operators, machinists, assemblers and metal craftsmen”).Overall, in NACE aggregated groups, the weight of those employed according to their professions at the level of ISCO two digit codes, is the highest in the education and health sectors. Yet it is also in these sectors that the employment indicator in accordance with qualification is also characterized by a tendency of reduc-tion.

The same indicator is also relatively high in the most diverse group, which include transport, hotels and restaurants, financial intermediation and public administration bodies. It should be noted that this fig-ure has a tendency to decrease.

In the industry and construction sectors, the indicator of employment according to qualification is in the range of average, although it is also characterized with a tendency to decrease.

The only sector where the indicator of employment in accordance with qualification shows a growth tendency is trade and households service, although this figure itself is too low, with quite weak growth.

In the agricultural sector, the employment indicator according to qualification is so low that it is not worth discussing.

Overall, in leading sectors, the clear reduction tendency of the employment indicator according to qualification once again underlines the fact that this problem is more connected with the education sys-tem, rather than with the Soviet legacy. While the Soviet legacy will decrease and transient, the downward trend is a sign of future problems.

Chart N49

0.2% 0.2% 0.3% 0.2% 0.2% 0.3% 0.5%

25%22% 22%

20% 20% 21% 21%

8% 7%9%

7% 7% 9% 10%

35%31%

28% 29% 28%31%

29%

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2009 2010 2011 2012 2013 2014 2015

The share of employed in accordance with certified professions on two digit ISCO codes levelin aggregated sectors of economy

Agriculture, forestry, fisher

Industry, construction

Trade and services

Transport, hotels, restaurants and other services

Educaiton and healthcare


50

The problem of matching the educational system with the labor market, revealed during the Integrat-ed Household Survey data analyses, was also confirmed by the in-depth interviews. Almost all respond-ents named the low level of actual knowledge as one of the main difficulties in searching for personnel. Against this background, it is only natural that the majority of surveyed companies applied headhunting as a recruitment practice.

From other in-depth interviews another issue was identified: entrepreneurs are not satisfied with the product of the education system or the qualifications of the labor force trained by it. However, none of the respondents think about taking any steps to improve the existing situation, not even through direct contact with higher educational institutions.

Thus, the problem of mismatch of the educational system and the economy has to be resolved by the state as the market, as world practice shows, cannot resolve it on its own.

51

5. Institutional Weaknesses of the Labor Market An important aspect of the in-depth labor market analysis is ways to search for jobs. The Integrated

Household Survey contains important information about the job search. According to the IHS, about 1/5 of the unemployed (18.8%) are actively looking for a job, while over

4/5 (81.2%) are not. Unemployed citizens who are job seekers were mostly looking for employment with contracts. Solving the employment problem through starting one’s own business is minimal.

Table N3: Distribution of the unemployed by job search methods (Percent)2009 2010 2011 2012 2013 2014 2015

Yes, I was looking for a paid work: 20.5 21.1 20.6 21.6 20.7 18.4 18.8I was screening announcements in the press, through TV, Internet and other means 2.7 2.4 2.5 3.0 3.4 3.0 3.0

I was searching for information through acquaintances 16.9 17.8 17.4 18.1 17.0 15.0 15.3I was directly contacting the administration 0.7 0.6 0.5 0.4 0.3 0.3 0.4I was publishing announcements in the press, through TV, Internet and other means 0.0 0.0 0.1 0.0 0.1 0.1 0.1

I applied to the employment service 0.1 0.1 0.1 0.0 0.0 0.0 0.0Other 0.1 0.1 0.0 0.0 0.0 0.0 0.0Yes, I tried to start my own business: 0.1 0.2 0.1 0.2 0.2 0.2 0.0For starting my own business, I applied to the relevant authorities for a per-mit 0.0 0.1 0.0 0.1 0.1 0.1 0.0

I established contacts with potential partners 0.0 0.1 0.1 0.0 0.0 0.0 0.0I tried to take a loan/credit to start a business 0.0 0.0 0.0 0.0 0.0 0.0 0.0I was looking for a building, raw materials, equipment, land plot 0.0 0.0 0.0 0.0 0.0 0.0 0.0Other 0.0 0.1 0.0 0.0 0.0 0.0 0.0No, I did not try: 79.4 78.6 79.3 78.2 79.1 81.4 81.2In total 100 100 100 100 100 100 100


It is important to group job search means according to the degree of institutionalization on the labor market. In other words, how the system works, by which citizens are looking for work. The means listed in the table subject above, we grouped depending on whether they include a formalized approach to search-ing for work or to starting one’s own business. Accordingly, we have defined two conditional job search groups:

Institutionalized job seeking, which includes respondents who answered the following questions 1. regarding their job search:

I was screening announcements in the press, through TV, Internet and other means;• I was directly contacting the administration;• I was publishing announcements in the press, through TV, Internet and other means;• I applied to the employment services• To start my own business I applied to the relevant authorities for a permit;• I established contacts with potential partners;• I tried to take a loan to start a business.•

Non-institutionalized job seeking, which included the respondents who answered the following 2. questions regarding the job search:

I was searching for information through acquaintances;• I was looking for a building, raw materials, equipment, land plot;• Other•

The distribution of aggregate estimates shows that in Georgia, the labor market is institutionalized only by 20 percent (see Chart N50). Thus, social capital remains the main source for seeking a job. .

The mainly non-institutional character of the job search, which has not changed over the years, high-

52

lights the imperfection of labor market. The institutionalisation of the demand and supply on the labor market is one of the first activities to address the problem of unemployment. This is quite a complex goal that requires thorough understanding and consideration of the specificity existing in Georgia.

Chart N50

17% 15% 16% 17% 19% 19% 19%

83% 85% 84% 83% 81% 81% 81%

0%

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2009 2010 2011 2012 2013 2014 2015

Distribution of unemployed by institutionalized job seeking

Institutionalized job seeking Non-institutionalized job seeking


The distribution of jobs according to their generation sources is important. From the database of the Integrated Household Survey, we have identified four job types according to the sources of their genera-tion:

Jobs created by the state, which included employees of state institutions and public sector organiza-1. tions;Jobs created by the private sector, which included employees of private enterprises and organiza-2. tions and entrepreneurs themselves with hired workers;Jobs created through own skills, which included those who were non-agricultural self-employed, 3. whose employment was determined by using their skills. Individual entrepreneurs self-employed using their professional knowledge, belong to this category.Spontaneously created jobs, which included those who are self-employed in agriculture and petty 4. trade, taxi drivers and others- in short, self-employed in the fields that require low capital capacity and in the fields those are not characterized by demand for high qualifications.

According to the situation in 2015, 53 percent of jobs were created spontaneously, 27 percent of jobs were created by the private sector, 15 percent were created by the state and 4 percent - based on their own skills.

The problem related to the spontaneous nature of employees and employers was revealed during the in-debt interviews. Despite all respondents using an Internet resource (jobs.ge, LinkedIn, Facebook, an-droid application and so on), these resources, due to the lack of a unified system, were not connected to each other. The institutionalization of the platform of “meeting” of employers and job seekers, defining relevant rules and framing them in one system, is a higher objective than disseminating vacancies via the Internet.

The general background highlighted as a result of conducting interviews reveals that the employee has just responsibilities and the employer has just rights. The state placing these processes within an insti-tutional and legal framework is an important and topical task.

53

6. Key Findings

6.1 Empirical fi ndings

The indicator of aggregated unemployment in Georgia (including under-employment and hidden 1. employment) was 25 percent in 2015. This indicator was characterized by a decreasing trend in 2009-2015, which became especially strong in 2014-2015.43 percent of the aggregated unemployment level consists of the unemployed according to ILO cri-2. terion, approximately one third - 32 percent is the share of under-employment and one fourth - 25 percent - the share of hidden unemployment. Aggregated unemployment indicators calculated by urban and rural areas are not that significantly 3. different from those of the indicators calculated by ILO criteria.In 2015, 38 percent of unemployed people identified by ILO criteria according to certified profes-4. sion were highly qualified specialists; 17 percent of unemployed people were mid-level specialists, and 4 percent lower than medium specialists.The distribution of the unemployed in aggregated groups by certified professions is analogous to 5. the structure of the employed in the same groups - the correlation coefficient equalling almost 1, which means that a certified profession according to a diploma does not have a decisive influence on employment.The structures of employed and unemployed by qualification are even identical according to ISCO 6. two digit codes: the correlation coefficient equals almost 1 here. In 2009-2015, the correlation coef-ficient showed an upward trend, i.e. the structure of employed and unemployed became more and more similar.The unemployment level among the highly qualified specialists according to ILO criteria in 2015 7. was higher than the overall unemployment level by 20.8 percent. The different vector was also analogous in 2009-2015. The unemployment level is almost twice lower than overall level among specialists with lower qualifications. It is also low among those who do not have a profession.48 percent of unemployed identified according to the ILO criteria in 2015 were short-term unem-8. ployed, while 52 percent were long-term unemployed. The distribution of unemployment by dura-tion did not change in 2009-2015. In 2015, nearly half of total employment - 48.4 percent - was a share of self-employment in the 9. agricultural sector. This indicator was characterized by a reducing trend in 2009-2015, as a result of which it dropped below 50 percent for the first time in the last 25 years.The next weighty component in the employment structure is trade and household services, the weight 10. of which was in the neighbourhood of 10 percent throughout the research period.According to the data of the Integrated Household Survey, the weight of employment in the real sec-11. tor of the economy (without the agricultural sector) is 10.6 percent of the total employment. This fig-ure remained unchanged throughout 2009-2015. The employment weight in the household service sector was 41.0 percent in 2015. In 2009-2015, it was characterized by an overall upward trend.In 2015, 53 percent of jobs were created spontaneously, 27 percent were generated by the private 12. sector, 15 percent by the state, and 4 percent based on a person’s own skills.In 2009-2015, the reduction in the weight of spontaneously created jobs and the increase of the 13. weight of jobs created by the private sector was clearly noticeable. At the same time, the slightly noticeable reduction in the weight of jobs created by the state and the stable weight of jobs created based on a person’s owns skills were apparent.The weight of the highly qualified professionals among the long-term employed was 32 percent 14. higher than their weight in the economically active population, which means that a highly qualified professional has a 32 percent higher than average chance to have “the status” of unemployed. In case of low qualified professionals, this chance is 42 percent lower than average. The chance of long-term unemployment is 16 percent lower than the average in the absence of a profession.

54

In the context of structural unemployment, the problem of “unsatisfied” employed is no less im-15. portant than the problem of long-term unemployment. These are people who could not obtain jobs according to their qualification and agreed to other jobs or jobs with lower qualifications. Formally they are employed, but in reality they are not satisfied by their jobs. The level of structural unem-ployment detected this way was 25.8 percent in 2015. In 2009-2015 this indicator showed a weak tendency of reduction. The level of hidden structural unemployment is the highest, as a rule, among the population with 16. vocational education - 58.2 percent. This indicator is also high among the population with higher education - 48.2 percent, but is substantially lower than the unemployment level among the popu-lation with vocational education. This means that vocational education gives a very low chance of finding employment according to qualification.The aggregate unemployment level, including hidden structural unemployment, is at a very high 17. level among the population with vocational education - almost 75 percent. The aggregate unemploy-ment level among the population with higher education is essentially low, but in general is still very high - almost 63 percent.The aggregate unemployment level, including hidden structural unemployment, was characterized 18. by a tendency of invariability in 2009-2015.The comparison of the distributions of employed according to the ISCO two digit codes demon-19. strates that the distribution of employed by certified and actual profession does not correlate and has a correlation coefficient of -0.0792. This means that the professional structure of certificates issued by educational institutions does not coincide with the needs of the labor market.If we consider the distribution of employed by certified and actual professions, without those who 20. are self-employed in the agricultural sector, the correlation coefficient increases significantly, but its absolute value still remains at a very low level (0.2085).At the level of ISCO two digit codes only 13.7 percent of the total number of employed are em-21. ployed according to their certified professions, which is a very low indicator.The number of those employed according to their professions is relatively high in the case of the 22. self-employment in the non-agricultural sector, where this rate is at the level of 17.2 percent or even higher than the average indicator, although the number in itself is very low.The employment level according to profession is highest among those who are employed by con-23. tract - 27.6 percent, which is also very low. In 2009-2013 this indicator reduced. After the increase in 2014, it again decreased in 2015. To name the Soviet legacy as the reason for this has already become illogical.Approximately 19 percent of the unemployed were actively searching for a job, while approximately 24. 81 percent were not. The unemployed citizens were mainly seeking jobs with contracts. Employ-ment by starting one’s own business is minimal.The assessments show that the labor market of Georgia is institutionalized by 20 percent. Thus, the 25. main source for job seekers is still social capital (acquaintances, friends, relatives).

6.2 Qualitative fi ndings

From the empirical analyses described above, the following qualitative findings were revealed:The majority of the jobs generated on the Georgian labor market do not require high qualification. 26. The country’s economy mainly creates jobs with low qualifications which do not require special education.Among the unemployed, the largest group are those who do not have a certified profession, i.e. those 27. who do not have a profession.The majority of the long-term unemployed (42 percent) are highly qualified specialists. This trend 28. was retained during the whole research period (2009-2015). The weight of specialists with mid-level and low qualifications is relatively low among the long-term employed.During the last 6 years, positive developments taking place in the employment structure, demon-29.

55

strated in the reduction of the agricultural employment weight, were determined by the weight in-crease in the service field. This positive trend has left practically untouched the real sector of the economy (without the agricultural sector). The weight of the private sector in generating jobs is increasing, which mainly takes place at the 30. expense of reducing the weight of spontaneously created jobs.The correlative analyses of the employed and unemployed according to certified profession demon-31. strated that certifying education received from the education system does not play an important role in searching for jobs. The analyses of the relevance of actual employment with a qualification according to a diploma 32. demonstrates that searching for jobs according to the qualification is very difficult in Georgia, which in reality can be a result of two aspects:

The education qualification and real knowledge do not coincide and the received diploma does a. not signify gained knowledge;

The structure of professions offered by educational institutions does not coincide with the struc-b. ture of the demand on the labor market and educational institutions are preparing personnel who have a diploma of educational qualification, but have lower chances of employment.The paradigm of structural unemployment in Georgia can be described in the following way: On the 33. one hand, the education system does not or cannot prepare personnel with relevant qualifications (in demand on the market). On the other hand, higher and vocational education does not provide students with relevant knowledge (qualifications), i.e. the education qualification and actual knowl-edge do not coincide. The personnel prepared by the education system lose their qualifications as a result of long-term unemployment, or are forced to work in jobs that require lower qualifications. De-qualification of the labor force is one of the negative results of the structural unemployment in Georgia.The problem of “unsatisfied” employed as the manifestation of structural unemployment is the re-34. sult of the low congruence of the education system and the labor market.The Georgian economy is unable to generate highly qualified jobs. As a result, hidden and “unsat-35. isfied” structural unemployment, as well as unemployment calculated by the ILO criterion, is the highest among those who have high qualifications according to education qualification.The agricultural sector remains the absorbent of the low-qualification work force. This sector “ab-36. sorbs” the part of the work force which is unable to find any kind of employment.The weight of the private sector in generating jobs is essentially increasing, which undoubtedly is a 37. positive trend, although its tendency is unsatisfactory and does not have great growth potential.The weight of agricultural self-employed in total employment is decreasing, which is also a positive 38. tendency. But the rate of decrease is not so high as to determine important changes in the employ-ment structure of Georgia.The hidden structural unemployment level is essentially high in the group with vocational education. 39. The certified specialists of this class, as a rule, are successfully replaced by those who do not have professional qualifications, but are more actively seeking jobs.The level of institutionalization of job searching is extremely low in Georgia, which means that in 40. the search for jobs, acquaintances, friends and relatives play the leading role.The non-institutionalized character of searching for jobs, which has not changed for years, denotes 41. the imperfection of the demand-supply mechanism on the labor market.

56

7. RecommendationsThe following recommendations were developed on the basis of the qualitative findings revealed as

a result of the research:In order to identify in-depth trends of the unemployment structure, it is necessary to conduct regular 1. complex analyses of the databases within the Integrated Household Survey. For more comprehensive study of unemployment and to develop a more effective employment pol-2. icy, the unemployment level should be calculated not only by the ILO criteria, but also using the aggregated indicator which also includes under-employment and hidden unemployment. In order to develop an effective employment policy, it is necessary to create a system of regular reg-3. istration of both the unemployed and job vacancies.It is expedient to start calculating the indicators of structural unemployment used in world practice; 4. including the construction of the Beveridge Curve.Taking into account that Georgia’s economy mainly creates jobs that require low qualifications, we 5. consider it necessary to speed up work on the Industrial Policy of Georgia which should determine the ways of transition to a knowledge-based competitive economy. As the largest group of unemployed are those who do not have professions, we consider it worth-6. while to develop a system that ensures the receipt of labor market-demanded certified professions by those who do not have professions.By taking into account that the majority of long-term unemployed are highly qualified profession-7. als, It would be expedient to conduct periodic research of the in-demand labor market professions that require a high level of qualification, as well as to regularly inform educational institutions about the results of those research and take the findings into account during the accreditation of education programs.As the weight of the real sector of the economy (without the agricultural sector) in total employment 8. does not increase, it is necessary to implement a more effective SME support policy in this sector, especially in terms of ensuring real access to finances.With the purpose of making a significant increase in the weight of the private sector in job genera-9. tion, we suggest a set of moral and financial (fiscal) incentives is developed for job creation by private enterprises.In order to ensure concurrence between the education background and real knowledge, it is essen-10. tial to make farther steps for improving the effectiveness of the quality management of higher and vocational education. The structure of professions offered by educational institutions should be in compliance with the 11. structure of the demand of the labor market, which requires the development of direct relations be-tween the educational institutions and the employers, their associations and leading HR companies.In order to address the problem of de-qualification of the labor force due to long-term unemploy-12. ment, it is necessary to establish an efficient system for identification and diagnosing of the long-term unemployed, and their professional rehabilitation or retraining.To increase the concurrence of the education system and labor market, we suggest including large 13. employers or their associations, and respective representatives of large HR companies in the process of the accreditation of appropriate educational programs. For further substantial reduction of the weight of rural self-employment in total employment, it is 14. necessary to speed up the concentration of agrarian farms through cooperation, development of agrarian clusters and the use of modern technologies. Taking into consideration that the hidden structural unemployment rate is substantially high in the 15. group of people with vocational education, we suggest revising the curricula of such educational institutions with regard to concurrence with the demands of the labor market and elaboration of targeted programs for the employment of graduates.Development of internet portals and organizing job fairs and weeks are not enough for improving 16.

57

the institutionalization level of job seeking - it is necessary to speed up the creation of the network of employment centers which is envisaged by the state strategy for formation of a labor market.In order to ensure the effectiveness of the programs elaborated within the frame of the employment 17. policy, we consider it essential to elaborate a complex system for monitoring and evaluation based on a net of measurable indicators.

58

8. Scenarios for Development of the Labor MarketUnemployment is a systemic problem and its reduction requires the implementation of complex meas-

ures. The present model cannot pretend for high preciseness, since elaboration of a precise model requires a wide circle of indicators. It is necessary to cooperate with the actors envisaged by the model and analyse the structure and possibilities. It is also important to study information arrays of institutional statistics and analyse informational flows.

The present model is based on the following three conditions, identified by the results of the study: High share of employed with qualifications lower than a certified profession in total employ-•

ment; High share of the labor force not having a certified profession in an economically active popula-•

tion; Amorphous high weight of self-employment in agriculture in total employment.•

Of the identified problems, the groups not having a certified profession and those self-employed in agriculture are substantially crosscutting.

Three scenarios for further development of the labor market are given below, a mean reduction of the scales of the above three problems:

Retraining of those not having a profession and encouraging them to obtain the skills in demand on • the labor market, which is outlined by recommendations Nos 6, 10, 11, 13 and 15;

Implementation of an efficient policy by the government in other equal conditions, with the pur-• pose of increasing the demand of the labor market for the professions necessary in the real sector, which is outlined in recommendations Nos 5, 8 and 9;

Reduction of the amorphous high number of self-employed in agriculture, to which the recom-• mendation No 14 is associated.

Due to the above mentioned, the following three scenarios are viewed:Scenario 1: The Ministry of Education and Science reviews the results of the survey, but the strate-

gies for vocational and higher education improves basically independently, without active participation of the ministries of Economy and Sustainable Development, Agriculture and Labor, Health and Social Af-fairs, due to which, the expected requirements of the labor market are not fully envisaged.

Chart N51

47% 47% 46% 46% 45% 45% 45% 44% 44% 43% 43% 43% 42% 42% 42%47% 46% 45% 44% 43% 42% 41% 40% 39% 38% 37% 36% 35% 34% 33%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Yr 11 Yr 12 Yr 13 Yr 14 Yr 15

The vector of possible change of aggregated unemployment level in case of implementationof 1st scenario

Option 1 Option 2

59

In such a case:The labor force retrained within the frame of vocational education will have just 24 percent chance •

for employment (taking into consideration in average 76 percent unemployment rate among those with vocational education);

The graduates of higher education institutions have a 34 percent chance for employment;• If the strategy for vocational education states merely the task of retraining and does not cover •

professional orientation of the students of upper grades of secondary school, almost 80 thousand11 individuals can be added to the potential labor force, of which about 60 thousand will be additional jobseekers, according to the existing proportions.

For the purpose of better illustration of the expected results of implementation of the first scenario, two options can be viewed (see Chart N 51): the first envisages professional retraining of 30 thousand in-dividuals during the year in conditions of an unchanged strategy for higher education, and second – voca-tional retraining of about 30 thousand individuals during the year and elaboration of the strategy of higher education with the focus on the labor market, independently from other public agencies.

Scenario 2: The Ministry of Economy and Sustainable Development takes into consideration the re-sults of the study and strengthens the policy focused on the increase of small and medium businesses in the real sector; at the same time the Ministry of Agriculture continues active promotion of the concentration of agrarian farms through cooperation and increase of their productivity. Taking into consideration these strategies, the Ministry of Education and Science ensures concurrence of the strategies12 of vocational and higher education with the demands of the labor market. Meanwhile, the level of institutionalization of the labor market is still low, i.e. the matching point of a trained labor force and announced vacancies is not institutionalized.

Chart N52

47% 47% 46% 45% 44% 44% 43% 42% 42% 41% 41% 40% 40% 39% 38%

47%46%

44%43%

41%40%

38%36%

35%33%

32%30%

29%27%

26%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%


The vector of possible change of aggregated unemployment levelin case of implementation of 2nd scenario

Option 1 Option 2

In such a case: 20 percent of the labor force retrained or having higher education and seeking jobs institutionally, •

have a very high chance to find employment, while for the remaining 80 percent, the chance remains the same as in the first scenario;

In order to better illustrate the implementation of this scenario, two options are viewed (see Chart N 52): the first envisages the retraining of about 30 thousand people during the year, in conditions of immu-11 According to data provided on the Geostat website12 In this scenario, vocational education should cover adults as well as students of the upper grades of secondary school.

60

tability of high education strategy, and second - vocational retraining of another about 30 thousand people during the year and elaboration of a strategy of higher education with the focus on the labor market.

Scenario 3: The Ministry of Economy and Sustainable Development takes into consideration the results of the survey and strengthens the policy focused on the increase of small and medium business in real economy sector. Further, the Ministry of Agriculture promotes the concentration of agrarian farms through cooperation and the increase of their productivity. The Ministry of Education and Science, also taking into consideration these strategies, ensures the concurrence of the strategies13 for vocational and higher education with the demands of the labor market; and the Ministry of Labor, Health and Social Af-fairs ensure the sharp increase of the level of institutionalization of the labor market.

Chart N53

The vector of possible change of aggregated unemployment level in case of implementationof 3rd scenario

Option1 Option 2

47%46%

44%42%

41%39%

38%36%

35%33%

32%30%

29%27%

26%

47%44%

42%39%

36%33%

31%28%

25%22%

19%17%

14%11%

8%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

In such case: The weight of retrained individuals or those with higher education, seeking jobs institutionally, •

will be substantially increased; they will have higher chances for employment. However, part of the labor force will continue non-institutional job seeking. Precise forecasting of this proportion is very difficult. Following the Pareto principle, it can compile 80:20. In other words, the weight of individuals seeking jobs institutionally will be increased up to 80 percent, while the weight of those seeking job not institutionally will be decreased to 20 percent.

Like in the previous scenarios, for better illustration of the expected results of implementation of this scenario, two options are viewed (see Chart N 53): the first envisages vocational training of about 30 thou-sand individuals during the year, in conditions of immutability of the higher education strategy, and the second - the vocational training of another 30 thousand people during the year and elaboration of a higher education strategy with the focus on the labor market.

The above mentioned analyses demonstrate that merely a focus on vocational education is not enough to solve the systemic problem of structural unemployment as this requires qualitative change at each stage of education.

It is clear that the problems accumulated over 30 years cannot be resolved promptly and the results of any, even the most effective measure, will need years to become substantial.

The simultaneous operation of one or several structures is not enough to achieve significant results, since that requires a synergy of all relevant structures. 13 In this scenario, vocational education should cover adults as well the students of the upper grades

61

Implementation of this task with complex content will be impossible without proper monitoring and assessment systems.

The present calculations demonstrate a basic direction, and they are far from the real model since its elaboration requires much more detailed institutional statistics and inside information. However, this is the first attempt to study the structure of unemployment and structural unemployment in Georgia and its further extension is not just desirable, but essential.

62

9. SourcesThe Government of Georgia, 2013. Decree N199, dated 2 August 2013. On approval of the state 1. strategy for formation of a labor market of Georgia and the action plan for realization of the state strategy for formation of a labor market of Georgia in 2013-2014; http://ssa.gov.ge/files/01_GEO/KANONMDEBLOBA/Kanon%20Qvemdebare/73.pdfThe Government of Georgia, 2014. Decree N400, dated 17 June 2014. On approval of the strategy 2. for social economic development of Georgia “Georgia 2020” and associated activities; https://mat-sne.gov.ge/ka/document/view/2373855The Government of Georgia, 2014. Decree N733, dated 26 December 2014. On approval of the con-3. cept for implementation and development of the information system of labor market and its action plan; https://matsne.gov.ge/ka/document/view/265970Geostat. Integrated Household Survey, databases of 2009, 2010, 2011, 2012, 2013, 2014 and 2015, 4. http://www.geostat.ge/?action=meurneoba_archive&lang=geoUSAID, IOM, 2010. National Labor Market of Georgia, the report of the study conducted in June – 5. July 2010, Tbilisi, USAID, IMO. http://www.mes.gov.ge/uploads/LMS_2010_Geo.pdf USAID, IOM, 2011. Supply of the labor force to the labor market of Georgia, the report of the study 6. carried out in February - March 2011, Tbilisi, USAID, IMO.EPRC, 2011. Employment and unemployment trends in Georgia, November, 2011. Tbilisi EPRC, 7. https://www.osgf.ge/files/publications/2011/EPRC_Georgian_Economic_Outlook_II,_Nov_2011_GEO.pdfBusiness Consulting Group (BCG), 2014. Labor Market Survey. 8. Business Consulting (BCG), 2015. Survey of labor market demand component, The Ministry of 9. Labor, Health and Social Affairs, http://www.moh.gov.ge/files/01_GEO/Shroma/kvleva/33.pdfACT, 2015. Survey of employers’ attitudes towards vocational education, the report of the study; 10. Tbilisi UNDP, http://www.mes.gov.ge/content.php?id=5962&lang=geoHussmanns R., Mehran F., Verma V., 1992. Surveys of the economically active population, employ-11. ment, unemployment and under-employment: An 110 manual on concepts and methods. Geneva, ILO. http://www.ilo.org/public/english/bureau/stat/download/lfs.pdfHussmanns R., Measurement of employment, unemployment and under-employment – Current in-12. ternational standards and issues in their application. http://ilo.org/public/english/bureau/stat/down-load/articles/2007-1.pdfKvaratskhelia V., Mukbaniani N., 2011. Unemployment and Labor Market Policy in Georgia. Tbi-13. lisi, Ivane Javakhishvili Tbilisi State University, http://iset.tsu.ge/files/5._valeriane_kvaratskhelia_and_nana_mukbaniani.pdfAring M., 2012. Report on Skills Gaps, Background paper prepared for the Education for All Glo-14. bal Monitoring Report 2012 Youth and skills: Putting education to work. UNESCO, http://unesdoc.unesco.org/images/0021/002178/217874e.pdfDilanchiev A., 2014. Relationship between Entrepreneurship and Unemployment: The Case of 15. Georgia. Journal of Social Sciences; Vol. 3, Issue 2, http://journal.ibsu.edu.ge/index.php/jss/article/view/637/533Arias O., Sánchez-Páramo C., Dávalos M., Santos I, Tiongson E., Gruen C., De Andrade Falcao N., 16. Saiovici G., Cancho C., 2014. Back to Work. Growing with Jobs in Europe and Central Asia, Wash-ington, DC, THE WORLD BANK, http://www.worldbank.org/content/dam/Worldbank/document/Back-to-Work-Full.pdfDEG, the Boston Consulting Group (BCG), 2016. Bridging the skills gaps in developing countries. 17. A practical guide for private-sector companies. EDFI., file:///C:/Users/USER/Desktop/EDFI%20lets%20work%20partnership%20-%20Bridging%20Skills%20Gaps%20Report%20-%20DEG%202016.pdf

óëóøäåðíáèñ ñòðóõòóðàãà ñòðóõòóðóêè óëóøäåðíáàñàõàðçåäêíøè

2016

óëóøäåðíáèñ ñòðóõòóðà ãàñòðóõòóðóêè óëóøäåðíáà

ñàõàðçåäêíøè

2016

éåêäåà âàìàþíðúèäêà ñàõàðçåäêíñ ñòðàòäâèèñà ãà ñàäðçàøíðèñí óðçèäðçíáäáèñ éåêäåèñ ôíìãëà (ðíìãäêèñ ôíìãè) ôðèãðèþ äáäðòèñ ôíìãèñ ëþàðãàýäðèç.

îðíäõòèñ éííðãèìàòíðè, éåêäåèñ þäêëûöåàìäêè: îðíôäñíðè ëäðàá éàéóêèàóôðíñè ëéåêäåàðè: ìíãàð éàîàìàûäëéåêäåàðäáè: åàþòàìâ êíëÿàðèà, êàêè õóðþóêè

ðäãàõòíðè: îðíôäñíðè èíñäá àðùåàûä

îóáêèéàúèàøè üàðëíãâäìèêèà àåòíðçà îèðàãè ëíñàæðäáäáè.ãàóøåäáäêèà ôðèãðèþ äáäðòèñ ôíìãèñ ëèäð âàëíúäëóêè ëàñàêäáèñ éíëäðúèóêè ëèæìèç âàëí÷äìäáà ôíìãèñ çàìþëíáèñ âàðäøä.

© ôðèãðèþ äáäðòèñ ôíìãè, 2016

ISBN 978-9941-0-9430-9

ñàðùäåèñàðùäåè

1. øäñàåàêè1. øäñàåàêè .............................................................................................................................. .............................................................................................................................. 51.1 უმუშევრობის სტატისტიკური აღრიცხვა საქართველოში ...........................................................51.2 კვლევის ამოცანა და მიზნები .............................................................................................................61.3 კვლევის წყაროები ................................................................................................................................71.4 კვლევის მეთოდოლოგია .....................................................................................................................7

2. óëóøäåðíáèñ ñòðóõòóðà2. óëóøäåðíáèñ ñòðóõòóðà .................................................................................................. .................................................................................................. 92.1 უმუშევრობის აგრეგირებული დონის შეფასება.............................................................................92.2 უმუშევრობისა და დასაქმების კვალიფიკაციური სტრუქტურის შესაბამისობა ....................112.3 უმუშევრობის დინამიკა კვალიფიკაციის მიხედვით ..................................................................152.4 უმუშევრობის სტრუქტურა ხანგრძლივობის მიხედვით ............................................................172.5 უმუშევრობის სტრუქტურა განათლების მიღწეული დონის მიხედვით ................................20

3. ãàñàõëäáèñ ñòðóõòóðà3. ãàñàõëäáèñ ñòðóõòóðà .................................................................................................... .................................................................................................... 223.1 დასაქმების სექტორული სტრუქტურა ...........................................................................................223.2 სამუშაო ადგილების გენერაციის წყაროები ..................................................................................28

4. ñòðóõòóðóêè óëóøäåðíáà4. ñòðóõòóðóêè óëóøäåðíáà ............................................................................................ ............................................................................................ 314.1 სტრუქტურული უმუშევრობა: მეთოდოლოგიური ასპექტი .....................................................314.2 ხანგრძლივი უმუშევრობა და დეკვალიფიკაცია, როგორც სტრუქტურული უმუშევრობის

გამოვლინება .........................................................................................................................................324.3 „დაუკმაყოფილებელი“ დასაქმებულები ანუ ფარული სტრუქტურული უმუშევრობა .......344.4 შრომის ბაზრის მოთხოვნისა და მიწოდების სტრუქტურული თავსებადობა .......................384.5 საგანმანათლებლო სისტემის ეფექტიანობა სტრუქტურული უმუშევრობის კონტექსტში .47

5. øðíëèñ áàæðèñ èìñòèòóúèóðè ñèñóñòääáè5. øðíëèñ áàæðèñ èìñòèòóúèóðè ñèñóñòääáè .................................................................... .................................................................... 53

6. ûèðèçàãè ëèâìäáäáè6. ûèðèçàãè ëèâìäáäáè ........................................................................................................... ........................................................................................................... 566.1 ემპირიული მიგნებები .......................................................................................................................566.2 თვისობრივი მიგნებები .....................................................................................................................58

7. ðäéíëäìãàúèäáè7. ðäéíëäìãàúèäáè ................................................................................................................ ................................................................................................................ 60

8. øðíëèñ áàæðèñ âàìåèçàðäáèñ ñúäìàðäáè8. øðíëèñ áàæðèñ âàìåèçàðäáèñ ñúäìàðäáè ......................................................................... ......................................................................... 62

9. ü÷àðíäáè9. ü÷àðíäáè ............................................................................................................................ ............................................................................................................................ 66

10. ãàìàðçäáè10. ãàìàðçäáè ........................................................................................................................ ........................................................................................................................ 67დანართი N1 ...............................................................................................................................................67დანართი N2 ...............................................................................................................................................68დანართი N3 ...............................................................................................................................................69

5

1. øäñàåàêè1. øäñàåàêè

1.1 óëóøäåðíáèñ ñòàòèñòèéóðè àöðèúþåà ñàõàðçåäêíøè1.1 óëóøäåðíáèñ ñòàòèñòèéóðè àöðèúþåà ñàõàðçåäêíøè

ñàõàðçåäêíøè óëóøäåðíáèñ ñòàòèñòèéàñ ñòàòèñòèéèñ äðíåìóêè ñàëñàþóðè (ñàõñòàòè) àüàðëíäáñ. èìôíðëàúèèñ ëçàåàðè ü÷àðí ñàõàðçåäêíñ øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåàà.

1996-2001 üêäáøè ëíñàþêäíáèñ äéíìíëèéóðè ñòàòóñèñ øäôàñäáà þãäáíãà ëþíêíã ëíéêä éèçþåàðèç, ðíëäêèú àð èûêäíãà ñàéèçþèñ öðëà àìàêèæèñ øäñàûêäáêíáàñ. 2000-2001 üêäáøè ëíþãà øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ çåèñíáðèåè âàóëÿíáäñäáà, ðèñ øäëãäâàú âàëíéåêäåèñ ôàðâêäáøè ãàèü÷í ãàñàõëäáèñà ãà óëóøäåðíáèñ ãäòàêóðè øäñüàåêà. àëèñçåèñ âàëíè÷äìäáà øèìàëäóðìäíáäáèñ èìòäâðèðäáóê âàëíéåêäåèñ èìñòðóëäìòè ,,øèìãà05_1“1, ðíëêèñ ëäøåäíáèçàú âàëíèéèçþäáà øäðùäóêè øèìàëäóðìäíáèñ 15 üêèñà ãà óôðíñè àñàéèñ çèçíäóêè üäåðè.

áíêí 20 üêèñ âàìëàåêíáàøè õàðçóê ñàæíâàãíäáàøè óëóøäåðíáèñ ãíìä ëàöàêè èìòäðäñèñà ãà ëóãëèåè âàìñÿèñ ñàâàìèà. þøèðàã èñëèñ îðäòäìæèà èëèñ øäñàþäá, ðíë äñ ëàùåäìäáäêè þäêíåìóðàãàà øäëúèðäáóêè. çóëúà, çó ñàéèçþèñ àðññ óôðí öðëàã ùàåüåãäáèç, óëóøäåðíáèñ àðñäáóêè, çóìãàú øäëúèðäáóêè ãíìä, ðíëäêèú øðíëèñ ñàäðçàøíðèñí íðâàìèæàúèèñ (øñí) éðèòäðèóëäáèñ âàçåàêèñüèìäáèç àðèñ ãàãâäìèêè, ðíâíðú õåäëíç åìàþàåç, ñóêàú àð àðèñ ãàáàêè.

ëèóþäãàåàã àëèñà, øñí-èñ éðèòäðèóëäáèç âàìñàæöåðóêè óëóøäåðíáèñ ãíìèñ ëàùåäìäáäêè àð èûêäåà àë ëüåàåä ñíúèàêóðè ãà äéíìíëèéóðè îðíáêäëèñ éíëîêäõñóðè øäôàñäáèñ øäñàûêäáêíáàñ. ëàâàêèçàã, èâè àð ëíèúàåñ àðàñðóê ãàñàõëäáàñà ãà ôàðóê óëóøäåðíáàñ - ëíåêäìäáñ, ðíëêäáèú ôàðçíãàà âàåðúäêäáóêè âàðãàëàåàêè äéíìíëèéèñ ëõíìä õåä÷ìäáøè, ëàç øíðèñ ñàõàðçåäêíøèú. øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëçà áàæà àðàñðóêè ãàñàõëäáèñ ãà ôàðóêè óëóøäåðíáèñ àìàêèæèñ ñàøóàêäáàñàú èûêäåà.

øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëçà áàæà øäèúàåñ àâðäçåä èìôíðëàúèàñ óëóøäåðíáèñ éåàêèôèéàúèóðè ñòðóõòóðèñ, ëèñè þàìâðûêèåíáèñ ëèþäãåèç ãèôäðäìúèàúèèñ, ñàëóøàí àãâèêäáèñ âäìäðàúèèñ ü÷àðíäáèñ ãà ñòðóõòóðóêè óëóøäåðíáèñ (Skills Gap) øäñàþäá, ðíëêèñ ðäâóêàðóêè ãàëóøàåäáà, ðíâíðú üäñè, àð þíðúèäêãäáà. àðàãà óëóøäåðíáèñ ñþåàãàñþåà ñòðóõòóðóêè àñîäõòèñà ãà ñòðóõòóðóêè óëóøäåðíáèñ ëíìàúäëçà àìàêèæè ëìèøåìäêíåàìè ãàñéåìäáèñ âàëíòàìèñ øäñàûêäáêíáàñ èûêäåà ãàñàõëäáèñ îíêèòèéèñà ãà æíâàãàã äéíìíëèéóðè îíêèòèéèñ äôäõòèàìíáèñ àñàëàöêäáêàã.

óëóøäåðíáèñ ñòðóõòóðèñà ãà ñòðóõòóðóêè óëóøäåðíáèñ ñèöðëèñäóêè òäìãäìúèäáèñ âàëíåêäìà áäåðàãàà ãàëíéèãäáóêè óëóøäåàðçà ëèëãèìàðä àöðèúþåèñ ñèñòäëèñ âàëàðçóêíáàæä. óëóøäåðíáèñ ëèëãèìàðä àöðèúþåèñ ñàëñàþóðè ñàõàðçåäêíøè 2004 üêàëãä àðñäáíáãà, çóëúà âàëàðçóêàã ëàñ àðàñãðíñ óëóøàåèà. ëíõàêàõääáè àõ ðäâèñòðèðãäáíãìäì, ðíâíðú óëóøäåðäáè, ëàâðàë àë ñèñòäëèç ëíúóêè ãàñàõëäáèñ ëñóðåäêçà ðàíãäìíáà óëìèøåìäêí è÷í (èþèêäç ãèàâðàëà N1).

óëóøäåàðçà ëèëãèìàðä àöðèúþåèñ ñèñòäëèñ àðàäôäõòèàìíáà ñðóêèàã éàìíìæíëèäðè è÷í, ðàãâàìàú óëóøäåðàã ðäâèñòðàúèà ãàñàõëäáèñ àðàìàèð îäðñîäõòèåàñ àð øäèúàåãà, þíêí óëóøäåðíáèñ øäëüäíáà ûàêèàì ëúèðä è÷í. ÷íåäêèåä äñ ìàçêàã àñàþàåãà íðè ñàóéóìèñ ëèÿìàæä ñàõàðçåäêíñ äéíìíëèéàøè àðñäáóê óàöðäñàã ðçóê ãà ñàåàêàêí åèçàðäáàñ. àöñàìèøìàåèà èñèú, ðíë àð àðñäáíáãà åàéàìñèäáèñ àöðèúþåèñ ñèñòäëàú, ðàú àæðñ óéàðâàåãà óëóøäåðíáèñ ëèëãèìàðä àöðèúþåàñ. ìèøàìãíáêèåèà, ðíë åàéàìñèäáèñ àöðèúþåà àðú àþêà àðñäáíáñ ãà øäñàáàëèñàã, àë òèîèñ èìôíðëàúèóêè ëàñèåäáèñ ëíûèäáà ãöäñàú øäóûêäáäêèà.

1 éèçþåàðè âàìçàåñäáóêèà ñòàòèñòèéèñ äðíåìóêè ñàëñàþóðèñ åäá-âåäðãæä. èþèêäç áëóêè: http://www.geostat.ge/cms/site_images/_files/georgian/kitxvarebi/shinda/Shinda05-1_2015_Geo.pdf

6

ãèàâðàëà N1

13%2% 4% 3% 3%

10%

73% 95% 92% 94% 93%87%

15%3% 4% 3% 4% 3%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1997 1998 1999 2000 2001 2002

უმუშევართა განაწილება უმუშევრად რეგისტრაციის მიხედვით

რეგისტრირებული უმუშევრები არარეგისტრირებული უმუშევრები

რეგისტრაციის სტატუსი გაურკვეველია

ü÷àðí: ñàõñòàòè. ñòàòèñòèéóðè üäêèüãäóêè, 2004.

óëóøäåðíáèñ ñòðóõòóðèñ öðëà àìàêèæè øäñàûêäáäêèà ëþíêíã óëóøäåàðçà ëèëãèìàðä àöðèúþåèñ âàëàðçóêè ñèñòäëèñ îèðíáäáøè. åèìàèãàì ñàõàðçåäêíøè àñäçè ñèñòäëà àð àðñäáíáñ, ëþíêíã øäðùäåèçè âàëíéåêäåèñ øäôàñäáäáèç óìãà øäëíåèôàðâêíç, àìó éåêàå óìãà ãàåä÷ðãìíç øèìàëäóðìäíáàçà èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëçà áàæäáñ. ëàðçàêèà, äñ ñþåà ðäâèñòðèñ ëíìàúäëäáèà ãà óëóøäåàðçà ëèëãèìàðä àöðèúþåèñ ñèñòäëèñ ôóìõúèäáñ åäð øäàñðóêäáñ, ëàâðàë ëèñ ñàôóûåäêæä èõëìäáà âàðéåäóêè ¸íëíâäìóðè èìôíðëàúèèñ ãðíèçè ëüéðèåè, ðíëäêèú ùàëí÷àêèáäáóêè òäìãäìúèäáèñ éåêäåèñ øäñàûêäáêíáàñ èûêäåà.

1.2 éåêäåèñ àëíúàìà ãà ëèæìäáè1.2 éåêäåèñ àëíúàìà ãà ëèæìäáè

üèìàëãäáàðä éåêäåèñ ûèðèçàãè àëíúàìàà ñàõàðçåäêíøè óëóøäåðíáèñ ñòðóõòóðóêè àñîäõòäáèñ ãà ñòðóõòóðóêè óëóøäåðíáèñ øäñüàåêà, ðíëäêèú ñúèêãäáà øðíëèñ ñàäðçàøíðèñí íðâàìèæàúèèñ éðèòäðèóëäáèç óëóøäåðíáèñ ãíìèñ øäôàñäáèñ ùàðùíñ ãà ëèæìàã èñàþàåñ:

óëóøäåðíáèñ àâðäâèðäáóêè ãíìèñ ãà ëèñè ñòðóõòóðèñ øäôàñäáàñ;1. óëóøäåðíáèñ ñòðóõòóðèñ àìàêèæñ, ëàç øíðèñ: 2.

