An Urban Area Primary Source Study of SupplyDemand in the Labor Market(en)

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Islamic Republic of AfghanistanMinistry of Labor and Social Affairs, Martyrs and Disabled

An Urban Area Primary Source Studyof

Supply & Demand in theLabor Market

The Labor Market Information and Analysis Unit(Supported by the National Skills Development Program)

January, 2009


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Table of Contents

Abbreviations ................................................................................................................................................. 4Foreword ........................................................................................................................................................ 5Executive Summary..8

Employment.8Key Incomes............................................................................................................................................... 8Demanded Skills......................................................................................................................................... 8Education.................................................................................................................................................... 8Vocational Training.................................................................................................................................... 9

Background .................................................................................................................................................. 10Study methodology and limitations.............................................................................................................. 12

Sampling and sample distribution......12

Respondent selection..13

Training of enumerators.13

Quality Control...14

Visual check...14

Phone check14

Application of labor market key indicators (KILM)..15Questionnaires.......................................................................................................................................... 15Reliability and validity ............................................................................................................................. 17

Translation and Interpretation .............................................................................................................. 17Motivation ............................................................................................................................................ 17Concerns relating to tax information collection ................................................................................... 17Expectations of support ........................................................................................................................ 17

Methodological approach to handling data............................................................................................... 17Collection ............................................................................................................................................. 17Data entry............................................................................................................................................. 17

Findings........................................................................................................................................................ 19Household data......................................................................................................................................... 19

Age distribution nationwide (urban)..................................................................................................... 19

Education.............................................................................................................................................. 20Incomes...21Employment to population ratio........................................................................................................... 26Methods of finding work...................................................................................................................... 26Mean hours worked, and willing to work, weekly........... ............ ......... ........... ............ ......... ........... ..... 27

Informal business data.............................................................................................................................. 31Percentage of informal businesses by sector ........................................................................................ 31Total numbers of employees by sector................................................................................................. 32Projected and stated future staff needs by sector.................................................................................. 33Average incomes .................................................................................................................................. 34Number of people employed ................................................................................................................ 38Day labor pick-up-point data................................................................................................................ 39Number of years worked by day laborers............................................................................................. 50

Education levels of day laborers........................................................................................................... 51Formal business data ................................................................................................................................ 52Future staff demand in the formal sector.............................................................................................. 53Export activity...................................................................................................................................... 53Employment of foreigners .................................................................................................................... 54Business expansion and contraction ..................................................................................................... 54

Data from vocational training centers....................................................................................................... 55Courses being taken.............................................................................................................................. 55Curriculum source................................................................................................................................ 56

References .................................................................................................................................................... 57Annexes........................................................................................................................................................ 59

Annex 1 Manual for enumerators on questionnaires..60Annex 1a Household questionnaire75Annex 1b Formal businesses questionnaire...77


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Annex 1c Informal businesses questionnaire.....79Annex 1d Individual skilled labor questionnaire80Annex 1e Vocational training centers questionnaire.81

Annex 2a Education levels province wise..84Annex 2b Education levels with gender breakdown province wise...95

Annex 3 Number of people working, working by occupation, province wise.103Annex 5 KILM2-Employment to population ratio in provinces..114Annex 6 Methods of finding work province wise125Annex 7a Average hours working per week by occupation province wise.136

Annex 7bAverage hours willing to work per week by occupation province wise...149Annex 8 Informal business by sector for each province..158

Annex 10 Informal business stated staffing needs, province wise...164

Annex 12a Low earners province wise...172Annex 13a Average monthly income province wise ...192Annex 13b Percentage at the 122 informal enterprise type earning more than AFS.20,000 per month

province wise208

Annex 16 How do your workers learn their skills province wise219


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Abbreviations

ACBAR Agency Coordination Body For Afghan Relief

ADB Asian Development BankAICC Afghanistan International Chamber of Commerce

AIMS Afghanistan Information Management System

AISA Afghanistan Investment Support Agency

ALTAI Altai Consulting

ANDS Afghanistan National Development Strategy

AREU Afghanistan Research and Evaluation Unit

ARDS Afghanistan Reconstruction and Development Services

ASMED Afghanistan Small & Medium Enterprise Development

AWBF Afghanistan Women's Business Federation

CIPE Centre of International Private Enterprise

CDP Capacity Development Project (USAID)