éåàêèôèéàúèäáèñ ëèþäãåèç;• þàìâðûêèåíáèñ ëèþäãåèç;• âàìàçêäáèñ ëèöüäóêè ãíìèñ ëèþäãåèç;•

ñàëóøàí àãâèêäáèñ âäìäðàúèèñ ü÷àðíäáèñ ñòðóõòóðèñ ãàãâäìàñ;3. ñòðóõòóðóêè óëóøäåðíáèñ (Skills Gap) àìàêèæñ, ëàç øíðèñ:4.

þàìâðûêèåè óëóøäåðíáèñà ãà ãäéåàêèôèéàúèèñ øäñüàåêàñ;• „ãàóéëà÷íôèêäáäêè“ ãàñàõëäáóêäáèñà ãà ôàðóêè ñòðóõòóðóêè óëóøäåðíáèñ •

âàëíéåêäåàñ;øðíëèñ áàæðèñ ëíçþíåìèñà ãà ëèüíãäáèñ ñòðóõòóðóêè çàåñäáàãíáèñ øäñüàåêàñ;• ñàâàìëàìàçêäáêí ñèñòäëèñ äôäõòèàìíáèñ àìàêèæñ ñòðóõòóðóêè óëóøäåðíáèñ •

àñîäõòøè.øðíëèñ áàæðèñ èìñòèòóúèóðè ñèñóñòääáèñ ãàãâäìàñ;5. øðíëèñ áàæðèñ âàìåèçàðäáèñ ñúäìàðäáèñ ùàëí÷àêèáäáàñ.6.

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1.3 éåêäåèñ ü÷àðíäáè1.3 éåêäåèñ ü÷àðíäáè

ãàñàþóêè ëèæìäáèñ ëèñàöüäåàã éåêäåàøè èìôíðëàúèèñ ðàëãäìèëä ü÷àðí èõìà âàëí÷äìäáóêè, ðíëäêçàâàìàú ÷åäêàæä ëìèøåìäêíåàìèà øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåà.

øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåà 1996 üêèãàì ãöäëãä óü÷åäò ðäïèëøè þíðúèäêãäáà. øäãäâàã ãàâðíåãà ñàéëàíã þàìâðûêèåè ãðíèçè ëüéðèåè, ðíëäêèú óëóøäåðíáèñ ãà ãàñàõëäáèñ ñèöðëèñäóêè àìàêèæèñ ôàðçí øäñàûêäáêíáäáñ èûêäåà. âàëíéåêäåèñ îèðåäêàãè ëíìàúäëçà áàæäáè þäêëèñàüåãíëèà ñàõàðçåäêíñ ñòàòèñòèéèñ äðíåìóêè ñàëñàþóðèñ (ñàõñòàòè) åäá-âåäðãæä.2 àõåäà üàðëíãâäìèêè âàëíéåêäåèñ èìñòðóëäìòàðèóëèú.3 àöìèøìóêè ëíìàúäëçà áàæà óëóøäåðíáèñ ñòðóõòóðóêè ãà ñèñòäëóðè çàåèñäáóðäáäáèñ øäñàþäá óæàðëàæàð, çóëúà øðíëèñ áàæàðæä ëíçþíåìà-ëèüíãäáèñ øäñàþäá ñàæíâàãíäáèñ çàìàëäãðíåä ëíçþíåìèêäáäáçàì øäãàðäáèç óàöðäñàã àðàñàéëàðèñ èìôíðëàúèàñ èûêäåà. øäñàáàëèñàã, øðíëèñ áàæàðæä ëíçþíåìà-ëèüíãäáèñ ñðóê÷íôèêè ñóðàçèñ øäñàõëìäêàã ñàýèðíà ãàëàòäáèçè èìôíðëàúèèñ ëíûèäáà.

øðíëèñ áàæðèñ éíìèóìõòóðèñ àìàêèæèñàçåèñ âàëí÷äìäáóê èõìà îðíôäñèóêè âàìàçêäáèñ ëèëàðç ãàëñàõëäáäêçà ãàëíéèãäáóêäáèñ âàëíéåêäåèñ àìâàðèøè, ðíëäêèú ùàòàðãà éíëîàìèà äè-ñè-çè-ñ ëèäð 2015 üäêñ ñàõàðçåäêíñ âàìàçêäáèñ ãà ëäúìèäðäáèñ ñàëèìèñòðíñ ãàéåäçèç.4 âàëí÷äìäáóêè èõìà àâðäçåä øðíëèñ áàæðèñ ëíçþíåìèñ éíëîíìäìòèñ âàëíéåêäåèñ àìâàðèøè, ðíëäêèú ùàòàðãà 2015 üäêñ éíëîàìèà áè-ñè-ÿè-ñ ëèäð øðíëèñ, ÿàìëðçäêíáèñà ãà ñíúèàêóðè ãàúåèñ ñàëèìèñòðíñ ãàéåäçèç.5

øðíëèñ áàæàðæä ëíçþíåìà-ëèüíãäáèñ àðñäáóêè ëãâíëàðäíáèñ óôðí ñðóê÷íôèêè øäôàñäáèñ ëèæìèç îðíäõòèñ ôàðâêäáøè ãàèâäâëà ãàñàõëäáèñ ëäòìàéêäáàã èìñòèòóúèíìàêèæäáóê ñàèìôíðëàúèí ü÷àðíäáøè àðñäáóêè øäçàåàæäáäáèñ ñèñòäëàòèæàúèà, ëíìàúäëçà áàæèñ ôíðëèðäáà ãà àìàêèæè.

àëâåàð ñàèìôíðëàúèí ü÷àðíäáàã ëèùìäóê èõìà:à) âàæäçè „ñèò÷åà ãà ñàõëä“, ðíëäêèú âàëíãèñ ÷íåäêéåèðäóêàã ãà ñàõàðçåäêíøè ÷åäêàæä

ãèãòèðàïèàì âàëíúäëàñ üàðëíàãâäìñ. áäýãóð ëäãèàøè èâè îðàõòèéóêàã äðçàãäðçè ü÷àðíà, ñàãàú ñàëóøàíñ ûäáìàñçàì ãàéàåøèðäáóêè âàìúþàãäáäáè õåä÷ìãäáà. àìàêíâèóðè èìôíðëàúèà õåä÷ìãäáà ñþåà âàæäçäáøèú, ëàâðàë ëàçè òèðàïè, âàåðúäêäáèñ àðäàêè - øäæöóãóêè, þíêí âàëíõåä÷ìäáóêè âàìúþàãäáäáèñ ðàíãäìíáà - ûàêèàì ëúèðäà;

á) åäá ðäñóðñè - jobs.ge, ðíëäêèú ãàñàõëäáèñ ûèðèçàã äêäõòðíìóê ñàèìôíðëàúèí ü÷àðíñ üàðëíàãâäìñ. ãààþêíäáèç çàìàæíëåàãè ëàñøòàáèñ ñàèìôíðëàúèí ü÷àðíã øäèûêäáà âàìåèþèêíç åäá ðäñóðñè HR.ge, ñàãàú õåä÷ìãäáà ñàÿàðí ñäõòíðøè àðñäáóêè åàéàìñèäáè, ëàâðàë éåêäåèñ ñîäúèôèéèãàì âàëíëãèìàðä, ôíéóñèðäáà èìôíðëàúèèñ øäãàðäáèç óìèåäðñàêóðè ü÷àðíñ - jobs.ge-èñ ëíìàúäëäáæä ëíþãà.

âàðãà àëèñà, éåêäåèñ ëèæìäáèãàì âàëíëãèìàðä îðíäõòèñ ôàðâêäáøè âàìþíðúèäêãà ùàöðëàåäáóêè èìòäðåèó ñþåàãàñþåà ãàðâèñ 10 ëñþåèê ãàëñàõëäáäêçàì (èþèêäç ãàìàðçè N2).

1.4 éåêäåèñ ëäçíãíêíâèà1.4 éåêäåèñ ëäçíãíêíâèà

ñàõàðçåäêíøè øðíëèñ áàæðèñ èìñòèòóúèíìàêèæàúèèñ þàðèñþè ûàêèàì ãàáàêèà. ñàõàðçåäêíøè ãàõèðàåäáèç ãàñàõëäáóêçà üèêè äéíìíëèéóðàã àõòèóð ëíñàþêäíáàøè, ñàõñòàòèñ áíêí ëíìàúäëäáèç, øäàãâäìñ ëþíêíã 37.3 îðíúäìòñ, ëàç øíðèñ çèçõëèñ ìàþäåàðè - ñàþäêëüèôí, ñàÿàðí ñäõòíðøè ãàñàõëäáóêäáæä ëíãèñ. àñäåä, ûàêèàì ãàáàêèà, ðíâíðú óéåä àöåìèøìäç, óëóøäåðíáèñ ëèëãèìàðä ñòàòèñòèéóðè àöðèúþåèñ þàðèñþè. äðçàãäðçè ñòàìãàðòäáèñ øäñàáàëèñè èìôíðëàúèóêè ëàñèåè øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëçà áàæàà. üèìàëãäáàðä éåêäåèñ ëèæìäáèñçåèñ àóúèêäáäêè âàþãà àöìèøìóêè áàæèñ ãàëàòäáèçè ãàëóøàåäáà, ðèñ ñàôóûåäêæäú ëíþäðþãà 2009-2015 üêäáèñ ãðíèçè ëüéðèåäáèñ ëðàåàêëþðèåè àìàêèæè.

àöìèøìóêè àìàêèæè, óüèìàðäñ ÷íåêèñà, âàìþíðúèäêãà øñí-èñ éðèòäðèóëäáñ ëèöëà ãàðùäìèêè èñäçè ñíúèàêóðè îêàñòäáèñ ðàíãäìíáðèåè øäôàñäáèñçåèñ, ðíâíðèúàà àðàñðóêè ãàñàõëäáà ãà ôàðóêè óëóøäåðíáà, ðàëàú øäñàûêäáäêè âàþàãà óëóøäåðíáèñ àâðäâèðäáóêè ãíìèñ ëàùåäìäáêèñ âààìâàðèøäáà ãà ëèñè ãèìàëèéèñà ãà ñòðóõòóðèñ ãàãâäìà.

2 http://www.geostat.ge/?action=meurneoba_archive&lang=geo3 http://www.geostat.ge/?action=page&p_id=697&lang=geo4 http://www.mes.gov.ge/content.php?id=5962&lang=geo5 http://www.moh.gov.ge/files/2015/Failebi/29.12.15.pdf

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øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëçà áàæèñ ãàëàòäáèçè àìàêèæèñ ñàôóûåäêæä îàñóþè âàäúà éèçþåàñ: ðàñ ñçàåàæíáäì óëóøäåðäáè îíòäìúèóð ãàëñàõëäáêäáñ? àë ëèæìèç ëíþãà øñí-èñ éðèòäðèóëèç âàëíåêäìèê óëóøäåàðçà îðíôäñèóêè ãà éåàêèôèéàúèóðè ñòðóõòóðèñ øäñüàåêà. âàëíéåêäåèñ éèçþåàðøè âàçåàêèñüèìäáóêèà ðäñîíìãäìòäáèñ ãèîêíëèñ àì ñþåà ñäðòèôèéàòèñ ëèþäãåèç ûèðèçàãè îðíôäñèèñ ëèçèçäáà. øäñàáàëèñàã âàéäçãà ãàøåäáà, ðíë óëóøäåðäáè ñàëñàþóðñ çàåèñè îðíôäñèèñ ëèþäãåèç äûäáäì.

øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ éèçþåàðè èçåàêèñüèìäáñ ñàëóøàíñ ñþåàãàñþåà ôíðëèç ûäáìèñ àìàêèæèñ øäñàûêäáêíáàñ. àëãäìàã îàñóþè âàäúà éèçþåàñ çó ðíâíð äûäáñ óëóøäåàðè ñàëóøàíñ? éèçþåàðèãàì èëèñ âàðéåäåàú øäèûêäáà, çó ðà ôíðëèç àëÿíáèìäáäì óëóøäåðäáè ãàñàõëäáàñ - ãàõèðàåäáèç çó çåèçãàñàõëäáèç?

èëàåä ü÷àðíãàì øäñàûêäáäêèà èëèñ øäôàñäáàú, çó ðàëãäìàãàà èìñòèòóúèóð ùàðùíäáøè ëíõúäóêè ñàëóøàíñ ûäáìèñ îðíúäñè? ðíâíðèà àë îðíúäñøè ñíúèàêóðè éàîèòàêèñ (ìàçäñàåäáèñà ãà ìàúìíá-ëäâíáðäáèñ) ãà èìñòèòóúèóðè ðäñóðñäáèñ âàìàüèêäáà? ðàëãäì þàìñ âðûäêãäáà ñàëóøàíñ ûäáìà? ãà à.ø.

÷åäêàæä ãèã ñèðçóêäñ ëíúäëóêè éåêäåèçè îðíäõòèñ âàìþíðúèäêäáèñ îðíúäñøè üàðëíàãâäìãà ñòðóõòóðóêè óëóøäåðíáèñ àìó øðíëèñ áàæàðæä ñàëóøàí ûàêèñ ëíçþíåìèñà ãà ëèüíãäáèñ éåàêèôèéàúèóðè ñòðóõòóðäáèñ øäóñàáàëíáèñ (Skills Gap) ðàíãäìíáðèåè øäôàñäáà, ðíëêèñ ñòàìãàðòóêè ëäçíãíêíâèà àð àðñäáíáñ. øñí-èñ åäá-âåäðãæä ëíûèäáóêè ëàñàêäáèñ ëèþäãåèç ñòðóõòóðóêè óëóøäåðíáèñ éíìúäôúèà ëþíêíã óëóøäåðíáèñ àë òèîèñ ãäòàêóðè âàìëàðòäáèç øäëíèôàðâêäáà.6 ñòðóõòóðóêè óëóøäåðíáèñ âààìâàðèøäáèñ ëàâàêèçäáèñ øäñüàåêàë àùåäìà, ðíë àë ëíåêäìèñ ðàíãäìíáðèåè øäôàñäáà âóêèñþëíáñ øðíëèñ áàæðèñ èìñòèòóúèíìàêèæàúèèñ ëàöàê ãíìäñ, ðíãäñàú éíëîàìèäáèãàì çàìàëøðíëêäáèñ âàìçàåèñóôêäáèñ ãà ãàñàõëäáèñ øäñàþäá ãäòàêóðè èìôíðëàúèà çàåñ è÷ðèñ ðíëäêèëä äðç óü÷äáàøè.

øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëäáèñ ëèþäãåèç øäñàûêäáäêèà ëþíêíã ñòðóõòóðóêè óëóøäåðíáèñ úàêéäóêè àñîäõòäáèñ ðàíãäìíáðèåè øäôàñäáà, ðàú, úþàãèà, ñðóê ñóðàçñ åäð èûêäåà. ëàâàêèçàã, óëóøäåðíáèñ þàìâðûêèåíáèñ àìàêèæè âàðéåäóê üàðëíãâäìàñ èûêäåà ñòðóõòóðóêè óëóøäåðíáèñ ëàñøòàáèñ øäñàþäá. àë ëþðèå ñàèìòäðäñíà ôàõòèóðè ãà ãèîêíëèñ ëèþäãåèç îðíôäñèäáèñ øäãàðäáèçè àìàêèæè, ðíëêèñ ñàôóûåäêæä øäèûêäáà éåàêèôèéàúèèñ øäñàáàëèñàã ãàñàõëäáèñ ãíìèñ ëàùåäìäáêèñ âààìâàðèøäáà, ðàú øèìààðñèç ûàêèàì àþêíñàà ñòðóõòóðóêè óëóøäåðíáèñ ëàùåäìäáäêçàì. ëèóþäãàåàã àëèñà, øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ãàëàòäáèçè àìàêèæèñ øäãäâàã ëèöäáóêè ëàùåäìäáêäáè åäð àìàúåêäáñ øðíëèñ áàæðèñ èìñòèòóúèíìàêèæàúèèñ þàðèñþèñ ëìèøåìäêíáàñ ñòðóõòóðóêè óëóøäåðíáèñ ñðóêôàñíåàì øäôàñäáàøè.

ñàëóøàíñ ûäáìèñ îðíúäñè ñàõàðçåäêíøè ëþíêíã ìàüèêíáðèåàà èìñòèòóúèíìàêèæäáóêè, èñèú èñä, ðíë ðàíãäìíáðèåè ãà çåèñíáðèåè àìàêèæèñ øäñàûêäáêíáäáè ëèìèëóëàëãäà ãà÷åàìèêè. éäðûíã, àð àðèñ éêàñèôèúèðäáóêè øäçàåàæäáóêè åàéàìñèäáè. àëãäìàã îèðåäê äòàîæä àóúèêäáäêè âàþãà ãàñàõëäáèñ ãàñàþäêäáóê ü÷àðíäáøè („ñèò÷åà ãà ñàõëä“; Jobs.ge) âàëíõåä÷ìäáóê âàìúþàãäáäáøè ëíúäëóêè èìôíðëàúèèñ ñèñòäëàòèæäáà. çèçíäóê âàìúþàãäáàøè üàðëíãâäìèêè èìôíðëàúèèñ ñàôóûåäêæä øäèåñí éèçþåàðè. øäåñäáóêè éèçþåàðäáè øäåèãà ëíìàúäëçà áàæàøè, ðíëêèñ ëäøåäíáèç øäñàûêäáäêèà øðíëèñ áàæàðæä àðñäáóêè åàéàìñèäáèñ ñòðóõòóðèñ âàìñàæöåðà.

çàåãàîèðåäêàã ùàôèõðäáóêè è÷í èìôíðëàúèèñ íðèåä ü÷àðíãàì ãðíèçè ëüéðèåèñ âäìäðèðäáà, ðíëäêñàú óìãà ëíäúåà 2009-2015 üêäáèñ îäðèíãè. âàæäç „ñèò÷åà ãà ñàõëèñ“ øäëçþåäåàøè äñ ëíþäðþãà: ëíûèäáóê èõìà 2010-2015 üêäáèñ ìíëðäáè, ðíëäêçàâàìàú øäèðùà ÷íåäêè üêèñ ëàèñèñà ãà ãäéäëáðèñ ëäíðä ìàþäåàðøè âàëíñóêè ìíëðäáè. ëàç ëíìàúäëäáæä ãà÷ðãìíáèç æäëíç þñäìäáóêè èìñòðóëäìòèñ ñàøóàêäáèç âàìþíðúèäêãà ëíìàúäëçà áàæèñ ôíðëèðäáà. ñàëüóþàðíã, àñäçèåä ëæàíáà àð âàëíàåêèìà èìòäðìäòðäñóðñ Jobs.ge-ñ àãëèìèñòðàúèàë, ðíëäêëàú àð èñóðåà ñàèòèñ àðõèåæä îðíäõòèñ ëéåêäåàðçà üåãíëèñ ãàøåäáà. øäãäâàã, øäñàûêäáäêè âàþãà ëþíêíã åàéàìñèäáèñ ñòðóõòóðèñ àìàêèæè 2016 üêèñ ëàèñèñ ëäíðä ìàþäåðèñ ëãâíëàðäíáèç. àöìèøìóêèñ âàëí íðèåä ü÷àðíãàì éíëáèìèðäáóêè èñòíðèóêè ëíìàúäëäáèñ ñàôóûåäêæä ðàíãäìíáðèåè øäôàñäáäáèñ âàéäçäáà åäöàð ëíþäðþãà.

îðíäõòèñ ôàðâêäáøè àñäåä ùàòàðãà ùàöðëàåäáóêè èìòäðåèóäáè ñþåàãàñþåà ãàðâèñ 10 ëñþåèê ãàëñàõëäáäêçàì, ðèñçåèñàú øäëóøàåãà ñîäúèàêóðè éèçþåàðè (èþèêäç ãàìàðçè N1). ùàöðëàåäáóêè èìòäðåèóäáèñ éíìòäìò àìàêèæèñ ñàôóûåäêæä øäôàñãà éàãðäáèñ ëíûèäáèñ èìñòèòóúèóðè îðíáêäëèñ ãà ëàçè îðíôäñèóêè øäñàáàëèñíáèñ îðíáêäëèñ ñèëüåàåä.

6 http://www.ilo.org/wcmsp5/groups/public/---dgreports/---stat/documents/publication/wcms_166604.pdf

9

2. óëóøäåðíáèñ ñòðóõòóðà2. óëóøäåðíáèñ ñòðóõòóðà

2.1 óëóøäåðíáèñ àâðäâèðäáóêè ãíìèñ øäôàñäáà2.1 óëóøäåðíáèñ àâðäâèðäáóêè ãíìèñ øäôàñäáà

óëóøäåðíáèñ ãíìèñ íôèúèàêóðè ëàùåäìäáäêè, ðíâíðú æäëíç àöèìèøìà, ä÷ðãìíáà øðíëèñ ñàäðçàøíðèñí íðâàìèæàúèèñ (øñí) éðèòäðèóëäáñ. àë éðèòäðèóëäáèç óëóøäåðíáèñ ãíìä ñàõàðçåäêíøè 2009-2015 üêäáøè øäëúèðäáèñ òäìãäìúèèç þàñèàçãäáíãà, ðíëäêèú âàìñàéóçðäáèç 2014-2015 üêäáøè âàûêèäðãà.

óëóøäåðíáèñ 12-îðíúäìòèàìè ãíìä ìèøìàåñ, ðíë äéíìíëèéóðàã àõòèóðè ëíñàþêäíáèñ 12 îðíúäìòè âàëíéèçþåèñ üèìà øåèãè ãöèñ âàìëàåêíáàøè äðçè ñààçèçàú éè àð ëóøàíáãà ôóêàãè àì ìàòóðàêóðè øäëíñàåêèñ ëèñàöäáàã. óìãà âàåèçåàêèñüèìíç èñèú, ðíë äéíìíëèéóðàã àõòèóð ëíñàþêäíáàøè àð øäãèàì îèðäáè, ðíëêäáèú àì àð ëóøàíáãìäì (ñòóãäìòäáè, ãèàñàþêèñäáè ãà ñþåà), àì àõòèóðàã àð äûäáãìäì ñàëóøàíñ. äéíìíëèéóðè àõòèóðíáèñ ëàùåäìäáäêè 2015 üäêñ 68 îðíúäìòè è÷í, àìó 15 üäêæä óôðíñè àñàéèñ ëíñàþêäíáèñ 32 îðíúäìòè ñþåàãàñþåà ëèæäæèç äéíìíëèéóðàã àõòèóðè àð ÷íôèêà.

ãèàâðàëà N2

15.2%16.0%

15.1% 15.0% 14.6%

12.4% 12.0%

27.7% 27.6%26.4% 26.2% 25.6%

22.1% 21.5%

6.1%7.2% 6.5% 7.0% 6.5%

5.4% 4.8%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

2009 2010 2011 2012 2013 2014 2015

შსო-ს კრიტერიუმით უმუშევრობის დონე ქალაქისა და სოფლის მიხედვით

ქვეყანაში, სულ ქალაქად სოფლად

ü÷àðí: ñàõàðçåäêíñ øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëçà áàæà ãàëóøàåäáóêè àåòíðçà ÿâóôèñ ëèäð

ðíâíðú æäëíç ëíòàìèêè ãèàâðàëèãàì ùàìñ, óëóøäåðíáèñ ãíìääáñ øíðèñ ñþåàíáà õàêàõàã ãà ñíôêàã ûàêèàì ãèãèà: 2015 üäêñ õàêàõàã óëóøäåðíáèñ ãíìèñ ëàùåäìäáäêè çèçõëèñ 5-ÿäð àöäëàòäáíãà ñíôêèñ àìàêíâèóð ëàùåäìäáäêñ. ñíôêàã óëóøäåðíáèñ ãàáàê ãíìäñ úàêñàþàã âàìñàæöåðàåñ çåèçãàñàõëäáà, ðàñàú óëóøäåðíáèñ ãíìèñ ëàùåäìäáäêè ñíôêàã ëèìèëàêóð ëìèøåìäêíáàëãä ãà¸÷àåñ. 2009-2015 üêäáøè óëóøäåðíáèñ ãíìä ðíâíðú õàêàõàã, èñä ñíôêàã øäëúèðäáèñ òäìãäìúèàñ àåêäìãà, çóëúà äñ òäìãäìúèà õàêàõàã ðàëãäìàãëä óôðí ûêèäðè è÷í, âàìñàéóçðäáèç 2014-2015 üêäáøè.

ëàðçàêèà, øñí-èñ éðèòäðèóëäáèç ãàçåêèêè óëóøäåðíáèñ ãíìèñ ëàùåäìäáäêè ñàéëàíã èìôíðëàòèóêèà, ëàâðàë óëóøäåðíáèñ ñóðàçè àð èõìäáíãà ñðóê÷íôèêè àðàñðóêè ãàñàõëäáèñà ãà ôàðóêè óëóøäåðíáèñ âàçåàêèñüèìäáèñ âàðäøä. øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåà àðàñðóêè ãàñàõëäáèñ ãà ôàðóêè óëóøäåðíáèñ àìàêèæèñ ñàøóàêäáàñàú èûêäåà.

üèìàëãäáàðä éåêäåàøè àðàñðóêè ãàñàõëäáèñ ãà ôàðóêè óëóøäåðíáèñ øäôàñäáèñàçåèñ ëèæàìøäüíìèêàã ëèåèùìèäç øäëãäâè éðèòäðèóëäáèñ âàëí÷äìäáà, ðíëêäáñàú àõòèóðàã è÷äìäáäì àìàêíâèóð ñàäðçàøíðèñí éåêäåäáøè: 7

7 üàðëíãâäìèêè éðèòäðèóëäáè èçåàêèñüèìäáñ øñí-ñ ëèäð ðäéíëäìãèðäáóê ëäçíãíêíâèàñ.

10

àðàñðóêàã ãàñàõëäáóêàã ùàèçåàêà èñ, åèìú:1. âàëíéèçþåèñ üèìà øåèãè ãöèñ âàìëàåêíáàøè àñðóêäáãà äðçæä ëäò ñàëóøàíñ, ðàú •

ûèðèçàãàã èëàñçàìàà ãàéàåøèðäáóêè, ðíë äðçè ñàëóøàíãàì ëèöäáóêè øäëíñàåàêè ëèñçåèñ ñàéëàðèñè àð àðèñ ãà èûóêäáóêèà ¸õíìãäñ ëäíðä ñàëóøàí;

âàëíéèçþåèñ üèìà øåèãè ãöèñ îäðèíãøè èûóêäáèç ëóøàíáãà àðàñðóêè ñàëóøàí ãðíèç, • ¸õíìãà ñðóêè ñàëóøàí ãðíèç ëóøàíáèñ ñóðåèêè ãà ñðóêè ñàëóøàí ãðíèç ñàëñàþóðèñ ëíûäáìèñ øäëçþåäåàøè ëæàã è÷í ãàó÷íåìäáêèå ãàäü÷í ëóøàíáà. ôàðóê óëóøäåðäáàã ùàèçåàêà èñ, åèìú:2.

âàëíéèçþåèñ üèìà øåèãè ãöèñ âàìëàåêíáàøè ãàñàõëäáóêè è÷í ñðóêè ñàëóøàí ãðíèç, • ëàâðàë ñàëóøàí àð àéëà÷íôèêäáãà;

äûäáãà ñþåà ñàëñàþóðñ ãà• ëíûäáìèñ øäëçþåäåàøè ëæàã è÷í ãàó÷íåìäáêèå øääúåàêà ñàëñàþóðè.•

àöìèøìóêè éðèòäðèóëäáèñ âàëí÷äìäáèç øäñàûêäáäêèà óëóøäåðíáèñ àâðäâèðäáóêè ëàùåäìäáêèñ âààìâàðèøäáà, ðíëäêèú ëíèúàåñ ðíâíðú øñí-èñ éðèòäðèóëèç èãäìòèôèúèðäáóê óëóøäåðäáñ, èñä àðàñðóêàã ãàñàõëäáóêäáñ ãà ôàðóê óëóøäåðäáñ. õåäëíç ëíúäëóêèà àë ëàùåäìäáêèñ ãèìàëèéà ëçêèàìàã õåä÷ìèñ, àâðäçåä õàêàõèñ ãà ñíôêèñ ýðèêäáøè.

ãèàâðàëà N3

39.1%38.4% 37.2% 36.2% 35.7%

31.7%29.6%

26.7%28.3% 28.1%

29.5% 27.0%24.4%

23.1%

31.9% 32.6% 32.0% 32.3%30.7%

27.4%25.9%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

2009 2010 2011 2012 2013 2014 2015

უმუშევრობის აგრეგირებული დონე

ქვეყანაში, სულქალაქად სოფლად


çåàêøè ñàúäëèà èñ âàðäëíäáà, ðíë õàêàõèñà ãà ñíôêèñ ëèþäãåèç ãàçåêèêè óëóøäåðíáèñ àâðäâèðäáóêè ëàùåäìäáêäáè èñä àðñäáèçàã àð âàìñþåàåãäáà äðçëàìäçèñàâàì, ðíâíðú øñí-èñ éðèòäðèóëèç ãàçåêèêè óëóøäåðíáèñ ëàùåäìäáêäáè. àëèñ ûèðèçàãè ëèæäæè èñäå ñíôêèñ ëäóðìäíáàøè çåèçãàñàõëäáàà: çåèçãàñàõëäáóêçà ñàéëàíã ãèãè ìàüèêè àðàñðóêàã ãàñàõëäáóêè àì ôàðóêè óëóøäåàðèà.

óëóøäåðíáèñ àâðäâèðäáóêè ëàùåäìäáêäáè, èñä ðíâíðú øñí-èñ éðèòäðèóëèç óëóøäåðíáèñ ãíìèñ ëàùåäìäáêäáè, éêäáèñ òäìãäìúèàñ àåêäìäì, ëàâðàë øäëúèðäáèñ òðäìãè àë øäëçþåäåàøè øäãàðäáèç óôðí üðôèåèà, åèãðä øñí-èñ éðèòäðèóëèç óëóøäåðíáèñ ãíìèñ òðäìãè.

óëóøäåðíáèñ àâðäâèðäáóêè ãíìèñ 43 îðíúäìòè øñí-èñ éðèòäðèóëèç óëóøäåðäáèñàâàì øäãâäáà, ãààþêíäáèç ëäñàëäãè - 32 îðíúäìòè - àðàñðóêè ãàñàõëäáèñ üèêàã ëíãèñ, þíêí ëäíçþäãè - 25 îðíúäìòè - ôàðóêè óëóøäåðíáèñ üèêàã.

11

ãèàâðàëà N4

44% 44% 42% 42% 43% 41% 43%

29% 28% 29% 27% 27% 30%32%

28% 28% 30% 31% 30% 29% 25%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

აგრეგირებული უმუშევრობის სტრუქტურა

უმუშევრობა შსო-ს კრიტერიუმით არასრული დასაქმების დონე ფარული უმუშევრობის დონე


ñàèìòäðäñíà, ðíë 2009-2015 üêäáøè óëóøäåðíáèñ àâðäâèðäáóêè ãíìèñ ñòðóõòóðà àðñäáèçàã àð øäúåêèêà. ëúèðäã âàèæàðãà àðàñðóêè ãàñàõëäáèñ þåäãðèçè üíìà, ôàðóêè óëóøäåðíáèñ þåäãðèçè üíìà éè ðàëãäìàãëä øäëúèðãà. ñþåà ëþðèå, óëóøäåðíáèñ àâðäâèðäáóêè ãíìèñ øäëàãâäìäêè éíëîíìäìòäáèñ þåäãðèçè üíìäáèñ úåêèêäáà ñòàòèñòèéóðè úãíëèêäáèñ ôàðâêäáøèà ãà àðñäáèçè àðàà.

2.2 óëóøäåðíáèñà ãà ãàñàõëäáèñ éåàêèôèéàúèóðè ñòðóõòóðèñ 2.2 óëóøäåðíáèñà ãà ãàñàõëäáèñ éåàêèôèéàúèóðè ñòðóõòóðèñ øäñàáàëèñíáàøäñàáàëèñíáà

øñí-èñ éðèòäðèóëäáèç èãäìòèôèúèðäáóê óëóøäåàðçàâàì 2015 üäêñ 38 îðíúäìòè ñäðòèôèúèðäáóêè îðíôäñèèñ ëèþäãåèç óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòè è÷í, óëóøäåàðçà 17 îðíúäìòè - ñàøóàêí ãíìèñ ñîäúèàêèñòè, þíêí 4 îðíúäìòè - ñàøóàêíæä ãàáàêè éåàêèôèéàúèèñ (óéàìàñéìäêè ëíèúàåñ ëä-4-9 ÿâóôäáñ).8

óëóøäåàðçà øíðèñ ÷åäêàæä ëñþåèê ÿâóôñ üàðëíãâäìãìäì èñ óëóøäåðäáè, ðíëäêçàú ñäðòèôèúèðäáóêè îðíôäñèà àð âààùìèàç àìó îðíôäñèèñ àðëõíìäìè.

éåàêèôèéàúèèñ ãíìèñ ëèþäãåèç âàëñþåèêäáóê ÿâóôäáøè (èþèêäç õåäëíç ëíòàìèêè úþðèêè) óëóøäåàðçà âàìàüèêäáà 2009-2015 üêäáøè àðñäáèçàã àð øäúåêèêà. øäãàðäáèç âàëíéåäçèêè òäìãäìúèà îðíôäñèèñ àðëõíìäçà þåäãðèçè üíìèñ óëìèøåìäêí æðãàà, ðíëäêèú ñàéëàíã ñóñòèà, þíêí úåêèêäáäáè - ñòàòèñòèéóðàã àðààðñäáèçè.

éåàêèôèéàúèèñ ãíìèñ ëèþäãåèç âàëñþåèêäáóê ÿâóôäáøè ãàñàõëäáóêçà 31 îðíúäìòè ãèîêíëèñ ëèþäãåèç óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòèà, 17 îðíúäìòè - ñàøóàêí ãíìèñ ñîäúèàêèñòè,

8 ãàñàõëäáóêçà ãà óëóøäåàðçà âàìàüèêäáà îðíôäñèäáèñ âàëñþåèêäáóê ÿâóôäáøè âàìþíðúèäêãà ISCO-ñ éêàñèôèéàòíðèñ áàæàæä, ðíëäêèú äðçìèøìà éíãäáèñ ãíìäæä ëíèúàåñ 9 ûèðèçàã ÿâóôñ:1 - ÷åäêà ãíìèñ þäêèñóôêäáèñà ãà ëàðçåèñ íðâàìíäáèñ þäêëûöåàìäêäáè, ãàüäñäáóêäáäáèñ, íðâàìèæàúèäáèñà ãà ñàüàðëíäáèñ þäêëûöåàìäêäáèñ ùàçåêèç2 - ñîäúèàêèñòäáè éåàêèôèúèèñ óëàöêäñè ãíìèç3 - ñîäúèàêèñòäáè éåàêèôèéàúèèñ ñàøóàêí ãíìèç4 - éàìòíðèñ ëóøàéäáè5 - ëíëñàþóðäáèñ ñôäðíñà ãà ñàåàýðí íðâàìèæàúèäáèñ ëóøàéäáè6 - éåàêèôèúèóðè ëóøàéäáè ñíôêèñ, ñàò÷äí, ñàëíìàãèðäí ëäóðìäíáäáèñ, ëäçäåæäíáèñà ãà çäåæýäðèñ ãàðâøè7 - ñàëðäüåäêí ñàüàðëíäáèñ, ëþàòåðóêè ðäüåèñ, ëøäìäáêíáèñ, òðàìñîíðòèñ, éàåøèðâàáëóêíáèñ, âäíêíâèèñà ãà üèàöèñ ñàûèäáí ñàëóøàíäáèñ ãàðâèñ éåàêèôèúèóðè ëóøäáè8 - ãàìàãâàðäáèñà ãà ëàìõàìäáèñ íîäðàòíðäáè, ëäàîàðàòääáè, ëäëàìõàìääáè ãà æäèìéàê-àëü÷íáäáè9 - àðàéåàêèôèúèóðè ëóøäáè

12

8 îðíúäìòè - ñàøóàêíæä ãàáàêè ãíìèñ, þíêí ãàñàõëäáóêçà 45 îðíúäìòñ ñîäúèàêíáà àð âààùìèà. âàëíéåäçèêè òäìãäìúèäáèãàì àöñàìèøìàåèà óëàöêäñè ãíìèñ ñîäúèàêèñòäáèñ þåäãðèçè üíìèñ ëúèðäãè æðãà. ñþåà ëþðèå, ðàèëä âàìñàéóçðäáóêè òðäìãè ãàñàõëäáóêçà îðíôäñèäáèñ âàëñþåèêäáóê ÿâóôäáøè, âàìàüèêäáàñ àð àþàñèàçäáñ.

ëìèøåìäêíåàìèà ãàñàõëäáèñ ñòðóõòóðèñ ñàñíôêí çåèçãàñàõëäáèñ âàðäøä âàìþèêåà, åèìàèãàì äñ èëãäìàã ëñþåèêè ãà àëíðôóêè ÿâóôèà, ðíë ôàðàåñ ãàìàðùäì ñäõòíðäáøè ëèëãèìàðä òäìãäìúèäáñ.

ñàñíôêí çåèçãàñàõëäáèñ âàðäøä ëçêèàìè ãàñàõëäáèñ 50 îðíúäìòè 2015 üäêñ óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòäáè è÷åìäì, 16 îðíúäìòè - ñàøóàêí éåàêèôèéàúèèñ ñîäúèàêèñòäáè, þíêí 9 îðíúäìòè - ñàøóàêíæä ãàáàêè éåàêèôèéàúèèñ ñîäúèàêèñòäáè. ñàñíôêí çåèçãàñàõëäáèñ âàðäøä ãàñàõëäáóêçà 25 îðíúäìòñ îðíôäñèà àð àõåñ.

úþðèêè N1: ãàñàõëäáóêçà ãà óëóøäåàðçà âàìàüèêäáà îðíôäñèäáèñ âàëñþåèêäáóê ÿâóôäáøè úþðèêè N1: ãàñàõëäáóêçà ãà óëóøäåàðçà âàìàüèêäáà îðíôäñèäáèñ âàëñþåèêäáóê ÿâóôäáøè (îðíúäìòè)(îðíúäìòè)

2009 2010 2011 2012 2013 2014 2015

óëóøäåàðçà âàìàüèêäáà ñäðòèôèúèðäáóêè îðíôäñèäáèñ âàëñþåèêäáóê ÿâóôäáøè

óëàöêäñè ãíìèñ ñîäúèàêèñòäáè 37 39 41 39 40 39 38

ñàøóàêí ãíìèñ ñîäúèàêèñòäáè 18 18 17 18 15 15 17

ãàìàðùäìè ñîäúèàêèñòäáè 8 7 5 5 7 5 4

îðíôäñèà àð àõåç 37 36 37 38 39 41 41

ñóê 100 100 100 100 100 100 100

ãàñàõëäáóêçà âàìàüèêäáà ñäðòèôèúèðäáóêè îðíôäñèäáèñ âàëñþåèêäáóê ÿâóôäáøè




îðíôäñèà àð àõåç 46 43 45 45 44 44 45

ñóê 100 100 100 100 100 100 100

ãàñàõëäáóêçà âàìàüèêäáà ñäðòèôèúèðäáóêè îðíôäñèäáèñ âàëñþåèêäáóê ÿâóôäáøè(ñàñíôêí çåèçãàñàõëäáèñ âàðäøä)




îðíôäñèà àð àõåç 24 21 22 23 23 24 25

ñóê 100 100 100 100 100 100 100ü÷àðí: ñàõàðçåäêíñ øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëçà áàæà ãàëóøàåäáóêè àåòíðçà ÿâóôèñ ëèäð.

ëçêèàìè ãàñàõëäáèñ ñòðóõòóðèñâàì ñàéëàíã âàìñþåàåãäáà ãàñàõëäáèñ ñòðóõòóðà ñàñíôêí çåèçãàñàõëäáèñ âàðäøä (èþèêäç úþðèêè N1), ðàú îðíôäñèèñ àðëõíìäçà þåäãðèçè üíìèñ àðñäáèç øäëúèðäáàñà ãà óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòäáèñ þåäãðèçè üíìèñ æðãàøè âàëíèþàòäáà. âàëíéåäçèêè òäìãäìúèäáèãàì àõ àöñàìèøìàåèà àâðäçåä ñàøóàêí ãà ãàáàêè éåàêèôèéàúèèñ ñîäúèàêèñòäáèñ þåäãðèçè üíìèñ øäëúèðäáà.

éåàêèôèéàúèèñ ãíìèñ ëèþäãåèç ãàñàõëäáóêçà ãà óëóøäåàðçà ñòðóõòóðäáèñ øäãàðäáèñàçåèñ éåêäåàøè âàëí÷äìäáóêèà éíðäêàúèóðè àìàêèæèñ ëäçíãè. éíðäêàúèèñ éíäôèúèäìòè ñàéëàíã æóñòàã àùåäìäáñ ñòðóõòóðàçà ëñâàåñäáèñ þàðèñþñ ãà ëèëàðçóêäáàñ. óôðí öðëà àìàêèæèñàçåèñ ðäéíëäìãèðäáóêèà ôàõòíðóêè àìàêèæèñ âàëí÷äìäáà.

ðíâíðú âàëñþåèêäáóêè ÿâóôäáèñ øäãàðäáèçè àìàêèæè àùåäìäáñ, ñäðòèôèúèðäáóêè îðíôäñèäáèñ âàëñþåèêäáóê ÿâóôäáøè óëóøäåàðçà âàìàüèêäáà èëàåä ÿâóôäáøè ëçêèàìàã ãàñàõëäáóêçà âàìàüèêäáèñ ñòðóõòóðèñ ëñâàåñèà. éíðäêàúèèñ éíäôèúèäìòè çèçõëèñ 1-èñ òíêèà, ðàú èëàñ ìèøìàåñ, ðíë íðèåä ñòðóõòóðà ôàõòíáðèåàã èãäìòóðèà.

ñàñíôêí çåèçãàñàõëäáèñ âàðäøä ãàñàõëäáóêçà ñòðóõòóðà ãà óëóøäåàðçà ñòðóõòóðà øäãàðäáèç ìàéêäáàã èãäìòóðèà ãà éíðäêàúèèñ éíäôèúèäìòè 0.9091 ìèøìóêæä ùàëíãèñ.

13

ãèàâðàëà N5

0.95670.9610

0.9454

0.96120.9663

0.9738

0.9852

0.9246 0.92070.9299 0.9272

0.92170.9130 0.9091

0.860

0.880

0.900

0.920

0.940

0.960

0.980

1.000

2009 2010 2011 2012 2013 2014 2015

უმუშევრების დიპლომით პროფესიის მიხედვით სტრუქტურის კორელაცია დასაქმებულების დიპლომით პროფესიის მიხედვით სტრუქტურასთან

ISCO-ს ერთნიშნა კოდების დონეზემთლიანი დასაქმების სტრუქტურასთანდასაქმების სტრუქტურასთან სასოფლო თვითდასაქმების გარეშე

ü÷àðí: ñàõàðçåäêíñ øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëçà áàæà ãàëóøàåäáóêè àåòíðçà ÿâóôèñ ëèäð.

ëçêèàìè ãàñàõëäáèñ ãà óëóøäåðíáèñ ñòðóõòóðàçà éíðäêàúèèñ éíäôèúèäìòè 2009-2015 üêäáøè âàëíéåäçèêè æðãèñ òäìãäìúèèç þàñèàçãäáíãà, þíêí àðàñàñíôêí ãàñàõëäáèñ ãà óëóøäåàðçà ñòðóõòóðèñ éíðäêàúèèñ éíäôèúèäìòè - éêäáèñ òäìãäìúèèç. óëóøäåàðçà ñòðóõòóðà íðèåä øäëçþåäåàøè äðçè ãà èâèåäà. àëãäìàã, úåêèêäáàñ ãàñàõëäáóêçà ñòðóõòóðäáñ øíðèñ âàìñþåàåäáà âàìàîèðíáäáñ, ðíëäêèú, ðíâíðú éíðäêàúèèñ éíäôèúèäìòäáèñ òäìãäìúèà àùåäìäáñ, æðãàãèà. âàìñþåàåäáèñ ûèðèçàãè ëèæäæè îðíôäñèèñ àðëõíìäçà þåäãðèçè üíìèñ ëàùåäìäáäêèà, ðíëäêèú ñàñíôêí çåèçãàñàõëäáèñ ëìèøåìäêíåàìè ëãâäìäêèà.

àëðèâàã, ñàñíôêí çåèçãàñàõëäáà àðèñ ãàñàõëäáèñ èñ àëíðôóêàã ëñþåèêè ãà ûàêæäã ãàáàêè äôäõòèàìíáèñ ëõíìä ñôäðí, ðíëäêèú àþãäìñ îðíôäñèèñ àðëõíìä ñàëóøàí ûàêèñ àáñíðáúèàñ ãà àóëÿíáäñäáñ ãàñàõëäáèñ ñòàòèñòèéóð ñóðàçñ. äñ, úþàãàã âàëíùìãà øñí-èñ éðèòäðèóëèç óëóøäåðíáèñ ãíìèñ ëàùåäìäáêäáèñ õàêàõ-ñíôêèñ ëèþäãåèç àðñäáóêè âàìñþåàåäáèñà ãà óëóøäåðíáèñ àâðäâèðäáóêè ëàùåäìäáêèñ èëàåä âàìñþåàåäáèñ øäãàðäáèñàñ.

àõäãàì âàëíëãèìàðä, ãàñàõëäáèñ ñòðóõòóðèñ ñèñòäëóðè âàóëÿíáäñäáèñ àóúèêäáäêè üèìàîèðíáà îðíôäñèèñ àðëõíìäçà ëðàåàêðèúþíåàìè ÿâóôèñ îðíôäñèóêè âàìàçêäáèñ ñîäúèàêóðè îðíâðàëèñ øäëóøàåäáà ãà àëíõëäãäáàà.

æäëíç âàìþèêóêè è÷í ãàñàõëäáóêçà ãà óëóøäåàðçà éåàêèôèéàúèèñ ãíìèñ ëèþäãåèç âàìàüèêäáèñ éíðäêàúèà ISCO-ñ äðçìèøìà éíãäáèñ ãíìäæä, âàëñþåèêäáóê ÿâóôäáøè, ðèñ âàëíú âàëí÷íôèêè ÿâóôäáè ìàéêäáàã ¸íëíâäìóðèà.

ISCO-ñ íðìèøìà éíãäáèñ9 ãíìäæä âàìþèêóêè ãàñàõëäáóêçà ãà óëóøäåàðçà ñòðóõòóðà 9 ISCO-ñ íðìèøìà éíãäáèñ ùàëíìàçåàêè øäëãäâèà:11 - þäêèñóôêäáèñà ãà ëàðçåèñ íðâàìíäáèñ þäêëûöåàìäêäáè (üàðëíëàãâäìêäáè)12 - ãàüäñäáóêäáäáèñ, íðâàìèæàúèäáèñ, ñàüàðëíäáèñà ãà ëàçè ñòðóõòóðóêè õåäãàìà÷íôäáèñ (ñàëñàþóðäáèñ) þäêëûöåàìäêäáè13 - ëúèðä ãàüäñäáóêäáäáèñ, íðâàìèæàúèäáèñà ãà ñàüàðëíäáèñ þäêëûöåàìäêäáè21 - ñîäúèàêèñòäáè ñàáóìäáèñëäò÷åäêí ãà ñàèìïèìðí ëäúìèäðäáèñ ãàðâøè22 - áèíêíâèèñ, ñàñíôêí-ñàëäóðìäí ëäúìèäðäáäáèñà ãà ÿàìãàúåèñ ãàðâèñ ñîäúèàêèñòäáè23 - âàìàçêäáèñ ãàðâèñ ñîäúèàêèñòäáè24 - ñþåà ñîäúèàêèñòäáè éåàêèôèéàúèèñ óëàöêäñè ãíìèç31 - ñîäúèàêèñòäáè éåàêèôèéàúèèñ ñàøóàêí ãíìèç ôèæèéóð ãà òäõìèéóð ëäúìèäðäáàçà ãàðâøè32 -ñîäúèàêèñòäáè éåàêèôèéàúèèñ ñàøóàêí ãíìèç ñàáóìäáèñëäò÷åäêí ëäúìèäðäáäáèñà ãà ÿàìãàúåèñ ãàðâøè ãà ãàëþëàðä îäðñíìàêè33 - ñîäúèàêèñòäáè éåàêèôèéàúèèñ ñàøóàêí ãíìèç âàìàçêäáèñ ñôäðíøè34 - ñàøóàêí îäðñíìàêè ñàôèìàìñí, àãëèìèñòðàúèóêè ãà ñíúèàêóðè ñàõëèàìíáèñ ñôäðíøè41 - èìôíðëàúèèñ ëíëæàãäáèçà ãà ãàëóøàåäáèç ãàéàåäáóêè ëíñàëñàþóðääáè42 - ëíëñàþóðäáèñ ñôäðíñ ëóøàéäáè51 - èìãèåèãóàêóðè ëíëñàþóðäáèñà ãà ëíõàêàõäçà ãà ñàéóçðäáèñ ãàúåèñ ñôäðíñ ëóøàéäáè52 - ëíãäêäáè, âàë÷èãåäêäáè ãà ñàõíìêèñ ãäëíìñòðàòíðäáè53 - éíëóìàêóðè ëäóðìäíáèñ ëóøàéäáè54 - éèìíñà ãà òäêäñòóãèäáèñ ëóøäáè55 - ñàðäéêàëí-âàñàôíðëäáäê ãà ñàðäñòàåðàúèí ñàëóøàíäáæä ãàéàåäáóêè ëóøäáè

14

øäãàðäáèç óôðí ¸íëíâäìóð ÿâóôäáñ âàëí÷íôñ. àëãäìàã, àë ýðèêøè éíðäêàúèèñ þàðèñþè óôðí ëðàåêèñëäò÷åäêèà, åèãðä âàëñþåèêäáóêè ÿâóôäáèñ øäëçþåäåàøè.

ãèàâðàëà N6

0.9651 0.9673

0.9590

0.9709 0.9719 0.9717

0.9813

0.9383

0.93060.9360 0.9356 0.9381

0.9347 0.9366

0.9

0.91

0.92

0.93

0.94

0.95

0.96

0.97

0.98

0.99

2009 2010 2011 2012 2013 2014 2015

დასაქმებულების დიპლომით პროფესიის მიხედვით სტრუქტურის კორელაცია უმუშევრების დიპლომით პროფესიის მიხედვით სტრუქტურასთან ISCO-ს ორნიშნა

კოდების დონეზე

სასოფლო თვითდასაქმების ჩათვლით სასოფლო თვითდასაქმების გარეშე


ãàñàõëäáóêçà ãà óëóøäåàðçà éåàêèôèéàúèóðè ñòðóõòóðà ISCO-ñ íðìèøìà éíãäáèñ ëèþäãåèçàú èãäìòóðèà: éíðäêàúèèñ éíäôèúèäìòè çèçõëèñ 1-èñ òíêèà àìó ãàñàõëäáóêçà ãà óëóøäåàðçà ñòðóõòóðà àë øäëçþåäåàøèú ëñâàåñèà. àöñàìèøìàåèà, ðíë 2009-2015 üêäáøè éíðäêàúèèñ éíäôèúèäìòè æðãèñ òäìãäìúèàñ àåêäìãà àìó ãàñàõëäáóêçà ãà óëóøäåàðçà îðíôäñèóê-úäìæíáðèåè ñòðóõòóðà ñóê óôðí äëñâàåñäáà äðçëàìäçñ.

ñíôêèñ ëäóðìäíáàøè çåèçãàñàõëäáèñ âàðäøä éíðäêàúèèñ éíäôèúèäìòè, øäëúèðäáèñ ëèóþäãàåàã, ëàèìú ûàêèàì ëàöàê ìèøìóêæäà - 0.9366. àë ëàùåäìäáêèñ òäìãäìúèà ñàéåêäå îäðèíãøè ôàõòíáðèå óûðàíáàñ àôèõñèðäáãà.

61 - ñàáàæðí íðèäìòàúèèñ ëõíìä éåàêèôèúèóðè ëóøàéäáè ñíôêèñ, ñàò÷äí, ñàëíìàãèðäí ëäóðìäíáäáèñ, ëäçäåæäíáèñà ãà çäåæýäðèñ ãàðâøè62 - éåàêèôèúèóðè ëóøàéäáè ñíôêèñ, ñàò÷äí, ñàëíìàãèðäí ëäóðìäíáäáèñ, ëäçäåæäíáèñà ãà çäåæýäðèñ ãàðâøè71 - ëóøäáè, ãàéàåäáóêè ëíîíåäáèç ëðäüåäêíáàøè ãà ëøäìäáêíáàæä72 - êèçíìãàëàëóøàåäáäêè ëðäüåäêíáèñ, ëàìõàìàçëøäìäáêíáèñà ãà ëíìàçäñàåä îðíôäñèäáèñ ëóøäáè73 - ëóøäáè, ãàéàåäáóêè îðäúèæèóêè èìñòðóëäìòäáèñà ãà þäêñàü÷íäáèñ ãàëæàãäáèç, ëþàòåðóêè ñàðäüèñ, îíêèâðàôèóêè üàðëíäáèñà ãà ñþåà ëíìàçäñàåä îðíôäñèäáèñ ëóøäáè74 - ëðäüåäêíáèñà ãà ëíìàçäñàåä îðíôäñèäáèñ ãàìàðùäìè éåàêèôèúèóðè ëóøäáè75 - òðàìñîíðòèñà ãà éàåøèðâàáëóêíáèñ ëóøäáèñ îðíôäñèäáè76 - âäíêíâèàøè ãà üèàöèñ ñàûèäáí ñàëóøàíäáæä ãàñàõëäáóêè ëóøäáèñ îðíôäñèäáè81 - ñàëðäüåäêí ãàìàãâàðäáèñ íîäðàòíðäáè, ëäàîàðàòääáè ãà ëäëàìõàìääáè82 - êèçíìãàëëóøàåäáäêè ãà ëèìäðàêóðè ìäãêäóêèñ âàãàñàëóøàåäáäêè ëíü÷íáèêíáäáèñ íîäðàòíðäáè ãà ëäëàìõàìääáè83 - ëíûðàåè ëíü÷íáèêíáäáèñ ëûöíêäáè, íîäðàòíðäáè ãà ëäëàìõàìääáè91 - åàýðíáèñà ãà ëíëñàþóðäáèñ ñôäðíñ àðàéåàêèôèúèóðè ëóøäáè92 - ñíôêèñ, ñàò÷äí, ñàëíìàãèðäí ëäóðìäíáäáèñ, ëäçäåæäíáèñà ãà çäåæýäðèñ àðàéåàêèôèúèóðè ëóøäáè93 - ëðäüåäêíáàøè, ëøäìäáêíáàøè, òðàìñîíðòøè, éàåøèðâàáëóêíáàøè, âäíêíâèàñà ãà üèàöèñäóêèñ ûèäáàøè ãàéàåäáóêè àðàéåàêèôèúèóðè ëóøäáè94 - àðàéåàêèôèúèóðè ëóøäáè ÷åäêà ãàìàðùäì ãàðâøè

15

ãèàâðàëà N7

0.9648 0.9637

0.9559

0.9655

0.9532

0.9394

0.9677

0.9711

0.99060.9865

0.9810

0.9881

0.96980.9756

0.91

0.92

0.93

0.94

0.95

0.96

0.97

0.98

0.99

1.00

2009 2010 2011 2012 2013 2014 2015

დასაქმებულების დიპლომით პროფესიის მიხედვით სტრუქტურის კორელაცია უმუშევრების დიპლომით პროფესიის მიხედვით სტრუქტურასთან ISCO-ს ორნიშნა

კოდების დონეზე პროფესიის არმქონეთა გაუთვალისწინებლად



çó ñòðóõòóðàñ îðíôäñèèñ àðëõíìäçà âàðäøä âàìåèþèêàåç (èþèêäç ãèàâðàëà N7), ñäðòèôèúèðäáóêè îðíôäñèäáèñ ëèþäãåèç ãàñàõëäáóêçà ãà óëóøäåàðçà ñòðóõòóðà èñäå èãäìòóðèà, ëàâðàë àðèñ äðçè, ìàéêäáàã ëàñøòàáóðè, çóëúà øèìààðñèç ëìèøåìäêíåàìè âàìñþåàåäáà: îðíôäñèèñ àðëõíìäçà âàðäøä, ISCO-ñ íðìèøìà éíãäáèñ ëèþäãåèç ãàñàõëäáóêçà ãà óëóøäåàðçà ñòðóõòóðà ñàñíôêí çåèçãàñàõëäáóêçà ùàçåêèç øäãàðäáèç ìàéêäáàã éíðäêèðäáäì äðçëàìäççàì, åèãðä ñàñíôêí çåèçãàñàõëäáóêäáèñ âàçåàêèñüèìäáèñ âàðäøä. ñþåàâåàðàã ðíë åçõåàç, ñàñíôêí çåèçãàñàõëäáèñ ôàõòíðè àë øäëçþåäåàøè éíðäêàúèàñ àëúèðäáñ, ðàú èëèçàà âàëíüåäóêè, ðíë îðíôäñèèñ àðëõíìäçà ûèðèçàã çàåøäñàôàðñ ñüíðäã ñíôêèñ ëäóðìäíáàøè çåèçãàñàõëäáà üàðëíàãâäìñ.

2.3 óëóøäåðíáèñ ãèìàëèéà éåàêèôèéàúèèñ ëèþäãåèç2.3 óëóøäåðíáèñ ãèìàëèéà éåàêèôèéàúèèñ ëèþäãåèç

2009-2015 üêäáèñ ëàìûèêæä øñí-èñ éðèòäðèóëèç, óëóøäåðíáèñ ãíìä ISCO-ñ îðíôäñèäáèñ ëä-2 ÿâóôøè, àìó óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòäáñ øíðèñ, ðíâíðú üäñè, óëóøäåðíáèñ ñàøóàêí ãíìäæä ëàöàêè è÷í, ëèóþäãàåàã ñàéëàíã ë÷àðè øäëúèðäáèñ òäìãäìúèèñà.

óëóøäåðíáèñ ëàùåäìäáäêè àë ÿâóôøè 2015 üäêñ 20.8 îðíúäìòèç àöäëàòäáíãà óëóøäåðíáèñ ñàøóàêí ãíìäñ. ðíâíðú øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëäáèãàì ùàìñ, ñüíðäã ñîäúèàêèñòçà äñ éàòäâíðèàà óëóøäåðíáèñ ëàöàêè ðèñéèñ ëàòàðäáäêè. ÷åäêà ñþåà ÿâóôøè óëóøäåðíáèñ ãíìä ñàøóàêíæä ìàéêäáèà.

ñàøóàêí éåàêèôèéàúèèñ ñîäúèàêèñòäáñ øíðèñ óëóøäåðíáèñ ãíìä óëóøäåðíáèñ ñàøóàêí ãíìäæä íãìàå ìàéêäáèà ãà ëàñàú øäëúèðäáèñ òäìãäìúèà àþàñèàçäáñ.

âàìñàéóçðäáèç àöñàìèøìàåè ãàáàêè éåàêèôèéàúèèñ ñîäúèàêèñòäáñ øíðèñ óëóøäåðíáèñ ñàøóàêíñçàì øäãàðäáèç çèçõëèñ íðÿäð ãàáàêè ãíìäà. ÷óðàãöäáàñ èõúäåñ èñ âàðäëíäáàú, ðíë äñ ëàùåäìäáäêè 2009-2015 üêäáøè ÷íåäêçåèñ ñàøóàêíæä ìàéêäáè è÷í, áíêí ñàëè üêèñ âàìëàåêíáàøè éè éèãäå óôðí ãàäúà.

16

ãèàâðàëà N8

19.3%20.4% 20.5%

19.5%18.6%

15.8%

14.4%

16.4%

15.2% 13.7% 14.3%

12.0%

10.7%11.7%12.8% 12.8%

9.9%10.4%

12.2%

7.8% 6.5%

12.5%13.7%

12.7% 13.0%13.1%

11.4%11.2%

15.2%

16.0%15.0% 15.0% 14.6%

12.4%12.0%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

2009 2010 2011 2012 2013 2014 2015

შსო-ს კრიტერიუმით უმუშევრობის დონე სერტიფიცირებული პროფესიების ჯგუფებში

ჯგუფი 2 ჯგუფი 3 ჯგუფი 4-9 პროფესია არ აქვს სულ


àöñàìèøìàåèà èñèú, ðíë øñí-èñ éðèòäðèóëèç óëóøäåðíáèñ ãíìä îðíôäñèèñ àðëõíìäçà ÿâóôøè ñàøóàêí ëàùåäìäáäêæä 6.2 îðíúäìòèç ãàáàêèà. àëèñ äðç-äðçè ûèðèçàãè âàìëàîèðíáäáäêè ôàõòíðè ñíôêèñ ëäóðìäíáàøè ëàñíáðèåè ãàñàõëäáàà. ìèøàìãíáêèåèà, ðíë óëóøäåðíáèñ ãíìä ëíúäëóê ÿâóôøèú ëçäêè ñàéåêäåè îäðèíãèñ ëàìûêæä, ñàøóàêíæä ãàáàêè è÷í, çóëúà äñ âàìñþåàåäáà àð è÷í èñäçè ëàñøòàáóðè, ðíâíðú ãàáàêè éåàêèôèéàúèèñ ñîäúèàêèñòäáèñ øäëçþåäåàøè.

ãèàâðàëà N9

27.3% 28.0%

36.5%29.8% 28.0% 27.7%

20.8%

8.0%

-4.7%-9.1%

-5.0%

-17.4%

-13.3%

-2.3%

-15.8%-19.5%

-34.4%-30.9%

-16.0%

-36.8%

-45.7%

-17.5%-14.1% -15.3% -13.4%

-9.9%-7.4% -6.2%

-50.0%

-40.0%

-30.0%

-20.0%

-10.0%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

2009 2010 2011 2012 2013 2014 2015

სერტიფიცირებული პროფესიების ჯგუფებში შსო-ს კრიტერიუმით უმუშევრობის დონის სხვაობა უმუშევრობის საერთო დონისაგან

ჯგუფი 2 ჯგუფი 3 ჯგუფი 4-9 პროფესია არ აქვს


÷íåäêèåä æäëíçõëóêè èëàæä ëäò÷åäêäáñ, ðíë ñàõàðçåäêíñ øðíëèñ áàæàðæä âäìäðèðäáóêè ñàëóøàí àãâèêäáèñ óëäòäñíáà àð ëíèçþíåñ ëàöàê éåàêèôèéàúèàñ.

17

ðàú øääþäáà ñàñíôêí çåèçãàñàõëäáàñ, èâè øäñàûêíà ñàéëàíã ëàöàê éåàêèôèéàúèàñ ëíèçþíåñ, ëàâðàë ñàõàðçåäêíñ øäëçþåäåàøè ûèðèçàãàã ëàèìú òðàãèúèäáñ äôóûìäáà. ñàõàðçåäêíñ ñíôäêøè ëúþíåðäá øðíëèñóìàðèàìè àñàéèñ àãàëèàìñ øäèûêäáà àð ¸õíìãäñ ëäöåèìèñ ñäðòèôèéàòè, ëàâðàë åàæèñ ëíåêà ãà öåèìèñ ãà÷äìäáà ëèñè úþíåðäáèñ üäñèñ ìàüèêèà, ðíëäêèú çàíáèãàì çàíáàñ âàãàäúäëà. àìàêíâèóðè ðàë øäèûêäáà èçõåàñ, ëàâàêèçàã, çóø ëäúþåàðäæä, ðíëäêñàú àð àõåñ ÷åäêèñ ãàëæàãäáèñ ñîäúèàêèñòèñ ñäðòèôèéàòè (ðàú çàåèñçàåàã ñàéëàíã ëàöàê éåàêèôèéàúèàñ âóêèñþëíáñ), çóëúà èñ ëàðçêàú ëàöàêè çàìðèâèñ ñîäúèàêèñòèà çàíáäáèñ ëàìûèêæä ãàâðíåèêè âàëíúãèêäáèç, íöíìã - ñäðòèôèéàòèñ âàðäøä.

2.4 óëóøäåðíáèñ ñòðóõòóðà þàìâðûêèåíáèñ ëèþäãåèç2.4 óëóøäåðíáèñ ñòðóõòóðà þàìâðûêèåíáèñ ëèþäãåèç

óëóøäåðíáèñ øäôàñäáèñ äðçäðçè ëìèøåìäêíåàìè àñîäõòè óëóøäåðíáèñ þàìâðûêèåíáèñ àìàêèæèà. àëàñ ñàôóûåêàã ðàëãäìèëä ëìèøåìäêíåàìè âàðäëíäáà óãäåñ, ðíëäêçàâàì íðè ÷åäêàæä ëìèøåìäêíåàìèà:

þàìâðûêèåè óëóøäåðíáà èüåäåñ ãäéåàêèôèéàúèàñ;1. ëàöàêè éåàêèôèéàúèèñ óëóøäåðäáè øäñàûêíà óôðí ëäòàã è÷åìäì þàìâðûêèåè óëóøäåðíáèç 2. ëíü÷åêàãè, åèìàèãàì ëàçè øäñàáàëèñè éåàêèôèéàúèèñ ñàëóøàíñ ëíûèäáà øäãàðäáèç ûìäêèà.

ðíâíðú øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëäáèãàì ùàìñ, 1 çåäëãä ãà 1-ãàì 3 çåäëãä þàìâðûêèåíáèñ óëóøäåðíáèñ þåäãðèçè üíìà øñí-èñ éðèòäðèóëèç óëóøäåðäáøè, ñàéåêäåè îäðèíãèñ ëàìûèêæä ñòàáèêóðàã 6-8 îðíúäìòèñ ìèøìóêèñ ëàþêíáêíáàøèà ãà ðàèëä ùàëí÷àêèáäáóê òäìãäìúèàñ àð àùåäìäáñ.

3-ãàì 12 çåäëãä þàìâðûêèåíáèñ óëóøäåðíáà 2015 üäêñ ëçêèàìè óëóøäåðíáèñ 18 îðíúäìòè è÷í ãà àñäçè þàìâðûêèåíáèñ óëóøäåðíáèñ þåäãðèçè üíìà 2009-2015 üêäáøè æðãèñ òäìãäìúèèç þàñèàçãäáíãà.

þàìâðûêèåíáèñ ëèþäãåèç óëóøäåðíáèñ ñòðóõòóðèãàì âàìñàéóçðäáèç àöñàìèøìàåèà 3 üäêæä ëäòè þàìâðûêèåíáèñ óëóøäåðäáèñ þåäãðèçè üíìèñ æðãà ãà ëóøàíáèñ âàëíúãèêäáèñ àðëõíìä óëóøäåàðçà øäëúèðäáà.

ñà÷óðàãöäáíà, ðíë èñäçè óëóøäåðäáèñ þåäãðèçè üíìà, ðíëêäáñàú àðàñíãäñ óëóøàåèàç, ëèóþäãàåàã øäëúèðäáèñ òäìãäìúèèñà, 2015 üäêñ ëàèìú 25-îðíúäìòèàì ìèøìóêæäà, àìó øñí-ñ éðèòäðèóëèç óëóøäåðäáèñ 25 îðíúäìòñ àðàñíãäñ óëóøàåèà. äñ ñàéëàíã ëàöàêè ëàùåäìäáäêèà.

ãèàâðàëà N10

4% 4% 4% 5% 4% 5% 6%9% 9% 10% 9% 8% 9% 8%

13% 14% 14% 16% 16% 16% 18%

13% 11% 10% 10% 9% 11% 11%6% 7% 6% 7% 6% 5% 5%

24% 26% 24% 26% 27% 27% 27%

31% 30% 31% 28% 29% 27% 25%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

შსო-ს კრიტერიუმით უმუშევართა განაწილება უმუშევრობის ხანგრძლივობის მიხედვით

1 თვემდე 1-დან 3 თვემდე 3-დან 12 თვემდე

1-დან 2 წლამდე 2-დან 3 წლამდე 3 წელზე მეტი

საერთოდ არ უმუშავია


ñàëóøàí âàëíúãèêäáèñ àðëõíìäçà ëàöàêè þåäãðèçè üíìèñ ñàéëàíã ëàöàêè ëàùåäìäáäêèñ äðçäðç ñàåàðàóãí ëèæäæàã øäèûêäáà âàìåèþèêíç àñàéè. éäðûíã, èñ âàðäëíäáà, ðíë øðíëèçè àñàéè 15 üêèãàì èü÷äáà ãà ëèóþäãàåàã èëèñà, ðíë øñí-èñ éðèòäðèóëèç óëóøäåðíáà âàëíðèúþàåñ

18

óëóøäåðäáøè ñòóãäìòäáèñ ãà ëíñüàåêääáèñ ëíþåäãðàñ (25 üêàëãä àñàéèñ ëíñàþêäíáèãàì 59.6 îðíúäìòè àð ëèäéóçåìäáà äéíìíëèéóðàã àõòèóð ëíñàþêäíáàñ, þíêí çàåàã àë àñàéèñ äéíìíëèéóðàã àõòèóð ëíñàþêäíáàøè óëóøäåðíáèñ ãíìä 30.8 îðíúäìòèà, àìó óëóøäåðíáèñ ñàøóàêí ãíìäæä 2.5-ÿäð ëàöàêè), ëàèìú àðèñ ñàéëàíã ãèãè øàìñè èëèñà, ðíë àñàéèñ âàëí øñí-èñ éðèòäðèóëèç óëóøäåàðñ àð ¸õíìãäñ ñàëóøàí âàëíúãèêäáà.

àñàéèñ ôàõòíðèñ âàçåàêèñüèìäáèç, øäãàðäáèç óôðí èìôíðëàòèóêèà 25 üäêæä óôðíñè àñàéèñ óëóøäåðíáèñ þàìâðûêèåíáèñ ñòðóõòóðà. 25 üäêæä óôðíñè àñàéèñ óëóøäåðèñàçåèñ ñàëóøàí âàëíúãèêäáèñ àðõíìà âàìñþåàåäáóêè çàìðèâèñ ôàõòíðèà, åèãðä 25 üêàëãä àñàéèàìçà øäëçþåäåàøè.

25 üäêæä óôðíñè àñàéèñ óëóøäåðäáèñ ñòðóõòóðà ãààþêíäáèç èñäçèåäà, ðíâíðú ëçêèàìàã óëóøäåàðè ëíñàþêäíáèñ âàìàüèêäáèñ ñòðóõòóðà, çóëúà îðíîíðúèäáñ øíðèñ âàìñþåàåäáà àðñäáíáñ ãà äñ âàìñþåàåäáäáè àðñäáèçèà. ñàëóøàí âàëíúãèêäáèñ àðëõíìäçà þåäãðèçè üíìà 13 îðíúäìòèà, ðàú çèçõëèñ íðÿäð ãàáàêèà ëçêèàìàã óëóøäåðäáèñ âàìàüèêäáèñ àìàêíâèóð ëàùåäìäáäêçàì øäãàðäáèç.

3 üäêæä óôðí ëäòè þàìâðûêèåíáèñ óëóøäåàðçà þåäãðèçè üíìà 25 üäêæä óôðíñè àñàéèñ óëóøäåðäáèãàì 33 îðíúäìòèà, ðàú àðñäáèçàã àöäëàòäáà ëçêèàìàã óëóøäåðäáèñ âàìàüèêäáèñ àìàêíâèóð ëàùåäìäáäêñ.

àìó ñàéëàíã ëàöàêè éàòäâíðèóêíáèç øäèûêäáà èçõåàñ, ðíë àñàéèñ æðãàñçàì äðçàã ðàëãäìàãëä èæðãäáà þàìâðûêèåè óëóøäåðíáèñ àêáàçíáà.


4% 5% 4% 5% 5% 5% 7%11% 10% 12% 10% 9% 10% 9%

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შსო-ს კრიტერიუმით 25 წელზე უფროსი ასაკის უმუშევრების განაწილება უმუშევრობის ხანგრძლივობის მიხედვით

1 თვემდე 1-დან 3 თვემდე 3-დან 12 თვემდე

1-დან 2 წლამდე 2-დან 3 წლამდე 3 წელზე მეტი

საერთოდ არ უმუშავია


þàìâðûêèåíáèñ çåàêñàæðèç 1 üêàëãä óëóøäåðíáà øäèûêäáà âàìåèþèêíç, ðíâíðú þàìëíéêä óëóøäåðíáà, þíêí óëóøäåðíáà, ðíëäêèú 1 üäêæä ëäòè âðûäêãäáà - ðíâíðú þàìâðûêèåè óëóøäåðíáà, ðíëäêèú ñúèêãäáà ôðèõúèóêè óëóøäåðíáèñ ôàðâêäáñ, øäèúàåñ ãäéåàêèôèéàúèèñ àðñäáèç ñàôðçþäñ ãà, ôàõòíáðèåàã, ñòðóõòóðóêè óëóøäåðíáèñ âàìæíëèêäáàøè âàãàãèñ.

âàðãà àëèñà, ëñþåèê ÿâóôäáàã àâðäâèðäáà âàìîèðíáäáóêèà èëèçàú, ðíë üåðèê ÿâóôäáøè øäôàñäáäáèñ ñàèëäãííáà àðñäáèçàã ãàáàêèà âàëñþåèêäáóê ÿâóôäáøè øäôàñäáäáçàì øäãàðäáèç. ëèç óëäòäñ, ðíë àñäçè àâðäâèðäáèç ñàéëàíã ¸íëíâäìóðè ÿâóôäáè ëèèöäáà.

óëóøäåàðçà 32 îðíúäìòñ 1 üêàëãä þàìâðûêèåíáèñ óëóøäåðäáè øäàãâäìãìäì, þíêí 43 îðíúäìòñ - 1 üäêæä ëäòè þìèñ óëóøäåðäáè. óëóøäåàðçà 25 îðíúäìòñ, ðíâíðú óéåä àöåìèøìäç, àðàñíãäñ óëóøàåèàç.

19


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შსო-ს კრიტერიუმით უმუშევრების განაწილება უმუშევრობის ხანგრძლივობის მიხედვით გამსხვილებულ ჯგუფებში

1 წლამდე უმუშევრები 1 წელზე მეტი ხნით უმუშევრები საერთოდ არ უმუშავიათ



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25 წელზე უფროსი ასაკის უმუშევრების განაწილება უმუშევრობის ხანგრძლივობის მიხედვით

მოკლევადიანი უმუშევრები ხანგრძლივი უმუშევრები


æäëíàöìèøìóêè âàìàüèêäáäáèãàì âàëíëãèìàðä, þàìâðûêèå óëóøäåðäáàã ùàåçåàêäç óëóøäåðäáè, ðíëêäáèú àéëà÷íôèêäáãìäì øäëãäâ éðèòäðèóëäáñ:

âàìàúþàãäñ, ðíë 1 üäêæä ëäòèà, ðàú óëóøäåðäáè àðèàì;1. 25 üäêæä óôðíñè àñàéèñ èñ óëóøäåðäáè, ðíëêäáñàú àðàñãðíñ óëóøàåèàç. óéàìàñéìäêè 2. ãàøåäáà âàìîèðíáäáóêèà èëèç, ðíë ñàëóøàí âàëíúãèêäáèñ ñàäðçíã àðõíìà ñüàåêèñ âàëí ëäòìàéêäáàã àþñìàãèà àþàêâàæðãà àñàéøè, ëàâðàë àñàéèñ æðãàñçàì äðçàã äñ àðâóëäìòè ûàêàñ éàðâàåñ.

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àñäçè ãàøåäáäáèñ ñàôóûåäêæä âàéäçäáóêè âààìâàðèøäáèñ ëèþäãåèç (èþäêäç ãèàâðàëà N13), óëóøäåðäáèñ 48 îðíúäìòè þàìëíéêä óëóøäåðäáè àðèàì, þíêí 52 îðíúäìòè - þàìâðûêèåè óëóøäåðäáè. 2009-2015 üêèñ ëàìûèêæä þàìâðûêèåíáèñ ìèøìèç óëóøäåðíáèñ âàìàüèêäáà àðñäáèçàã àð øäúåêèêà. øäèûêäáà èçõåàñ, ðíë øäèìèøìäáà þàìâðûêèåè óëóøäåðíáèñ øäëúèðäáèñ ñóñòè òäìãäìúèà, ðíëäêèú àðñäáèçè úåêèêäáèñ ëàùåäìäáäêè àð àðèñ.

2.5 óëóøäåðíáèñ ñòðóõòóðà âàìàçêäáèñ ëèöüäóêè ãíìèñ ëèþäãåèç2.5 óëóøäåðíáèñ ñòðóõòóðà âàìàçêäáèñ ëèöüäóêè ãíìèñ ëèþäãåèç

øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåà èûêäåà âàìàçêäáèñ ëèöüäóêè ãíìèñ ëèþäãåèç ñþåàãàñþåà ëàùåäìäáêäáèñ âààìâàðèøäáèñ øäñàûêäáêíáàñ. àëèñàçåèñ øèìàëäóðìäíáèñ èìòäâðèðäáóê âàëíéåêäåàøè âàëíè÷äìäáà âàìàçêäáèñ ëèöüäóêè ãíìèñ éíãèðäáèñ 11 ñàôäþóðèàìè ñèñòäëà. âàëíëãèìàðä èõäãàì, ðíë 11 ÿâóôàã ãàøêèêè ëíìàúäëçà ëàñèåè åäð óæðóìåäê÷íôñ ñàèëäãí øäôàñäáäáèñ âäìäðèðäáàñ, ëèæàìøäüíìèêèà çèçíäóêè ÿâóôèñ âàëñþåèêäáóê ÿâóôäáøè âàìþèêåà. ÿâóôäáèñ âàëñþåèêäáà âàìþíðúèäêãà øèìààðñèñ ëèþäãåèç ãà àðà ëäõàìèéóðàã. éäðûíã, æäëíàöìèøìóêè 11 ÿâóôè 4 ûèðèçàã áêíéàã âàäðçèàìãà:

ñóáèäõòäáè ñàøóàêíæä ãàáàêè âàìàçêäáèç, ñàãàú øäåèãìäì èñèìè, åèñè âàìàçêäáèñ 1. ëèöüäóêè ãíìèñ øäñàáàëèñè éíãè è÷í:

üäðà-éèçþåèñ óúíãèìàðè;• àð àõåñ ãàü÷äáèçè âàìàçêäáà, ëàâðàë øäóûêèà üäðà-éèçþåà;• æíâàãè âàìàçêäáèñ ãàü÷äáèçè ñàôäþóðè;• æíâàãè âàìàçêäáèñ ñàáàæí ñàôäþóðè.•

ñóáèäõòäáè ñàøóàêí âàìàçêäáèç, ñàãàú øäåèãìäì èñèìè, åèñè âàìàçêäáèñ ëèöüäóêè ãíìèñ 2. øäñàáàëèñè éíãè è÷í:

ñðóêè æíâàãè âàìàçêäáà (ñàøóàêí ñéíêà).• ñóáèäõòäáè îðíôäñèóêè âàìàçêäáèç, ñàãàú øäåèãìäì èñèìè, åèñè âàìàçêäáèñ ëèöüäóêè 3. ãíìèñ øäñàáàëèñè éíãè è÷í:

ñàþäêíáí âàìàçêäáèñ ñäðçèôèéàòè (ãàü÷äáèçè îðíôäñèóêè âàìàçêäáèñ ãèîêíëè);• ñàøóàêí îðíôäñèóêè (ñàøóàêí ñîäúèàêóðè) âàìàçêäáèñ ãèîêíëè.•

ñóáèäõòäáè óëàöêäñè âàìàçêäáèç, ñàãàú øäåèãìäì èñèìè åèñè âàìàçêäáèñ ëèöüäóêè ãíìèñ 4. øäñàáàëèñè éíãè è÷í:

óëàöêäñè îðíôäñèóêè âàìàçêäáèñ àì ëàñçàì âàçàìàáðäáóêè óëàöêäñè ñàâàìëàìàçêäáêí • îðíâðàëèñ ãèîêíëè;

áàéàêàåðèñ àì ãèîêíëèðäáóêè ëäãèéíñèñ/åäòäðèìàðèñ àì ëàñçàì âàçàìàáðäáóêè • óëàöêäñè ñàâàìëàìàçêäáêí îðíâðàëèñ ãèîêíëè;

ëàâèñòðèñ/ðäæèãäìòóðèñ éóðñãàëçàåðäáóêèñ àì ëàñçàì âàçàìàáðäáóêè óëàöêäñè • ñàâàìëàìàçêäáêí îðíâðàëèñ ãèîêíëè;

ãíõòíðè àì ëàñçàì âàçàìàáðäáóêè þàðèñþè.• àìàêèæëà àùåäìà (èþèêäç ãèàâðàëà N14), ðíë äéíìíëèéóðàã àõòèóðè ëíñàþêäíáèñ 6

îðíúäìòñ ñàøóàêíæä ãàáàêè âàìàçêäáà ̧ õíìãà; 41 îðíúäìòñ - ñàøóàêí âàìàçêäáà; 22 îðíúäìòñ - îðíôäñèóêè, þíêí 31 îðíúäìòñ - óëàöêäñè âàìàçêäáà. âàìàüèêäáà 2009-2015 üêäáèñ âàìëàåêíáàøè îðàõòèéóêàã àð øäúåêèêà. âàëíìàéêèñè ëþíêíã 2010 üäêè è÷í, èñèú- òäõìèéóðè ãà àðà øèìààðñíáðèåè þàñèàçèñ ëèæäæèç10.

10 àöñàìèøìàåèà, ðíë 2009 üäêñ âàëí÷äìäáóêè è÷í âàìàçêäáèñ ëèöüäóêè ãíìèñ éíãèðäáèñ 7 ñàôäþóðèàìè ñèñòäëà, ðíëäêèú àñäåä àâðäâèðãäáà æäëíàöìèøìóê 4 ÿâóôøè. éíãèðäáèñ ñèñòäëà 2010 üäêñ øäèúåàêà. éíãèðäáèñ àþàê ñèñòäëàæä âàãàñåêàñçàì ãàéàåøèðäáóêëà îðíáêäëäáëà àðñäáèçè æäâàåêäìà ëíàþãèìà 2010 üêèñ âàìàüèêäáàæä. àëàñ ãàäëàòà èñèú, ðíë úåêèêäáà âàìþíðúèäêäáóêèà 2010 üêèñ ëä-2 ãà ëä-3 éåàðòàêóð âàëíéåêäåäáñ øíðèñ ãà âàðãàëàåàêè îäðèíãèñ áàæèñ àâðäâèðäáà ñàéëàíã ðçóêè àöëíùìãà. àëãäìàã, 2010 üêèñ âàìàüèêäáà éíìòäõñòèãàì ðàëãäìàãëä àëíåàðãìèêèà.

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2009 2010 2011 2012 2013 2014 2015

ეკონომიკურად აქტიური მოსახლეობის განაწილება განათლების მიღწეული დონის მიხედვით

საშუალოზე დაბალი განათლებით საშუალო განათლებით

პროფესიული განათლებით უმაღლესი განათლებით


øñí-èñ éðèòäðèóëèç óëóøäåðíáèñ ãíìä óëàöêäñè âàìàçêäáèñ ëõíìä äéíìíëèéóðàã àõòèóð ëíñàþêäíáàøè, ðíâíðú üäñè, óôðí ëàöàêèà, åèãðä óëóøäåðíáèñ ñàøóàêí ãíìä. àöñàìèøìàåèà, ðíë íðèåä äñ ëàùåäìäáäêè ñàéåêäå îäðèíãøè øäëúèðäáèñ òäìãäìúèàñ àåêäìãà, âàìñàéóçðäáèç àöñàìèøìàåèà, ðíë óëàöêäñè âàìàçêäáèñ ëõíìä ëíñàþêäíáàøè óëóøäåðíáèñ ëàùåäìäáäêèñ øäëúèðäáèñ òäìãäìúèà óôðí ûêèäðèà, 2009-2015 üêäáøè èñ çàìãàçàì óàþêíåãäáà óëóøäåðíáèñ ñàøóàêí ëàùåäìäáäêñ. øäëúèðäáèñ ãàãäáèçè òäìãäìúèà âàìñàéóçðäáèç 2014-2015 üêäáøè âàûêèäðãà. âàìàçêäáèñ ÷åäêà ñþåà ãíìèñ ÿâóôøè óëóøäåðíáèñ ëàùåäìäáäêè óôðí ãàáàêèà åèãðä ñàøóàêí ëàùåäìäáäêè. àõäãàì âàìñàéóçðäáèç àöñàìèøìàåèà ñàøóàêíæä ãàáàêè âàìàçêäáèñ ëõíìäçà ÿâóôè, ñàãàú óëóøäåðíáèñ ãíìä ÷åäêàæä ãàáàêèà.

ëçêèàìíáàøè, 2009-2015 üêäáèñ òäìãäìúèäáèãàì àöñàìèøìàåèà âàìàçêäáèñ ñþåàãàñþåà ãíìèñ ÿâóôäáøè óëóøäåðíáèñ ëàùåäìäáêäáèñ ãààþêíäáèñ òäìãäìúèà: 2015 üêèñ ëíìàúäëäáèç óëóøäåðíáèñ ãíìääáñ øíðèñ âàìñþåàåäáà èñäçè àðñäáèçè àöàðàà, ðíâíðèú è÷í 2009 àì 2011 üêäáøè.

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3. ãàñàõëäáèñ ñòðóõòóðà3. ãàñàõëäáèñ ñòðóõòóðà

3.1 ãàñàõëäáèñ ñäõòíðóêè ñòðóõòóðà3.1 ãàñàõëäáèñ ñäõòíðóêè ñòðóõòóðà

ñäõòíðäáèñ ëèþäãåèç ãàñàõëäáèñ ñòðóõòóðà àñàþàåñ øðíëèñ áàæàðæä àðñäáóêè ëíçþíåìèñ ãà ëèüíãäáèñ üíìàñüíðíáèñ ëãâíëàðäíáàñ. äñ àðèñ äðçâåàðè øäãäâè, ðíëäêèú ëíèúàåñ øðíëèñ áàæàðæä àðñäáóê ÷åäêà - äîèæíãóð, ñòðóõòóðóê çó ñèñòäëóð îðíáêäëàñ.

ãàñàõëäáèñ ñòðóõòóðà ñàõàðçåäêíøè äðçíá ñîäúèôèéóðèà (èþèêäç ãèàâðàëà N15). ëçêèàìè ãàñàõëäáèñ çèçõëèñ ìàþäåàðè - 48.4 îðíúäìòè - ñíôêèñ ëäóðìäíáàæä ëíãèñ. ìèøàìãíáêèåèà, ðíë ñíôêèñ ëäóðìäíáèñ þåäãðèçè üíìèñ ëàùåäìäáäêè 2009-2015 üêäáøè øäëúèðäáèñ òäìãäìúèèç þàñèàçãäáíãà ãà îèðåäêàã áíêí 25 üêèñ ëàìûèêæä ùàëíñúãà 50 îðíúäìòñ. äñ óãàåíã îíæèòèóðè ìèøàìèà, âàìñàéóçðäáèç èëèñ âàçåàêèñüèìäáèç, ðíë ñíôêèñ ëäóðìäíáèñ üèêè ëçêèàì øèãà îðíãóõòøè âàìóþðäêè éêäáèñ òäìãäìúèèç âàëíèðùäíãà ãà ëþíêíã áíêí íðè üêèñ ëàìûèêæä âàëíèéåäçà àë ëàùåäìäáäêèñ ñóñòè æðãà. ëèóþäãàåàã àëèñà, ñíôêèñ ëäóðìäíáèñ þåäãðèçè üíìà ëçêèàì ãàñàõëäáàøè àðñäáèçàã ñüíðäã áíêí íðè üêèñ ëàìûèêæä øäëúèðãà. äñ òäìãäìúèà âàìñàéóçðäáèç îíæèòèóð ãàòåèðçåàñ èûäìñ ãàñàõëäáèñ ãíìèñ óëìèøåìäêí, ëàâðàë ëàèìú, æðãèñ ôíìæä, ðàú èëàñ ìèøìàåñ, ðíë âàèæàðãà ñþåà ãàðâäáøè ãàñàõëäáóêçà ðàíãäìíáà. ñíôêèñ ëäóðìäíáèñ þåäãðèçè üíìà ëçêèàì ãàñàõëäáàøè èëãäìàã ãèãèà, ðíë àõ çåèçãàñàõëäáóêçà ðàëãäìèëä îðíúäìòèàìè øäëúèðäáà àðñäáèçàã åäð úåêèñ ãàñàõëäáèñ ñàäðçí äôäõòèàìíáèñ ãíìäñ, ëàâðàë ñàéóçðèå ñàñíôêí çåèçãàñàõëäáèñ øäëúèðäáà úàêñàþàã ãàãäáèçè ëíåêäìàà.