CSO Central Statistics Office

ESC Employment Service Centre

GTZ Deutsche Gesellschaft fur Technische Zusammenarbeit

ILO International labor Organization

IRC International Rescue Committee

ISAF International Security Assistance force

JICO Japanese International Cooperation Agency

KILM Key Indicators of the Labour Market

KOICA Korean International cooperation Agency

LMIAU Labor Market Information Analysis UnitMOC Ministry of Commerce

MOE Ministry of Education

MOEC Ministry of Economics

MOHE Ministry of Higher Education

MOLSAMD Ministry of Labor, Social Affairs, Martyrs and Disabled

MOPW Ministry of Public Works

MRRD Ministry of Rural Rehabilitation and Development

MOWA Ministry of Women's Affairs

NRVA National Risk & Vulnerability Assessment

NSDP National Skills Development & Market Linkages Project

NSS National Surveillance SystemPDT Peace Dividend Trust

PRT Provincial Reconstruction Team

RFP Request for Proposal

SAB Solidarite Afghanistan Belgique

SDO Sanayee Development Organization

UNDP United Nations Development Program

USAID United States Agency for International Development

WB World Bank

WFP World Food Program


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Foreword

In early 2006, the Afghanistan National Development Strategy (ANDS) published adevelopment benchmark (BM 4.1.3) which required the production of a Human Resource

Study. (IANDS, February 2006, Chapter 8). This study was assigned to the National

Skills Development Program (NSDP) under the Ministry of Labor, Social Affairs and

Martyrs and Disabled (MOLSAMD).

Although the scope of the study was not defined, after discussions with the ANDS team it

was agreed that it should be primary-data study having a focus on labor force supply and

demand.

After some difficulties in procuring the vital technical assistance to support this

undertaking, and after considering the highly technical nature of such studies and the lack

of in-country expertise, in 2007 the ANDS team agreed to revise the plan and allow for

the production of two studies. It was agreed that the first, and simpler of the two, would

be based on secondary source data whilst the second would be based on primary data -

this approach allowing for a more gradual and manageable development of in-country

expertise.

It was also agreed that the process of undertaking the studies should be a capacity

building process and should create a long term and sustainable resource within the

MOLSAMD by building a Labour Market Information and Analysis Unit (LMIAU)

which could undertake similar studies in the future.

The responsibility for both studies, and the management of the capacity building process,

remained with the (NSDP).

The first study, and accompanying report, was completed in July 2007. It was circulated

widely and allowed agencies to obtain a relatively up-to-date picture of key aspects of the

labor market. (This study is available from the NSDP office.)

This report covers the second study and is based on urban-area primary data obtained

from the provincial capitals across Afghanistan. It is hoped that this will provide useful

labor market supply and demand data for a variety of stakeholders, and inform economic

policy making, and planning for skills training and business development.

Over 13,800 households, 8,000 informal businesses, 1000 day laborers, 400 formal

businesses and 100 vocational training centres were sampled across 31 out of 34

provinces, and over 24,000 interviews were conducted. This represents one of the most

extensive studies of its type undertaken in recent times in Afghanistan. In the process,

staff from the LMIAU, the NSDP and the MOLSAMD participated as trainers,enumerators, controllers and supervisors.

The LMIAU staff cleaned the data and the NSDP hired and trained a carefully selected

batch of data entry clerks to enter the data into an MS ACCESS Database. The

involvement of the fledgling LMIAU team in all the steps of the study, prior to the


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analysis of the data, has contributed greatly in improving their understanding and skills

related to the design and execution of major, country-wide data collection and dataprocessing exercises. This represents a very valuable capacity building experience

Other entities have also been involved in various labor market studies over the past twoyears and a summary of many of these were captured in the first report published by theNSDP in 2007. It is hoped that in the future, now that the LMIAU has been established,

much more synergy and coordination of effort can be brought to bear on the task of

obtaining and disseminating reliable and well-analyzed labor market information.

It should be noted that although the Central Statistics Office (CSO) is mandated to carry

out statistical surveys for the Government, through staffing constraints the CSO was

unable to assist directly in this particular case. However, much valuable information on

data collection, statistical frames and analysis methodologies was conveyed to the NSDPand LMIAU teams and sincere thanks goes to the CSO for this valuable cooperation and

support. In future it is hoped that much more active synergy can be established with theCSO.

Still, almost seven years after the Taliban government was toppled, security and a climate

for sustainable capacity development have yet to be established in Afghanistan. In such a

situation, undertaking extensive and complex studies of this nature, and building a

sustainable human resource in the process, is extremely difficult. However, numerouspeople, and particularly those mentioned below, eased this difficulty by freely and

generously offering their support and encouragement.