53.8 52.3 52.4 52.0 51.2 50.4 48.4

0.5 0.7 0.8 0.8 0.8 0.9 1.2

4.5 4.8 4.7 4.5 4.8 4.6 4.7

1.1 1.2 1.3 1.2 1.3 1.0 0.9

3.6 3.4 3.7 3.6 3.4 3.9 3.9

9.9 9.7 9.7 10.1 10.1 9.7 10.5

1.1 1.2 1.1 1.3 1.4 1.1 1.5

4.84 4.36 3.86 4.29 4.67 5.27 4.95

1.0 1.2 1.0 1.1 1.6 1.6 1.81.8 1.6 1.6 1.5 1.7 1.8 2.0

4.0 4.3 4.7 4.7 4.8 4.8 5.7

7.6 7.7 7.5 7.0 7.8 8.2 7.6

2.66 3.35 3.07 2.97 2.87 3.06 3.142.4 2.9 3.1 3.4 2.6 2.8 3.21.1 1.1 1.3 1.3 0.8 0.7 0.60.1 0.1 0.1 0.2 0.1 0.1 0.1

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

დასაქმებულთა განაწილება დასაქმების სექტორის მიხედვით სასოფლო თვითდასაქმების ჩათვლით სოფლის მეურნეობა მომპოვებელი მრეწველობა გადამამუშავებელი მრეწველობა ელ-ენერგია, გაზი, წყალმომარაგება

მშენებლობა ვაჭრობა და მომსახურება სასტუმროები და რესტორნები ტრანსპორტი და კომუნიკაცია

ოპერაციები უძრავი ქონებით საფინანსო შუამავლობა სახელმწიფო მართვა განათლება

ჯანდაცვა სხვა მომსახურება შინამეურნეობებში დაქირავება ექსტერიტორიული ორგანიზაციები


ãàñàõëäáèñ ñòðóõòóðàøè øäëãäâè üíìàãè éíëîíìäìòèà åàýðíáà ãà ñà÷íôàúþíåðäáí ëíëñàþóðäáà, ðíëêèñ ûèðèçàãè ìàüèêè åàýðíáàà. àë ñäõòíðèñ þåäãðèçè üíìèñ ëàùåäìäáäêè ñòàáèêóðàã 10 îðíúäìòèñ ëàþêíáêíáàøè è÷í ëçäêè ñàéåêäåè îäðèíãèñ âàìëàåêíáàøè ãà ðàèëä âàëíéåäçèêè òäìãäìúèà àõ àð øäèìèøìäáíãà.

àìàêíâèóðè ðàë øäèûêäáà èçõåà ãàñàõëäáèñ ñòðóõòóðèñ éèãäå äðç ëìèøåìäêíåàì øäëàãâäìäêæä - âàìàçêäáèñ ñäõòíðæä.

ãàñàõëäáèñ ñòðóõòóðèñ ñàõàðçåäêíñ ñîäúèôèéèãàì âàëíëãèìàðä, ëèæàìøäüíìèêèà ëèñè âàìþèêåà ñàñíôêí çåèçãàñàõëäáèñ âàðäøä, ðàëãäìàãàú óéàìàñéìäêèñ þåäãðèçè üíìà èëãäìàã ëàöàêèà, ðíë ÷åäêà ñþåà ñäõòíðøè ëèëãèìàðä îðíúäñäáèñà ãà òäìãäìúèäáèñ ìèåäêèðäáàñ àþãäìñ. (èþèêäç ãèàâðàëà N16).

23

ñàñíôêí çåèçãàñàõëäáèñ âàðäøä ãàñàõëäáèñ ñòðóõòóðàøè øäãàðäáèç âàðùäåàãè þãäáà ñþåà ãàðâäáèñ þåäãðèçè üíìà. ëèóþäãàåàã àëèñà, ûàêèàì ãàáàêèà ñàëçíëíëîíåäáäê ãà âàãàëàëóøàåäáäê ëðäüåäêíáàøè, àìó äéíìíëèéèñ ðäàêóð ñäõòíðøè, ãàñàõëäáóêçà þåäãðèçè üíìà. 2009-2015 üêäáøè äñ ëàùåäìäáäêè 11 îðíúäìòèñ ëàþêíáêíáàøè è÷í.

ëçêèàìíáàøè, ñàéåêäå îäðèíãøè ñàñíôêí çåèçãàñàõëäáèñ âàðäøä ãàñàõëäáèñ ñòðóõòóðà àðñäáèçàã àð øäúåêèêà. äñ àðúàà âàñàéåèðè, åèìàèãàì àñäç úåêèêäáäáñ çåèçãèìäáèñ îèðíáäáøè àçäóêè üêäáèñ ñýèðãäáà, çóëúà äôäõòèàìè èìãóñòðèóêè îíêèòèéèñ øäëóøàåäáèñà ãà âàòàðäáèñ øäëçþåäåàøè øäñàûêäáäêèà øðíëèñ áàæðèñ ñòðóõòóðèñ àðñäáèçè úåêèêäáà 3-4 üêèñ ëàìûèêæäú éè.


2.6 3.0 2.8 2.9 2.8 2.3 3.01.0 1.4 1.7 1.7 1.5 1.8 2.29.6 9.7 9.5 9.1 9.5 9.1 8.82.4 2.5 2.6 2.4 2.7 2.0 1.77.6 6.8 7.6 7.4 6.8 7.7 7.3

20.9 19.8 19.7 20.5 20.1 19.1 19.7

2.2 2.5 2.3 2.5 2.8 2.2 2.8

10.2 8.9 7.9 8.7 9.3 10.4 9.3

2.2 2.5 2.1 2.2 3.2 3.1 3.33.9 3.3 3.3 3.0 3.4 3.6 3.8

8.5 8.7 9.7 9.5 9.5 9.5 10.8

16.0 15.6 15.3 14.215.6 16.1 14.3

5.6 6.8 6.3 6.05.7 6.0 5.9

5.1 6.0 6.4 6.85.2 5.6 5.9

2.2 2.2 2.7 2.7 1.7 1.3 1.10.2 0.2 0.3 0.3 0.2 0.1 0.1

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

დასაქმებულთა განაწილება დასაქმების სექტორის მიხედვით სასოფლო თვითდასაქმების გარეშე სოფლის მეურნეობა მომპოვებელი მრეწველობა გადამამუშავებელი მრეწველობა ელ - ენერგია, გაზი, წყალმომარაგება

მშენებლობა ვაჭრობა და მომსახურება სასტუმროები და რესტორნები ტრანსპორტი და კომუნიკაცია

ოპერაციები უძრავი ქონებით საფინანსო შუამავლობა სახელმწიფო მართვა განათლება

ჯანდაცვა სხვა მომსახურება შინამეურნეობებში დაქირავება ექსტერიტორიული ორგანიზაციები


ðíâíðú N15 ãà N16 ãèàâðàëäáøè àñàþóêè ëíìàúäëäáè àãàñòóðäáäì, ãäòàêóðè ñäõòíðóêè âàìàüèêäáà ìàéêäáàã èìôíðëàòèóêèà. óôðí ñà÷óðàãöäáí øäèûêäáà è÷íñ âàìàüèêäáà äéíìíëèéóðè ñàõëèàìíáäáèñ óôðí ëñþåèê ÿâóôäáøè - ðäàêóð ñäõòíðñà ãà ëíëñàþóðäáèñ ñôäðíøè. àëàñçàì, ñàñàðâäáêí èõìäáà âàåèçåàêèñüèìíç ñàõàðçåäêíøè ãàñàõëäáèñ ãàðâíáðèåè ñòðóõòóðèñ ñîäúèôèéà ãà âàìþèêóêè 16 ñäõòíðèãàì âàëíå÷íç 3 ûèðèçàãè äéíìíëèéóðè çåàêñàæðèñèç äðçëàìäçèñàâàì ûàêæäã ëìèøåìäêíåìàã âàìñþåàåäáóêè ÿâóôè (èþèêäç ãèàâðàëà N17):

àâðàðóêè ñäõòíðè, ñàãàú øäåèãìäì ñíôêèñ ëäóðìäíáàøè, ëäò÷äåäíáàñà ãà çäåæýäðèñ 1. ñäõòíðøè ãàñàõëäáóêäáè. ñàõàðçåäêíñ øäëçþåäåàøè ëàçè àáñíêóòóðè óëðàåêäñíáà - 95 îðíúäìòæä ëäòè ñíôêèñ ëäóðìäíáàøè çåèçãàñàõëäáóêäáè àðèàì. úþàãèà, äñäú äéíìíëèéèñ ðäàêóðè ñäõòíðèà, ëàâðàë øèìààðñèç ãàñàõëäáèñ àöìèøìóêè ôíðëà óôðí ñíúèàêóð ãàòåèðçåàñ àòàðäáñ, åèãðä äéíìíëèéóðñ. àõäãàì âàëíëãèìàðä, äéíìíëèéèñ ðäàêóð ñäõòíðøè ñíôêèñ ëäóðìäíáèñ ùàðçåà, ùåäìè éåêäåèñ ëèæìäáèãàì âàëíëãèìàðä, ëèæàìøäóüíìêàã ùàåçåàêäç;ðäàêóðè ñäõòíðè, ñàãàú øäåèãìäì ñàëçí ëíëîíåäáäê ëðäüåäêíáàøè, âàãàëàëóøàåäáäê 2. ëðäüåäêíáàøè, ëøäìäáêíáèñ ãà äêäõòðíäìäðâäòèéèñ, âàæèñ ãà ü÷àêëíëàðàâäáèñ ñäõòíðäáøè ãàñàõëäáóêäáè;ëíëñàþóðäáèñ ñäõòíðè, ñàãàú øäåèãìäì ãàìàðùäìè ñäõòíðäáèñ üàðëíëàãâäìêäáè, èë 3. ñäõòíðäáèñà, ðíëêäáèú îðíãóõúèàñ ìàòóðàêóð-ìèåçíáðèåè ôíðëèç àð àüàðëíäáäì.

àâðàðóê ñäõòíðøè ãàñàõëäáèñ àëíðôóêàã ëàöàêè þåäãðèçè üíìèñ øäñàþäá óéåä àöèìèøìà. äñ ëíåêäìà ñàõàðçåäêíñ äéíìíëèéèñ äðçäðçè óëçàåðäñè îðíáêäëàà. àë øäëçþåäåàøè óôðí ëìèøåìäêíåàìè äéíìíëèéèñ ðäàêóð ñäõòíðñà ãà ëíëñàþóðäáèñ ñôäðíøè ãàñàõëäáèñ îðíîíðúèäáèà.

24


53.8% 52.3% 52.4% 52.0% 51.2% 50.4% 48.4%

9.7% 10.1% 10.5% 10.2% 10.3% 10.5% 10.6%

36.5% 37.6% 37.2% 37.8% 38.5% 39.1% 41.0%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

დასაქმებულთა განაწილება დასაქმების გამსხვილებულ სექტორებში

აგრარული სექტორი რეალური სექტორი მომსახურების სექტორი


øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëäáèç, äéíìíëèéèñ ðäàêóð ñäõòíðøè ãàñàõëäáèñ þåäãðèçè üíìà ëçêèàìè ãàñàõëäáèñ 10.6 îðíúäìòèà ãà äñ ëàùåäìäáäêè 2009-2015 üêäáèñ ëàìûèêæä óúåêäêè ãàðùà.

ëíëñàþóðäáèñ ñäõòíðøè ãàñàõëäáèñ þåäãðèçè üíìà 2015 üäêñ 41.0 îðíúäìòè è÷í ãà 2009-2015 üêäáøè æðãèñ òäìãäìúèèç âàëíèðùäíãà.

äðçâåàðè øäÿàëäáèñàçåèñ øäèûêäáà èçõåàñ, ðíë ãàñàõëäáèñ ñòðóõòóðàøè áíêí 6 üêèñ ëàìûèêæä âàìåèçàðäáóêè îíæèòèóðè ëíåêäìäáè, ðíëäêèú àâðàðóêè ñäõòíðèñ þåäãðèçè üíìèñ øäëúèðäáàøè âàëíèþàòà, ûèðèçàãàã ëíëñàþóðäáèñ ñôäðíøè ãàñàõëäáèñ þåäãðèçè üíìèñ æðãèç è÷í âàìîèðíáäáóêè. àöìèøìóêè îíæèòèåè äéíìíëèéèñ ðäàêóð ñäõòíðñ îðàõòèéóêàã àð øäþäáèà, ðíëêèñ þåäãðèçè üíìà óúåêäêèà.

óëóøäåðíáèñ ñòðóõòóðóêè àñîäõòäáèñ øäñüàåêèñàçåèñ ëìèøåìäêíåàìèà ãàñàõëäáèñ øäñüàåêà îðíôäñèäáèñ ëèþäãåèç ISCO-ñ éêàñèôèéàòíðèñ øäñàáàëèñàã.

îðíôäñèäáèñ ëèþäãåèç ãàñàõëäáèñ ñòðóõòóðèñ ÷åäêàæä ëñþåèêè ëä-6 ÿâóôèà, ñàãàú øäãèàì ñíôêèñ, ñàò÷äí, ñàëíìàãèðäí ëäóðìäíáäáèñ, ëäçäåæäíáèñà ãà çäåæýäðèñ éåàêèôèúèóðè ëóøàéäáè. äñ èë ñàñíôêí çåèçãàñàõëäáóêçà àðëèàà, ðíëäêæäú 2015 üäêñ ãàñàõëäáóêçà 46.7 îðíúäìòè ëíãèíãà. àöñàìèøìàåèà, ðíë àë ÿâóôèñ þåäãðèçè üíìà 2009-2015 üêäáøè øäëúèðäáèñ, úàêñàþàã ãàãäáèçè òäìãäìúèèç âàëíèðùäåà.

25


3.0% 3.1% 2.9% 2.9% 2.4% 2.0% 2.0%3.4% 3.4% 3.8% 3.9% 3.7% 3.6% 4.1%

11.8% 11.4% 11.1% 10.9% 11.1% 12.2% 11.8%

6.2% 7.3% 6.8% 6.8% 7.7% 7.8% 7.6%1.2% 1.5% 1.2% 1.8% 1.4% 1.5% 1.8%8.7% 9.6% 9.8% 8.9% 9.6% 9.4% 10.1%

52.2% 50.4% 50.7% 50.3% 49.7% 49.1% 46.7%

4.8% 4.2% 4.2% 4.5% 4.6% 4.6% 5.1%4.0% 4.0% 3.8% 4.3% 4.5% 5.0% 5.0%4.9% 5.1% 5.6% 5.7% 5.2% 4.9% 5.9%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

დასაქმებულთა განაწილება დაკავებული პროფესიების მიხედვით სასოფლო თვითდასაქმების ჩათვლით

NA ჯგუფი 1 ჯგუფი 2 ჯგუფი 3 ჯგუფი 4

ჯგუფი 5 ჯგუფი 6 ჯგუფი 7 ჯგუფი 8 ჯგუფი 9


ûàêæä ëìèøåìäêíåàìèà éåàêèôèéàúèèñ ãíìèñ ëèþäãåèç âàëñþåèêäáóê ÿâóôäáøè ãàñàõëäáèñ ûèðèçàã ñäõòíðäáøè ãàñàõëäáóêçà âàìàüèêäáà.

àë ìèøìèç ñíôêèñ ëäóðìäíáàøè ãàñàõëäáóêçà âàìàüèêäáà úàêñàþàã îðíôäñèèñ àð ëõíìäçà ñàñàðâäáêíãàà: ëàçè þåäãðèçè üíìà 2015 üäêñ ñíôêèñ ëäóðìäíáàøè ãàñàõëäáóêçà 66 îðíúäìòè è÷í. äñ ëàùåäìäáäêè ñàéåêäå îäðèíãøè çèçõëèñ àð øäúåêèêà.


10% 10% 9% 10% 10% 10% 10%

16% 18% 18% 19% 19% 18% 18%

8% 9% 8% 7% 8% 7% 6%

67% 64% 66% 65% 63% 64% 66%

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2009 2010 2011 2012 2013 2014 2015

სოფლის მეურნეობაში დასაქმებულთა განაწილება სერტიფიცირებული პროფესიების მიხედვით



26

óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòäáèñ þåäãðèçè üíìà ñíôêèñ ëäóðìäíáàøè ãàñàõëäáóêäáñ øíðèñ ñòàáèêóðàã 10 îðíúäìòèà, ñàøóàêí ãíìèñ ñîäúèàêèñòäáèñà éè - 18 îðíúäìòè. àëãäìàã, ãàñàõëäáèñ ñòðóõòóðèñ ñèñòäëóðè úåêèêäáèñàçåèñ ñàéëàíã ëûèëä îèðíáäáè èéåäçäáà, åèìàèãàì àâðàðóêè ãàñàõëäáèñ àñèëäòðèóêàã ëàöàêè þåäãðèçè üíìèñ øäëúèðäáèñàçåèñ ëäòìàéêäáàã ëæàã àë ñôäðíøè ëíëóøàåäçà ëþíêíã 34 îðíúäìòèà, þíêí 66 îðíúäìòè àë ãàðâèãàì ñþåà ãàðâøè âàãàñàñåêäêàã ëæàã àðàà ãà îðíôäñèóê-òäõìèéóðè ñüàåêäáèñ ôàðçíëàñøòàáèàìè îðíâðàëèñ âàðäøä ãàñàõëäáèñ ñòðóõòóðèñ úåêèêäáàñ ñàéëàíã ãèãè ãðí, øäñàûêíà àçüêäóêäáè, ãàñýèðãäñ.

ëðäüåäêíáèñà ãà ëøäìäáêíáèñ ãàðâäáøè ãàñàõëäáóêçà 31 îðíúäìòè óëàöêäñè éåàêèôèéàúèèñ ëóøàéäáè àðèàì, þíêí 36 îðíúäìòè - îðíôäñèèñ àðëõíìäìè. ñà÷óðàãöäáíà, ðíë óëàöêäñè ãà ñàøóàêí éåàêèôèéàúèèñ ëõíìä ñîäúèàêèñòäáèñ þåäãðèçè üíìà àöìèøìóê ÿâóôøè øäëúèðäáèñ, þíêí îðíôäñèèñ àðëõíìäçà þåäãðèçè üíìà - æðãèñ òäìãäìúèàñ àåêäìñ. óéàìàñéìäêè ñàéëàíã ûìäêàã àñàþñìäêèà, çóëúà ëçêèàìíáàøè àõ øäèûêäáà àë ñôäðíøè ãàñàõëäáóêçà ãäéåàêèôèéàúèèñ ñóñòè, çóëúà äðçëìèøåìäêíåìàã ìäâàòèóðè òäìãäìúèà ãàåèìàþíç.


36% 37% 38% 35% 33% 32% 31%

16% 18% 20% 20%19% 19% 16%

17% 15%14%

14%14% 14% 16%

30% 30% 28% 31% 35% 36% 36%

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2009 2010 2011 2012 2013 2014 2015

მრეწველობასა და მშენებლობაში დასაქმებულთა განაწილება სერტიფიცირებული პროფესიების მიხედვით



åàýðíáàñà ãà ñà÷íôàúþíåðäáí ëíëñàþóðäáàøè ãàñàõëäáóêçà 37 îðíúäìòè ãèîêíëèñ ëèþäãåèç óëàöêäñè éåàêèôèéàúèèñ îðíôäñèèñ ëõíìä ñîäúèàêèñòèà. çèçõëèñ àëãäìèåäñ - 36 îðíúäìòñ - îðíôäñèà àð àõåñ. 19 îðíúäìòè ãèîêíëèñ ëèþäãåèç ñàøóàêí ãíìèñ ñîäúèàêèñòèà. îðíôäñèèñ àðëõíìäçà ãà óëàöêäñè éåàêèôèéàúèèñ ëõíìäçà þåäãðèçè üíìèñ ëàùåäìäáäêè àë ÿâóôøè ñóñòàã âàëíþàòóêè æðãèñ òäìãäìúèèç þàñèàçãäáà, þíêí ñàøóàêí ãíìèñ éåàêèôèéàúèèñ ëõíìä ñîäúèàêèñòçà þåäãðèçè üíìà øäëúèðäáèñ òäìãäìúèàñ àåêäìñ.

27


32% 36% 33% 34% 38% 37% 37%

22%26%

25% 26% 21% 20% 19%

9%

8%8% 7% 8% 7% 8%

37%30% 33% 33% 34% 36% 36%

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2009 2010 2011 2012 2013 2014 2015

ვაჭრობასა და საყოფაცხოვრებო მომსახურებაში დასაქმებულთა განაწილება სერტიფიცირებული პროფესიების მიხედვით



÷åäêàæä ñàèìòäðäñí âàìàçêäáèñ ãà ÿàìãàúåèñ ñôäðíäáøè ãàñàõëäáóêçà éåàêèôèéàúèèñ ëèþäãåèç âàìàüèêäáàà. àë ãàðâäáøè ãàñàõëäáóêçà óãèãäñè ìàüèêè óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòèà ãà ëàçè þåäãðèçè üíìà æðãèñ îíæèòèóð òäìãäìúèàñ àåêäìñ. àëàñçàì, ñàéëàíã ãàáàêèà ñàøóàêí éåàêèôèéàúèèñ ñîäúèàêèñòçà þåäãðèçè üíìà, ðíëäêèú øäëúèðäáèñ òäìãäìúèàñ àåêäìãà. âàìàçêäáèñ ñôäðíøè àëâåàðè òäìãäìúèà øäèûêäáà îíæèòèóðàã øäôàñãäñ, ëàâðàë ÿàìãàúåèñ ñôäðíøè èâè óôðí àðàñàþàðáèäêí ëãâíëàðäíáèñ ëàìèøìäáäêèà.


70% 67% 70% 71% 73% 73% 74%

20% 23% 22% 20% 18% 18% 17%

2% 2% 2% 2% 2% 2% 2%8% 7% 7% 7% 7% 7% 8%

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70%

80%

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2009 2010 2011 2012 2013 2014 2015

განათლებისა და ჯანდაცვის სექტორებში დასაქმებულთა განაწილება სერტიფიცირებული პროფესიების მიხედვით



28


52% 54% 54% 54% 53% 51% 54%

14% 16% 16% 14% 16% 15% 14%

14%12% 11% 11% 11% 12% 10%

20% 18% 19% 21% 20% 22% 21%

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2009 2010 2011 2012 2013 2014 2015

სახელმწიფო მართვაში, ტრანსპორტში, კომუნიკაციებში, სასტუმროებსა და მომსახურების სხვა დარგებში დასაქმებულთა განაწილება

სერტიფიცირებული პროფესიების მიხედვით



èñäç ëðàåàêôäðíåàì ÿâóôøè, ðíâíðèúàà ñàþäêëüèôí ëàðçåèñ íðâàìíäáè, òðàìñîíðòè, ñàñòóëðíäáè ãà ëíëñàþóðäáèñ ñþåà ñàþääáè, ãàñàõëäáóêçà ÷åäêàæä ãèãè ìàüèêè óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòäáæä ëíãèñ (èþèêäç ãèàâðàëà N23). ñàçèçàíã àë ÿâóôäáèñ âàìþèêåà ñàèëäãí øäôàñäáäáñ åäð èûêäåà, çóëúà, óëàöêäñè éåàêèôèéàúèèñ ëõíìä ãàñàõëäáóêçà þåäãðèçè üíìà àë ñàéëàíã àëíðôóê ÿâóôøè 2015 üäêñ ÷åäêà üèìà üäêçàì øäãàðäáèç ëàöàêè è÷í, ðàú øäèûêäáà ãàãäáèçè òäìãäìúèèñ ãàü÷äáèñ ìèøìàã ùàèçåàêíñ.

3.2 ñàëóøàí àãâèêäáèñ âäìäðàúèèñ ü÷àðíäáè3.2 ñàëóøàí àãâèêäáèñ âäìäðàúèèñ ü÷àðíäáè

øðíëèñ áàæàðæä ëíçþíåìèñ øäñüàåêèñàçåèñ ûàêæä ëìèøåìäêíåàìèà ñàëóøàí àãâèêäáèñ âàìàüèêäáà ëàçè âäìäðàúèèñ ü÷àðíäáèñ ëèþäãåèç. àë ìèøìèç øèìàëäóðäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëçà áàæèãàì âàëíå÷àåèç ñàëóøàí àãâèêäáèñ íçþè òèîè:

ñàþäêëüèôíñ ëèäð øäõëìèêè ñàëóøàí àãâèêäáè - ñàãàú øäåèãìäì ñàþäêëüèôí 1. ãàüäñäáóêäáäáøè ãà ñàþäêëüèôí ñäõòíðèñ íðâàìèæàúèäáøè ãàñàõëäáóêäáè;éäðûí ñäõòíðèñ ëèäð øäõëìèêè ñàëóøàí àãâèêäáè, ñàãàú øäåèãìäì éäðûí ñàüàðëíäáñà 2. ãà íðâàìèæàúèäáøè ãàõèðàåäáèç ãàñàõëäáóêäáè ãà çåèçíì ëäüàðëääáè ãàõèðàåäáóêè ëóøàéäáèç;ñàéóçàðè óìàðäáèç øäõëìèêè ñàëóøàí àãâèêäáè, ñàãàú øäåèãìäì èñ àðàñàñíôêí 3. çåèçãàñàõëäáóêäáè, ðíëäêçà ãàñàõëäáàú ëàçè óìàðäáèñ âàëí÷äìäáèç ëíþãà. àñäç ãàñàõëäáóêäáñ ëèäéóçåìäì èìãèåèãóàêóðè ëäüàðëääáè, ðíëêäáèú çàåèñ îðíôäñèóêè úíãìèç àðèàì çåèçãàñàõëäáóêäáè;ñòèõèóðàã øäõëìèêè ñàëóøàí àãâèêäáè, ñàãàú øäåèãìäì ñíôêèñ ëäóðìäíáàøè 4. çåèçãàñàõëäáóêäáè, üåðèê åàýðíáàøè çåèçãàñàõëäáóêäáè, òàõñèñòäáè ãà ñþåà, ðàú àð ëíèçþíåñ âàìñàéóçðäáèç ëàöàê éåàêèôèéàúèàñ.

2015 üêèñ ëãâíëàðäíáèç, ñàëóøàí àãâèêäáèñ 53 îðíúäìòè ñòèõèóðàã è÷í øäõëìèêè, 27 îðíúäìòè - éäðûí ñäõòíðèñ ëèäð è÷í âäìäðèðäáóêè, 15 îðíúäìòè - ñàþäêëüèôíñàâàì, 4 îðíúäìòè éè - ñàéóçàð óìàðäáæä ãà÷ðãìíáèç.

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17% 17% 16% 16% 14% 14% 15%

19% 22% 23% 23% 25% 26% 27%

5% 4% 4% 4% 4% 4% 4%

60% 57% 57% 57% 57% 56% 53%

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70%

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100%

2009 2010 2011 2012 2013 2014 2015

სამუშაო ადგილების განაწილება მათი გენერაციის წყაროების მიხედვით

სახელმწიფოს მიერ შექმნილი კერძო სექტორის მიერ შექმნილი

საკუთარ უნარებზე დაყრდნობით შექმნილი სტიქიურად შექმნილი სამუშაო ადგილები


âàëíéåäçèêè òäìãäìúèäáè ñàéëàíã ëìèøåìäêíåàìèà ãà ñàèìòäðäñí ñóðàçñ àùåäìäáñ. 2009-2015 üêäáøè ñàéëàíã ëéàôèíãàà ùàëí÷àêèáäáóêè ñòèõèóðè ñàëóøàí àãâèêäáèñ þåäãðèçè üíìèñ øäëúèðäáà ãà éäðûí ñäõòíðèñ ëèäð âäìäðèðäáóêè ñàëóøàí àãâèêäáèñ þåäãðèçè üíìèñ æðãà. àëàåä ãðíñ øäèìèøìäáà ñàþäêëüèôíñ ëèäð øäõëìèêè ñàëóøàí àãâèêäáèñ þåäãðèçè üíìèñ ñóñòàã âàëíþàòóêè øäëúèðäáà ãà ñàéóçàð óìàðäáæä ãà÷ðãìíáèç øäõëìèêè ñàëóøàí àãâèêäáèñ þåäãðèçè üíìèñ ñòàáèêóðíáà.


35% 34% 33% 32% 29% 28% 29%

40% 44% 46% 47% 49% 51% 52%

10% 8% 8% 7% 8% 8% 8%

15% 14% 12% 13% 14% 13% 12%

0%

10%

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30%

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50%

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70%

80%

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100%

2009 2010 2011 2012 2013 2014 2015

სამუშაო ადგილების განაწილება მათი გენერაციის წყაროების მიხედვით სასოფლო თვითდასაქმების გარეშე

სახელმწიფოს მიერ შექმნილი კერძო სექტორის მიერ შექმნილი

საკუთარ უნარებზე დაყრდნობით შექმნილი სტიქიურად შექმნილი სამუშაო ადგილები


30

æäëíàöìèøìóêè òäìãäìúèäáè, ëçêèàìíáàøè, ñàéëàíã ëàöàêè îíæèòèåèñ ëàòàðäáäêèà, ðàú ñàëóøàí àãâèêäáèñ âäìäðèðäáàøè éäðûí ñäõòíðèñ þåäãðèçè üíìèñ æðãàøè âàëíèþàòäáà, ðíëäêèú ûèðèçàãàã ñòèõèóðàã øäõëìèêè ñàëóøàí àãâèêäáèñ þåäãðèçè üíìèñ øäëúèðäáèñ þàðÿæä þãäáà. çóëúà, àöñàìèøìàåèà èñèú, ðíë îðíáêäëèñ ëàñøòàáèñ ôíìæä äñ ãàãäáèçè òäìãäìúèäáè ñàéëàíã ãàáàêè òäëîèç þàñèàçãäáà.

üèìàëãäáàðä àìàêèæè éèãäå äðçþäê àùåäìäáñ, ðíë ãàñàõëäáèñ ñôäðíøè ñàõàðçåäêíñ äðçäðçè ÷åäêàæä ëìèøåìäêíåàìè îðíáêäëà ñíôêàã çåèçãàñàõëäáèñ ¸èîäðòðíôóêàã ëàöàêè þåäãðèçè üíìàà. ñíôêàã çåèçãàñàõëäáèñàâàì àáñòðàâèðäáèç, æäëíàöìèøìóêè òäìãäìúèäáè âàúèêäáèç óôðí çåàêñàùèìíã ãà îíæèòèóðàã âàëíè÷óðäáèàì (èþèêäç ãèàâðàëà N25).

31

4. ñòðóõòóðóêè óëóøäåðíáà4. ñòðóõòóðóêè óëóøäåðíáà

4.1 ñòðóõòóðóêè óëóøäåðíáà: ëäçíãíêíâèóðè àñîäõòè4.1 ñòðóõòóðóêè óëóøäåðíáà: ëäçíãíêíâèóðè àñîäõòè

ñòðóõòóðóêè óëóøäåðíáèñ ëäò-ìàéêäáàã æóñò îðíúäìòóê âàìæíëèêäáàøè øäôàñäáà ðçóêèà, âàìñàéóçðäáèç ñàõàðçåäêíøè. àëèñàçåèñ àóúèêäáäêèà øðíëèñ áàæàðæä àðñäáóêè åàéàìñèäáèñ øäñüàåêà. ñàõàðçåäêíøè ñàëóøàíñ ëàûèäáäêçà àöðèúþåà óéåä ãèãè þàìèà àöàð þíðúèäêãäáà ãà ëàçè îðíôäñèóêè ñòðóõòóðèñ øäôàñäáèñ äðçàãäðçè ü÷àðí øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåàà.

ñòðóõòóðóêè óëóøäåðíáèñ îàðàãèâëà ñàõàðçåäêíøè øäèûêäáà øäëãäâìàèðàã àöèüäðíñ: âàìàçêäáèñ ñèñòäëà àð àì åäð àëæàãäáñ øäñàáàëèñè (øðíëèñ áàæàðæä ëíçþíåìàãè) •

ñîäúèàêíáèñ (éåàêèôèéàúèèñ) éàãðäáñ. ñþåàâåàðàã ðíë åçõåàç, âàìàçêäáèñ ñèñòäëà ãà øðíëèñ áàæàðè àð àðèñ éíìâðóäìòóêè. ëàâàêèçàã, øðíëèñ áàæàðæä àðèñ ëíçþíåìà æííòäõìèéíñäáæä, âàìàçêäáèñ ñèòäëà éè àëæàãäáñ àðààãäéåàòóðàã ýàðáè ðàíãäìíáèç áèæìäñèñ àãëèìèñòðèðäáèñ ñîäúèàêèñòäáñ;

ëäíðä ëþðèå, âàìàçêäáèñ ñèñòäëà, ðíâíðú óëàöêäñè, èñä îðíôäñèóêè, åäð èûêäåà • øäñàáàëèñ úíãìàñ (éåàêèôèéàúèàñ) àìó âàìàçêäáèñ úäìæè ãà ëèñè ëôêíáäêèñ ôàõòíáðèåè úíãìà ãà øäûäìèêè óìàðäáè äðçëàìäçñ àð øääñàáàëäáà. ëàâàêèçàã, èìïèìðèñ ãèîêíëè àð ìèøìàåñ çàìàëäãðíåä èìïèìðèñ ðäàêóð éåàêèôèéàúèàñ. àëàñ øäèûêäáà äüíãíñ úäìæèñ øäóñàáàëí éåàêèôèéàúèèñ îðíáêäëà.

÷íåäêèåä àëèñ øäãäâàã, õåä÷ìèñ äéíìíëèéà åäð óæðóìåäê÷íôñ áàæàðæä àðñäáóêè ñàëóøàí ûàêèñ (øðíëèçè ðäñóðñèñ) àãäõåàòóðè ñàëóøàí àãâèêäáèñ âäìäðèðäáàñ. àëàñçàì ãàéàåøèðäáèç þàæè óìãà âàäñåàñ èë âàðäëíäáàñàú, ðíë, ðíâíðú æäëíç àöåìèøìäç, ñàõàðçåäêíñ äéíìíëèéà óîèðàòäñàã ãàáàêè éåàêèôèéàúèèñ ñàëóøàí àãâèêäáñ õëìèñ, ðíëäêçà ãàéàåäáà óëäòäñ øäëçþåäåäáøè, ñîäúèàêóð âàìàçêäáàñ àð ñàýèðíäáñ.

âàìàçêäáèñ ñèñòäëèñ ëèäð ëíëæàãäáóêè éàãðè þàìâðûêèåè óëóøäåðíáèñ øäãäâàã éàðâàåñ éåàêèôèéàúèàñ, àì èûóêäáóêèà óôðí ãàáàêè éåàêèôèéàúèèñ (ãà àìàæöàóðäáèñ) ñàëóøàíæä èëóøàíñ. ñàëóøàí ûàêèñ ãäéåàêèôèéàúèà ñòðóõòóðóêè óëóøäåðíáèñ äðçäðçè ëçàåàðè ìäâàòèóðè øäãäâèà, çóëúà àöñàìèøìàåèà, ðíë äñ îðíáêäëà, çàåèñ ëþðèå, àðàäðçâåàðíåàìèà. àðñäáóêè èìôíðëàúèóêè ëàñèåäáèç øäñàûêäáäêèà ëþíêíã èëèñ øäôàñäáà, çó:

ðíâíðèà øñí-èñ éðèòäðèóëèç óëóøäåðäáèãàì óëàöêäñè àì ñàøóàêí éåàêèôèéàúèèñ ëõíìä • þàìâðûêèåè óëóøäåðäáèñ þåäãðèçè üíìà;

ðíâíðèà ãàñàõëäáóêçà øíðèñ âàìàçêäáèñ úäìæèñ øäóñàáàëíã, ñäðçèôèúèðäáóêæä óôðí • ãàáàêè éåàêèôèéàúèèç ãàñàõëäáèñ þåäãðèçè üíìà.

àñäçè øäôàñäáäáèñ øäñàûêäáêíáà ëñíôêèíñ áäåð õåä÷àìàøè àð àðñäáíáñ. àë éóçþèç ñàõàðçåäêíøè èìôíðëàúèóêè óæðóìåäê÷íôèñ ñàéèçþè ñàéëàíã ëàöàê ãíìäæäà, çóëúà àðèñ øäôàñäáèñçåèñ ûàêæä ëìèøåìäêíåàìè âàðäëíäáà, ðíëêèñ ãðíñàú íðèåä æäëíàöìèøìóê îèðíáàñ çàìàáàðè üàðëàòäáèç øäèûêäáà àéëà÷íôèêäáãìäì èñ àãàëèàìäáè, ðíëäêçàçåèñàú:

ðäàêóðè éåàêèôèéàúèà àð øääñàáàëäáà úäìæèç ëèöäáóêñ. èñèìè åäð îíóêíáäì úäìæèñ 1. øäñàáàëèñè éåàêèôèéàúèèñ ñàëóøàíñ ãà/àì èûóêäáóêè àðèàì ãàçàìþëãìäì ãàáàêè éåàêèôèéàúèèñ ñàëóøàíñ, àì þàìâðûêèåàã äêíãíì ñàéóçàðè úäìæèñ øäñàáàëèñè éåàêèôèéàúèèñ ñàëóøàíñ;ëèöäáóêè éåàêèôèéàúèèñ úäìæè øääñàáàëäáà ëàç ðäàêóð óìàðäáñ, ëàâðàë øðíëèñ áàæðèñ 2. èìñòèòóúèóðè ñèñóñòèñ âàëí èñèìè åäð àþäðþäáäì øäñàáàëèñè éåàêèôèéàúèèñ ñàëóøàíñ ëíûäáìàñ ãà/àì èûóêäáóêè àðèàì ãàçàìþëãìäì ãàáàêè éåàêèôèéàúèèñ ñàëóøàíñ, àì þàìâðûêèåàã äêíãíì ñàéóçàðè úäìæèñ øäñàáàëèñè éåàêèôèéàúèèñ ñàëóøàíñ, åèìàèãàì àð àõåç ñàëóøàíñ ëíûäáìèñàçåèñ ñàýèðí àðàôíðëàêóðè éàåøèðäáè;úäìæèñ ëèþäãåèç éåàêèôèéàúèà, àìó ãèîêíëè ëèöäáóêè àõåç ãèãè þìèñ üèì ãà àëèñ 3. øäëãäâ òäõìíêíâèóð âàìåèçàðäáàñ ôäþè åäð àóü÷äñ, ðèñ âàëíú ëàçè úíãìà çàìàëäãðíåä ëíçþíåìäáèñà ãà îðàõòèéóêè ñàðâäáêèàìíáèñàçåèñ ëíðàêóðàã ëíûåäêäáóêèà. èñèìè èûóêäáóêè àðèàì àì ãàçàìþëãìäì ãàáàêè éåàêèôèéàúèèñ ñàëóøàíñ, àì þàìâðûêèåàã äêíãíì ëàçè úäìæèñ øäñàáàëèñè éåàêèôèéàúèèñ ñàëóøàíñ.

ûàêèàì ðçóêè ñàçõëäêèà, çó ðíëäêè éàòäâíðèà ðà þåäãðèçè üíìèç âàìñàæöåðàåñ ñòðóõòóðóêè óëóøäåðíáèñ ãíìäñ. àë ñèöðëèñ àìàêèæèñ ùàòàðäáà ñàãöäèñíã øäóûêäáäêèà.

32

àñäçè øäôàñäáäáèñàçåèñ, âàìàçêäáèñ êèéåèãóðíáèñ øäñüàåêèñ ëèæìèç àóúèêäáäêèà ëàñøòàáóðè âàëíéåêäåèñ ùàòàðäáà. âàìàçêäáèñ êèéåèãóðíáèñ øäñüàåêà äðçäðçè óëìèøåìäêíåàìäñè ñàéèçþèà, ðíëäêèú úäìòðàêóðè ëìèøåìäêíáèñ àðà ëþíêíã ñòðóõòóðóêè óëóøäåðíáèñ øäñüàåêèñ çåàêñàæðèñèçàà, àðàëäã èñ äðçäðç âàãàëü÷åäòè èìôíðëàúèóêè ñà÷ðãäìèà âàìàçêäáèñ ñèñòäëèñ øäëãâíëè âàìåèçàðäáèñ ñòðàòäâèèñ øäëóøàåäáèñàçåèñ. õåäëíç åìàþàåç, çó ðàëãäìàã øçàëáäýãàåè ëàñøòàáèñàà ñòðóõòóðóêè óëóøäåðíáèñ îðíáêäëèñ èñ ìàüèêè, ðíëêèñ øäôàñäáàú àðñäáóêè èìôíðëàúèóêè ëàñèåäáèçàà øäñàûêäáäêè.

4.2 þàìâðûêèåè óëóøäåðíáà ãà ãäéåàêèôèéàúèà, ðíâíðú ñòðóõòóðóêè 4.2 þàìâðûêèåè óëóøäåðíáà ãà ãäéåàêèôèéàúèà, ðíâíðú ñòðóõòóðóêè óëóøäåðíáèñ âàëíåêèìäáàóëóøäåðíáèñ âàëíåêèìäáà

ñòðóõòóðóêè óëóøäåðíáèñ àñîäõòøè âàìñàéóçðäáèç ëìèøåìäêíåàìè þàìâðûêèåè óëóøäåðíáèñ îðíôäñèóêè ìèøìèç âàìþèêåàà.

þàìâðûêèåè óëóøäåðäáèñ ûèðèçàãè ìàüèêè, ëçäêè ñàéåêäåè îäðèíãèñ ëàìûèêæä, óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòäáè ãà îðíôäñèèñ àðëõíìäìè è÷åìäì. ñàøóàêí ãà ãàáàêè éåàêèôèéàúèèñ ñîäúèàêèñòäáèñ þåäãðèçè üíìà þàìâðûêèå óëóøäåðäáøè øäãàðäáèç ãàáàêèà. àõäãàì âàìñàéóçðäáèç àöñàìèøìàåè ãàáàêè éåàêèôèéàúèèñ ñîäúèàêèñòäáè àðèàì, ðíëäêçà þåäãðèçè üíìà ëçäêè ñàéåêäåè îäðèíãèñ ëàìûèêæä 4-5 îðíúäìòèñ ëàþêíáêíáàøèà.


41% 41% 41% 43% 42% 43% 42%

19% 19% 20% 19% 16% 18% 17%

5% 6% 4% 3%5% 5% 4%

35% 34% 34% 35% 37% 35% 37%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

ხანგრძლივი უმუშევრების განაწილება ISCO-ს ერთნიშნა კოდების გამსხვილებულ ჯგუფებში

უმაღლესი კვალიფიკაციის სპეციალისტები საშუალო კვალიფიკაციის სპეციალისტები

დაბალი კვალიფიკაციის სპეციალისტები პროფესია არ აქვთ


àöñàìèøìàåèà, ðíë ñòðóõòóðóêè óëóøäåðíáèñ çåàêñàæðèñèç ëþíêíã þàìâðûêèåè óëóøäåðäáèñ îðíôäñèóêè ìèøìèç âàìàüèêäáà ñàéëàðèñè àðàà. úþàãèà, äñ âàìàüèêäáà øäèúàåñ âàðéåäóê èìôíðëàúèàñ, ëàâðàë óôðí ëäòàã èìôíðëàòèóêè àë ñòðóõòóðèñà ãà äéíìíëèéóðàã àõòèóðè ëíñàþêäíáèñ èëàåä ýðèêøè ëíúäëóêè âàìàüèêäáèñ øäãàðäáàà.

ñòðóõòóðäáèñ øäãàðäáèñ ëèþäãåèç, óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòäáèñ þåäãðèçè üíìà þàìâðûêèå óëóøäåðäáñ øíðèñ 32 îðíúäìòèç àöäëàòäáà ëçêèàìàã äéíìíëèéóðàã àõòèóð ëíñàþêäíáàøè óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòäáèñ þåäãðèç üíìàñ. äñ âàìñþåàåäáà 2009-2015 üêäáèñ ëàìûèêæä øäëúèðäáèñ òäìãäìúèàñ àòàðäáñ, ëàâðàë 32 îðíúäìòèç óôðí ëàöàêè þåäãðèçè üíìà ìèøìàåñ, ðíë óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòñ þàìâðûêèåàã óëóøäåðíáèñ ñàøóàêíæä 1/3-èç óôðí ëàöàêè øàìñè àõåñ, þíêí ãàáàêè éåàêèôèéàúèèñ îðíôäñèèñ øäëçþåäåàøè àñäçè øàìñè ñàøóàêíæä 42 îðíúäìòèç ìàéêäáèà. ñàøóàêíæä àñäåä 16 îðíúäìòèç ãàáàêèà þàìâðûêèåè óëóøäåðíáèñ øàìñè îðíôäñèèñ àðõíìèñ øäëçþåäåàøè.

33


40% 36% 36%41%

34%40%

32%

10%0%

9%3%

-9%

1%

0%

-41%-31%

-44%

-58%

-43% -41% -43%

- 22% -20% -21% -20%-13%

-21%-16%

-80%

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2009 2010 2011 2012 2013 2014 2015

ხანგრძლივ უმუშევრებში ISCO-ს ერთნიშნა კოდების გამსხვილებულიჯგუფების ხვედრითი წონის პროცენტული სხვაობა ეკონომიკურადაქტიურ მოსახლეობაში ISCO-ს ერთნიშნა კოდების გამსხვილებული

ჯგუფების ხვედრით წონასთან


დაბალი კვალიფიკაციის სპეციალისტები პროფესია არ აქვთ


àõäãàì âàëíëãèìàðä, øäèûêäáà èçõåàñ, ðíë þàìâðûêèåè óëóøäåðíáèñ øäãäâàã âàëíüåäóêè ãäéåàêèôèéàúèèñ îðíáêäëà ûàêæäã ëìèøåìäêíåàìèà. àë ãàñéåìèñ ñàôóûåäêñ âåàûêäåñ èñ âàðäëíäáà, ðíë þàìâðûêèåè óëóøäåðíáèñ çèçõëèñ 60 îðíúäìòñ óëàöêäñè ãà ñàøóàêí éåàêèôèéàúèèñ ëõíìä ñîäúèàêèñòäáè øäàãâäìäì, ñàèãàìàú ûèðèçàãè ìàüèêè (43 îðíúäìòè) óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòèà þàìâðûêèåè óëóøäåðíáà éè ëçêèàìè óëóøäåðíáèñ çèçõëèñ ìàþäåàðèà. àëãäìàã, ëçêèàìè óëóøäåðíáèñ çèçõëèñ 30 îðíúäìòè ãäéåàêèôèúèðäáóêè óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòäáèñàâàì øäãâäáà. ãäéåàêèôèéàúèèñ àñäçè ëàñøòàáè çåàêìàçêèå àãàñòóðäáñ ñàõàðçåäêíøè ñòðóõòóðóêè óëóøäåðíáèñ îðíáêäëèñ ñèëüåàåäñ.


15% 15%14% 14%

13% 13%

11%

8%10%

8% 8%9%

8% 7%

11%12%

11% 11% 11%10%

9%

0%

2%

4%

6%

8%

10%

12%

14%

16%

2009 2010 2011 2012 2013 2014 2015

ხანგრძლივი უმუშევრობის დონე ISCO-ს ერთნიშნა კოდების გამსხვილებულ ჯგუფებში

უმაღლესი ან საშუალო კვალიფიკაციის სპეციალისტები

დაბალი კვალიფიკაციის სპეციალისტები ან პროფესიის არმქონენი

საშუალოდ


34

þàìâðûêèåè óëóøäåðíáèñ ãíìèñ ëàùåäìäáäêè 2009-2015 üêäáøè ñàéëàíã éàðâàã ùàëí÷àêèáäáóêè øäëúèðäáèñ òäìãäìúèèç þàñèàçãäáà (èþäêäç ãèàâðàëà N 28). àöñàìèøìàåèà, ðíë þàìâðûêèåè óëóøäåðíáèñ ãíìä ñàøóàêí ãà ëàöàêè éåàêèôèéàúèèñ ëõíìä ñîäúèàêèñòäáñ øíðèñ, ðíâíðú üäñè, óôðí ëàöàêèà, åèãðä ãàáàêè éåàêèôèéàúèèñ àì ñîäúèàêíáèñ àðëõíìäçà øíðèñ. þàìâðûêèåè óëóøäåðíáèñ ãíìä 2015 üêèñ ëíìàúäëäáèç 9 îðíúäìòè è÷í, àìó ëçêèàìè óëóøäåðíáèñ 12-îðíúäìòèàì ãíìäæä àðúçó àðñäáèçàã ãàáàêè. äñ ìèøìàåñ, ðíë ñàõàðçåäêíøè ôðèõúèóêè óëóøäåðíáèñ ãíìä ëþíêíã 3 îðíúäìòèñ ãíìäæäà, ðàú æíâàãàã ìíðëàêóðàã ëèùìäóêèñ ãèàîàæíìøèà.

ñàøóàêí ãà óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòäáèñ äðç ÿâóôøè âàäðçèàìäáà ãà àë ÿâóôèñ ëàùåäìäáêäáèñ øäãàðäáà ãàáàêè éåàêèôèéàúèèñ ëõíìä ñîäúèàêèñòäáèñà ãà îðíôäñèèñ àðëõíìäçà âàäðçèàìäáóê ÿâóôçàì âàìîèðíáäáóêèà èëèç, ðíë àë íð ÿâóôøè ùàëí÷àêèáäáóêè òäìãäìúèäáè ëäòìàéêäáàã ¸íëíâäìóðèà.


16%16%

15%16%

15% 14%

12%12% 12% 12%11%

10% 10%9%

7%

8%

6%

5%

6% 6%5%

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9% 9%9%

8% 8%

11%12%

11% 11%

11%10%

9%

0%

2%

4%

6%

8%

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12%

14%

16%

18%

2009 2010 2011 2012 2013 2014 2015

ხანგრძლივი უმუშევრობის დონე ISCO-ს ერთნიშნა კოდების გამსხვილებულ ჯგუფებში


დაბალი კვალიფიკაციის სპეციალისტები პრფესია არ აქვთ



ðàú øääþäáà øäãàðäáèç ãäòàêóð âàìþèêåàñ (èþèêäç ãèàâðàëà N29), òäìãäìúèäáè èñäçèåäà, ðíâíðú íð ÿâóôàã àâðäâèðäáóêè ëàùåäìäáêäáèñ øäëçþåäåàøè, çóëúà àøéàðàã âàëíðùäóêè óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòäáèñ ÿâóôèà, ñàãàú þàìâðûêèåè óëóøäåðíáèñ ãíìä, ðíâíðú üäñè, ÷åäêà ñþåà ÿâóôçàì øäãàðäáèç âàëíéåäçèêàã ëàöàêèà. ëàðçàêèà 2009-2015 üêäáøè øäëúèðäáèñ ëéàôèí òäìãäìúèà ñüíðäã àë ÿâóôøèà, ëàâðàë 2015 üäêñàú þàìâðûêèåè óëóøäåðíáèñ ãíìä ñàéëàíã ëàöàê - 12 îðíúäìòèàì ìèøìóêæäà.

4.3 „ãàóéëà÷íôèêäáäêè“ ãàñàõëäáóêäáè àìó ôàðóêè ñòðóõòóðóêè 4.3 „ãàóéëà÷íôèêäáäêè“ ãàñàõëäáóêäáè àìó ôàðóêè ñòðóõòóðóêè óëóøäåðíáàóëóøäåðíáà

ñòðóõòóðóêè óëóøäåðíáèñ éíìòäõñòøè þàìâðûêèå óëóøäåðíáàæä àðàìàéêäá ëìèøåìäêíåàìèà „ãàóéëà÷íôèêäáäêè“ ãàñàõëäáóêäáèñ îðíáêäëà. äñ èñ àãàëèàìäáè àðèàì, ðíëêäáèñ úäìæèç ëèöäáóêè éåàêèôèéàúèèç ñàëóøàí àãâèêè åäð ëèèöäñ ãà ãàçàìþëãìäì ñþåà éåàêèôèéàúèèñ àì óôðí ãàáàêè éåàêèôèéàúèèñ ñàëóøàíñ. ëàðçàêèà, ôíðëàêóðàã èñèìè ãàñàõëäáóêìè àðèàì, ëàâðàë ôàõòíáðèåàã ëàç ñàëóøàí àð àéëà÷íôèêäáç. àë ëíåêäìàñ øäèûêäáà ôàðóêè ñòðóõòóðóêè óëóøäåðíáà åóüíãíç. àõ øäèûêäáà âàìåèþèêíç íðè øäëçþåäåà:

ðíãäñàú ñàëóøàí ûàêà ãàñàõëäáóêèà, ëàâðàë äûäáñ ñþåà ñàëóøàíñ, ðèñ ëèæäæèú, ðíâíðú 1. üäñè, îðíôäñèóêè øäóñàáàëíáàà;ðíãäñàú ñàëóøàí ûàêà åäð àþäðþäáñ çàåèñè éåàêèôèéàúèèñ øäñàáàëèñè ñàëóøàíñ ëíûäáìàñ 2. ãà èûóêäáóêèà óôðí ãàáàêè éåàêèôèéàúèèñ ñàëóøàíñ ãà÷àáóêãäñ.

35

ëäíðä øäëçþåäåèñçåèñ àåèöäç çèçíäóêè ãàñàõëäáóêèñ ûèðèçàãè îðíôäñèà ãèîêíëèñ ëèþäãåèç ãà øäåàãàðäç ëèñè ãàñàõëäáèñ ôàõòèóð îðíôäñèàñ. âàëíåðèúþäç èñ ãàñàõëäáóêäáè, ðíëêäáèú ôàõòèóðè ãàñàõëäáèç ëèäéóçåìäáèàì ISCO-ñ 1-ê ÿâóôñ, àìó þäêëûöåàìäê çàìàëãäáíáäáñ, àìó îðíôäñèäáñ, ðíëäêèú ãèîêíëèç ñäðòèôèúèðäáóêè àðàà.


22.6%

25.0% 24.7% 25.3% 25.9% 25.2% 25.8%

1.7% 1.2% 0.9% 0.9% 0.8% 0.7% 0.5%

22.8%25.1% 24.8% 25.4% 26.0% 25.3% 25.8%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

2009 2010 2011 2012 2013 2014 2015

“დაუკმაყოფილებელი” დასაქმებულების ხვედრითი წონაეკონომიკურად აქტიურ მოსახლეობაში

ISCO-ს მიხედვით სერტიფიცირებულზე დაბალი კვალიფიკაციით დასაქმების დონე

პროფესიული შეუსაბამობის გამო დამატებითი სამუშაოს ძებნის დონე“დაუკმაყოფილებელი” დასაქმებულების ხვედრითი წონა, სულ


ðíâíðú âààìâàðèøäáäáëà âåèùåäìà, îðíôäñèóêè øäóñàáàëíáèñ âàëí ãàëàòäáèçè ñàëóøàíñ ëûäáìäêçà þåäãðèçè üíìà ñòàòèñòèéóðè úãíëèêäáèñ ôàðâêäáøèà ãà òäìãäìúèàú øäëúèðäáàñ àùåäìäáñ - 2015 üêèñ ëíìàúäëäáèç àñäçè ãàñàõëäáóêäáè äéíìíëèéóðàã àõòèóðè ëíñàþêäíáèñ ñóê ðàöàú 0.5 îðíúäìòñ øäàãâäìãìäì.

ðàú øääþäáà ãàáàêè éåàêèôèéàúèèç ãàñàõëäáóêäáñ, ðíâíðèúàà ãèîêíëèàìè òàõñèñòäáè, ÿèþóðèñ âàë÷èãåäêäáè àì ñàéóçàð ëèüàæä ëíëóøàåä èìïèìðäáè, àñäççà þåäãðèçè üíìà äéíìíëèéóðàã àõòèóðè ëíñàþêäíáèñ 25 îðíúäìòèà ãà òäìãäìúèàú ûàêèàì ñóñòàã âàëíþàòóê, ëàâðàë âàðéåäóê æðãàñ àùåäìäáñ.

ðíâíðú æäëíç ëíúäëóêëà àìàêèæëà àùåäìà „ãàóéëà÷íôèêäáäêè“ ãàñàõëäáóêäáèñ îðíáêäëà, ðíâíðú ôàðóêè ñòðóõòóðóêè óëóøäåðíáèñ âàëíåêèìäáà, ÷åäêàæä ëäòàã âàìàçêäáèñ ñèñòäëèñà ãà øðíëèñ áàæðèñ ãàáàêè éíìâðóäìòóêíáèñ øäãäâèà. æäëíç âàìþèêóêè è÷í ISCO-ñ éêàñèôèéàúèèç îðíôäñèóê ÿâóôäáøè ãàñàõëäáóêçà ãà óëóøäåàðçà âàìàüèêäáà, ðíâíðú ñäðòèôèúèðäáóêè îðíôäñèèñ, èñä ôàõòèóðè ãàñàõëäáèñ îðíôäñèèñ ëèþäãåèç. éåêäåàë àùåäìà, ðíë ñòðóõòóðäáè, äðçè ëþðèå, ñäðòèôèúèðäáóêè îðíôäñèäáèñ ëèþäãåèçà ãà, ëäíðä ëþðèå, ôàõòèóðè ãàñàõëäáèñà, äðçëàìäççàì îðàõòèéóêàã àð éíðäêèðäáäì. àëãäìàã, øäèûêäáà èçõåàñ, ðíë „ãàóéëà÷íôèêäáäêè“ ãàñàõëäáóêäáèñ îðíáêäëèñ äðçäðçè ëìèøåìäêíåàìè ëãâäìäêè ñüíðäã äñ âàðäëíäáàà.

36


6.9%

11.6%

7.1% 7.1%

10.7%

7.4% 7.0%

19.4%20.9% 20.5%

19.5%18.7%

15.8%14.4%15.2% 16.0%

15.9%14.5%

15.1%13.7%

12.9%

15.0%13.8%13.7%

14.6%13.3%

12.3%12.4%

11.7%10.4%

12.0%11.3%

11.0%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

2009 2010 2011 2012 2013 2014 2015

შსო-ს კრიტერიუმით უმუშევრობა განათლების მიღწეული დონის ჯგუფებში




15.1%14.0%


ôàðóêè ñòðóõòóðóêè óëóøäåðíáèñ ùåäìè ëèãâíëèç âààìâàðèøäáóêè ëàùåäìäáêäáèñ øäëçþåäåàøè ÿâóôäáñ øíðèñ âàìñþåàåäáà ûàêèàì àðñäáèçè ãà, øäèûêäáà èçõåàñ, ãðàëàòóêèú éèà.


0.5% 3.4%0.2% 0.1% 0.2% 0.1% 0.0%

0.6%

8.4%

0.2% 0.2% 0.2% 0.1% 0.2%

53.9%

47.5%

58.1% 58.5% 57.2% 56.1% 58.2%

37.0% 38.9% 38.3% 39.6% 41.2% 40.6% 41.8%

22.8%25.1% 24.8% 25.4% 26.0% 25.3% 25.8%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

2009 2010 2011 2012 2013 2014 2015

ფარული სტრუქტურული უმუშევრობა განათლებისმიღწეული დონის ჯგუფებში





ñà÷óðàãöäáíà, ðíë ôàðóêè ñòðóõòóðóêè óëóøäåðíáèñ ãíìä ÷åäêàæä ëàöàêè, ðíâíðú üäñè, îðíôäñèóêè âàìàçêäáèñ ëõíìä ëíñàþêäíáàøèà (èþèêäç ãèàâðàëà N32). äñ ëàùåäìäáäêè àñäåä ëàöàêèà óëàöêäñè âàìàçêäáèñ ëõíìä ëíñàþêäíáàøè, çóëúà èâè ëàèìú àðñäáèçàã ùàëíðùäáà óëóøäåðíáèñ ãíìäñ îðíôäñèóêè âàìàçêäáèñ ëõíìä ëíñàþêäíáàøè.

äñ ñàéëàíã ñà÷óðàãöäáí òäìãäìúèàà ãà þàæñ óñåàëñ èë âàðäëíäáàñ, ðíë îðíôäñèóêè âàìàçêäáà éåàêèôèéàúèèñ øäñàáàëèñè ãàñàõëäáèñ ûàêèàì ãàáàê øàìññ èûêäåà.

37

ñðóêèàã áóìäáðèåèà èñ âàðäëíäáà, ðíë ôàðóêè ñòðóõòóðóêè óëóøäåðíáèñ ãíìä ôàõòíáðèåàã ìóêíåàìèà ñàøóàêí ãà ñàøóàêíæä ãàáàêè âàìàçêäáèñ ëõíìä ëíñàþêäíáàøè: äñ ñüíðäã îðíôäñèèñ àðëõíìäçà èñ ÿâóôèà, ðíëäêçà àáñíðáúèàú ûèðèçàãàã ñàñíôêí çåèçãàñàõëäáàøè þãäáà.

àñäåä ñà÷óðàãöäáíà óëóøäåðíáèñ àâðäâèðäáóêè ãíìä âàìàçêäáèñ ñþåàãàñþåà ãíìèñ ÿâóôäáøè. çó âàìåèþèêàåç óëóøäåðíáèñ àâðäâèðäáóê ãíìäñ ôàðóêè ñòðóõòóðóêè óëóøäåðíáèñ âàðäøä, ãàåèìàþàåç, ðíë äñ ëàùåäìäáäêè ÷åäêà ÿâóôøè øäëúèðäáèñ òäìãäìúèèç þàñèàçãäáà. ûàêèàì ëìèøåìäêíåàìèà èñèú, ðíë èâè çèçõëèñ ÷åäêà ÿâóôèñàçåèñ ãààþêíäáèç äðç, ñàéëàíã åèüðí ãèàîàæíìøèà ëíõúäóêè, ðíëäêèú âàìñàéóçðäáèç 2014-2015 üêäáøè øäåèüðíåãà.

ñðóêèàã âàìúàêéäåäáóê øäëçþåäåàñ üàðëíàãâäìñ ñàøóàêíæä ãàáàêè âàìàçêäáèñ ëõíìä ëíñàþêäíáèñ ÿâóôè, ðíëäêøèú óëóøäåðíáèñ àâðäâèðäáóêè ãíìèñ ëàùåäìäáäêè ÷åäêàæä ãàáàêèà. øäëúèðäáèñ òäìãäìúèà àë ÿâóôøèú èéåäçäáà, çóëúà äñ ÷åäêàæä ãàáàêè éåàêèôèéàúèèç ãàñàõëäáèñ þàðÿæäà.


16.8%

26.2%

15.4%17.5%

19.5%17.8%

15.0%

29.2% 30.6% 31.2% 30.9%28.9%

26.2%24.8%

38.4%

34.1%

31.9%

38.0%

34.3%

32.6%

37.0%

32.5%

32.0%

36.1%34.5%

32.3%

34.7%

31.9%

30.7%

30.3%28.5%

27.4%

28.0%27.9%25.9%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

45.0%

2009 2010 2011 2012 2013 2014 2015

უმუშევრობის აგრეგირებული მაჩვენებელი ფარული სტრუქტურული უმუშევრობის გარეშე განათლების მიღწეული დონის ჯგუფებში





âàìñþåàåäáà àðñäáèçè þãäáà, çó âàìåèþèêàåç óëóøäåðíáèñ àâðäâèðäáóê ãíìäñ ãàéåèðåäáàãè ñòðóõòóðóêè óëóøäåðíáèñ ùàëçåêèç. àñäç øäëçþåäåàøè, îðíôäñèóêè âàìàçêäáèñ ëõíìä ëíñàþêäíáàøè óëóøäåðíáèñ ëàùåäìäáäêè óéåä ûàêèàì ëàöàê ìèøìóêñ àöüäåñ. ëàñæäã àðñäáèçàã ãàáàêè, ëàâðàë æíâàãàã ëàèìú ëàöàêèà óëóøäåðíáèñ àâðäâèðäáóêè ãíìèñ ëàùåäìäáäêè óëàöêäñè âàìàçêäáèñ ëõíìä ëíñàþêäíáàøè.

38


17.0%

28.5%

15.4% 17.5% 19.6% 17.8% 15.0%

29.4%

37.2%31.4% 30.9% 28.9% 26.3% 24.9%

76.3%72.0%

77.7% 79.4%76.5% 73.8% 75.2%

65.6% 68.0% 66.9% 66.3% 66.9%62.9% 62.9%

49.1%52.2% 51.3% 51.7% 51.0%

47.7% 47.2%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

2009 2010 2011 2012 2013 2014 2015

უმუშევრობის აგრეგირებული მაჩვენებელი ფარული სტრუქტურული უმუშევრობის ჩათვლით განათლების მიღწეული დონის ჯგუფებში





ñàøóàêí ãà ñàøóàêíæä ãàáàêè âàìàçêäáèñ ëõíìä ëíñàþêäíáèñ óëóøäåðíáèñ àâðäâèðäáóêè ãíìèñ ëàùåäìäáäêèñ ñàøóàêíñçàì øäãàðäáèç âàúèêäáèç ãàáàêè ãíìä âàìîèðíáäáóêèà àë ÿâóôèñàçåèñ ìàéêäáàã ãàëàþàñèàçäáäêè ñòðóõòóðóêè óëóøäåðíáèç.

÷åäêàæä ëìèøåìäêíåàìè èñàà, ðíë ãàéåèðåäáàãè ñòðóõòóðóêè óëóøäåðíáèñ ùàçåêèç óëóøäåðíáèñ àâðäâèðäáóêè ãíìèñ ëàùåäìäáäêè 2009-2015 üêäáøè óúåêäêíáèñ òäìãäìúèèç âàëíèðùäåà.

4.4 øðíëèñ áàæðèñ ëíçþíåìèñà ãà ëèüíãäáèñ ñòðóõòóðóêè çàåñäáàãíáà4.4 øðíëèñ áàæðèñ ëíçþíåìèñà ãà ëèüíãäáèñ ñòðóõòóðóêè çàåñäáàãíáà

øðíëèñ áàæàðæä ëèüíãäáèñ øäñüàåêà øäãàðäáèç óôðí ðçóêèà, åèìàèãàì àëèñàçåèñ ëèëãèìàðä àöðèúþåèñ ñàýèðíäáà óôðí ãèãèà, åèãðä ëíçþíåìèñ ñòðóõòóðèñ øäñüàåêèñàçåèñ. øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëçà áàæèñ âàëí÷äìäáà àë çåàêñàæðèñèçàúàà øäñàûêäáäêè, çóëúà ëþíêíã äñ èìôíðëàúèóêè ëàñèåè ñàéëàðèñè àð àðèñ.

øðíëèñ áàæàðæä ëíçþíåìèñà ãà ëèüíãäáèñ çåàêñàæðèñèç ëìèøåìäêíåàìèà ãàñàõëäáóêäáèñ ôàõòèóðè éåàêèôèéàúèèñà ãà ñäðòèôèúèðäáóêè îðíôäñèäáèñ ëèþäãåèç âàìàüèêäáèñ øäãàðäáà. ôàõòèóðè îðíôäñèäáèñ ëèþäãåèç âàìàüèêäáà üàðëíãâäìàñ âåèõëìèñ áàæàðæä ñàëóøàí ûàêèñ ëíçþíåìèñ ñòðóõòóðàæä. ñäðòèôèúèðäáóêè îðíôäñèèñ ëèþäãåèç âàìàüèêäáà éè àöüäðñ ðíâíðú ñàëóøàí àãâèêäáèñ ëíçþíåìèñ, èñä øðíëèñ áàæàðæä ñàëóøàí ûàêèñ ëèüíãäáèñ ñòðóõòóðàñ.

ñäðòèôèúèðäáóêè îðíôäñèäáèñ ëèþäãåèç âàìàüèêäáà, àìó ñàëóøàí ûàêèñ ëèüíãäáèñ éíëîíìäìòè, âàìþèêóêèà øðíëèñ áàæðèñ ñäõòíðóêè àìàêèæèñ ìàüèêøè. àõ éè âàìåèþèêíç, çó ðàëãäìàã àãäõåàòóðèà ëèüíãäáèñ ñòðóõòóðà ëíçþíåìèñ ñòðóõòóðàñçàì ëèëàðçäáàøè.

âàìþèêåèñçåèñ øäãàðãà âàìàüèêäáà ISCO-ñ íðìèøìà éíãäáèñ ëèþäãåèç. ðíâíðú øäãàðäáà àùåäìäáñ, ãàñàõëäáóêçà âàìàüèêäáà ñäðòèôèúèðäáóêè ãà ôàõòèóðè îðíôäñèäáèñ ëèþäãåèç îðàõòèéóêàã äðçëàìäççàì àð éíðäêèðäáñ: éíðäêàúèèñ éíäôèúèäìòè -0.0792 øäàãâäìñ.

ãàñàõëäáóêçà âàìàüèêäáèñ ñàñíôêí çåèçãàñàõëäáóêäáèñ âàðäøä âàìþèêåèñàñ, éíðäêàúèèñ éíäôèúèäìòè àðñäáèçàã èæðãäáà, ëàâðàë ëèñè àáñíêóòóðè ëìèøåìäêíáà ëàèìú ãàáàêèà ãà ëþíêíã 0.2085 ìèøìóêæäà. äñ èëàñ ìèøìàåñ, ðíë äñ íðè ñòðóõòóðà äðçëàìäçèñâàì ñàéëàíã âàìñþåàåäáóêèà èë øäëçþåäåàøèú éè, çó ëàñ âàìåèþèêàåç ñàñíôêí çåèçãàñàõëäáèñ âàðäøä.

ñàñíôêí çåèçãàñàõëäáèñ ùàçåêèç ãàñàõëäáóêçà ñäðòèôèúèðäáóêè ãà ôàõòèóðè îðíôäñèäáèñ ëèþäãåèç âàìàüèêäáèñ éíðäêàúèà ãààþêíäáèç ëñâàåñèà ëçêèàìàã ñàéåêäåè îäðèíãèñ ëàìûèêæä; ñàñíôêí çåèçãàñàõëäáèñ âàðäøä âàìþèêåèñ øäëçþåäåàøè éè ñòðóõòóðäáèñ éíðäêàúèà âàðéåäóêè øäëúèðäáèñ òäìãäìúèèç þàñèàçãäáà. øäëúèðäáèñ òäëîè àð àðèñ ëàöàêè,

39

ëàâðàë çåèç òðäìãè ñàéëàíã ùàëí÷àêèáäáóêè þàñèàçèñàà ãà âàìàçêäáèñ ñèñòäëèñ øðíëèñ áàæðèñ ëèëàðç éêäáàã éíìâðóäìòóêíáàæä ëäò÷åäêäáñ.


-0.0764 -0.0812 -0.0833 -0.0831 -0.0791 -0.0760 -0.0792

0.2734

0.2319

0.2016 0.2118 0.21760.2471

0.2085

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

2009 2010 2011 2012 2013 2014 2015

დიპლომით პროფესიის მიხედვით სტრუქტურის კორელაცია ფაქტიურიპროფესიის მიხედვით სტრუქტურასთან ISCO-ს ორნიშნა კოდების დონეზე



ñäðòèôèúèðäáóêè ãà ôàõòèóðè îðíôäñèäáèñ ëèþäãåèç ãàñàõëäáóêçà âàìàüèêäáäáèñ øäãàðäáèñàñ éíðäêàúèèñ ëìèøåìäêíåàìè øäëàëúèðäáäêè ôàõòíðèà îðíôäñèèñ àðëõíìäçà ñàéëàíã ëðàåàêðèúþíåàìè ÿâóôè. äñ èñ îèðäáèà, ðíëêäáñàú àðàìàèðè ñäðòèôèúèðäáóêè îðíôäñèà àð âààùìèàç, ëàâðàë ôàõòíáðèåàã ðàöàú, çóìãàú ûàêèàì ãàáàêè éåàêèôèéàúèèñ ñàëóøàíæä, ëàèìú àðèàì ãàñàõëäáóêìè.

çó ñòðóõòóðèãàì âàëíåðèúþàåç îðíôäñèèñ àðëõíìäçà ÿâóôñ ãà ôàõòèóðè ãà ñäðòèôèúèðäáóêè îðíôäñèäáèñ ëèþäãåèç âàìàüèêäáäáñ ëàç âàðäøä øäåàãàðäáç, ñíôêèñ ëäóðìäíáàøè çåèçãàñàõëäáèñ ùàçåêèç ñòðóõòóðäáèñ éíðäêàúèà ëàèìú ìóêíåàìèà. èñ âàðäëíäáà, ðíë -0.0972-èñ ìàúåêàã éíðäêàúèèñ éíäôèúèäìòè -0.0228-ñ òíêèà, àðàìàèðàã àð ìèøìàåñ àðñäáèç âàìñþåàåäáàñ ãà éíðäêàúèà, ðíâíðú üèìà øäëçþåäåàøè, ôàõòíáðèåàã àõàú ìóêíåàìèà.

çó ñòðóõòóðèãàì âàëíåðèúþàåç ñíôêèñ ëäóðìäíáàøè çåèçãàñàõëäáàñ, éíðäêàúèèñ éíäôèúèäìòè çèçõëèñ 14-ÿäð - 0,0288-ãàì 0.4061-ëãä èæðãäáà. óéàìàñéìäêè çàåèñçàåàã àð àðèñ ëàöàêè ëàùåäìäáäêè, ëàâðàë àøéàðàà èñ âàðäëíäáà, ðíë ñàñíôêí çåèçãàñàõëäáèñà ãà îðíôäñèèñ àðëõíìäçà âàëíéêäáèç, ãàñàõëäáèñ ñäðòèôèúèðäáóêè ãà ôàõòèóðè îðíôäñèäáèñ ñòðóõòóðà áäåðàã ëäò éíðäêàúèàøèà äðçëàìäççàì.

40


-0.0394 -0.0470 -0.0488 -0.0466 -0.0339 -0.0246 -0.0228

0.4708

0.37440.3452

0.3852 0.3866

0.44520.4061

-0.1

0

0.1

0.2

0.3

0.4

0.5

2009 2010 2011 2012 2013 2014 2015

დიპლომით პროფესიის მიხედვით სტრუქტურის კორელაცია ფაქტიური პროფესიის მიხედვით სტრუქტურასთან ISCO-ს ორნიშნა კოდების დონეზე

პროფესიის არმქონეთა გაუთვალისწინებლად



ãàñàõëäáóêçà ãà óëóøäåàðçà îðíôäñèóêè ñòðóõòóðäáèñ éíðäêàúèóðè àìàêèæè àùåäìäáñ, ðíë ñàõàðçåäêíøè âàìàçêäáèñ ñèñòäëèñà ãà øðíëèñ áàæðèñ øäñàáàëèñíáèñ þàðèñþè ûàêèàì ãàáàêèà: ãàñàõëäáóêçà ôàõòèóðè ãà ñäðòèôèúèðäáóêè îðíôäñèäáèñ ëèþäãåèç âàìàüèêäáà äðçëàìäççàì çèçõëèñ ìóêíåàìè éíðäêàúèèç þàñèàçãäáà.

éíðäêàúèèñ þàðèñþè ðàëãäìàãëä èæðãäáà, çó ñòðóõòóðèãàì âàëíåðèúþàåç èñäç ëñþåèê ëãâäìäêñ, ðíâíðèúàà îðíôäñèèñ àðëõíìäçà ÿâóôè. ëèóþäãàåàã àëèñà, ñòðóõòóðàçà éíðäêàúèà 0.5-æä ìàéêäáèà àìó ãàáàêèà. äñ èëàñ ìèøìàåñ, ðíë ñäðòèôèúèðäáóêè îðíôäñèà ìàéêäáàã âàìàîèðíáäáñ ãàñàõëäáèñ ôàõòèóð àãâèêñ àìó âàìàçêäáèñ ñèñòäëèñ ëèäð ñîäúèàêèñòäáèñ âàëíøåäáà àð àéëà÷íôèêäáñ øðíëèñ áàæðèñ ëíçþíåìèêäáäáñ.

ñäðòèôèúèðäáóêè îðíôäñèäáèñ ëèþäãåèç ãàñàõëäáóêçà ãà óëóøäåàðçà éíðäêàúèà çèçõëèñ 1-èñ òíêèà, ðàú èëàñ ìèøìàåñ, ðíë ñäðòèôèúèðäáóêè îðíôäñèèñ æäâàåêäìà ãàñàõëäáàæä ûàêèàì ãàáàêèà. äñ àñäåä ìèøìàåñ èëàñàú, ðíë âàìàçêäáèñ ñèñòäëèãàì ëèöäáóêè âàìàçêäáèñ ãàëàãàñòóðäáäêè ñäðòèôèéàòèñ üíìà ñàëóøàí àãâèêèñ ëíûäáìàøè àð çàëàøíáñ ëìèøåìäêíåàì ðíêñ.

âàðãà àëèñà, âàìàçêäáèñ ñèñòäëà óæðóìåäê÷íôñ îðíôäñèèñ àðëõíìäçà ëçäêè „àðëèèñ“ âäìäðèðäáàñ, ðíëäêçà éíìéóðäìòóìàðèàìíáà øðíëèñ áàæàðæä ûàêèàì ãàáàêèà ãà ëàçè óãèãäñè óëðàåêäñíáà ñàñíôêí çåèçãàñàõëäáàøè àì ûàêèàì ãàáàêè éåàêèôèéàúèèñ ñàëóøàíäáæä çó ãàñàõëãäáà.

àëãäìàã, ðíâíðú æäëíçàú àöèìèøìà, äðçäðçè ëçàåàðè îðíáêäëà îðíôäñèèñ àðëõíìäçàçåèñ âàðéåäóêè îðíôäñèóêè âàìàçêäáèñ îðíâðàëèñ øäëóøàåäáà ãà àëíõëäãäáàà. äñ, úþàãèà, àð ìèøìàåñ îðíáêäëèñ àåòíëàòóðàã ëíâåàðäáàñ.

âàìñàéóçðäáèç ëìèøåìäêíåàìè àðàà, ëàâðàë ñàèêóñòðàúèíã ñàèìòäðäñíà ãàñàõëäáóêäáèñ ôàõòèóðè îðíôäñèèñ ãà óëóøäåàðçà ñäðòèôèúèðäáóêè îðíôäñèäáèñ ëèþäãåèç ñòðóõòóðäáèñ éíðäêàúèà. àõàú, ðíâíðú ãàñàõëäáóêçà ôàõòèóðè ãà ñäðòèôèúèðäáóêè îðíôäñèäáèñ ëèþäãåèç âàìàüèêäáèñ øäëçþåäåàøè, éíðäêàúèà ìóêíåàìèà, þíêí ñàñíôêí çåèçãàñàõëäáèñ âàðäøä éíðäêàúèèñ éíäôèúèäìòè ðàëãäìàãëä èæðãäáà, ëàâðàë éíðäêàúèà, øäèûêäáà èçõåàñ, ëàèìú ìóêíåàìèà. çàìàú, àë çèçõëèñ ìóêíåàì éíðäêàúèàñàú éè øäëúèðäáèñ òäìãäìúèà àõåñ.

41


-0.0653-0.0743 -0.0768 -0.0752 -0.0733 -0.0726 -0.0707

0.1089

0.0823

0.06240.0740 0.0694

0.0579 0.0569

-0.1

-0.05

0

0.05

0.1

0.15

2009 2010 2011 2012 2013 2014 2015

დასაქმებულების ფაქტიური პროფესიის მიხედვით სტრუქტურის კორელაციაუმუშევრების დიპლომით პროფესიის მიხედვით სტრუქტურასთან ISCO-ს

ორნიშნა კოდების დონეზე



éíðäêàúèà àðñäáèçàã èæðãäáà ñòðóõòóðèãàì îðíôäñèèñ àðëõíìäçà âàëíðèúþåèñ øäëçþåäåàøè, çóëúà èñ ñàéëàíã øíðñàà èñäçè ãíìèñàâàì, ðàñàú ëàöàêè éíðäêàúèà øäèûêäáà äüíãíñ.


-0.0238 -0.0378 -0.0398 -0.0345 -0.0284 -0.0246 -0.0130

0.4230

0.34430.3069

0.36610.3480 0.3484

0.3680

-0.1

0

0.1

0.2

0.3

0.4

0.5

2009 2010 2011 2012 2013 2014 2015

დასაქმებულების ფაქტიური პროფესიის მიხედვით სტრუქტურის კორელაცია უმუშევრების დიპლომით პროფესიის მიხედვით სტრუქტურასთან ISCO-ს ორნიშნა

კოდების დონეზე პროფესიის არმქონეთა გაუთვალისწინებლად



âàìàçêäáèñ ñèñòäëèñà ãà øðíëèñ áàæðèñ ñòðóõòóðóêè øäñàáàëèñíáèñ þàðèñþè äðçíá ãàáàêèà ãà àëàñ àùåäìäáñ èñ âàðäëíäáà, ðíë ãàñàõëäáóêçà ôàõòèóðè ãà ñäðòèôèúèðäáóêè îðíôäñèäáèñ ëèþäãåèç ñòðóõòóðäáèñ äðçëàìäççàì ãàëíéèãäáóêäáà çèçõëèñ ìóêíåàìè éíðäêàúèèç þàñèàçãäáà. éíðäêàúèèñ þàðèñþè ðàëãäìàãä èæðãäáà, çó ñòðóõòóðèãàì âàëíåðèúþàåç èñäç ëñþåèê ëãâäìäêñ, ðíâíðèúàà îðíôäñèèñ àðëõíìäçà ÿâóôè, ëàâðàë ëèóþäãàåàã

42

àëèñà, ñòðóõòóðàçà éíðäêàúèà 0.5-æä ìàéêäáèà, àìó äñ íðè ñòðóõòóðà äðçëàìäççàì ãàáàê éíðäêàúèàøèà. äñ ìèøìàåñ, ðíë ñäðòèôèúèðäáóêè îðíôäñèà ìàéêäáàã âàìàîèðíáäáñ ãàñàõëäáèñ ôàõòèóð àãâèêñ. àìó âàìàçêäáèñ ñèñòäëèñ âàëíøåäáà øðíëèñ áàæàðæä àðñäáóê ëíçþíåìàñ ìàéêäáàã äëçþåäåà.


62% 62% 62% 63%60%

67% 67%

43%40% 41% 41% 41% 42% 42%

45%42% 43% 44% 43% 44% 44%

0%

10%

20%

30%

40%

50%

60%

70%

80%

2009 2010 2011 2012 2013 2014 2015

პროფესიის არმქონეთა ხვედრითი წონა ეკონომიკურად აქტიურ მოსახლეობაში ასაკის მიხედვით

25 წლამდე 25 წლის და უფროსი ასაკის სულ


ãàñàõëäáóêçà øíðèñ îðíôäñèèñ àðëõíìäçà ëàöàêè þåäãðèçè üíìèñ àþñìà øäñàûêäáäêèà àñàéíáðèåè ôàõòíðèç (èþèêäç ãèàâðàëà N39). îíòäìúèóð ñàëóøàí ûàêàøè øäãèñ 15 üêèñà ãà óôðíñè àñàéèñ ëíñàþêäíáà, ðíëäêèú ëíèúàåñ ëíñüàåêääáñ ãà ñòóãäìòäáñ àìó âàìàçêäáèñ àãðäóê ñàôäþóðæä ë÷íô ëíñàþêäíáàñ, ðíëäêñàú ÿäð àð ëèóöèà ðíëäêèëä îðíôäñèèñ ãàëàãàñòóðäáäêè ñäðòèôèéàòè. îðíôäñèèñ àðëõíìäçà þåäãðèçè üíìà 25 üêàëãä àñàéèñ äéíìíëèéóðàã àõòèóð ëíñàþêäíáàøè 67 îðíúäìòèà. äñ ëàùåäìäáäêè ñàéåêäå îäðèíãøè æðãèñ ìàéêäáàã îíæèòèóð òäìãäìúèàñ àåêäìãà.

àñäåä, ûàêèàì ëàöàêèà ñäðòèôèúèðäáóêè îðíôäñèèñ àðëõíìäçà þåäãðèçè üíìà 25 üäêæä óôðíñè àñàéèñ äéíìíëèéóðàã àõòèóð ëíñàþêäíáàøèú. 2015 üêèñ ëíìàúäëäáèç èâè 42 îðíúäìòè è÷í ãà ñàéåêäåè îäðèíãèñ ëàìûèêæä îðàõòèéóêàã óúåêäêè ãàðùà, çóëúà âàðéåäóêè æðãèñ àêáàçíáèç, åèìàèãàì îðíôäñèèñ àðëõíìäçà þåäãðèçè üíìà 25 üêàëãä àñàéèñ äéíìíëèéóðàã àõòèóð ëíñàþêäíáàøè áíêí îäðèíãøè æðãèñ òäìãäìúèàñ àòàðäáñ.

îðíôäñèèñ àðëõíìä 25 üäêæä óôðíñè àñàéèñ ëíñàþêäíáèñ ãèãè ìàüèêè, ëàöàêè àêáàçíáèç, ñîäúèàêóðè øäçàåàæäáèñ âàðäøä ãàëíóéèãäáêàã îðíôäñèèñ øäñàûäìàã ñüàåêàñ àð ãàèü÷äáñ, àìó øðíëèñ áàæàðè éåêàå âàÿäðäáóêè èõìäáà ãàáàêè éåàêèôèéàúèèñ ëóøà þäêèç, ðàú øðíëèçè óðçèäðçíáäáèñ ãà ñàæíâàãíã øðíëèñ áàæðèñ ãäâðàãàúèèñ üèìàîèðíáà øäèûêäáà âàþãäñ.

øðíëèñ áàæàðæä ëèüíãäáèñ ñòðóõòóðèñ øäñüàåêèñàçåèñ àåèðùèäç íðè ü÷àðí - ñàèòè Jobs.ge, ãà âàæäçè „ñèò÷åà ãà ñàõëä“. ðàñàéåèðåäêèà, äñ ü÷àðíäáè ñðóê÷íôèêàã åäð ôàðàåñ øðíëèñ áàæàðæä àðñäáóêè åàéàìñèäáñ, ëàâðàë âàðéåäóê üàðëíãâäìàñ õëìèñ ñàëóøàí àãâèêäáèñ ëèüíãäáèñ îðíôäñèóê ñòðóõòóðàæä. ãðíèçè ëüéðèåèñ âäìäðèðäáèñ ëèæìèç øäåäúàãäç íðèåä ü÷àðíãàì 2009-2015 üêèñ èãäìòóðè îäðèíãèñ ëàñàêèñ ëíîíåäáàñ. çóëúà èë ñèðçóêääáèñ âàëí, ðíëêäáæäú æäëíç óéåä åèñàóáðäç (î.1.4 – „éåêäåèñ ëäçíãíêíâèà“) íðèåä ü÷àðíãàì éíëáèìèðäáóêè èñòíðèóêè ëíìàúäëäáèñ ñàôóûåäêæä ðàíãäìíáðèåè øäôàñäáäáèñ âàéäçäáà åäöàð ëíþäðþãà. àëèñ âàëí õåäëíç âàìþèêóêèà ëþíêíã ñòðóõòóðäáèñ àìàêèæè ãà àðà ðàíãäìíáðèåè øäôàñäáäáè.

äðçñà ãà èëàåä îäðèíãøè àöìèøìóêè íðè ü÷àðíñ ëäøåäíáèç âàìçàåñäáóêè åàéàìñèäáèñ ñòðóõòóðà îðíôäñèäáèñ ëèþäãåèç àðñäáèçàã âàìñþåàåäáóêèà. Jobs.ge-æä âàìçàåñäáóê åàéàìñèäáøè ñýàðáíáñ ëíçþíåìà þäêëûöåàìäêè ðâíêèñ ëóøàéäáæä ãà ñîäúèàêèñòäáæä éåàêèôèéàúèèñ óëàöêäñè ãíìèç, ëàøèì ðíãäñàú àë ÿâóôèñ îðíôäñèäáèñ ëíçþíåìà âàæäç „ñèò÷åà ãà ñàõëèñ“

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ëäøåäíáèç óëìèøåìäêíà. ñàëàâèäðíã, âàæäçè „ñèò÷åà ãà ñàõëèñ“ ñàøóàêäáèç âàìçàåñäáóê åàéàìñèäáøè ûàêèàì ëàöàêèà ëíëñàþóðäáèñ ñôäðíñà ãà ñàåàýðí íðâàìèæàúèäáèñ ëóøàéäáèñ üèêè. àëàåä ÿâóôèñ ñîäúèàêèñòäáæä ëíçþíåìà Jobs.ge æäú ñàéëàíã ëàöàêèà, ëàâðàë ëàçè üèêè ñòðóõòóðàøè àðñäáèçàã ùàëíðùäáà „ñèò÷åà ãà ñàõëä“-øè àë ÿâóôèñ ñîäúèàêèñòäáæä ëíçþíåìèñ üèêñ. ñà÷óðàãöäáíà èñèú, ðíë âàæäçøè àðñäáèçàãàà üàðëíãâäìèêè ñàëðäüåäêíñ ñàüàðëíäáèñ éåàêèôèúèóðè ëóøäáèñà ãà àðàéåàêèôèúèóðè ëóøäáèñ ÿâóôäáæä ëíçþíåìàú. ëàøèì, ðíãäñàú Jobs.ge-æä àñäçè îðíôäñèäáèñ ëíçþíåìèñ üèêè óëìèøåìäêíà.

àëãäìàã øäèûêäáà èçõåàñ, ðíë äñ íðè ü÷àðí àáñíêóòóðàã âàìñþåàåäáóê ñäâëäìòäáæä ëóøàíáñ.