I thank both Noor Mohammad Qarqin, Minister of Labor, Social Affairs, Martyrs and

Disabled and Mohammad. Ghaus Bashiri, Deputy Minister, for their enthusiastic supportin selecting and allocating Ministry staff to assist with enumeration thereby exposing

them to modern data collection methods in the field.

Mr. Khair Mohammed Niru, LMIAU Manager and my counterpart during the earlier part

of the planning, made vital and important technical and administrative contributions forwhich I am truly thankful.

Mr. Eng.Hameedullah Hamdard, NSDPs Database Officer, developed and design

essential database and data handling routines which were so essential for such an

extensive study. His unending patience and hard work deserves the highest possible

recognition.

Sincere thanks also goes the temporary data entry clerks and the Labor Market

Information Analysis Unit (LMIAU) staff whose commitment and effort was crucial to

the successful production of this report.

Finally, there are five people without whom this study and report would have been

impossible. These are Eng. Rahim Wardak, NSDP Program Director; Abdul Rahim


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Nasry, NSDP Program Coordinator; Mohammad Asif Stanakzai, NSDP Monitoring and

Evaluation Manager; and Dr. Fareed-u-Din Noori, NSDP Monitoring and EvaluationOfficer and Acting LMIAU Manager. I convey warm and sincere thanks to each of them.

Jon RothenbergOctober 2008


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Executive Summary

Employment

47.1% of all individuals in the urban sample areas, over 15 years old, stated thatthey had some form of paid employment.

64.3% of those over 15, and living in Kabul, stated that they had some form ofpaid employment.

57.6% of the core working age population (25 to 54 years) is employednationwide (urban).

Approximately 20% of all Individuals interviewed are working fewer than 40hours per week, and stated that they would prefer to work more hours.

Services and construction occupy the largest number of urban-based individuals.The most frequent type of informal sector business is general stores.

Key Incomes The average monthly income of an employed individual, nationally (urban), is

Afs. 4,989.

The average income of employed females, nationally (urban), is Afs. 3,139 permonth.

The average income of employed males, nationally (urban), is Afs. 5,256 permonth.

The average income nationwide (urban) for all unskilled (carters, fruit andvegetable sellers etc.), laborers, is Afs. 1,687 per month.

The average income nationwide (urban) for day laborer carpenters is Afs. 7,500per month.

The average income nationwide (urban) for day laborer electricians is Afs. 7,076per month.

The average income nationwide (urban) for day labour masons is Afs. 7,280 permonth.

The average income nationwide (urban) for day laborer painters is Afs. 7163 permonth.

The average income nationwide (urban) for day laborer plumbers is Afs. 5,723per month.

Demanded Skills

In urban areas, skills related to the construction and services sector, are in highestdemand.

Education 22.5% of men and 25.1% of women do not consider themselves to be literate.

11.8% of men and 7.8% of women in urban areas have had some primary schooleducation.

7.1% of men and 2.5% of women in urban areas have completed secondaryschool.

25.8% of secondary school graduates interviewed in urban areas were women.

2.2% of men and 0.6% of women in urban areas have completed a university

course.


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Vocational Training

The percentage of males formally trained in vocational centres, nationally(urban), is 2.7% of total male age group.

The percentage of females formally trained in vocational centres, nationally(urban), 2.3% of total female age group.

Over 95% of workers are trained on the job in informal apprenticeships.


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Background

Earlier studies1,2

recognize the need for labor market information to determine the skillsrequired by business/industry (with associated potential labor requirements) and

recognize ongoing changes in the economy which result in changing skill demands.

This information is vital as it informs government employment policies as well as

policies and investment support decisions for a wide range of labor force skills

development activities, both public and non-public.

According to Grey et al (1993)3, key elements that secure relevant but cost effective and

sustainable labor market information are:

Inclusion of all relevant stakeholders at a local level, includingindustry/business, vocational training providers, funding organizations and

local government.

Effectiveness of key informants.

Simple, clear and concise operational procedures identified with relevantstaff trained at the local level.

Provision of analysis technologies.

These requirements, and particularly the need to gather information from local

stakeholders and ensuring their participation, were born in mind at all stages of design,design revision and execution of the study,

Due to time constraints only key stakeholders participated in the design phase of the

study although almost all stakeholders were informed of the study and provided with

background information and an opportunity to offer suggestions for improvement.

Key stakeholders include the NSDP, the MOLSAMD, Afghanistan Information

Management System (AIMS), the Central Statistical Office (CSO), Altai Consultants, theAfghanistan Investment Support Agency (AISA), the USAID-funded CapacityDevelopment Program (CDP), Afghanistan Research and Evaluation Unit (AREU) and

The National Surveillance System NSS. Other large stakeholders include the Afghan

National Police (ANP), several provincial governors, international and local NGOs

(especially the NSDP contracted training providers), other government ministries and the

ANDS. It was decided not to inform business owners or the general public in advance of

the study since this might have lead to confusion with the forthcoming national census.