úþðèêè N2: âàæäç "ñèò÷åà ãà ñàõëä"-øè ãà ñàèò Jobs.ge-æä 2016 üêèñ ëàèñèñ ëäíðä ìàþäåàðøè úþðèêè N2: âàæäç "ñèò÷åà ãà ñàõëä"-øè ãà ñàèò Jobs.ge-æä 2016 üêèñ ëàèñèñ ëäíðä ìàþäåàðøè âàìçàåñäáóêè åàéàìñèäáèñ ñòðóõòóðà ISCO-ñ ûèðèçàã ÿâóôäáøè (îðíúäìòè)âàìçàåñäáóêè åàéàìñèäáèñ ñòðóõòóðà ISCO-ñ ûèðèçàã ÿâóôäáøè (îðíúäìòè)

"ñèò÷åà ãà ñàõëä" Jobs.ge ñóê

÷åäêà ãíìèñ þäêëûöåàìäêäáè 1 21 16

ñîäúèàêèñòäáè éåàêèôèúèèñ óëàöêäñè ãíìèç 2 25 20

ñîäúèàêèñòäáè éåàêèôèéàúèèñ ñàøóàêí ãíìèç 3 13 11

éàìòíðèñ ëóøàéäáè 8 16 14

ëíëñàþóðäáèñ ñôäðíñà ãà ñàåàýðí íðâàìèæàúèäáèñ ëóøàéäáè 45 18 24

éåàêèôèúèóðè ëóøàéäáè ñíôêè ëäóðìäíáäáèñ ãàðâøè 1 0 0

ñàëðäüåäêí ñàüàðëíäáèñ éåàêèôèúèóðè ëóøäáè 16 3 6

ãàìàãâàðäáèñà ãà ëàìõàìäáèñ íîäðàòíðäáè 2 1 2

àðàéåàêèôèúèóðè ëóøäáè 21 4 8

ñóê 100 100 100

ëàðçàêèà, àöìèøìóêè íðèñ ü÷àðí âàìñþåàåäáóê ñäâëäìòäáæä ëóøàíáñ, ëàâðàë èñèìè äðçëàìäçèñ àåñäáäì, ðàñàú éíðäêàúèóðè àìàêèæèñ øäãäâäáèú àãàñòóðäáäì.

ñàñíôêí çåèçãàñàõëäáèñ ùàçåêèç ëçêèàìàã ãàñàõëäáèñ ñòðóõòóðàñà ãà åàéàìñèäáèñ ñòðóõòóðàñ øíðèñ éíðäêàúèà óàð÷íôèçèà, ðàú èëèç àèþñìäáà, ðíë ñàñíôêí çåèçãàñàõëäáèñ ëàñøòàáè çàåèñçàåàã ûàêæä ãèãèà ãà àëíðôóêè. ñíôêèñ ëäóðìäíáàøè ãàñàõëäáàæä ëíçþíåìà åàéàìñèäáøè ñàäðçíã àðàà, ãàñàõëäáèñ ñòðóõòóðàøè éè àë ñäõòíðñ ÷åäêàæä ãèãè üèêè àõåñ.

ëìèøåìäêíåàìèà èñ, ðíë úàêéä „ñèò÷åà ãà ñàõëèñ“ ãà úàêéä Jobs.ge-ñ ñàøóàêäáèç âàëíúþàãäáóêè åàéàìñèäáèñ ñòðóõòóðäáèñ ãàñàõëäáèñ ôàõòèóð ñòðóõòóðàñçàì éíðäêàúèèñ éíäôèúèäìòè àðñäáèçàã ãàáàêèà, åèãðä íðèåä ü÷àðíñ áàæàæä âàëíúþàãäáóêè åàéàìñèäáèñ âàäðçèàìäáóêè ñòðóõòóðèñ éíðäêàúèà ãàñàõëäáèñ ôàõòèóð ñòðóõòóðàñçàì. äñ éè ìèøìàåñ, ðíë àöìèøìóêè íðè ü÷àðí äðçëàìäçñ àåñäáñ.

44


0.389

0.562

0.661

0

0.1

0.2

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“სიტყვა და საქმე” Jobs.ge სულ

მოთხოვნის სტრუქტურის კორელაცია ფაქტიური დასაქმების სტრუქტურასთან სასოფლო თვითდასაქმების გარეშე

ñà÷óðàãöäáíà àâðäçåä ëíçþíåìèñ ñòðóõòóðèñ éíðäêàúèà ñàñíôêí çåèçãàñàõëäáèñ âàðäøä âàìþèêóê ãàñàõëäáèñ ñòðóõòóðàñçàì.


-0.193

-0.355

-0.395

-0.45

-0.4

-0.35

-0.3

-0.25

-0.2

-0.15

-0.1

-0.05

0

“სიტყვა და საქმე” Jobs.ge სულ

მოთხოვნის სტრუქტურის კორელაცია ფაქტიური დასაქმების სტრუქტურასთან სასოფლო თვითდასაქმების ჩათვლით

îèðåäê ðèâøè àöñàìèøìàåèà éíðäêàúèèñ åäõòíðèñ ñàîèðèñîèðí ìèøìèç úåêèêäáà - çó ñàñíôêí çåèçãàñàõëäáèñ ùàçåêèç ëíçþíåìèñà ãà ôàõòèóðè ãàñàõëäáèñ éíðäêàúèà óàð÷íôèçè è÷í, ñàñíôêí çåèçãàñàõëäáèñ âàðäøä éíðäêàúèà ãàãäáèçèà.

âàæäç „ñèò÷åà ãà ñàõëèñ“ åàéàìñèäáèñ ñòðóõòóðà øäãàðäáèç ìàéêäáàã éíðäêèðäáñ ñàñíôêí çåèçãàñàõëäáèñ âàðäøä ãàñàõëäáèñ ôàõòèóð ñòðóõòóðàñçàì - éíðäêàúèèñ éíäôèúèäìòè 0.389 ìèøìóêæäà, ëàâðàë àõ ñà÷óðàãöäáí éíðäêàúèèñ åäõòíðèà - éíðäêàúèà ãàãäáèçèà. Jobs.ge-ñ ñòðóõòóðà øäãàðäáèç ëàöàê éíðäêàúèàøèà - éíðäêàúèèñ éíäôèúèäìòè àõ 0.562 ìèøìóêæäà.

45

ñà÷óðàãöäáíà, ðíë éíðäêàúèèñ éíäôèúèäìòè âàæäç „ñèò÷åà ãà ñàõëèñ“ ãà Jobs.ge-ñ ëíìàúäëäáèñ âàäðçèàìäáèñ øäëãäâ àðñäáèçàã èæðãäáà ãà 0.661 ìèøìóêàëãä àãèñ.

÷íåäêèåä äñ àãàñòóðäáñ ñòðóõòóðóêè óëóøäåðíáèñ îðíáêäëèñ ëíâåàðäáèñ ãà ñàäðçíã ãàñàõëäáèñ âàëàðçóêè îíêèòèéèñ üàðëíäáèñàçåèñ åàéàìñèäáèñ äðçèàìè èìôíðëàúèóêè ëàñèåèñ øäõëìèñ àóúèêäáêíáàñ éóëóêàòèóðè ëíìàúäëçà áàæèñ ôíðëèðäáèñ âæèç.

ðíâíðú æäëíç àöåìèøìäç, ãðíèçè ëüéðèåèñ âäìäðèðäáà ëíþäðþãà ëþíêíã âàæäç „ñèò÷åà ãà ñàõëèñ“ ëíìàúäëäáèñàçåèñ. ðàñàéåèðåäêèà, äñ ëíìàúäëäáè àðàñðóêèà ãà, ðíâíðú æäëíçàú åìàþäç, ëþíêíã âàðéåäóê ñäâëäìòæä ëóøàíáñ. ëèóþäãàåàã àëèñà, ëàèìú ñàèìòäðäñíà àë ü÷àðíñ ëäøåäíáèç âàëíúþàãäáóêè åàéàìñèäáèñ ãèìàëèéà ñàéåêäå îäðèíãøè.

ðíâíðú õåäëíç ëíòàìèêè ëíìàúäëäáèãàì ùàìñ (èþèêäç ãèàâðàëà N42), àøéàðàà óëàöêäñè ãà ñàøóàêí éåàêèôèéàúèèñ ëóøàéäáæä ëíçþíåìèñ üèêèñ éêäáà ãà èëàåãðíóêàã, ëíëñàþóðäáèñ ñôäðíñà ãà ñàåàýðí íðâàìèæàúèäáèñ ëóøàéäáæä ëíçþíåìèñ þåäãðèçè üèêèñ àðñäáèçè æðãà. ñþåàçà øíðèñ, äñ òäìãäìúèà æóñòàã äñàãàâäáà ãàñàõëäáèñ ñòðóõòóðàøè ñàñíôêí çåèçãàñàõëäáèñ þåäãðèçè üíìèñ øäëúèðäáèñà ãà ëíëñàþóðäáèñ ñôäðíøè ãàñàõëäáèñ þåäãðèçè üíìèñ æðãèñ òäìãäìúèàñ. àìó âàðéåäóêè ñèìõðíìóêíáà àøéàðàã ñàþäæäà, ëàâðàë ðàíãäìíáðèåàã äñ òðàìñôíðëàúèà àøéàðàã àðàà èñäçè ëàñøòàáäáèñ, ðíë ëàì çåèñíáðèåè úåêèêäáäáèñ âàëíüåäåà øäûêíñ. àöñàìèøìàåèà èñèú, ðíë äéíìíëèéèñ ðäàêóð ñäõòíðøè ãàñàõëäáèñ øäñàûêäáêíáäáè àìó åàéàìñèäáè, àð øäúåêèêà.


2010

6 4 6 4 1

8

6 119

96

2

8

1711

7

10

8

4

4

26

22

9

916

5

38

23

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4238

33

52

0

00

00

0 0

15 7 8

17 11

15 13

21 2 4

54

3

6 9 10 10 12 1620

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2010 2011 2012 2013 2014 2015 2016

გაზეთ ,,სიტყვა და საქმე”-ში 2010 - 2016 წლების მაისისა და დეკემბრის თვეებში გამოქვეყნებული ვაკანსიებისსტრუქტურა ISCO-ს ს პროფესიების ძირითად ჯგუფებში

ყველა დონის ხელმძღვანელები სპეციალისტები კვალიფიციის უმაღლესი დონით

სპეციალისტები კვალიფიკაციის საშუალო დონით კანტორის მუშაკები

მომსახურების სფეროსა და სავაჭრო ორგანიზაციების მუშაკები კვალიფიციური მუშაკები სოფლი მეურნეობების დარგში

სამრეწველო საწარმოების კვალიფიციური მუშები დანადგარებისა და მანქანების ოპერატორებიარაკვალიფიციური მუშები

âàæäç "ñèò÷åà ãà ñàõëäøè" âàìçàåñäáóêèà àðà ëþíêíã åàéàìñèäáèñ, àðàëäã ñàëóøàíñ øäçàåàæäáèñ âàìúþàãäáäáèú. àëãäìàã, äñ ü÷àðí èûêäåà äðçãðíóêàã ëíçþíåìèñà ãà ëèüíãäáèñ éíðäêàúèóðè àìàêèæèñ øäñàûêäáêíáàñ. ðíâíðú 2009-2015 üêèñ ÿàëóðè ñòðóõòóðäáèãàì ùàìñ, ëèüíãäáàñ ãà ëíçþíåìàñ àðñäáèçàã âàìñþåàåäáóêè ñòðóõòóðà âààùìèàç.

óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòèñ îðíôäñèàæä øäçàåàæäáèñ 30 îðíúäìòèñ ñàîàñóþíã ëíçþíåìèñ ìàüèêøè åàéàìñèäáèñ ëþíêíã 8 îðíúäìòè ëíãèñ (èþèêäç ãèàâðàëà N43).

àìàêíâèóðè àñèëäòðèà øäèëùìäåà ñàëðäüåäêí ñàüàðëíäáèñ éåàêèôèúèóðè ëóøàéäáèñ øäëçþåäåàøèú, ðíãäñàú øäçàåàæäáäáèñ 35 îðíúäìòèñ ñàîàñóþíã åàéàìñèäáèñ ëþíêíã 12 îðíúäìòèà.

ñàëàâèäðíã, ëíëñàþóðäáèñ ñôäðíñà ãà ñàåàýðí íðâàìèæàúèäáèñ ëóøàéäáèñ øäçàåàæäáèñ 16 îðíúäìòèñ ñàîàñóþíã ëíçþíåìèñ ìàüèêøè åàéàìñèäáèñ 37 îðíúäìòèà.

ñàäðçí ÿàëøè äñ íðè ñòðóõòóðà äðçëàìäççàì ûàêèàì ñóñò éíðäêàúèàøèà ãà éíðäêàúèèñ éíäôèúèäìòè ëþíêíã 0.2921 ìèøìóêæäà.

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æäëíç ëíúäëóêè ñòðóõòóðóêè àìàêèæè ëþíêíã îðíúäìòóê âàìàüèêäáäáñ àñàþàåñ. äñ çàåèñçàåàã ûàêèàì ëìèøåìäêíåàìèà ëíçþíåìà-ëèüíãäáèñ çåèñíáðèåè àìàêèæèñçåèñ. ëàâðàë óìãà âàåèçåàêèñüèìíç, ðíë äðçè ãà èëàåä ìíëðäáèñ ëèþäãåèç ôíðëèðäáóê ëíìàúäëçà áàæàøè óëóøäåðäáèñ ëèäð ñàëóøàíñ øäçàåàæäáà 1.8-ÿäð ëäòèà ãàëñàõëäáêäáèñ ëèäð ñàëóøàíñ ëíçþíåìàæä.


60

830

9

9

13

1

37

16

0

0

12

35

3

4126

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90%

100%

დამქირავებელი (მოთხოვნა) უმუშევარი (მიწოდება)

გაზეთ ,,სიტყვა და საქმე”-ში 2010 - 2016 წლების მაისისა და დეკემბრის თვეებში გამოქვეყნებულივაკანსიებისა და სამუშაოს ძებნის ჯამური სტრუქტურა ISCO-ს პროფესიების ძირითად ჯგუფებში

ყველა დონის ხელმძღვანელები სპეციალისტები კვალიფიციის უმაღლესი დონითსპეციალისტები კვალიფიკაციის საშუალო დონით კანტორის მუშაკები

მომსახურების სფეროსა და სავაჭრო ორგანიზაციების მუშაკები კვალიფიციური მუშაკები სოფლი მეურნეობების დარგშისამრეწველო საწარმოების კვალიფიციური მუშები დანადგარებისა და მანქანების ოპერატორებიარაკვალიფიციური მუშები

ãàëõèðàåäáêäáçàì ùàöðëàåäáóêè èìòäðåèóäáèñ ãðíñ âàëíèéåäçà, ðíë ëàççåèñ Jobs.ge ÷åäêàæä ëìèøåìäêíåàìè îíðòàêèà, ñàãàú ñàëóøàíñ ëàûèäáäêè ãà ãàëõèðàåäáäêè þåãäáèàì äðçëàìäçñ. ùàöðëàåäáóêè èìòäðåèóäáèñ ãðíñ âàëíèéèçþà äéíìíëèéèñ 10 ñþåàãàñþåà ãàðâèñ üàë÷åàìè 10 éíëîàìèà. àðúäðç ëàçâàìñ ñàëóøàí ûàêèñ ûäáìèñ ü÷àðíã âàæäçè „ñèò÷åà ãà ñàõëä“ àð ãàóñàþäêäáèà. äñ éèãäå äðçþäê àãàñòóðäáñ ùåäìñ ëèäð æäëíç âàëíçõëóê åàðàóãñ, ðíë äñ ðäñóðñè ñðóêèàã âàìñþåàåäáóê ñäâëäìòæä ëóøàíáñ.

ùàöðëàåäáóêè èìòäðåèóäáèñ óéêäáêèå ÷åäêà ðäñîíìãäìòëà ëóøàþäêèñ ûäáìèñ ñàøóàêäáàã ðíëäêèëä èìòäðìäò-ðäñóðñè ëèóçèçà, ðàú èëàñ ìèøìàåñ, ðíë ñà÷íåäêçàí èìòäðìäòèæàúèèñ îðíäõòè, ðíëäêèú àëïàëàã þíðúèäêãäáà, ûàêèàì ëìèøåìäêíåàìèà ãàñàõëäáèñ éíìòäõñòøèú. àõåä àöñàìèøìàåèà èñèú, ðíë ëñþåèêè éíëîàìèäáèú éè ñàðâäáêíáäì ìàúìíá-ëäâíáðäáèñ ñàøóàêäáèç ñàñóðåäêè éàãðäáèñ ëíûäáìèñ îðàõòèéèç. ìèøàìãíáêèåèà, ðíë ðàú óôðí ãèãèà éíëîàìèà, ëèç óôðí ëúèðäà ñàëóøàí ûàêèñ àðàèìñòèòóúèóðè ûäáìèñ àêáàçíáà.

éàãðäáèñ ãäìàãíáèñ ûèðèçàãè ëèæäæäáèãàì ãèñúèîêèìàðóêè ôàõòíðè ëìèøåìäêíåàì ëèæäæàã ãààñàþäêà çèçõëèñ ÷åäêà ðäñîíìãäìòëà. àöñàìèøìàåèà, ðíë àë ëèæäæèç éàãðäáèñ ãäìàãíáà àð ãààñàþäêà ëþíêíã öåèìèñ ëüàðëíäáäêëà ðäñîíìãäìòëà. óãàåíã ñàèìòäðäñíà èñèú, ðíë ÷åäêà ñþåà èìòäðåèóøè, âàðãà àë ðäñîíìãäìòèñà, àøéàðàã èâðûìíáíãà ãàûàáóêíáà ãàõèðàåäáóêñà ãà ãàëõèðàåäáäêñ øíðèñ.

ðçóêàã ãà ëàðòèåàã ëíûèäáàãè îðíôäñèäáèñ ùàëíìàçåàêèãàì ëìèøåìäêíåàìè âàðäëíäáà èéåäçäáà. ðíâíðú üäñè, ûìäêàã ëíûèäáàãèà òäõìèéóðè âàìþðèñ ãà ôóìãàëäìòóðè ñàáóìäáèñëäò÷åäêí ãèñúèîêèìäáèñ (ôèæèéà, ëàçäëàòèéà, õèëèà) ñîäúèàêèñòäáè, þíêí ëàðòèåàã ëíûèäáàãè - ñíúèàêóðè ãà ¸óëàìèòàðóêè ñîäúèàêíáäáèñ ëõíìä éàãðäáè.

47

4.5 ñàâàìëàìàçêäáêí ñèñòäëèñ äôäõòèàìíáà ñòðóõòóðóêè óëóøäåðíáèñ 4.5 ñàâàìëàìàçêäáêí ñèñòäëèñ äôäõòèàìíáà ñòðóõòóðóêè óëóøäåðíáèñ éíìòäõñòøèéíìòäõñòøè

ãàñàõëäáèñà ãà óëóøäåðíáèñ àìàêèæèñ óëìèøåìäêíåàìäñè éíëîíìäìòèà ãàñàõëäáèñ îðíôäñèèñà ãà âàìàçêäáèç ëèöäáóêè îðíôäñèèñ øäñàáàëèñíáà. øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåà èûêäåà àñäçè àìàêèæèñ øäñàûêäáêíáàñ. éäðûíã, âàëíéåêäåèñ èìñòðóëäìòàðèóëè èçåàêèñüèìäáñ, ðíâíðú ðäñîíìãäìòèñ ôàõòèóðè ãàñàõëäáèñ îðíôäñèèñ, èñä ãèîêíëèç àì ñþåà ñàþèñ ñäðòèôèéàòèç ãàãàñòóðäáóêè ûèðèçàãè îðíôäñèèñ éêàñèôèúèðäáàñ.


33.19%

29.28%26.86% 26.95% 26.70%

29.31%27.64%

15.7% 16.7%15.6%

13.7%

17.3% 17.3% 17.2%

0.1% 0.1% 0.3% 0.2% 0.2% 0.1% 0.1%

13.7% 13.1% 12.1% 12.1% 12.4%13.6% 13.7%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

2009 2010 2011 2012 2013 2014 2015

ISCO-ს ორნიშნა კოდების დონეზე პროფესიის შესაბამისად დასაქმებულთა ხვედრითი წონა დასაქმების ტიპების მიხედვით

დაქირავებით დასაქმებული არასასოფლო თვითდასაქმებული

სასოფლო თვითდასაქმებული სულ


âàëíéåêäåèñ ëíìàúäëäáèç (èþèêäç ãèàâðàëà N44), ISCO-ñ íðìèøìà éíãäáèñ ãíìäæä ñäðòèôèúèðäáóêè îðíôäñèèñ øäñàáàëèñàã ãàñàõëäáóêçà ëçêèàìè ðàíãäìíáèñ ëþíêíã 13.7 îðíúäìòèà ãàñàõëäáóêè, ðàú óàöäñàã ãàáàêè ëàùåäìäáäêèà.

èñä ðíâíðú ÷åäêâàì, àõàú ñàøóàêí ëàùåäìäáêèñ ëçàåàðè âàìëñàæöåðäêè ñàñíôêí çåèçãàñàõëäáàà, ðíëäêèú ëçêèàìè ãàñàõëäáèñ çèçõëèñ ìàþäåàðèà. àë ôíðëèç ãàñàõëäáóêäáñ øíðèñ ñäðòèôèúèðäáóêè îðíôäñèèñ øäñàáàëèñàã ëþíêíã óëìèøåìäêí ìàüèêèà ãàñàõëäáóêè.

îðíôäñèèñ øäñàáàëèñàã ãàñàõëäáèñ ãíìä ÷åäêàæä ëàöàêè ãàõèðàåäáèç ãàñàõëäáóêäáñ øíðèñàà - 27.6 îðíúäìòè, ðàú æíâàãàã, ûàêèàì ãàáàêèà. 2009-2013 üêäáøè äñ ëàùåäìäáäêè øäëúèðäáèñ òäìãäìúèèç þàñèàçãäáíãà. 2014 üäêñ æðãèñ øäëãäâ éè 2015 üäêñ èñäå øäëúèðãà. ðàú øäþäáà àðàñàñíôêí çåèçãàñàõëäáóêäáøè øäñàáàëèñ ëàùåäìäáäêñ, ëàçè üèêè óëìèøåìäêíã, ëþíêíã 3.5 îðíúäìòóêè îóìõòèç àöäëàòäáà ñàøóàêí ëàùåäìäáäêñ (øäñàáàëèñàã, 17.2% ãà 13.7%).

îðíôäñèèñ øäñàáàëèñàã ãàñàõëäáóêçà þåäãðèçè üíìèñ ëàùåäìäáêèñ àðúçó ñàþàðáèäêí òäìãäìúèà íð ðàëäæä øäèûêäáà ëäò÷åäêäáãäñ:

âàìàçêäáèñ àðñäáóêè ñèñòäëà åäð èûêäåà èñäç úíãìàñ, ðíëäêèú øäëãâíëøè îðíôäñèèñ 1. øäñàáàëèñàã ãàñàõëäáàñ óæðóìåäê÷íôñ;ñàáýíçà îäðèíãøè ëèöäáóêè âàìàçêäáà åäð àéëà÷íôèêäáñ øðíëèñ áàæàðæä àðñäáóê 2. ëíçþíåìäáñ.

ãàñàþäêäáóêè íðè âàðäëíäáèãàì óôðí àðñäáèçè îèðåäêèà, åèìàèãàì ñàáýíçà îäðèíãèãàì ãàøíðäáèñ éåàêíáàæä ñàáýíçà éàåøèðøè ëèöäáóêè âàìàçêäáèñ ëõíìäçà þåäãðèçè üíìà øðíëèñ áàæàðæä ëúèðãäáà. àëãäìàã àë ôàõòíðèñ âàëí éåàêèôèéàúèèñ øäóñàáàëí ãàñàõëäáèñ þåäãðèçè üíìà âàìóþðäêè øäëúèðäáèñ òäìãäìúèèñ ëàòàðäáäêè óìãà è÷íñ. âàëíéåêäåèñ ëíìàúäëäáè éè ñàüèìààöëãäâí òäìãäìúèàæä ëäò÷åäêäáäì, ðàú èëàñ ìèøìàåñ, ðíë âàãàëü÷åäòèà îèðåäêè âàðäëíäáà.

48


34.3%

30.5%27.9% 28.0% 27.5%

30.2%28.4%

0%

5%

10%

15%

20%

25%

30%

35%

40%

2009 2010 2011 2012 2013 2014 2015

ISCO-ს ორნიშნა კოდების დონეზე პროფესიის შესაბამისად დასაქმებულთა ხვედრითი წონა დაქირავებით დასაქმებულებში


ãàõèðàåäáèç ãàñàõëäáóêçà 12 îðíúäìòè ãèîêíëèñ éåàêèôèéàúèàæä óôðí ëàöàêè éåàêèôèéàúèèçàà ãàñàõëäáóêè, þíêí 35 îðíúäìòè - óôðí ãàáàêè éåàêèôèéàúèèç. ãàõèðàåäáóêçà 24 îðíúäìòñ ñäðòèôèúèðäáóêè îðíôäñèà ñàäðçíã àð àõåç. ñà÷óðàãöäáíà, ðíë àë éàòäâíðèèñ ãàñàõëäáóêçà þåäãðèçè üíìà 2015 üäêñ üèìà üäêçàì øäãàðäáèç ðàëãäìàãëä âàèæàðãà.


3% 4% 4% 4% 3% 3% 1%

31% 34% 37% 35% 37% 35% 35%

33% 29% 27% 27% 27% 29% 28%

13% 14% 14% 14% 13% 12%12%

20% 19% 19% 21% 21% 21% 24%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

დაქირავებით დასაქმებულთა განაწილება ფაქტიური პროფესიისა და დიპლომით პროფესიის შესაბამისობის მიხედვით

NA უფრო დაბალი კვალიფიკაციით

შესაბამისი კვალიფიკაციით უფრო მაღალი კვალიფიკაციით

პროფესია არ აქვს


ãèîêíëèñ ëèþäãåèç éåàêèôèéàúèàñçàì ôàõòèóðè ãàñàõëäáèñ øäñàáàëèñíáèñ ñòðóõòóðà àùåäìäáñ, ðíë ëèöäáóêè éåàêèôèéàúèèñ ëèþäãåèç ñàëóøàíñ îíåìà ñàõàðçåäêíøè ðçóêèà, ðàú íðè ûèðèçàãè âàðäëíäáèç øäèûêäáà è÷íñ âàìîèðíáäáóêè:

49

ëèöäáóêè âàìàçêäáèñ úäìæè ãà ðäàêóðè úíãìà àð àðèñ äðçëàìäçèñ øäñàáàëèñè àìó • ëèöäáóêè ãèîêíëè àð ìèøìàåñ ëèöäáóê úíãìàñ;

ñàâàìëàìàçêäáêí ãàüäñäáóêäáèñ ëèäð øäçàåàæäáóêè îðíôäñèäáèñ ñòðóõòóðà • àúèêäáóêèà øðíëèñ áàæðèñ ëíçþíåìèñ ñòðóõòóðàñ, àìó ñàâàìëàìàçêäáêí ãàüäñäáóêäáäáè àëæàãäáäì úäìæèñ ëèþäãåèç âàìàçêäáóê, ëàâðàë ãàñàõëäáèñ ìàéêäáè îäðñîäõòèåèñ ëõíìä éàãðäáñ.

äñ íðèåä ëèæäæè ñàåàðàóãíã òíêôàðãè ûàêèñàà ãà èëàæä ëèóçèçäáñ, ðíë âàìàçêäáèñ ñèñòäëà ìàéêäáàãàà øðíëèñ áàæàðæä íðèäìòèðäáóêè. àëàæäåä ëäò÷åäêäáñ ôàõòèóðè îðíôäñèèñà ãà ãèîêíëøè ëèçèçäáóêè îðíôäñèèñ øäñàáàëèñíáèñ ëèþäãåèç ãàõèðàåäáèç ãàñàõëäáóêçà âàìàüèêäáèñ ñòðóõòóðà, ðàú áíêí ðåà üêèñ ëàìûèêæä (2009-2015 üü.) àðñäáèçàã àð øäúåêèêà.

àðàñàñíôêí-ñàëäóðìäí ãàðâäáøè çåèçãàñàõëäáóêäáèñ 35 îðíúäìòè çàåèñ ãèîêíëèñ îðíôäñèàæä óôðí ãàáàêè éåàêèôèéàúèèçàà ãàñàõëäáóêè, þíêí 33 îðíúäìòñ îðíôäñèà ñàäðçíã àð àõåñ. ñàéåêäå îäðèíãøè àöèìèøìà îðíôäñèèñ àðëõíìäçà þåäãðèçè üíìèñ ëàòäáà, ðàú óãàåíã ìäâàòèóð òäìãäìúèàñ üàðëíàãâäìñ. ãèîêíëèñ ëèþäãåèç îðíôäñèàæä óôðí ëàöàêè éåàêèôèéàúèèç àðàñàñíôêí çåèçãàñàõëäáóêçà 13 îðíúäìòèà ãàñàõëäáóêè (èþèêäç ãèàâðàëà N47).

ãèîêíëèñ ëèþäãåèç îðíôäñèèñ ãàñàõëäáèñ ôàõòèóð îðíôäñèàñçàì øäñàáàëèñíáèñ éóçþèç ÷åäêàæä ëûèëä ëãâíëàðäíáà, ðíâíðú ëíñàêíãìäêè è÷í, ñàñíôêí çåèçãàñàõëäáèñ ñôäðíøèà. ñàñíôêí çåèçãàñàõëäáóêäáèñ 66 îðíúäìòñ îðíôäñèà àð àõåñ, þíêí 29 îðíúäìòè óôðí ãàáàêè éåàêèôèéàúèèçàà ãàñàõëäáóêè (èþèêäç ãèàâðàëà N48). äñ èñ éíìòèìâäìòèà, ðíëäêëàú ëèèöí âàðéåäóêè âàìàçêäáà, ëàâðàë çàåèñè ñîäúèàêíáèç ñàëóøàí àãâèêè åäð ìàþà ãà èûóêäáóêè âàþãà ñàéóçàð ëäóðìäíáàøè ãàñàõëäáóêè÷í.

éåàêèôèéàúèèñ øäñàáàëèñè ãàñàõëäáèñ þåäãðèçè üíìà ñíôêèñ ëäóðìäíáàøè îðàõòèéóêàã ìóêíåàìèà, àìó ñäðòèôèúèðäáóêè àâðíìíëäáèñ, åäòäðèìàðäáèñ, ëäõàìèæàòíðäáèñ, ëäêèíðàòíðäáèñ ãà ñþåà ñäðòèôèúèðäáóêè àâðàðóêè ñîäúèàêíáèñ ëõíìä ñàñíôêí çåèçãàñàõëäáóêçà þåäãðèçè üíìà ìóêçàì àþêíñàà. àõäãàì âàëíëãèìàðä, øäèûêäáà ãàåàñéåìàç, ðíë ñäðòèôèúèðäáóêè àâðàðóêè ñîäúèàêíáèñ ëõíìä îèðäáè çèçõëèñ àð ëèëàðçàåäì ñàñíôêí çåèçãàñàõëäáàñ, çóëúà äñ àð ìèøìàåñ, ðíë ëàç àõåç ñîäúèàêíáèç ãàñàõëäáèñ ðäàêóðè øäñàûêäáêíáà.


6% 6% 6% 6% 7% 5% 2%

32%40% 36% 37% 35%

33% 35%

16%17%

16% 14% 17%17% 17%

14%12% 15% 15% 13%

13% 13%

32% 26% 27% 28% 28% 32% 33%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

არასასოფლო თვითდასაქმებულთა განაწილება ფაქტიური პროფესიისა და დიპლომით პროფესიის შესაბამისობის მიხედვით





50

2009-2015 üêäáøè âàëíéåäçèêè òäìãäìúèäáèãàì àöñàìèøìàåèà îðíôäñèèñ àðëõíìä ñàñíôêí çåèçãàñàõëäáóêäáèñ þåäãðèçè üíìèñ óëìèøåìäêí æðãà. ðàú øääþäáà óôðí ëàöàêè ñäðòèôèúèðäáóêè éåàêèôèéàúèèñ ëõíìäçà þåäãðèçè üíìèñ ëàùåäìäáäêñ, èñ ñòàáèêóðàã 30 îðíúäìòèñ ëàþêíáêíáàøèà.

ñàñíôêí çåèçãàñàõëäáóêäáøè óôðí ëàöàêè éåàêèôèéàúèèç ãàñàõëäáóêäáèñ üèêè ëþíêíã 4-5 îðíúäìòèà. äñ äðçè øäþäãåèç óúìàóðèà, ëàâðàë àðèñ èñäçè îðíôäñèäáè, ðíëêäáèú óôðí ãàáàê éåàêèôèéàúèàã èçåêäáà, åèãðä ñíôêèñ ëäóðìäíáàøè ñàõëèàìíáà (ëàâàêèçàã,ëä-9 ÿâóôè - „àðàéåàêèôèúèóðè ëóøäáè“, ëä-8 ÿâóôè - „ëäàîàðàòääáè ãà íîäðàòíðäáè“).


2% 2% 2% 2% 1% 1% 0%

28% 30% 28% 30% 31% 30% 29%

0% 0% 0% 0% 0% 0% 0%5% 6% 5% 5% 5% 5% 4%

65% 62% 65% 64% 62% 64% 66%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 2010 2011 2012 2013 2014 2015

სასოფლო თვითდასაქმებულთა განაწილება ფაქტიური პროფესიისა და დიპლომით პროფესიის შესაბამისობის მიხედვით





ñàäðçí ÿàëøè, NACE-ñ âàëñþåèêäáóê ÿâóôäáøè ISCO-ñ íðìèøìà éíãäáèñ ãíìäæä îðíôäñèèñ øäñàáàëèñàã ãàñàõëäáóêçà þåäãðèçè üíìà ÷åäêàæä ëàöàêè âàìàçêäáèñà ãà ÿàìãàúåèñ ñäõòíðäáøèà, ðàú ñðóêèàã âàñàâäáèà, çóëúà àöñàìèøìàåèà, ðíë àë ãàðâäáøèú éåàêèôèéàúèèñ øäñàáàëèñè ãàñàõëäáèñ ëàùåäìäáäêè øäëúèðäáèñ òäìãäìúèèç âàëíèðùäåà.

èâèåä ëàùåäìäáäêè øäãàðäáèç ëàöàêèà àâðäçåä æäëíç àöìèøìóê ÷åäêàæä ëðàåàêôäðíåàì ÿâóôøè, ñàãàú øäãèñ òðàìñîíðòè, ñàñòóëðíäáè, ðäñòíðìäáè, ñàôèìàìñí øóàëàåêíáà ãà ñàþäêëüèôí ëàðçåèñ íðâàìíäáè. àöñàìèøìàåèà, ðíë àë ëàùåäìäáäêñ àõàú øäëúèðäáèñ òäìãäìúèà àþàñèàçäáñ.

ëðäüåäêíáàñà ãà ëøäìäáêíáàøè éåàêèôèéàúèèñ øäñàáàëèñàã ãàñàõëäáóêçà þåäãðèçè üíìèñ ëàùåäìäáäêè ñàõàðçåäêíñ ñàøóàêí ëàùåäìäáäêèñ ëàþêíáêíáàøèà, çóëúà èñèú øäëúèðäáèñ òäìãäìúèèç þàñèàçãäáà.

äðçàãäðçè ãàðâè, ñàãàú éåàêèôèéàúèèñ øäñàáàëèñè ãàñàõëäáèñ ëàùåäìäáäêè æðãèñ òäìãäìúèàñ àåêäìñ, åàýðíáà ãà ñà÷íôàúþíåðäáí ëíëñàþóðäáàà, çóëúà óìãà àöèìèøìíñ, ðíë äñ ëàùåäìäáäêè çàåèñçàåàã ûàêèàì ãàáàê ìèøìóêæäà, ñàéëàíã ñóñòè æðãèñ òäìãäìúèèç.

ñíôêèñ ëäóðìäíáàøè éåàêèôèéàúèèñ øäñàáàëèñàã ãàñàõëäáèñ ëàùåäìäáäêè èëãäìàã ãàáàêèà, ðíë ëèñè âàìþèêåàú àð öèðñ.

ñàäðçí ÿàëøè, éåàêèôèéàúèèñ øäñàáàëèñè ãàñàõëäáèñ ëàùåäìäáäêèñ üàë÷åàì ãàðâäáøè âàëíéåäçèêè øäëúèðäáèñ òäìãäìúèà éèãäå äðçþäê ëèóçèçäáñ èëàæä, ðíë äñ îðíáêäëà ñàáýíçà ëäëéåèãðäíáàæä ëäòàã âàìàçêäáèñ àðñäáóêè ñèñòäëèñ âàóëàðçàíáèçàà âàëíüåäóêè, åèìàèãàì ñàáýíçà ëäëéåèãðäíáà, ëèêäåàãè ãà üàðëàåàêèà, þíêí øäëúèðäáèñ òäìãäìúèà ëíëàåàêè îðíáêäëäáèñ ìèøàìèà.

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0.2% 0.2% 0.3% 0.2% 0.2% 0.3% 0.5%

25%22% 22%

20% 20% 21% 21%

8% 7%9%

7% 7% 9% 10%

35%31%

28% 29% 28%31%

29%

46%43%

37%40% 41% 42%

40%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

2009 2010 2011 2012 2013 2014 2015

ISCO-ს ორნიშნა კოდების დონეზე პროფესიის შესაბამისად დასაქმებულთახვედრითი წონა ეკონომიკის გამსხვილებულ სექტორებში

სოფლის მეურნეობა, მეტყევეობა, თევზჭერამრეწველობა, მშენებლობავაჭრობა და საყოფაცხოვრებო მოსახურებატრასპორტი, სასტუმროები, რესტორნები და სხვა მომსახურებაგანათლება და ჯანდაცვა


îðíôäñèèñ øäñàáàëèñàã ãàñàõëäáèñ ëàùåäìäáäêè øäãàðäáèç ëàöàêèà, çó ôàõòèóðè ãàñàõëäáèñ ãà ñäðòèôèúèðäáóêè îðíôäñèèñ çàìþåäãðàñ ISCO-ñ ëþíêíã äðçìèøìà éíãäáèñ ãíìäæä, àìó ÷åäêàæä ëñþåèê ÿâóôäáøè âàìåèþèêàåç.

àë øäëçþåäåàøè ãàõèðàåäáèç éåàêèôèéàúèèñ øäñàáàëèñàã ãàñàõëäáèñ þåäãðèçè üíìèñ ëàùåäìäáäêè 27.6 îðíúäìòèãàì 36.5 îðíúäìòàëãä èæðãäáà. äñ ëàùåäìäáäêè èë çåàêñàæðèñèçàà ñàèìòäðäñí, ðíë óôðí ìàçêàã àùåäìíñ, çó ðàëãäìàã ãàáàêèà ñäðòèôèúèðäáóêè éåàêèôèéàúèèñ øäñàáàëèñè ãàñàõëäáèñ ãíìä, åèìàèãàì ISCO-ñ äðç ìèøìà éíãäáèñ ãíìä ûàêæäã ëñþåèê ãà àðàäðçâåàðíåàìè îðíôäñèäáèñ âàäðçèàìäáàñ üàðëíàãâäìñ. ëèóþäãàåàã àëèñà, àñäç ãíìäæäú éè ñäðòèôèúèðäáóêè éåàêèôèéàúèèñà ãà ôàõòèóðè îðíôäñèèñ çàìþåäãðà, ãàõèðàåäáèç ãàñàõëäáèñçåèñàú éè ëþíêíã 36.5 îðíúäìòèà.

÷åäêà ñþåà ãàìàðùäìè ëàùåäìäáêäáèú, ñàñíôêí çåèçãàñàõëäáèñ ùàçåêèç ãà ëèñ âàðäøäú, èñäçèåä îðíîíðúèèç èúåêäáà, ðíâíðú ISCO-ñ íðìèøìà éíãäáèñ ãíìäæä çàìþåäãðèñ øäëçþåäåàøè.

âàìàçêäáèñ ñèñòäëèñ øðíëèñ áàæàðçàì çàåñäáàãíáèñ îðíáêäëà, ðàú øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëçà áàæèñ àìàêèæèñàñ âàëíèéåäçà, ùàöðëàåäáóêëà èìòäðåèóäáëàú ãààãàñòóðà. çèçõëèñ ÷åäêà ðäñîíìãäìòëà éàãðäáèñ ëíûèäáèñ äðçäðç ëçàåàð ñèðçóêäã ñüíðäã ñàâàìëàìàçêäáêí úäìæçàì øäãàðäáèç ñàëóøàíñ ëàûèäáêèñ ôàõòíáðèåè úíãìèñ ãàáàêè ãíìä ãààñàþäêà. àë ôíìæä ñðóêèàã áóìäáðèåèà èñ âàðäëíäáà, ðíë âàëíéèçþóêè éíëîàìèäáèñ óëðàåêäñíáà ëèëàðçàåñ éíìéóðäìòè éíëîàìèäáèñ éåàêèôèúèðäáóêè îäðñíìàêèñ âàãëíáèðäáèñ îðàõòèéàñ (Headhunting).

èëàåä ùàöðëàåäáóêè èìòäðåèóäáèãàì éèãäå äðçè ëìèøåìäêíåàìè âàðäëíäáà âàëíèéåäçà: ëäüàðëääáè éëà÷íôèêè àð àðèàì âàìàçêäáèñ ñèñòäëèñ îðíãóõòèç àìó ëèñ ëèäð ëíëæàãäáóêè ñàëóøàí ûàêèñ éåàêèôèéàúèèç. ëèóþäãàåàã àëèñà, àðú äðç ðäñîíìãäìòñ àð óôèõðèà ðàèëä ìàáèÿèñ âàãàãâëà àðñäáóêè åèçàðäáèñ âàñàóëÿíáäñäáêàã, çóìãàú óëàöêäñ ñàñüàåêäáäêçàì óøóàêí éíìòàõòèñ âæèç.

àëãäìàã, âàìàçêäáèñ ñèñòäëèñà ãà äéíìíëèéèñ øäóçàåñäáêíáèñ îðíáêäëà ñàþäêëüèôíñ ëíñàâåàðäáäêèà ãà áàæàðè ëàñ, ðíâíðú ëñíôêèí îðàõòèéà àùåäìäáñ, çàåèñçàåàã åäð âàãàü÷åäòñ.

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5. øðíëèñ áàæðèñ èìñòèòóúèóðè ñèñóñòääáè5. øðíëèñ áàæðèñ èìñòèòóúèóðè ñèñóñòääáèãàñàõëäáèñà ãà óëóøäåðíáèñ ñèöðëèñäóêè àìàêèæèñ ëìèøåìäêíåàìè àñîäõòèà ñàëóøàíñ

ûäáìèñ âæäáè. øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ èìñòðóëäìòàðèóëè ñàâóêèñþëí èìôíðëàúèàñ øäèúàåñ ñàëóøàíñ ûäáìèñ âæäáèñ øäñàþäá.

âàëíéåêäåèñ ëíìàúäëäáèç, ãàóñàõëäáäêçà ãààþêíäáèç 1/5 (18.8%) àõòèóðàã äûäáãà ñàëóøàíñ, þíêí 4/5-æä ëäòè (81.2%) ñàëóøàíñ àð äûäáãà. ñàëóøàíñ ëàûèäáäêè ãàóñàõëäáäêè ëíõàêàõääáè, ûèðèçàãàã ãàõèðàåäáèç ãàñàõëäáàñ äûäáãìäì. ñàéóçàðè áèæìäñèñ üàëíü÷äáèñ âæèç ãàñàõëäáèñ îðíáêäëèñ âàãàýðà ëèìèëàêóðèà.

úþðèêè N 3: ãàóñàõëäáäêçà âàìàüèêäáà ñàëóøàíñ ûäáìèñ þäðþäáèñ ëèþäãåèç (îðíúäìòè)úþðèêè N 3: ãàóñàõëäáäêçà âàìàüèêäáà ñàëóøàíñ ûäáìèñ þäðþäáèñ ëèþäãåèç (îðíúäìòè)

2009 2010 2011 2012 2013 2014 2015

ãèàþ, åäûäáãè þäêôàñèàì ñàëóøàíñ:ãèàþ, åäûäáãè þäêôàñèàì ñàëóøàíñ: 20.5 21.1 20.6 21.6 20.7 18.4 18.8

åäúìíáíãè âàìúþàãäáäáñ îðäñèñ, òäêäåèæèèñ, èìòäðìäòèñ ãà ñþåà ñàøóàêäáèç

2.7 2.4 2.5 3.0 3.4 3.0 3.0

ëíåèîíåäáãè èìôíðëàúèàñ ìàúìíáäáèñ ñàøóàêäáèç 16.9 17.8 17.4 18.1 17.0 15.0 15.3

óøóàêíã åóéàåøèðãäáíãè àãëèìèñòðàúèàñ 0.7 0.6 0.5 0.4 0.3 0.3 0.4

åàõåä÷ìäáãè âàìúþàãäáäáñ îðäñèñ, òäêäåèæèèñ èìòäðìäòèñ ãà ñþåà ñàøóàêäáèç

0.0 0.0 0.1 0.0 0.1 0.1 0.1

ëèåëàðçä ãàñàõëäáèñ ñàëñàþóðñ 0.1 0.1 0.1 0.0 0.0 0.0 0.0

ñþåà 0.1 0.1 0.0 0.0 0.0 0.0 0.0

ãèàþ, åúãèêíáãè ñàéóçàðè ñàõëèñ ãèàþ, åúãèêíáãè ñàéóçàðè ñàõëèñ üàëíü÷äáàñ:üàëíü÷äáàñ: 0.1 0.2 0.1 0.2 0.2 0.2 0.0

ñàéóçàðè ñàõëèñ üàëíü÷äáèñàçåèñ ëèåëàðçä øäñàáàëèñ íðâàìíäáñ ìäáàðçåèñ ëèñàöäáàã;

0.0 0.1 0.0 0.1 0.1 0.1 0.0

ãàåàë÷àðä éàåøèðäáè îíòäìúèóð îàðòìèíðäáçàì; 0.0 0.1 0.1 0.0 0.0 0.0 0.0

åúàãä ëèëäöí ñàõëèñ ãàñàü÷äáàã ñäñþè, éðäãèòè; 0.0 0.0 0.0 0.0 0.0 0.0 0.0

åäûäáãè øäìíáàñ, ìäãêäóêñ, ëíü÷íáèêíáäáñ, ëèüèñ ìàéåäçñ; 0.0 0.0 0.0 0.0 0.0 0.0 0.0

ñþåà 0.0 0.1 0.0 0.0 0.0 0.0 0.0

àðà, àð ëèúãèààðà, àð ëèúãèà 79.4 78.6 79.3 78.2 79.1 81.4 81.2

ñóê 100 100 100 100 100 100 100ü÷àðí: ñàõàðçåäêíñ øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëçà áàæà ãàëóøàåäáóêè àåòíðçà ÿâóôèñ ëèäð.

ûàêæä ëìèøåìäêíåàìèà ñàëóøàíñ ûäáìèñ âæäáèñ ãàÿâóôäáà øðíëèñ áàæðèñ èìñòèòóúèíìàêèæàúèèñ þàðèñþèñ ëèþäãåèç. ñþåàâåàðàã ðíë åçõåàç, ðàëãäìàã ëóøàíáñ ñèñòäëà, ðíëêèñ ëäøåäíáèçàú ëíõàêàõääáè ñàëñàþóðñ äûäáäì. éåêäåèñ ëèæìäáèãàì âàëíëãèìàðä, æäëíç ëíòàìèêè úþðèêèñ õåäëãäáàðäøè ùàëíçåêèêè ñàøóàêäáäáè âàãàåàÿâóôäç èëèñ ëèþäãåèç, ðàëãäìàã øäèúàåãìäì èñèìè éàãðäáèñ ëíûäáìèñ àì/ãà ñàéóçàðè ñàõëèñ ãàü÷äáèñ ôíðëàêèæäáóê ëèãâíëàñ. øäñàáàëèñàã âàëíå÷àåèç ñàëóøàíñ ûäáìèñ íðè îèðíáèçè ÿâóôè:

ñàëóøàíñ èìñòèòóúèíìàêèæäáóêè ûäáìà, ñàãàú øäåèãìäì ðäñîíìãäìòäáè, ðíëêäáëàú 1. ñàëóøàíñ ûäáìèñ øäñàþäá âàñúäñ øäëãäâè îàñóþäáè:

åäúìíáíãè âàìúþàãäáäáñ îðäñèñ, òäêäåèæèèñ, èìòäðìäòèñ ãà ñþåà ñàøóàêäáèç;• óøóàêíã åóéàåøèðãäáíãè àãëèìèñòðàúèàñ;• åàõåä÷ìäáãè âàìúþàãäáäáñ îðäñèñ, òäêäåèæèèñ, èìòäðìäòèñ ãà ñþåà ñàøóàêäáèç;• ëèåëàðçä ãàñàõëäáèñ ñàëñàþóðñ;•

53

ñàéóçàðè ñàõëèñ üàëíü÷äáèñàçåèñ ëèåëàðçä øäñàáàëèñ íðâàìíäáñ ìäáàðçåèñ ëèñàöäáàã; • ãàåàë÷àðä éàåøèðäáè îíòäìúèóð îàðòìèíðäáçàì; • åúàãä ëèëäöí ñàõëèñ ãàñàü÷äáàã ñäñþè. •

ñàëóøàíñ àðàèìñòèòóúèíìàêèæäáóêè ûäáìà, ñàãàú øäåèãìäì ðäñîíìãäìòäáè, ðíëêäáëàú 2. ñàëóøàíñ ûäáìèñ øäñàþäá âàñúäñ øäëãäâè îàñóþäáè:

ëíåèîíåäáãè èìôíðëàúèàñ ìàúìíáäáèñ ñàøóàêäáèç;• åäûäáãè øäìíáàñ, ìäãêäóêñ, ëíü÷íáèêíáäáñ, ëèüèñ ìàéåäçñ; • ñþåà.•

àâðäâèðäáóêè øäôàñäáäáèñ âàìàüèêäáà àùåäìäáñ, ðíë ñàõàðçåäêíøè øðíëèñ áàæàðè ëþíêíã 20 îðíúäìòèçàà èìñòèòóúèíìàêèæäáóêè (èþèêäç ãèàâðàëà N50). àëãäìàã, ñàëóøàíñ ûäáìèñ ûèðèçàãè ü÷àðí éåêàå ñíúèàêóðè éàîèòàêèà.

ñàëóøàíñ ûäáìèñ âæäáèñ óîèðàòäñàã àðàèìñòèòóúèóðè þàñèàçè, ðíëäêèú üêäáèñ âàìëàåêíáàøè àð èúåêäáà, øðíëèñ áàæðèñ àðàñðóê÷íôèêäáàæä ëèóçèçäáñ. øðíëèñ áàæàðæä ëíçþíåìà-ëèüíãäáèñ èìñòèòóúèíìàêèæäáà óëóøäåðíáèñ îðíáêäëèñ ñèñòäëóðè ëíâåàðäáèñ äðçäðçè îèðåäêè öíìèñûèäáàà. äñ ñàéëàíã ðçóêè ñèñòäëàà, ðíëäêèú ñàéàìíìëãäáêí ùàðùíøè ëíçàåñäáàëãä ñàõàðçåäêíøè àðñäáóêè ñîäúèôèéèñ ñàôóûåêèàì âààæðäáàñà ãà âàçåàêèñüèìäáàñ ëíèçþíåñ.


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უმუშევართა განაწილება სამუშაოს ინსტიტუციონალიზებული ძებნის მიხედვით

სამუშაო ინსტიტუციური ძებნა სამუშაოს არაინსტიტუციური ძებნა


ëìèøåìäêíåàìèà ñàëóøàí àãâèêäáèñ âàìàüèêäáà ëàçè âäìäðàúèèñ ü÷àðíäáèñ ëèþäãåèç. øèìàëäóðäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëçà áàæèãàì âàëíå÷àåèç ñàëóøàí àãâèêäáèñ íçþè òèîè ëàçè âäìäðàúèèñ ü÷àðíäáèñ ëèþäãåèç:

ñàþäêëüèôíñ ëèäð øäõëìèêè ñàëóøàí àãâèêäáè - ñàãàú øäåèãìäì ñàþäêëüèôí 1. ãàüäñäáóêäáäáøè ãà ñàþäêëüèôí ñäõòíðèñ íðâàìèæàúèäáøè ãàñàõëäáóêäáè;éäðûí ñäõòíðèñ ëèäð øäõëìèêè ñàëóøàí àãâèêäáè, ñàãàú øäåèãìäì éäðûí ñàéóçðäáèñ 2. ñàüàðëíäáñà ãà íðâàìèæàúèäáøè ãàõèðàåäáèç ãàñàõëäáóêäáè ãà çåèç ëäüàðëääáè ãàõèðàåäáóêè ëóøàéäáèç;ñàéóçàðè óìàðäáèç øäõëìèêè ñàëóøàí àãâèêäáè, ñàãàú øäåèãìäì èñ àðàñàñíôêí 3. çåèçãàñàõëäáóêäáè, ðíëäêçà ãàñàõëäáàú ëàçè óìàðäáèñ âàëí÷äìäáèç ëíþãà. àñäç ãàñàõëäáóêäáñ ëèäéóçåìäì èìãèåèãóàêóðè ëäüàðëääáè, ðíëêäáèú çàåèñ îðíôäñèóêè úíãìèç àðèàì çåèçãàñàõëäáóêäáè;ñòèõèóðàã øäõëìèêè ñàëóøàí àãâèêäáè, ñàãàú øäåèãìäì çåèçãàñàõëäáóêäáè 4.

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ñíôêèñ ëäóðìäíáàñà ãà üåðèê åàýðíáàøè, òàõñèñòäáè ãà ñþå. ëíéêäã ðíë åçõåàç, çåèçãàñàõëäáóêäáè ãàáàêè éàîèòàêòäåàãíáèñà ãà ëóøàéçà ëàöàê éåàêèôèéàúèàæä îðäòäìæèèñ àðëõíìä ãàðâäáøè.

2015 üêèñ ëãâíëàðäíáèç ñàëóøàí àãâèêäáèñ 53 îðíúäìòè ñüíðäã ñòèõèóðàã è÷í øäõëìèêè, 27 îðíúäìòè - éäðûí ñäõòíðèñ ëèäð è÷í øäõëìèêè, 15 îðíúäìòè - ñàþäêëüèôíñàâàì, þíêí 4 îðíúäìòè - ñàéóçàð óìàðäáæä ãà÷ðãìíáèç.

ãàëõèðàåäáäêèñà ãà ãàõèðàåäáóêèñ øäþåäãðèñ ñòèõèóðè þàñèàçèñ îðíáêäëóðíáà ùàöðëàåäáóêè èìòäðåèóäáèñ ãðíñàú âàëíèéåäçà. ëèóþäãàåàã èëèñà, ðíë óéêäáêèå ÷åäêà ðäñîíìãäìòè éàãðäáèñ ëíûèäáèñàçåèñ ðíëäêèëä èìòäðìäò ðäñóðññ è÷äìäáñ (Jobs.ge, LinkedIn-è, Facebook ãà à.ø.), äñ ðäñóðñäáè, äðçèàìè ñèñòäëèñ àðàðñäáíáèñ âàëí äðçëàìäççàì éàåøèðøè àð àðèàì. ãàëõèðàåäáêèñà ãà ñàëóøàíñ ëàûèäáäêèñ øäþåäãðèñ ëíäãìèñ èìñòèòóúèíìàêèæàúèà, øäñàáàëèñè çàëàøèñ üäñäáèñ âàìñàæöåðà ãà äðç ñèñòäëàøè ëíõúäåà óôðí ëàöàêè çàìðèâèñ àëíúàìàà, åèãðä èìòäðìäòèñ ëäøåäíáèç åàéàìñèäáèñ âàåðúäêäáà. ùàöðëàåäáóêè èìòäðåèóäáèãàì âàëíéåäçèêè ñàäðçí ôíìè àùåäìäáñ, ðíë ãàõèðàåäáóêñ - ëþíêíã ëíåàêäíáäáè, þíêí ãàëõèðàåäáóêñ - ëþíêíã óôêäáäáè àõåñ. ñàþäêëüèôíñ ëèäð àë îðíúäñäáèñ èìñòèòóúèóð, ëàç øíðèñ ñàéàìàìëãäáêí, ùàðùíøè ëíõúäåà äðçíá ëìèøåìäêíåàìè ãà àõòóàêóðè àëíúàìàà.

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6. ûèðèçàãè ëèâìäáäáè6. ûèðèçàãè ëèâìäáäáè

6.1 äëîèðèóêè ëèâìäáäáè6.1 äëîèðèóêè ëèâìäáäáè

óëóøäåðíáèñ àâðäâèðäáóêè ãíìèñ ëàùåäìäáäêè ñàõàðçåäêíøè (àðàñðóêè ãàñàõëäáèñà ãà 1. ôàðóêè óëóøäåðíáèñ ùàçåêèç) 2015 üäêñ 25 îðíúäìòñ øäàãâäìãà. äñ ëàùåäìäáäêè 2009-2015 üêäáøè øäëúèðäáèñ òäìãäìúèèç þàñèàçãäáíãà, ðíëäêèú âàìñàéóçðäáèç 2014-2015 üêäáøè âàûêèäðãà; óëóøäåðíáèñ àâðäâèðäáóêè ãíìèñ 43 îðíúäìòè øñí-ñ éðèòäðèóëèç óëóøäåðäáèñàâàì 2. øäãâäáà, ãààþêíäáèç ëäñàëäãè - 32 îðíúäìòè - àðàñðóêè ãàñàõëäáèñ üèêàã ëíãèñ, þíêí ëäíçþäãè - 25 îðíúäìòè - ôàðóêè óëóøäåðíáèñ üèêàã;õàêàõèñà ãà ñíôêèñ óëóøäåðíáèñ àâðäâèðäáóê ëàùåäìäáêäáñ øíðèñ âàìñþåàåäáà èñäçè 3. àðñäáèçè àð àðèñ, ðíâíðú øñí-ñ éðèòäðèóëäáèç âàìñàæöåðóêè óëóøäåðíáèñ ãíìèñ øäëçþåäåàøèà; øñí-ñ éðèòäðèóëäáèç èãäìòèôèúèðäáóê óëóøäåàðçà øíðèñ 2015 üäêñ 38 îðíúäìòè 4. óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòè è÷í, 17 îðíúäìòè - ñàøóàêí ãíìèñ ñîäúèàêèñòè, þíêí 4 îðíúäìòè - ñàøóàêíæä ãàáàêè éåàêèôèéàúèèñ ñîäúèàêèñòè;ñäðòèôèúèðäáóêè îðíôäñèäáèñ âàëñþåèêäáóê ÿâóôäáøè óëóøäåàðçà âàìàüèêäáà èëàåä 5. ÿâóôäáøè ãàñàõëäáóêçà âàìàüèêäáèñ ñòðóõòóðèñ ëñâàåñèà: éíðäêàúèèñ éíäôèúèäìòè çèçõëèñ 1-èñ òíêèà, ðàú èëàñ ìèøìàåñ, ðíë ãèîêíëèñ ëèþäãåèç îðíôäñèàñ ãàñàõëäáàæä âàãàëü÷åäòè æäâàåêäìà àð àõåñ;ãàñàõëäáóêçà ãà óëóøäåàðçà éåàêèôèéàúèóðè ñòðóõòóðà ISCO-ñ íðìèøìà éíãäáèñ 6. ëèþäãåèçàú èãäìòóðèà: éíðäêàúèèñ éíäôèúèäìòè àõàú çèçõëèñ 1-èñ òíêèà. àöñàìèøìàåèà, ðíë 2009-2015 üêäáøè éíðäêàúèèñ éíäôèúèäìòè æðãèñ òäìãäìúèàñ àåêäìãà, àìó ãàñàõëäáóêçà ãà óëóøäåàðçà ñòðóõòóðà óôðí ãà óôðí ëñâàåñè þãäáà;øñí-ñ éðèòäðèóëèç, óëóøäåðíáèñ ãíìä óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòäáñ øíðèñ 7. 2015 üäêñ 20.8 îðíúäìòèç àöäëàòäáíãà óëóøäåðíáèñ ñàøóàêí ãíìäñ. âàìñþåàåäáèñ åäõòíðè àìàêíâèóðè è÷í 2009-2015 üêäáøèú. óëóøäåðíáèñ ãíìä ñàøóàêíæä çèçõëèñ íðÿäð ãàáàêèà ãàáàêè éåàêèôèéàúèèñ ñîäúèàêèñòäáñ øíðèñ, àñäåä ãàáàêèà èâè îðíôäñèèñ àðëõíìäçà øíðèñ;2015 üäêñ øñí-ñ éðèòäðèóëäáèç èãäìòèôèúèðäáóê óëóøäåðäáèñ 48 îðíúäìòè þàìëíéêä 8. óëóøäåðäáè è÷åìäì, þíêí 52 îðíúäìòè - þàìâðûêèåè óëóøäåðäáè. 2009-2015 üêäáøè þàìâðûêèåíáèñ ìèøìèç óëóøäåðíáèñ âàìàüèêäáà àðñäáèçàã àð øäúåêèêà;2015 üäêñ ëçêèàìè ãàñàõëäáèñ çèçõëèñ ìàþäåàðè - 48.4 îðíúäìòè - ñíôêèñ ëäóðìäíáàøè 9. çåèçãàñàõëäáèñ üèêàã ëíãèñ. äñ ëàùåäìäáäêè 2009-2015 üêäáøè øäëúèðäáèñ òäìãäìúèèç þàñèàçãäáíãà, ðèñ øäãäâàãàú îèðåäêàã áíêí 25 üêèñ ëàìûèêæä èâè 50 îðíúäìòñ ùàëíñúãà;ãàñàõëäáèñ ñòðóõòóðàøè øäëãäâè üíìàãè éíëîíìäìòèà åàýðíáà ãà ñà÷íôàúþíåðäáí 10. ëíëñàþóðäáà, ðíëêèñ þåäãðèçè üíìà ëçäêè ñàéåêäåè îäðèíãèñ âàìëàåêíáàøè 10 îðíúäìòèñ ëàþêíáêíáàøè è÷í;øèìàëäóðìäíáäáèñ èìòäâðèðäáóêè âàëíéåêäåèñ ëíìàúäëäáèç, äéíìíëèéèñ ðäàêóð 11. ñäõòíðøè (àâðàðóêè ñäõòíðèñ âàðäøä) ãàñàõëäáèñ þåäãðèçè üíìà ëçêèàìè ãàñàõëäáèñ 10.6 îðíúäìòèà. äñ ëàùåäìäáäêè 2009-2015 üêäáøè óúåêäêèà. ëíëñàþóðäáèñ ñäõòíðøè ãàñàõëäáèñ þåäãðèçè üíìà 2015 üäêñ 41.0 îðíúäìòè è÷í. 2009-2015 üêäáøè èâè æðãèñ òäìãäìúèèç âàëíèðùäíãà;2015 üêèñ ëãâíëàðäíáèç, ñàëóøàí àãâèêäáèñ 53 îðíúäìòè ñòèõèóðàã è÷í øäõëìèêè, 27 12. îðíúäìòè - éäðûí ñäõòíðèñ ëèäð è÷í âäìäðèðäáóêè, 15 îðíúäìòè - ñàþäêëüèôíñ ëèäð, þíêí 4 îðíúäìòè - ñàéóçàð óìàðäáæä ãà÷ðãìíáèç;2009-2015 üêäáøè ñàéëàíã ëéàôèíãàà ùàëí÷àêèáäáóêè ñòèõèóðàã øäõëìèêè ñàëóøàí 13. àãâèêäáèñ þåäãðèçè üíìèñ øäëúèðäáà ãà éäðûí ñäõòíðèñ ëèäð âäìäðèðäáóêè ñàëóøàí àãâèêäáèñ þåäãðèçè üíìèñ æðãà. àëàåä ãðíñ, øäèìèøìäáà ñàþäêëüèôíñ ëèäð øäõëìèêè ñàëóøàí àãâèêäáèñ þåäãðèçè üíìèñ ñóñòàã âàëíþàòóêè éêäáà ãà ñàéóçàð óìàðäáæä ãà÷ðãìíáèç øäõëìèêè ñàëóøàí àãâèêäáèñ þåäãðèçè üíìèñ ñòàáèêóðíáà;óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòäáèñ þåäãðèçè üíìà þàìâðûêèå óëóøäåðäáøè 32 14.

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îðíúäìòèç àöäëàòäáà ëàçñàåä üíìàñ äéíìíëèéóðàã àõòèóð ëíñàþêäíáàøè àìó óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòñ þàìâðûêèåàã óëóøäåðèñ „ñòàòóñèñ“ ëíîíåäáèñ ñàøóàêíæä 32 îðíúäìòèç óôðí ëàöàêè øàìñè àõåñ. ãàáàêè éåàêèôèéàúèèñ îðíôäñèèñ øäëçþåäåàøè, àëèñ øàìñè ñàøóàêíæä 42 îðíúäìòèç ìàéêäáèà. ñàøóàêíæä 16 îðíúäìòèç ìàéêäáèà þàìâðûêèåè óëóøäåðíáèñ øàìñè îðíôäñèèñ àðõíìèñ øäëçþåäåàøè;ñòðóõòóðóêè óëóøäåðíáèñ éíìòäõñòøè þàìâðûêèå óëóøäåðíáàæä àðàìàéêäá 15. ëìèøåìäêíåàìèà „ãàóéëà÷íôèêäáäêè“ ãàñàõëäáóêäáèñ îðíáêäëà. äñ èñ àãàëèàìäáè àðèàì, ðíëäêçàú úäìæèç ëèöäáóêè éåàêèôèéàúèèç ñàëóøàí àãâèêè åäð ëèèöäñ ãà ãàçàìþëãìäì ñþåà àì óôðí ãàáàêè éåàêèôèéàúèèñ ñàëóøàíñ. ôíðëàêóðàã èñèìè ãàñàõëäáóêìè àðèàì, ëàâðàë ôàõòíáðèåàã ëàç ñàëóøàí àð àéëà÷íôèêäáç. àëâåàðè ñòðóõòóðóêè óëóøäåðíáèñ ãíìä 2015 üäêñ 25.8 îðíúäìòè è÷í. 2009-1015 üêäáøè äñ ëàùåäìäáäêè øäëúèðäáèñ ñóñò òäìãäìúèàñ àåêäìãà; ôàðóêè ñòðóõòóðóêè óëóøäåðíáèñ ãíìä ÷åäêàæä ëàöàêè, ðíâíðú üäñè, îðíôäñèóêè 16. âàìàçêäáèñ ëõíìä ëíñàþêäíáàøèà - 58.2 îðíúäìòè. àñäåä ëàöàêèà äñ ëàùåäìäáäêè óëàöêäñè âàìàçêäáèñ ëõíìä ëíñàþêäíáàøè - 48.2 îðíúäìòè, ëàâðàë èâè àðñäáèçàã ùàëíðùäáà ñàøóàêí-ñîäúèàêóðè âàìàçêäáèñ ëõíìä ëíñàþêäíáàøè óëóøäåðíáèñ ãíìäñ. äñ èëàñ ìèøìàåñ, ðíë ñàøóàêí ñîäúèàêóðè âàìàçêäáà éåàêèôèéàúèèñ øäñàáàëèñè ãàñàõëäáèñ ûàêèàì ãàáàê øàìññ èûêäåà;óëóøäåðíáèñ àâðäâèðäáóê ãíìä ôàðóêè ñòðóõòóðóêè óëóøäåðíáèñ ùàçåêèç 17. îðíôäñèóêè âàìàçêäáèñ ëõíìä ëíñàþêäíáàøè ûàêèàì ëàöàê ìèøìóêæäà - çèçõëèñ 75 îðíúäìòè. ëàñæä àðñäáèçàã ãàáàêè, ëàâðàë æíâàãàã ëàèìú ûàêæä ëàöàêèà óëóøäåðíáèñ àâðäâèðäáóêè ãíìèñ ëàùåäìäáäêè óëàöêäñè âàìàçêäáèñ ëõíìä ëíñàþêäíáàøè - çèçõëèñ 63 îðíúäìòè;ôàðóêè ñòðóõòóðóêè óëóøäåðíáèñ ùàçåêèç óëóøäåðíáèñ àâðäâèðäáóêè ãíìèñ 18. ëàùåäìäáäêè 2009-2015 üêäáøè óúåêäêíáèñ òäìãäìúèèç âàëíèðùäåà;ISCO-ñ íðìèøìà éíãäáèñ ëèþäãåèç ãàñàõëäáóêçà âàìàüèêäáäáèñ øäãàðäáà àùåäìäáñ, ðíë 19. ñäðòèôèúèðäáóêè ãà ôàõòèóðè îðíôäñèäáèñ ëèþäãåèç ãàñàõëäáóêäáèñ âàìàüèêäáà îðàõòèéóêàã äðçëàìäççàì àð éíðäêèðäáñ: éíðäêàúèèñ éíäôèúèäìòè -0.0792-èà. äñ ìèøìàåñ, ðíë ñàâàìëàìàçêäáêí ãàüäñäáóêäáäáèñ ëèäð âàúäëóêè ñäðòèôèéàòäáèñ îðíôäñèóêè ñòðóõòóðà îðàõòèéóêàã àð àðèñ çàìþåäãðàøè øðíëèñ áàæðèñ ëíçþíåìèñ ñòðóõòóðàñçàì;çó ñäðòèôèúèðäáóêè ãà ôàõòèóðè îðíôäñèäáèñ ëèþäãåèç ãàñàõëäáóêçà âàìàüèêäáàñ 20. âàìåèþèêàåç ñàñíôêí çåèçãàñàõëäáóêäáèñ âàðäøä, éíðäêàúèèñ éíäôèúèäìòè àðñäáèçàã èæðãäáà, ëàâðàë ëèñè àáñíêóòóðè ëìèøåìäêíáà ëàèìú ûàêèàì ãàáàê ìèøìóêæä (0.2085) ðùäáà;ISCO-ñ íðìèøìà éíãäáèñ ãíìäæä ñäðòèôèúèðäáóêè îðíôäñèèñ øäñàáàëèñàã ãàñàõëäáóêçà 21. ëçêèàìè ðàíãäìíáèñ ëþíêíã 13.7 îðíúäìòèà ãàñàõëäáóêè, ðàú ûàêèàì ãàáàêè ëàùåäìäáäêèà;îðíôäñèèñ øäñàáàëèñàã ãàñàõëäáóêçà þåäãðèçè üíìà øäãàðäáèç ëàöàêèà àðàñàñíôêí 22. çåèçãàñàõëäáèñ øäëçþåäåàøè, ñàãàú äñ ëàùåäìäáäêè 17.2 îðíúäìòèñ ãíìäæäà àìó óôðí ëàöàêèà, åèãðä ñàøóàêí ëàùåäìäáäêè, çóëúà çàåèñçàåàã ëàèìú äðçíá ãàáàêèà;îðíôäñèèñ øäñàáàëèñàã ãàñàõëäáèñ ãíìä ÷åäêàæä ëàöàêè ãàõèðàåäáèç ãàñàõëäáóêäáñ 23. øíðèñàà - 27.6 îðíúäìòè, ðàú àñäåä ûàêèàì ãàáàêèà. 2009-2013 üêäáøè äñ ëàùåäìäáäêè øäëúèðäáèñ òäìãäìúèèç þàñèàçãäáíãà. 2014 üäêñ æðãèñ øäëãäâ, 2015 üäêñ èâè èñäå øäëúèðãà. àëèñ ëèæäæàã ñàáýíçà ëäëéåèãðäíáèñ ãàñàþäêäáà çàìãàçàì àæðñ ëíéêäáóêè þãäáà; ãàóñàõëäáäêçà ãààþêíäáèç 19 îðíúäìòè àõòèóðàã äûäáãà ñàëóøàíñ, þíêí ãààþêíäáèç 81 24. îðíúäìòè ñàëóøàíñ àð äûäáãà. ñàëóøàíñ ëàûèäáäêè ãàóñàõëäáäêè ëíõàêàõääáè, ûèðèçàãàã ãàõèðàåäáèç ãàñàõëäáàñ äûäáãìäì. ñàéóçàðè áèæìäñèñ üàëíü÷äáèñ âæèç ãàñàõëäáèñ âàåðúäêäáà ëèìèëàêóðèà;àâðäâèðäáóêè øäôàñäáäáèñ âàìàüèêäáà àùåäìäáñ, ðíë ñàõàðçåäêíøè øðíëèñ áàæàðè ëþíêíã 25. 20 îðíúäìòèçàà èìñòèòóúèíìàêèæäáóêè. àëãäìàã, ñàëóøàíñ ûäáìèñ ûèðèçàã ü÷àðíñ éåêàå ñíúèàêóðè éàîèòàêè (ìàúìíáäáè, ëäâíáðäáè, ìàçäñàåäáè) üàðëíàãâäìñ.

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6.2 çåèñíáðèåè ëèâìäáäáè6.2 çåèñíáðèåè ëèâìäáäáè

æäëíç ëíòàìèêè äëîèðèóêè àìàêèæèãàì âàëíèéåäçà çåèñíáðèåè þàñèàçèñ øäëãäâè ûèðèçàãè ëèâìäáäáè:

ñàõàðçåäêíñ øðíëèñ áàæàðæä âäìäðèðäáóêè ñàëóøàí àãâèêäáèñ óëäòäñíáà àð ëíèçþíåñ 26. ëàöàê éåàêèôèéàúèàñ. õåä÷ìèñ äéíìíëèéà óîèðàòäñàã ãàáàêè éåàêèôèéàúèèñ ñàëóøàí àãâèêäáñ õëìèñ, ðíëäêçà ãàéàåäáà ñîäúèàêóð âàìàçêäáàñ ûèðèçàãàã àð ñàýèðíäáñ;óëóøäåàðçà øíðèñ ÷åäêàæä ëñþåèê ÿâóôñ øäàãâäìãìäì èñ óëóøäåðäáè, ðíëäêçàú 27. ñäðòèôèúèðäáóêè îðíôäñèà àð âààùìèàç àìó îðíôäñèèñ àðëõíìäìè;þàìâðûêèåè óëóøäåðäáèñ ãèãè ìàüèêè (42 îðíúäìòè), óëàöêäñè éåàêèôèéàúèèñ 28. ñîäúèàêèñòäáè àðèàì. äñ òäìãäìúèà ëçäêè ñàéåêäåè îäðèíãèñ (2009-2015 üêäáè) ëàìûèêæäà øäìàðùóìäáóêè. ñàøóàêí ãà ãàáàêè éåàêèôèéàúèèñ ñîäúèàêèñòäáèñ þåäãðèçè üíìà þàìâðûêèå óëóøäåðäáøè øäãàðäáèç ãàáàêèà;ãàñàõëäáèñ ñòðóõòóðàøè áíêí 6 üêèñ ëàìûèêæä âàìåèçàðäáóêè îíæèòèóðè ëíåêäìäáè, 29. ðíëäêèú àâðàðóêè ãàñàõëäáèñ þåäãðèçè üíìèñ øäëúèðäáàøè âàëíèþàòà, ûèðèçàãàã ëíëñàþóðäáèñ ñôäðíøè ãàñàõëäáèñ þåäãðèçè üíìèñ æðãèç è÷í âàìîèðíáäáóêè. àöìèøìóêè îíæèòèåè äéíìíëèéèñ ðäàêóð ñäõòíðñ (àâðàðóêè ñäõòíðèñ âàðäøä) îðàõòèéóêàã àð øäþäáèà - ëèñè þåäãðèçè üíìà óúåêäêèà;èæðãäáà éäðûí ñäõòíðèñ þåäãðèçè üíìà ñàëóøàí àãâèêäáèñ âäìäðèðäáàøè, ðàú ûèðèçàãàã 30. ñòèõèóðàã øäõëìèêè ñàëóøàí àãâèêäáèñ þåäãðèçè üíìèñ øäëúèðäáèñ þàðÿæä þãäáà;ñäðòèôèúèðäáóêè îðíôäñèäáèñ ëèþäãåèç ãàñàõëäáóêçà ãà óëóøäåàðçà éíðäêàúèóðëà 31. àìàêèæëà àùåäìà, ðíë âàìàçêäáèñ ñèñòäëèãàì ëèöäáóêè âàìàçêäáèñ ãàëàãàñòóðäáäêè ñäðòèôèéàòè àð çàëàøíáñ ëìèøåìäêíåàì ðíêñ ñàëóøàí àãâèêèñ ëíûäáìàøè. ãèîêíëèñ ëèþäãåèç éåàêèôèéàúèàñçàì ôàõòèóðè ãàñàõëäáèñ øäñàáàëèñíáèñ àìàêèæè 32. àùåäìäáñ, ðíë ëèöäáóêè éåàêèôèéàúèèñ ëèþäãåèç ñàëóøàíñ îíåìà ñàõàðçåäêíøè äðçíá ðçóêèà, ðàú íðè ûèðèçàãè âàðäëíäáèç øäèûêäáà è÷íñ âàìîèðíáäáóêè:

ëèöäáóêè âàìàçêäáèñ úäìæè ãà ðäàêóðè úíãìà àð àðèñ äðçëàìäçèñ øäñàáàëèñè àìó a. àöäáóêè ãèîêíëè àð ìèøìàåñ ëèöäáóê úíãìàñ;

ñàâàìëàìàçêäáêí ãàüäñäáóêäáèñ ëèäð øäçàåàæäáóêè îðíôäñèäáèñ ñòðóõòóðà b. àúèêäáóêèà øðíëèñ áàæðèñ ëíçþíåìèñ ñòðóõòóðàñ àìó ñàâàìëàìàçêäáêí ãàüäñäáóêäáäáè àëæàãäáäì úäìæèñ ëèþäãåèç âàìàçêäáèñ ëõíìä, ëàâðàë ãàñàõëäáèñ ìàéêäáè îäðñîäõòèåèñ ëõíìä éàãðäáñ;

ñòðóõòóðóêè óëóøäåðíáèñ îàðàãèâëà ñàõàðçåäêíøè øäèûêäáà øäëãäâìàèðàã àöèüäðíñ: 33. äðçè ëþðèå, âàìàçêäáèñ ñèñòäëà àð àì åäð àëæàãäáñ øäñàáàëèñè (øðíëèñ áàæàðæä ëíçþíåìàãè) ñîäúèàêíáèñ (éåàêèôèéàúèèñ) éàãðäáñ; ëäíðä ëþðèå éè, âàìàçêäáèñ ñèñòäëà, ðíâíðú óëàöêäñè, èñä ñîäúèàêóðè, åäð èûêäåà øäñàáàëèñ úíãìàñ (éåàêèôèéàúèàñ) àìó âàìàçêäáèñ úäìæè ãà ëèñè ëôêíáäêèñ ôàõòíáðèåè úíãìà ãà øäûäìèêè óìàðäáè äðçëàìäçñ àð øääñàáàëäáà; âàìàçêäáèñ ñèñòäëèñ ëèäð ëíëæàãäáóêè éàãðäáè þàìâðûêèåè óëóøäåðíáèñ øäãäâàã éàðâàåäì éåàêèôèéàúèàñ, àì èûóêäáóêè àðèàì óôðí ãàáàêè éåàêèôèéàúèèñ ñàëóøàíæä èëóøàíì. ñàëóøàí ûàêèñ ãäéåàêèôèéàúèà ñàõàðçåäêíøè ñòðóõòóðóêè óëóøäåðíáèñ äðçäðçè ëçàåàðè óàð÷íôèçè øäãäâèà; „ãàóéëà÷íôèêäáäêè“ ãàñàõëäáóêäáèñ îðíáêäëà, ðíâíðú ñòðóõòóðóêè óëóøäåðíáèñ 34. âàëíåêèìäáà, ÷åäêàæä ëäòàã âàìàçêäáèñ ñèñòäëèñà ãà øðíëèñ áàæðèñ ãàáàêè éíìâðóäìòóêíáèñ øäãäâèà;ñàõàðçåäêíñ äéíìíëèéà åäð àþäðþäáñ ëàöàêè éåàêèôèéàúèèñ ñàëóøàí àãâèêäáèñ 35. âäìäðèðäáàñ. øäãäâàã, ðíâíðú ôàðóêè ãà ãàóéëà÷íôèêäáäêè ñòðóõòóðóêè óëóøäåðíáà, èñä øñí-èñ éðèòäðèóëèç âààìâàðèøäáóêè óëóøäåðíáà ÷åäêàæä ëàöàêè ñüíðäã âàìàçêäáèñ úäìæèñ ëèþäãåèç óëàöêäñè éåàêèôèéàúèèñ ëõíìä ñîäúèàêèñòäáñ øíðèñàà;àâðàðóêè ñäõòíðè ðùäáà ãàáàêè éåàêèôèéàúèèñ ëóøàþäêèñ àáñíðáäìòàã: ñüíðäã äñ 36. ñäõòíðè ,,èüíåñ“ ñàëóøàí ûàêèñ èë ìàüèêñ, ðíëäêëàú åäðàìàèðè ñàëóøàíñ îíåìà åäð øäûêí;éäðûí ñäõòíðèñ þåäãðèçè üíìà ñàëóøàí àãâèêäáèñ âäìäðèðäáàøè àðñäáèçàã èæðãäáà, ðàú 37. óãàåíã ãàãäáèçè òäìãäìúèàà, çóëúà ëèñè ãèìàëèéà àðàãàëàéëà÷íôèêäáäêèà ãà æðãèñ éèãäå ãèãè îíòäìúèàêè âààùìèà;

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ñàñíôêí çåèçãàñàõëäáèñ þåäãðèçè üíìà ëçêèàì ãàñàõëäáàøè ëúèðãäáà, ðàú àñäåä ãàãäáèçè 38. òäìãäìúèàà, ëàâðàë ëèñè òäëîèú àð àðèñ èñäçè ëàöàêè, ðíë ëìèøåìäêíåàìè ûåðäáè âàëíèüåèíñ ñàõàðçåäêíøè ãàñàõëäáèñ ñòðóõòóðàøè;ôàðóêè ñòðóõòóðóêè óëóøäåðíáèñ ãíìä àðñäáèçàã ëàöàêèà îðíôäñèóêè âàìàçêäáèñ 39. ëõíìäçà ÿâóôøè. àñäçè éêàñèñ ñäðòèôèúèðäáóê ñîäúèàêèñòäáñ, ðíâíú üäñè, üàðëàòäáèç àìàúåêäáäì îðíôäñèèñ àðëõíìä, ëàâðàë ñàëóøàíñ óôðí àõòèóðè ëàûèäáêäáè;ñàëóøàí àãâèêèñ ûäáìèñ èìñòèòóúèíìàêèæàúèèñ þàðèñþè ñàõàðçåäêíøè óéèãóðäñàã 40. ãàáàêèà àìó ñàëóøàíñ ûäáìàøè üàë÷åàìè ðíêè èñäå ãà èñäå ìàúìíáäáñ, ëäâíáðäáñ ãà ìàçäñàåäáñ äìèýäáàç. ñàëóøàíñ ûäáìèñ âæäáèñ óîèðàòäñàã àðàèìñòèòóúèíìàêóðè þàñèàçè, ðíëäêèú 41. üêäáèñ âàìëàåêíáàøè àð èúåêäáà, øðíëèñ áàæàðæä ëíçþíåìà-ëèüíãäáèñ ëäõàìèæëèñ àðàñðóê÷íôèêäáàæä ëèóçèçäáñ.

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7. ðäéíëäìãàúèäáè7. ðäéíëäìãàúèäáèéåêäåèñ øäãäâàã ëèöäáóêè çåèñíáðèåè ëèâìäáäáèñ ñàôóûåäêæä øäåèëóøàåäç øäëãäâè

ðäéíëäìãàúèäáè:óëóøäåðíáèñ ñòðóõòóðèñ ñèöðëèñäóêè òäìãäìúèäáèñ âàëíñàåêäìàã àóúèêäáäêèà 1. øèìàëäóðìäíáàçà èìòäâðèðäáóêè âàëíéåêäåäáèñ ëíìàúäëçà áàæäáèñ ðäâóêàðóêè éíëîêäõñóðè àìàêèæè; óëóøäåðíáèñ óôðí ñðóê÷íôèêè éåêäåèñà ãà ãàñàõëäáèñ óôðí õëäãèçè îíêèòèéèñ 2. øäëóøàåäáèñ ëèæìèç ñàýèðíã ëèâåàùìèà óëóøäåðíáèñ ãíìèñ, ðíâíðú øñí-èñ éðèòäðèóëäáèç, èñä àâðäâèðäáóêè ëàùåäìäáêèç âààìâàðèøäáà, ðíëäêèú ëíèúàåñ àñäåä ôàðóê óëóøäåðíáàñ ãà àðàñðóê ãàñàõëäáàñ;ãàñàõëäáèñ äôäõòèàìè îíêèòèéèñ øäëóøàåäáèñàçåèñ ñàýèðíà óëóøäåàðçà ãà åàéàìñèäáèñ 3. ðäâóêàðóêè ðäâèñòðàúèèñ ñèñòäëèñ ùàëí÷àêèáäáà;óìãà ãàèü÷íñ ñòðóõòóðóêè óëóøäåðíáèñ ëñíôêèí îðàõòèéàøè âàëí÷äìäáóêè 4. èìãèéàòíðäáèñ âààìâàðèøäáà, ëàç øíðèñ, áäåäðèÿèñ ëðóãèñ àâäáà; èëèñ âàçåàêèñüèìäáèç, ðíë ñàõàðçåäêíñ äéíìíëèéà óîèðàòäñàã ãàáàêè éåàêèôèéàúèèñ 5. ñàëóøàí àãâèêäáñ õëìèñ, ëèæàìøäüíìèêàã åçåêèç ãàùõàðãäñ ëóøàíáà õåä÷ìèñ èìãóñòðèóê îíêèòèéàæä, ðíëäêëàú óìãà âàìñàæöåðíñ ñàõàðçåäêíøè úíãìàæä ãàôóûìäáóê éíìéóðäìòóê äéíìíëèéàæä âàãàñåêèñ âæäáè;ðàëãäìàãàú óëóøäåàðçà øíðèñ ÷åäêàæä ëñþåèê ÿâóôñ îðíôäñèèñ àðëõíìäìè øäàãâäìäì, 6. ñàýèðíã ëèâåàùìèà ùàëí÷àêèáãäñ ñèñòäëà, ðíëäêèú óæðóìåäê÷íôñ îðíôäñèèñ àðëõíìäçà ëèäð ëíçþíåìàãè ñäðòèôèúèðäáóêè îðíôäñèäáèñ ãàóôêäáàñ;èëèñ âàçåàêèñüèìäáèç, ðíë þàìâðûêèåè óëóøäåðäáèñ óëäòäñíáà óëàöêäñè éåàêèôèéàúèèñ 7. óëóøäåðäáè àðèàì, ëèæàìøäüíìèêèà øðíëèñ áàæàðæä óëàöêäñè éåàêèôèéàúèèñ ëíçþíåìàãè îðíôäñèäáèñ îäðèíãóêè éåêäåà, ëèñè øäãäâäáèñ øäñàáàëèñè ñàâàìëàìàçêäáêí ãàüäñäáóêäáàçàçåèñ ðäâóêàðóêàã âàúìíáà ãà ëþäãåäêíáàøè ëèöäáà ñàâàìëàìàçêäáêí îðíâðàëäáèñ àéðäãèòàúèèñ ãðíñ;ðàëãäìàãàú äéíìíëèéèñ ðäàêóðè ñäõòíðèñ (àâðàðóêèñ âàðãà) þåäãðèçè üíìà ëçêèàì 8. ãàñàõëäáàøè àð èæðãäáà, àóúèêäáäêèà àë ñäõòíðøè ëúèðä ãà ñàøóàêí áèæìäñèñ ëþàðãàýäðèñ óôðí õëäãèçè îíêèòèéèñ âàòàðäáà, âàìñàéóçðäáèç ôèìàìñäáèñ üåãíëèñ þäêøäü÷íáèñ ëèëàðçóêäáèç;ñàëóøàí àãâèêäáèñ âäìäðèðäáàøè éäðûí ñäõòíðèñ þåäãðèçè üíìèñ ëìèøåìäêíåìàã âàæðãèñ 9. ëèæìèç ñàýèðíã ëèâåàùìèà øäëóøàåãäñ ñàëóøàí àãâèêäáèñ øäõëìèñàçåèñ éäðûí ñäõòíðèñ ñàüàðëíçà ðíâíðú ëíðàêóðè, èñä ôèìàìñóðè (ôèñéàêóðè) ñòèëóêèðäáèñ ëäõàìèæëè;ëèöäáóêè âàìàçêäáèñ úäìæèñà ãà ðäàêóðè úíãìèñ øäñàáàëèñíáèñ óæðóìåäêñà÷íôàã 10. àóúèêäáäêèà øäëãâíëè ìàáèÿäáèñ âàãàãâëà óëàöêäñè ãà îðíôäñèóêè âàìàçêäáèñ þàðèñþèñ ëàðçåèñ äôäõòèàìíáèñ àñàëàöêäáêàã;ñàâàìëàìàçêäáêí ãàüäñäáóêäáäáèñ ëèäð øäçàåàæäáóêè îðíôäñèäáèñ ñòðóõòóðà 11. øäñàáàëèñíáàøè óìãà ëíåèãäñ øðíëèñ áàæðèñ ëíçþíåìèñ ñòðóõòóðàñçàì, ðèñçåèñàú ñàýèðíà îèðãàîèðè óðçèäðçíáäáèñ âàìåèçàðäáà, äðçè ëþðèå, ñàâàìëàìàçêäáêí ãàüäñäáóêäáäáñà ãà, ëäíðä ëþðèå, óøóàêíã ãàëñàõëäáêäáñ, ëàç àñíúèàúèäáñ àì üàë÷åàì HR éíëîàìèäáñ øíðèñ;þàìâðûêèåè óëóøäåðíáèñ âàëí ñàëóøàí ûàêèñ ãäéåàêèôèéàúèèñ çàåèãàì àñàúèêäáêàã 12. àóúèêäáäêèà þàìâðûêèåàã óëóøäåðäáèñ àöðèúþåèñ ãà ãèàâìíñòèéèñ ãà ëàçè îðíôäñèóêè ðäàáèêèòàúèèñ àì âàãàëæàãäáèñ õëäãèçè ñèñòäëèñ ãàëéåèãðäáà;âàìàçêäáèñ ñèñòäëèñà ãà øðíëèñ áàæðèñ óðçèäðççàåñäáàãíáèñ âàæðãèñ ëèæìèç 13. ëèæàìøäüíìèêàã ëèâåàùìèà îðíôèêóðè ñàâàìëàìàçêäáêí îðíâðàëäáèñ àéðäãèòàúèèñ îðíúäñøè ëñþåèêè ãàëñàõëäáêäáèñ, ëàçè àñíúèàúèäáèñ ãà øäñàáàëèñè éíëîäòäìúèèñ ëõíìä HR éíëîàìèäáèñ üàðëíëàãâäìäêçà ùàðçåà;ëçêèàì ãàñàõëäáàøè ñàñíôêí çåèçãàñàõëäáèñ þåäãðèçè üíìèñ øäëãâíëè, óéåä àðñäáèçè 14. øäëúèðäáèñàçåèñ àóúèêäáäêèà ãàùõàðãäñ éííîäðàúèèñ âæèç àâðàðóêè ëäóðìäíáäáèñ âàëñþåèêäáà (éíìúäìòðàúèà), àâðíéêàñòäðäáèñ ùàëí÷àêèáäáà ãà àëèñ áàæàæä óàþêäñè àâðàðóêè òäõìíêíâèäáèñ âàëí÷äìäáà;èëèñ âàçåàêèñüèìäáèç, ðíë ôàðóêè ñòðóõòóðóêè óëóøäåðíáèñ ãíìä àðñäáèçàã 15.