Key informants used in this study include household heads, informal and formal-sector

business managers, semi-skilled and skilled independent workers (at labor pickup points)

1International Labour Organization (2008), Afghanistan: Towards a Resuscitated Labour Market, International Labour

Office, Kabul, Afghanistan

2International Rescue Committee (IRC), (2003). Afghanistan Labour Market Information Survey, In association with the

Ministry of Labour & Social Affairs, Kabul.3Gray, L. et al. (1993) Reducing the cost of technical and vocational education: a report to the Overseas Development

Administration, ODA Education Paper No.3


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and vocational training providers.

Although the interview questions were primarily relevant to labor market supply and

demand the survey also provided an opportunity to gather data on larger economic issues

such as what common goods and services appear to be needed in a particular locality.

Over a two-month period the LMIAU manager developed operational and training

procedures. Key decisions included how to train and use MOLSAMD staff as

enumerators to survey households for supply data, skilled laborers, informal and formal

businesses for demand data and vocational training centers for both types of data.

It was decided to train enumerators and collect forms at the regional level and provide

inter-provincial travel for both enumerators from smaller provinces and the

supervisors/trainers from Kabul.

Although in one case, Oruzgan, this reliance on travel in insecure areas resulted in aprovince not being surveyed, this choice promoted sustainability by creating knowledgeand resources in both the provinces and Kabul.


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Survey methodology and limitations

1) Sampling and sample distribution:

The study included all provincial capitals except Urozgan, Wardak, and Daikundi. Thefirst two were omitted due to lack of trained personnel and insecurity. Daikundi was not

included due to its extremely small urban population and inaccessibility. . The Sharwali

(Municipality) defines the urban population as those who are living with in the municipallimit. Municipalities are divided into Nahias (Districts)

Based on the CSO data two percent of households in each provincial capital were

covered. The informal businesses sample size was obtained using business data gathered

as a part for the study from Charikar and Kabul and the CSO data for Kabul, the Formal

businesses sample size was determined from the AISA directory and the Vocational

Training Centre (VTC) sample size was obtained from NSDP VTC directory.

The CSO Nahia (district) data was used to determine the number of households in each ofthe provincial capitals. Two percent of that number was interviewed.The two percent sample size was agreed after technical consultations with the CSO and

other organizations involved in similar studies. In Kabul, this two percent sample size

was extended down to the district level. Recent maps were then used to establish the

enumeration areas.

Throughout the design process the CSO, ALTAI Consulting and other specialists assistedin providing advisory support based on their own experience, and so helped to ensure theintegrity of the methodology.

Rather than random sampling, a repeated systematic sampling methodology was used.

This decision was based on lessons learned which had shown that enumerators were

much more likely, and able, to follow instructions correctly if the interval between

samples was repeated and systematic.

Regarding the basic definitions of formal and informal enterprises, after extensivediscussions with CSO officials it was decided to define a formal business as an entity

registered with the Afghanistan Investment Support Agency (AISA) or the Afghanistan

International Chamber of Commerce, or owned by the government. The definition of an

informal business was the converse of this and defined as an entity not registered with

either AISA or AICC or owned by the government. Questionnaires were developed andrun only with businesses that conformed to these definitions.

2) Respondent selection:

For the household questionnaire the enumerators were given Sharpie markers and

instructions to go to every fourth household and to mark the houses upon completion of

surveying.

For the informal business survey a complete count of businesses in Charikar town (a

small-to-medium sized town) was carried out before the survey. This provided a

proportion of informal businesses to the number of households (obtained from the CSO)


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in smaller provincial capitals. This ratio of informal businesses-to-households was used

to calculate the informal business sample size in smaller capitals.

To estimate the number of informal businesses to interview in larger provincial capitals

the total number of households in that city, using CSO data, was compared with the totalnumber of households in Kabul. Since the CSO had data on the number of informalbusinesses in Kabul this provided an estimate of the ratio of informal businesses to

population in larger provincial capitals and so informed the informal business sample size

in the larger provincial capitals. The LMIAU team also counted informal businesses in

selected districts in Kabul to compare with the CSOs numbers and found they were very

close to each other. For smaller cities, as mentioned above, the count of the informal

businesses in Charikar was used to estimate the sample size.

The enumerators were instructed to interview all the informal businesses, formalbusinesses and vocational training centers in any capital city with less than 2,375

households - according to CSO information.