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ëàöàêèà îðíôäñèóêè âàìàçêäáèñ ëõíìäçà ÿâóôøè, ëèæàìøäüíìèêàã ëèâåàùìèà àë òèîèñ ñàâàìëàìàçêäáêí ãàüäñäáóêäáäáèñ îðíâðàëäáèñ âàãàþäãåà øðíëèñ áàæðèñ ëíçþíåìàñçàì çàåñäáàãíáèñ éóçþèç ãà éóðñãàëçàåðäáóêçà ãàñàõëäáèñ ëèæìíáðèåè îðíâðàëäáèñ øäëóøàåäáà;ñàëóøàí àãâèêäáèñ ûäáìèñ èìñòèòóúèíìàêèæàúèèñ þàðèñþèñ àñàëàöêäáêàã ñàéëàðèñè àð 16. àðèñ èìòäðìäò-îíðòàêäáèñ øäõëìà, ãàñàõëäáèñ ôíðóëäáèñà ãà éåèðäóêäáèñ ðäâóêàðóêàã íðâàìèæäáà. ñàýèðíà ãàñàõëäáèñ þäêøäü÷íáèñ úäìòðäáèñ õñäêèñ øäõëìèñ ãàùõàðäáà, ðàñàú èçåàêèñüèìäáñ éèãäú øðíëèñ áàæðèñ ôíðëèðäáèñ ñàþäêëüèôí ñòðàòäâèà.ãàñàõëäáèñ îíêèòèéèñ ôàðâêäáøè øäëóøàåäáóêè îðíâðàëäáèñ äôäõòèàìíáèñ óæðóìåäê÷íôèñ 17. ëèæìèç àóúèêäáêàã ëèâåàùìèà æíëåàã èìãèéàòíðçà áàãäæä ãàôóûìäáóêè ëíìèòíðèìâèñà ãà øäôàñäáèñ éíëîêäõñóðè ñèñòäëèñ ùàëí÷àêèáäáà.

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8. øðíëèñ áàæðèñ âàìåèçàðäáèñ ñúäìàðäáè8. øðíëèñ áàæðèñ âàìåèçàðäáèñ ñúäìàðäáèóëóøäåðíáà ñèñòäëóðè îðíáêäëàà ãà ëèñè ãíìèñ øäëúèðäáà éíëîêäõñóðè öíìèñûèäáäáèñ

âàòàðäáàñ ëíèçþíåñ. üèìàëãäáàðä ëíãäêñ åäð äõìäáà ëàöàêè ñèæóñòèñ îðäòäìæèà, åèìàèãàì æóñòè ëíãäêèñ øäëóøàåäáà ëàùåäìäáäêçà ûàêæä ôàðçí üðäñ ñàýèðíäáñ. âàðãà àëèñà, àóúèêäáäêèà ëíãäêèç âàçåàêèñüèìäáóê ëíçàëàøääáçàì ëýèãðí çàìàëøðíëêíáà, íðâàìèæàúèóêè ñòðóõòóðèñà ãà øäñàûêäáêíáäáèñ àìàêèæè. àóúèêäáäêèà àâðäçåä óü÷äáðèåè ñòàòèñòèéèñ èìôíðëàúèóêè ëàñèåäáèñ øäñüàåêà ãà èìôíðëàúèóêè ìàéàãäáèñ àìàêèæè.

üèìàëãäáàðä ëíãäêè äôóûìäáà éåêäåèñ øäãäâäáèç ãàãâäìèê øäëãäâ ñàë âàðäëíäáàñ: ñäðçèôèúèðäáóê îðíôäñèàæä óôðí ãàáàêè éåàêèôèéàúèèç ãàñàõëäáóêäáèñ ëàöàêè •

þåäãðèçè üíìà ëçêèàì ãàñàõëäáàøè;ñäðçèôèúèðäáóêè îðíôäñèèñ àðëõíìä ñàëóøàí ûàêèñ ëàöàêè þåäãðèçè üíìà äéíìíëèéóðàã •

àõòèóð ëíñàþêäíáàøè;ñíôêèñ ëäóðìäíáàøè çåèçãàñàõëäáèñ àëíðôóêàã ëàöàêè þåäãðèçè üíìà ëçêèàì •

ãàñàõëäáàøè.âàëíéåäçèêè îðíáêäëäáèãàì ñäðçèôèúèðäáóêè îðíôäñèèñ àðëõíìäçà ãà ñíôêèñ

ëäóðìäíáàøè çåèçãàñàõëäáóêçà ÿâóôè àðñäáèçàã çàìàéåäçàãèà.õåäëíç ëíúäëóêè øðíëèñ áàæðèñ øäëãâíëè âàìåèçàðäáèñ ñàëè ñúäìàðè âóêèñþëíáñ

æäëíàöìèøìóêè ñàëè ëñþåèêè îðíáêäëèñ ëàñøòàáäáèñ øäëúèðäáàñ. äñ éè çàåèñ ëþðèå, øäèûêäáà ìèøìàåãäñ:

îðíôäñèèñ àðëõíìäçà âàãàëæàãäáàñ ãà ëàç ëèäð øðíëèñ áàæàðæä ëíçþíåìàãè ñîäúèàêíáäáèñ • ãàóôêäáàñ, ðàñàú èçåàêèñüèìäáñ ëä-6, ëä-10, ëä-11, ëä-13ãà ëä-15 ðäéíëäìãàúèäáè;

ñþåà çàìàáàð îèðíáäáøè ñàþäêëüèôíñ ëèäð õëäãèçè îíêèòèéèñ âàòàðäáàñ äéíìíëèéèñ • ðäàêóð ñäõòíðøè ñàýèðí îðíôäñèäáæä øðíëèñ áàæðèñ ëíçþíåìèñ âàæðãèñ ëèæìèç, ðàñàú âóêèñþëíáñ ëä-5, ëä-8 ãà ëä-9 ðäéíëäìãàúèäáè;

ñíôêèñ ëäóðìäíáàøè çåèçãàñàõëäáèñ àëíðôóêàã ëàöàêè þåäãðèçè üíìèñ øäëúèðäáàñ, • ðàñàú óéàåøèðãäáà ëä-14-ä ðäéíëäìãàúèà.

æäëíçõëóêèãàì âàëíëãèìàðä, âàìèþèêäáà øäëãäâè ñàëè ñúäìàðè:ñúäìàðè 1: âàìàçêäáèñ ãà ëäúìèäðäáèñ ñàëèìèñòðí èçåàêèñüèìäáñ éåêäåèñ øäãäâäáñ, ëàâðàë

îðíôäñèóêè ãà óëàöêäñè âàìàçêäáèñ ñòðàòäâèäáèñ ñðóê÷íôàñ ûèðèçàãàã ãàëíóéèãäáêàã àþíðúèäêäáñ, äéíìíëèéèñ ãà ëãâðàãè âàìåèçàðäáèñ, ñíôêèñ ëäóðìäíáèñà ãà øðíëèñ, ÿàìëðçäêíáèñ ãà ñíúèàêóðè ãàúåèñ ñàëèìèñòðíäáèñ àõòèóðè ùàðçóêíáèñ âàðäøä, ðèñ âàëíú åäð þäðþãäáà øðíëèñ áàæðèñ ëíñàêíãìäêè ëíçþíåìäáèñ ñðóê÷íôèêè âàçåàêèñüèìäáà. àñäç øäëçþåäåàøè:

îðíôäñèóêè âàìàçêäáèñ ôàðâêäáøè âàãàëæàãäáóê ñàëóøàí ûàêàñ ãàñàõëäáèñ ëþíêíã • 24-îðíúäìòèàìè øàìñè äõìäáà (îðíôäñèóêè âàìàçêäáèñ ëõíìäçà øíðèñ óëóøäåðíáèñ ñàøóàêíã 76-îðíúäìòèàìè ãíìèñ âàçåàêèñüèìäáèç);

óëàöêäñè ñàâàìëàìàçêäáêí ãàüäñäáóêäáäáèñ éóðñãàëçàåðäáóêäáñ éè ãàñàõëäáèñ 34-• îðíúäìòèàìè øàìñè øäèûêäáà ëèäúäç;

çó îðíôäñèóêè âàìàçêäáèñ ñòðàòäâèà ëþíêíã âàãàëæàãäáèñ àëíúàìàñ ãàèñàþàåñ • ãà àð ëíèúàåñ ñàøóàêí ñéíêäáèñ ãàëàëçàåðäáäêè éêàñäáèñ ëíñüàåêäçà îðíôäñèóê íðèäìòàúèàñ, îíòäìúèóð ñàëóøàí ûàêàñ ÷íåäêüêèóðàã ãààþêíäáèç 80 àçàñàëãä11 îðíôäñèèñ àðëõíìä øäèûêäáà øääëàòíñ, ðíëäêçàâàì àðñäáóêè îðíîíðúèäáèñ çàìàþëàã, ãààþêíäáèç 60 àçàñè ñàëóøàíñ ãàëàòäáèçè ëàûèäáäêè èõìäáà.

îèðåäêè ñúäìàðèñ âàìþíðúèäêäáèñ ëíñàêíãìäêè øäãäâèñ óéäç èêóñòðèðäáèñ ëèæìèç øäèûêäáà íðè åàðèàìòèñ âàìþèêåà: îèðåäêè èçåàêèñüèìäáñ üêèñ âàìëàåêíáàøè ãààþêíäáèç 30 àçàñè àãàëèàìèñ îðíôäñèóê âàãàëæàãäáàñ óëàöêäñè âàìàçêäáèñ ñòðàòäâèèñ óúåêäêíáèñ îèðíáäáøè, þíêí ëäíðä - üêèñ âàìëàåêíáàøè ãààþêíäáèç 30 àçàñè àãàëèàìèñ îðíôäñèóê âàãàëæàãäáàñ ãà óëàöêäñè âàìàçêäáèñ øðíëèñ áàæàðæä íðèäìòèðäáóêè ñòðàòäâèèñ øäëóøàåäáàñ ñþåà ñàþäêëüèôí ñòðóõòóðäáèñàâàì ãàëíóéèãäáêàã.

11 ñòàòèñòèéèñ ñàëñàþóðèñ åäáñàèòæä âàìçàåñäáóêè âàìàçêäáèñ óü÷äáðèåè ñòàòèñòèéèñ ëíìàúäëäáèñ ëèþäãåèç.

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უმუშევრობის აგრეგირებული დონის სავარაუდო ცვლილების ვექტორიI სცენარის განხორციელების შემთხვევაში

ვარიანტი 1 ვარიანტი 2

ñúäìàðè 2: äéíìíëèéèñ ãà ëãâðàãè âàìåèçàðäáèñ ñàëèìèñòðí èçåàêèñüèìäáñ éåêäåèñ øäãäâäáñ ãà àûêèäðäáñ äéíìíëèéèñ ðäàêóðè ñäõòíðøè ëúèðä ãà ñàøóàêí ëäüàðëäíáèñ æðãàæä íðèäìòèðäáóê îíêèòèéàñ, èëàåãðíóêàã ñíôêèñ ëäóðìäíáèñ ñàëèìèñòðí ààõòèóðäáñ éííîäðèðäáèñ âæèç àâðàðóêè ëäóðìäíáäáèñ éíìúäìòðàúèèñ ãà ëàçè îðíãóõòèóêíáèñ æðãèñ þäêøäü÷íáàñ, âàìàçêäáèñ ãà ëäúìèäðäáèñ ñàëèìèñòðí éè àë ñòðàòäâèäáèñ âàçåàêèñüèìäáèç óæðóìåäê÷íôñ ñàøóàêí ñîäúèàêóðè, îðíôäñèóêè ãà óëàöêäñè âàìàçêäáèñ ñòðàòäâèäáèñ12 øðíëèñ áàæðèñ ëíçþíåìäáçàì çàåñäáàãíáàñ. àëàåä ãðíñ, øðíëèñ áàæðèñ èìñòèòóúèíìàêèæàúèèñ þàðèñþè éåêàå ãàáàêèà àìó ëíëæàãäáóêè ñàëóøàí ûàêèñà ãà âàëíúþàãäáóêè åàéàìñèäáèñ øäþåäãðèñ àãâèêè àð àðèñ èìñòèòóúèíìàêèæäáóêè. àñäç øäëçþåäåàøè:

ñàëóøàíñ èìñòèòóúèóðàã ëàûèäáäêè âàãàëæàãäáóêè ãà óëàöêäñè ñàñüàåêäáêäáèñ • éóðñãàëçàåðäáóêè ñàëóøàí ûàêèñ 20 îðíúäìòñ ãàñàõëäáèñ ûàêèàì ëàöàêè øàìñè àõåñ, þíêí ãàðùäìèêè 80 îðíúäìòèñàçåèñ ãàñàõëäáèñ øàìñè èñäçèåä ðùäáà, ðíâíðú 1-êè ñúäìàðèñ øäëçþåäåàøè;

àë ñúäìàðèñ âàìþíðúèäêäáèñ ëíñàêíãìäêè øäãäâèñ óéäç èêóñòðèðäáèñ ëèæìèç âàìèþèêäáà íðè åàðèàìòè: îèðåäêè èçåàêèñüèìäáñ üêèñ âàìëàåêíáàøè ãààþêíäáèç 30 àçàñè àãàëèàìèñ îðíôäñèóê âàãàëæàãäáàñ óëàöêäñè âàìàçêäáèñ ñòðàòäâèèñ óúåêäêíáèñ îèðíáäáøè, þíêí ëäíðä - üêèñ âàìëàåêíáàøè àñäåä ãààþêíäáèç 30 àçàñè àãàëèàìèñ îðíôäñèóê âàãàëæàãäáàñ ãà óëàöêäñè âàìàçêäáèñ øðíëèñ áàæàðæä íðèäìòèðäáóêè ñòðàòäâèèñ øäëóøàåäáàñ.

12 àë ñúäìàðøèú îðíôäñèóêè âàìàçêäáèç ëíúóêè óìãà è÷íñ, ðíâíðú æðãàñðóêè ëíñàþêäíáà èñä ãàëàëçàåðäáäêè éêàñäáèñ ëíñüàåêääáèú.

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უმუშევრობის აგრეგირებული დონის სავარაუდო ცვლილების ვექტორიII სცენარის განხორციელების შემთხვევაში


ñúäìàðè 3: äéíìíëèéèñ ãà ëãâðàãè âàìåèçàðäáèñ ñàëèìèñòðí èçåàêèñüèìäáñ éåêäåèñ øäãäâäáñ ãà àûêèäðäáñ äéíìíëèéèñ ðäàêóðè ñäõòíðøè ëúèðä ãà ñàøóàêí ëäüàðëäíáèñ æðãàæä íðèäìòèðäáóê îíêèòèéàñ. èëàåãðíóêàã, ñíôêèñ ëäóðìäíáèñ ñàëèìèñòðí ààõòèóðäáñ éííîäðèðäáèñ âæèç àâðàðóêè ëäóðìäíáäáèñ éíìúäìòðàúèèñ ãà ëàçè îðíãóõòèóêíáèñ æðãèñ þäêøäü÷íáàñ, âàìàçêäáèñ ãà ëäúìèäðäáèñ ñàëèìèñòðí àë ñòðàòäâèäáèñ âàçåàêèñüèìäáèç óæðóìåäê÷íôñ ñàøóàêí ñîäúèàêóðè, îðíôäñèóêè ãà óëàöêäñè âàìàçêäáèñ ñòðàòäâèäáèñ13 øðíëèñ áàæðèñ ëíçþíåìäáçàì çàåñäáàãíáàñ, øðíëèñ ÿàìëðçäêíáèñà ãà ñíúèàêóðè ãàúåèñ ñàëèìèñòðí éè óæðóìåäê÷íôñ øðíëèñ áàæðèñ èìñòèòóúèíìàêèæàúèèñ þàðèñþèñ ëéåäçð àëàöêäáàñ. àñäç øäëçþåäåàøè:

àðñäáèçàã âàèæðãäáà âàãàëæàãäáóêè ãà óëàöêäñè ñàñüàåêäáêäáèñ éóðñãàëçàåðäáóêè • ñàëóøàíñ èìñòèòóúèóðàã ëàûèäáäêçà þåäãðè üíìà, ðíëäêçàú ãàñàõëäáèñ ûàêèàì ëàöàêè øàìñè äõìäáàç, þíêí âàðéåäóêè ìàüèêè èñäå âààâðûäêäáñ ñàëóøàíñ àðàèìñòèòóúèóðàã ûäáìàñ. àë îðíîíðúèèñ æóñòè îðíâìíæèðäáà ûàêèàì ðçóêèà. çó îàðäòíñ îðèìúèîèç åèñàðâäáêäáç, ëàì øäèûêäáà øäàãâèìíñ 80:20. ñþåàâåàðàã ðíë åçõåàç, ñàëóøàíñ èìñòèòóúèóðàã ëàûèäáäêçà þåäãðèçè üíìà 80 îðíúäìòàëãä âàèæðãäáà, àðàèìñòèòóúèóðàã ëàûèäáêäáèñ þåäãðèçè üíìà éè 20 îðíúäìòàëãä øäëúèðãäáà.

ðíâíðú üèìà ñúäìàðäáøè àë ñúäìàðèñ âàìþíðúèäêäáèñ ëíñàêíãìäêè øäãäâèñ óéäç èêóñòðèðäáèñ ëèæìèç âàìèþèêäáà íðè åàðèàìòè: îèðåäêè èçåàêèñüèìäáñ üêèñ âàìëàåêíáàøè ãààþêíäáèç 30 àçàñè àãàëèàìèñ îðíôäñèóê âàãàëæàãäáàñ óëàöêäñè âàìàçêäáèñ ñòðàòäâèèñ óúåêäêíáèñ îèðíáäáøè, þíêí ëäíðä - üêèñ âàìëàåêíáàøè ãààþêíäáèç 30 àçàñè àãàëèàìèñ îðíôäñèóê âàãàëæàãäáàñ ãà óëàöêäñè âàìàçêäáèñ øðíëèñ áàæàðæä íðèäìòèðäáóêè ñòðàòäâèèñ øäëóøàåäáàñ.

13 àë ñúäìàðøèú îðíôäñèóêè âàìàçêäáèç ëíúóêè óìãà è÷íñ, ðíâíðú æðãàñðóêè ëíñàþêäíáà èñä ãàëàëçàåðäáäêè éêàñäáèñ ëíñüàåêääáèú.

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უმუშევრობის აგრეგირებული დონის სავარაუდო ცვლილების ვექტორიIII სცენარის განხორციელების შემთხვევაში


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æäëíðä àìàêèæèãàì ùàìñ, ðíë ëþíêíã îðíôäñèóê âàìàçêäáàæä àõúäìòèñ âàéäçäáà ñàéëàðèñè àðàà èñäçè ñèñòäëóðè îðíáêäëèñ âàãàñàýðäêàã, ðíâíðèú ñòðóõòóðóêè óëóøäåðíáàà. àóúèêäáäêèà âàìàçêäáèñ çèçíäóêè ñàôäþóðèñ çåèñíáðèåè úåêèêäáà.

àëàñçàìàåä ìàçäêèà, ðíë 30 üêèñ âàìëàåêíáàøè ãàâðíåèêè îðíáêäëèñ ëíâåàðäáà ë÷èñèäðàã åäð ëíþãäáà ãà ìäáèñëèäðè, çóìãàú ÷åäêàæä äôäõòèàìè öíìèñûèäáèñ øäãäâäáèñ ãàãâíëàñ üêäáè ãàñýèðãäáà.

àöñàìèøìàåèà èñèú, ðíë ñàâðûìíáè øäãäâèñ ëèöüäåèñàçåèñ ñàéëàðèñè àð àðèñ äðçè àì ðàëãäìèëä ñòðóõòóðèñ ñèìõðíìóêè ëóøàíáà. àóúèêäáäêèà ÷åäêà øäñàáàëèñè ñòðóõòóðèñ ûàêèñþëäåèñ ñèìõðíìèæàúèà.

ëíúäëóêè, éíëîêäõñóðè øèìààðñèñ àëíúàìèñ àëíþñìà øäóûêäáäêè èõìäáà âàëàðçóêè ëíìèòíðèìâèñà ãà øäôàñäáäáèñ ñèñòäëèñ âàðäøä.

üèìàëãäáàðä âààìâàðèøäáäáè àùåäìäáñ ëþíêíã ûèðèçàã ëèëàðçóêäáàñ ãà èñ ÿäð éèãäå øíðñàà ðäàêóðè ëíãäêèñàâàì, åèìàèãàì ðäàêóðè ëíãäêèñ øäëóøàåäáà âàúèêäáèç óôðí ëàöàêè ãäòàêèæàúèèñ óü÷äáðèå ñòàòèñòèéàñ ãà ä.ü. èìñàèãäðóê èìôíðëàúèàñ ñàýèðíäáñ. çóëúà àöñàìèøìàåèà, ðíë äñ àðèñ ñàõàðçåäêíøè óëóøäåðíáèñ ñòðóõòóðèñà ãà ñòðóõòóðóêè óëóøäåðíáèñ ñèñòäëóðè øäñüàåêèñ îèðåäêè ëúãäêíáà ãà ëèñè øäëãâíëè âàöðëàåäáà àðà ëþíêíã ñàñóðåäêè, àðàëäã àóúèêäáäêèúàà.

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9. ü÷àðíäáè9. ü÷àðíäáèñàõàðçåäêíñ ëçàåðíáà, 2013. 2013 üêèñ 2 àâåèñòíñ ¹199 ãàãâäìèêäáà ñàõàðçåäêíñ øðíëèñ 1. áàæðèñ ôíðëèðäáèñ ñàþäêëüèôí ñòðàòäâèèñà ãà ñàõàðçåäêíñ øðíëèñ áàæðèñ ôíðëèðäáèñ ñàþäêëüèôí ñòðàòäâèèñ ðäàêèæàúèèñ 2013-2014 üêäáèñ ñàëíõëäãí âäâëèñ ãàëòéèúäáèñ øäñàþäá, http://ssa.gov.ge/files/01_GEO/KANONMDEBLOBA/Kanon%20Qvemdebare/73.pdf

ñàõàðçåäêíñ ëçàåðíáà, 2014. 2014 üêèñ 17 èåìèñèñ N400 ãàãâäìèêäáà ñàõàðçåäêíñ 2. ñíúèàêóð-äéíìíëèéóðè âàìåèçàðäáèñ ñòðàòäâèèñ „ñàõàðçåäêí 2020“ ãàëòéèúäáèñà ãà ëàñçàì ãàéàåøèðäáóêè æíâèäðçè öíìèñûèäáèñ çàíáàæä, https://matsne.gov.ge/ka/document/view/2373855

ñàõàðçåäêíñ ëçàåðíáà, 2014. 2014 üêèñ 26 ãäéäëáäðèñ ¹733 ãàãâäìèêäáà øðíëèñ áàæðèñ 3. ñàèìôíðëàúèí ñèñòäëèñ ãàìäðâåèñà ãà âàìåèçàðäáèñ éíìúäôúèèñà ãà ëèñè âàìþíðúèäêäáèñ ñàëíõëäãí âäâëèñ ãàëòéèúäáèñ øäñàþäá, https://matsne.gov.ge/ka/document/view/2659790

ñàõàðçåäêíñ ñòàòèñòèéèñ äðíåìóêè ñàëñàþóðè (ñàõñòàòè). øèìàëäóðìäíáäáèñ 4. èìòäâðèðäáóêè âàëíéåêäåèñ 2009, 2010, 2011, 2012, 2013, 2014 ãà 2015 üêèñ ëíìàúäëçà áàæäáè, http://www.geostat.ge/?action=meurneoba_archive&lang=geo

àøø-ñ ñàäðçàøíðèñí âàìåèçàðäáèñ ñààâäìòí (USAID), ëèâðàúèèñ ñàäðçàøíðèñí íðâàìèæàúèà 5. (IOM), 2010. ñàõàðçåäêíñ äðíåìóêè øðíëèñ áàæàðè. 2010 üêèñ èåìèñ-èåêèñøè ùàòàðäáóêè éåêäåèñ àìâàðèøè. çáèêèñè, USAID, IMO. http://www.mes.gov.ge/uploads/LMS_2010_Geo.pdf àøø-ñ ñàäðçàøíðèñí âàìåèçàðäáèñ ñààâäìòí (USAID), ëèâðàúèèñ ñàäðçàøíðèñí 6. íðâàìèæàúèà (IOM), 2011. ñàõàðçåäêíñ øðíëèñ áàæàðæä ñàëóøàí ûàêèñ ëèüíãäáà. 2011 üêèñ çäáäðåàê-èåìèñøè ùàòàðäáóêè éåêäåèñ àìâàðèøè. çáèêèñè, USAID, IMO.äéíìíëèéóðè îíêèòèéèñ éåêäåèñ úäìòðè (EPRC), 2011. ãàñàõëäáèñà ãà óëóøäåðíáèñ 7. òäìãäìúèäáè ñàõàðçåäêíøè, ìíäëáäðè 2011. çáèêèñè, EPRC, https://www.osgf.ge/files/publications/2011/EPRC_Georgian_Economic_Outlook_II,_Nov_2011_GEO.pdf

áèæìäñ éíìñàêòèìâèñ ÿâóôè (BCG), 2014. øðíëèñ áàæðèñ éåêäåà. 8. áèæìäñ éíìñàêòèìâèñ ÿâóôè (BCG), 2015. øðíëèñ áàæðèñ ëíçþíåìèñ éíëîíìäìòèñ éåêäåà. 9. çáèêèñè, ñàõàðçåäêíñ øðíëèñ ÿàìëðçäêíáèñà ãà ñíúèàêóðè ãàúåèñ ñàëèìèñòðí, https://www.moh.gov.ge/files/01_GEO/Shroma/kvleva/33.pdf

ACT, 2015. ãàëñàõëäáäêçà ãàëíéèãäáóêäáèñ éåêäåà îðíôäñèóêè âàìàçêäáèñ ëèëàðç, 10. éåêäåèñ àìâàðèøè. çáèêèñè, UNDP,http://www.mes.gov.ge/content.php?id=5962&lang=geo

Hussmanns R., Mehran F., Verma V., 1992. Surveys of economically active population, employment, 11. unemployment and underemployment: An 110 manual on concepts and methods. Geneva, ILO http://www.ilo.org/public/english/bureau/stat/download/lfs.pdfHussmanns R., Measurement of employment, unemployment and underemployment – Current 12. international standards and issues in their application. http://www.ilo.org/public/english/bureau/stat/download/lfs.pdfKvaratskhelia V., Mukbaniani N., 2011. Unemployment and Labor Market Policy in Georgia. Tbilisi, 13. Ivane Javakhishvili Tbilisi State University, http://iset.tsu.ge/files/5._valeriane_kvaratskhelia_and_nana_mukbaniani.pdf

Aring M., 2012. Report on Skills Gaps, Background paper prepared for the Education for All Global 14. Monitoring Report 2012 Youth and skills: Putting education to work. UNESCO, http://unesdoc.unesco.org/images/0021/002178/217874e.pdf

Dilanchiev A., 2014. Relationship between Entrepreneurship and Unemployment: The Case of 15. Georgia. Journal of Social Sciences; Vol. 3, Issue 2, http://journal.ibsu.edu.ge/index.php/jss/article/view/637/533

Arias O., Sanchez-Paramo C., Davalos M., Santos I, Tiongson E., Gruen C., De Andrade Falcao 16. N., Saiovici G., Cancho C., 2014. Back to Work. Growing with Jobs in Europe and Central Asia, Washington, DC, THE WORLD BANK, http://www.worldbank.org/content/dam/Worldbank/document/Back-to-Work-Full.pdf DEG, the Boston Consulting Group (BCG), 2016. Bridging the skills gaps in developing countries. A 17. practical guide for private-sector companies. EDFI., file:///C:/Users/USER/Desktop/EDFI%20lets%20work%20partnership%20-%20Bridging%20Skills%20Gaps%20Report%20-%20DEG%202016.pdf

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10. ãàìàðçäáè10. ãàìàðçäáè

ãàìàðçè N1ãàìàðçè N1

éåêäåèñ îðíúäñøè âàëí÷äìäáóêè ùàöðëàåäáóêè èìòäðåèóñ éèçþåàðèéåêäåèñ îðíúäñøè âàëí÷äìäáóêè ùàöðëàåäáóêè èìòäðåèóñ éèçþåàðè

ðäñîíìãäìòèñ ñàþäêè ãà âåàðè.1. éíëîàìèèñ ñàþäêüíãäáà.2. éíëîàìèèñ ñàõëèàìíáèñ ñôäðí (àöüäðäç ðàú øäèûêäáà ãäòàêóðàã).3. ðàëãäìè üäêèà ðàú éíëîàìèà ñàõëèàìíáñ?4. çàåèñè ñàõëèàìíáèñ ëàìûèêæä éíëîàìèàñ þíë àð øäóúåêèà îðíôèêè?5. çó øäèúåàêà, ðà è÷í àëèñ ëèæäæè ãà ðíëäêè ñàõëèàìíáèãàì ðíëäêæä âàãàäðçí?6. ðàëãäìè çàëàøðíëäêèç ãàèü÷í éíëîàìèàë ñàõëèàìíáà?7. ðàëãäìè çàìàëøðíëäêè ¸÷àåñ éíëîàìèàñ àëïàëàã?8.

ëàç øíðèñ, ðàëãäìèà þäêëûöåàìäêè ðâíêèñ üàðëíëàãâäìäêè?a. ðàëãäìèà óëàöêäñè éåàêèôèéàúèèñ ñîäúèàêèñòè?b. ðàëãäìèà ñàøóàêí éåàêèôèéàúèèñ ñîäúèàêèñòè?c. ðàëãäìèà ãàáàêè éåàêèôèéàúèèñ ñîäúèàêèñòè?d.

ëíõëäãäáñ çó àðà éíëîàìèàøè îðäëèðäáèñ ñèñòäëà?9. àü÷íáñ çó àðà éíëîàìèèñ þäêëûöåàìäêíáà çàìàëøðíëäêçà üàëàþàêèñäáäê öíìèñûèäáäáñ 10. ãà çó àü÷íáñ ðà öíìèñûèäáäáèà äñ ãà ðàëãäìàã þøèðàã äü÷íáà?ðàëãäìàã çàåèñóôêàã øäóûêèà éíëîàìèèñ çàìàëøðíëäêñ ëèëàðçíñ éíëîàìèèñ 11. þäêëûöåàìäêíáàñ? (àöüäðäç îðíúäãóðà çó ðíâíð øäóûêèà éíëîàìèèñ ÷åäêàæä ãàáàêè ðâíêèñ çàìàëøðíëäêñ ëèëàðçíñ éíëîàìèèñ þäêëûöåàìäêíáàñ).áíêí þóçè üêèñ âàìëàåêíáàøè ãàèõèðàåà çó àðà éíëîàìèàë àþàêè çàìàëøðíëêäáè?12. çó ãàèõèðàåà, ûèðèçàãàã ðíâíðè éåàêèôèéàúèèñ çàìàëøðíëêäáñ äûäáãà?13. çó ãàèõèðàåà, ûèðèçàãàã ðíâíð äûäáãà çàìàëøðíëêäáñ? 14.

ìàúìíáäáèñ ëäøåäíáèç;a. âàëíàúþàãà éíìéóðñè éíëîàìèèñ åäá âåäðãæä; b. âàëíàúþàãà éíìéóðñè ñþåà ðíëäêèëä äêäõòðíìóêè ëäãèà ñàøóàêäáèç; c. âàëíàõåä÷ìà âàìúþàãäáà âàæäçøè ãà àñä øäëãäâ.d.

ûèðèçàãàã ðà ëíäçþíåäáíãàç éàìãèãàòäáñ? (ëèóçèçäç ëàöàêè, ñàøóàêí ãà ãàáàêè 15. éåàêèôèéàúèèñ éàìãèãàòäáèñ ëíçþíåìäáñ øíðèñ àðñäáóêè ñþåàíáäáè).ãààþêíäáèç ðàëãäìè àþàêè çàìàëøðíëäêè ãàèõèðàåà éíëîàìèàë áíêí þóçè üêèñ 16. âàìëàåêíáàøè?

ëàç øíðèñ, ðàëãäìè è÷í óëàöêäñè éåàêèôèéàúèèñ?a. ñàøóàêí éåàêèôèéàúèèñ?b. ãàáàêè éåàêèôèéàúèèñ? c.

ãààþêíäáèç ðàëãäìè éàìãèãàòóðà âàìèþèêäñ éíëîàìèàøè çàìàëøðíëêäáèñ øäðùäåèñàñ 17. áíêí þóçè üêèñ ëàìûèêæä?ðà è÷í èñ ûèðèçàãè ìèøàìè, ðèñ âàëíú éàìãèãàòäáèñàçåèñ óàðèñ çõëà âèüäåãàç?18. ðàëãäìàã éëà÷íôèêè þàðç à÷åàìèêè çàìàëøðíëêäáèç? (ãäòàêóðàã àöüäðäç éëà÷íôèêäáèñ 19. ãà óéëà÷íôèêäáèñ ëèæäæäáè).áíêí þóçè üêèñ ëàìûèêæä ëíâèüèàç çó àðà çàìàëøðíëêäáèñ âàçàåèñóôêäáà?20. çó ëíâèüèàç, þäêëûöåàìäêè ðâíêèñ ðàëãäìè çàìàëøðíëäêè âààçàåèñóôêäç ãà ðà 21. ëèæäæèç?çó ëíâèüèàç, óëàöêäñè éåàêèôèéàúèèñ ðàëãäìè çàìàëøðíëäêè âààçàåèñóôêäç ãà ðà 22. ëèæäæèç?çó ëíâèüèàç, ñàøóàêí éåàêèôèéàúèèñ ðàëãäìè çàìàëøðíëäêè âààçàåèñóôêäç ãà ðà 23.

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ëèæäæèç?çó ëíâèüèàç, ãàáàêè éåàêèôèéàúèèñ ðàëãäìè çàìàëøðíëäêè âààçàåèñóôêäç ãà ðà 24. ëèæäæèç?àëïàëàã äûäáç çó àðà çàìàëøðíëêäáñ?25.

çó äûäáç, ðà ñîäúèàêíáèñ çàìàëøðíëêäáñ äûäáç?a. çó äûäáç, ðíâíð äûäáç?b. çó äûäáç, ðà àðèñ ûèðèçàãè îèðíáäáè, ðíëêäáñàú óìãà àéëà÷íôèêäáãìäì c.

éàìãèãàòäáè?çõåäìè øäôàñäáèç, ðàëãäìàã àãåèêèà ñàõàðçåäêíøè ëàöàêè éåàêèôèéàúèèñ îäðñíìàêèñ 26. ëíûèäáà? ðíëäêè ñîäúèàêíáèñ çàìàëøðíëêäáèñ ëíûèäáàà àãåèêè ãà ðíëêèñ ðçóêè? ðà àðèñ àë ñèàãåèêèñ àì ñèðçóêèñ ëèæäæè?ûèðèçàãàã ðà àñàéèñ çàìàëøðíëêäáæä àéäçäáç àõúäìòñ ãà ðà àðèñ àëèñ ëèæäæè? çó 27. ñþåàãàñþåà îðíôäñèèñçåèñ àñàéíáðèåè éðèòäðèóëäáè âàìñþåàåäáóêèà, ðàøè ëãâíëàðäíáñ äñ âàìñþåàåäáà ãà ðà àðèñ àëèñ ëèæäæè?çõåäìè àæðèç, ðà àðèñ ñàõàðçåäêíøè ñàëóøàíñ ëíûäáìèñ ëçàåàðè îðíáêäëà?28. çõåäìè àæðèç, ðà àðèñ ñàõàðçåäêíøè éàãðäáèñ ëíûäáìèñ ëçàåàðè ñèðçóêä?29. ðíâíðèà ìàþäåàðè àì ëíõìèê âàìàéåäçèàìè éíìòðàõòäáèñ üèêè (%) øðíëèç 30. þäêøäéðóêäáäáøè?


éåêäåèñ îðíúäñøè âàëíéèçþóêè éíëîàìèäáèéåêäåèñ îðíúäñøè âàëíéèçþóêè éíëîàìèäáè

ñ.ñ. “çè-áè-ñè áàìéè”:ìèìí âàùäùèêàûä - àãàëèàìóðè ðäñóðñäáèñ ëàðçåèñ âàì÷íôèêäáèñ óôðíñè;ñ.ñ. “ÿäíñäêè”: çàëóìà âàôðèìãàøåèêè - àãàëèàìóðè ðäñóðñäáèñ ëàðçåèñ âàì÷íôèêäáèñ óôðíñè;ñ.ñ. “ìèéíðà”: ñíôèí çíôóðèà - àãàëèàìóðè ðäñóðñäáèñ ëàðçåèñ âàì÷íôèêäáèñ óôðíñè;ñ.ñ. “IDS áíðÿíëè ñàõàðçåäêí”:ðóñóãàì âíâêèûä - àãàëèàìóðè ðäñóðñäáèñ ëàðçåèñ ñàëñàþóðèñ óôðíñè;øîñ "ÿíðÿèàì ëàìâàìäæè": çàëàð ýèîàøåèêè - àëèàìóðè ðäñóðñäáèñ ëàðçåèñ ñàëñàþóðèñ óôðíñè;ñ.ñ. “çäêèàìè åäêè”: ñàêíëä âóðâäìèûä - àãàëèàìóðè ðäñóðñäáèñ ëàðçåèñ âàì÷íôèêäáèñ óôðíñè;ø.î.ñ. “ñàëéäðåàêí ôàáðèéà êàóðà öàýàåà”: ëà÷åàêà éàåêäêàøåèêè - àãàëèàìóðè ðäñóðñäáèñ ëàðçåèñ âàì÷íôèêäáèñ óôðíñè;ø.î.ñ.“Adjara Group Hospitality”: þàçóìà òóöóøè - àãàëèàìóðè ðäñóðñäáèñ ëàðçåèñ âàì÷íôèêäáèñ óôðíñè ñîäúèàêèñòè;ø.î.ñ. “êàøàðè”: ÿäìäðè àðõàìèà - ñéíêèñ ãèðäõòíðè;ññ "ñàõðóñäìäðâí":çäìâèæ àêàåèûä - àãàëèàìóðè ðäñóðñäáèñ ëàðçåèñà ãà ñàëàðçêäáðèåè óæðóìåäê÷íôèñ ãäîàðòàëäìòèñ þäêëûöåàìäêè.

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àìâàðèøèñ øóàêäãóðè âàìþèêåèñ ëíìàüèêääáèàìâàðèøèñ øóàêäãóðè âàìþèêåèñ ëíìàüèêääáè

äêæà ÿâäðäìàèà - øðíëèñ, ÿàìëðçäêíáèñà ãà ñíúèàêóðè ãàúåèñ ñàëèìèñòðíñ øðíëèñà ãà ãàñàõëäáèñ îíêèòèéèñ ãäîàðòàëäìòèñ óôðíñè;

âèíðâè âàë÷ðäêèûä - øðíëèñ, ÿàìëðçäêíáèñà ãà ñíúèàêóðè ãàúåèñ ñàëèìèñòðíñ øðíëèñà ãà ãàñàõëäáèñ îíêèòèéèñ ãäîàðòàëäìòèñ øðíëèñ áàæðèñ àìàêèæèñ ñàëëàðçåäêíñ óôðíñèñ ëíåàêäíáèñ øäëñðóêäáäêè;

øíðäìà òèäêèûä - øðíëèñ, ÿàìëðçäêíáèñà ãà ñíúèàêóðè ãàúåèñ ñàëèìèñòðíñ øðíëèñà ãà ãàñàõëäáèñ îíêèòèéèñ ãäîàðòàëäìòèñ øðíëèñ áàæðèñ àìàêèæèñ ñàëëàðçåäêíñ ëçàåàðè ñîäúèàêèñòè;

âèíðâè éàêàéàøåèêè - ñòàòèñòèéèñ äðíåìóêè ñàëñàþóðèñ ñíúèàêóðè ñòàòèñòèéèñ ñàëëàðçåäêíñ óôðíñè;

úèñìàëè ñàáàûä - äéíìíëèéèñà ãà ëãâðàãè âàìåèçàðäáèñ ñàëèìèñòðíñ äéíìíëèéóðè æðãèñ îíêèòèéèñà ãà ãàâäâëåèñ ãäîàðòàëäìòèñ óôðíñèñ ëíåàêäíáèñ øäëñðóêäáäêè;

ðäåàæ âäðàûä - äéíìíëèéèñà ãà ëãâðàãè âàìåèçàðäáèñ ñàëèìèñòðíñ ëàéðíäéíìíëèéóðè àìàêèæèñ ñàëñàþóðèñ óôðíñè;

âäìí ÿàìöèûä - ñíôêèñ ëäóðìäíáèñ ñàëèìèñòðíñ àìàêèòèéóðè ãäîàðòàëäìòèñ óôðíñèñ ëíàãâèêä;

ñíôèí ùèòàûä - âàìàçêäáèñ ãà ëäúìèäðäáèñ ñàëèìèñòðíñ óëàöêäñè âàìàçêäáèñ ãà ëäúìèäðäáèñ âàìåèçàðäáèñ ãäîàðòàëäìòèñ óëàöêäñè âàìàçêäáèñ âàìåèçàðäáèñ ñàëëàðçåäêíñ óôðíñè ñîäúèàêèñòè;

þàòèà ìàãàðàèà - âàìàçêäáèñ ãà ëäúìèäðäáèñ ñàëèìèñòðíñ îðíôäñèóêè âàìàçêäáèñ âàìåèçàðäáèñ ãäîàòðàëäìòèñ ãàëþëàðä ñîäúèàêèñòè;

èíñäá àðùåàûä - èå. ÿàåàþèñåèêèñ ñàþäêíáèñ çáèêèñèñ ñàþäêëüèôí óìèåäðñèòäòèñ îðíôäñíðè;

íçàð âðèâíêèà - àðàñàëçàåðíáí íðâàìèæàúèà "ñàõàðçåäêíñ îðíâðäñóêè ôíðóëèñ" àìàêèòèéíñè;

áäõà ôäðàûä - àðàñàëçàåðíáí íðâàìèæàúèà "ñàõàðçåäêíñ îðíâðäñóêè ôíðóëèñ" àìàêèòèéíñè.

Structure of Unemployment and Structural Unemployment in … · 2017. 1. 18. · 6 Detection of the...

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