In three capitals there were undercounts of households and in three there were

undercounts of informal businesses. In Mehterlam both were undercounted because the

security was uncertain, however, local NSDP staff carried out more interviews in

Mehterlam when the situation improved.

In Sherberghan and Mehmood Raqi all informal enterprises were interviewed. In several

provincial capitals a larger sample was taken than needed. In order to balance these

provincial samples with the others the extra questionnaires were randomly selected,

packed together and not entered into the database.

3) Training of enumerators:

The provincial capitals were clustered into seven zones with the largest capitals (Kabul,Jalalabad, Gardez, Herat, Kandahar, Mazar-e-Sharif and Kundoz city) being used as zone

centers. One LMIAU staff member and one NSDP staff member was assigned inchargeof each zone. They conducted enumerator training and supervised the enumerators in the

assigned zones. In Kabul the LMIAU manager trained and supervised the enumerators.

Due to Kabuls large size, six of the LMIAU staff worked as coordinators and

coordinated over sixty MOLSAMD enumerators.

4) Quality control:

Visual check:After the data collection in the 31 provincial capitals all the forms were brought back to

Kabul. LMIAU staff cleaned the collected data, separated the uncompleted forms and

filled them out over the phone by calling the respondents.

Thirty trained data entry clerks entered the data into an Access database. At the end of

each day they spent one hour cross-checking a statistically valid number of each others

forms for errors, and flagged them for correction. After all the forms were entered a

secondary check was made. This ensured a high accuracy rate for data entry.


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The number of Informal business, Individual Laborers, Formal Business and Vocational

Training Provider questionnaires that were incomplete after cleaning were statisticallyinsignificant. The Informal Business and Individual Laborers questionnaires are each of

only one page and were, as a result, generally answered completely. Because the Formal

Business forms were self-administered, we expected a very low return rate and thereforedistributed five times as many forms as needed. Ultimately, there were enough returnsand the respondents filled the questionnaires out adequately.

In Kabul the NSDP Monitoring and Evaluation staff conducted the vocational training

provider questionnaires. Since the providers are either funded by, or have had a previous

relationship with NSDP, the majority of the questionnaires were answered satisfactorily.

In the other provinces the much smaller number of enumerators, questionnaires and

geoChartical areas enabled good control to be maintained and an insignificant number of

incomplete forms were received.

Phone check:For validity and reliability of the collected data a 6% of the total forms were randomlychecked by phone. Consequently, 84% of completed forms were found to be correct, 4%

of respondents could not be reached by phone, and 12% of contact numbers were

incorrect due clerical mistake or by giving intentionally wrong number by the

respondents. Where it was necessary to collect additional data, enumerators were sent to

interview new households and businesses in between the ones previously marked.

5) Application of Labor Market Key Indicators (KILM):

Most countries use the ILOs twenty Key Indicators of the Labor Market (KILM) for

national labor market information analysis in order to be able to compare this informationbetween countries. This study considered nine of the most important Indicators for

Afghanistan, as follows:

KILM 2 - Employment-to-population ratio

KILM 3 - Status in employment

KILM 4 - Employment by sector

KILM 6 - Hours of work

KILM 8 - Unemployment

KILM 9 Youth Employment

KILM 12 -Time-related underemployment

KILM 14 - Educational attainment and literacy

KILM 16 - Occupational wage and earning indices

Some of these were obtained by simple direct questions (e.g. KILM 2 and 4) and others

through comparison of several questions (KILM 3). It is felt that KILM 2 is especiallyuseful in Afghanistan and agree with the ILO KILM guide when it states, "The

employment-to-population ratio provides information on the ability of an economy to

create employment; for many countries the indicator is often more insightful than the

unemployment rate.


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6) Questionnaires:

The questionnaires were developed in English and translated into Dari and Pashto.

In developing questionnaires different draft versions were shared with important

stakeholders including AREU, Altai Consulting, CDP, CSO, Kabul University andAISA, and their feedback was used to develop the final versions.

The LMAIU Manager trained all LMIAU staff members to be enumerators and a pilot

survey was conducted in Charikar (a small to medium size provincial capital), and some

districts of Kabul (the largest capital) to test the survey methodology, logistics and

wording of the questionnaires in Dari and Pashto.

After corrections the LMAIU Manager then conducted training-of-trainers sessions for

LMIAU staff and selected NSDP staff.


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Sample Distribution

S/N Province City HH

Actual

HH

Planned

IB

Actual

IB

Planned

Ind

Actual

Ind

Planned A

1 Nangrahar Jalalabad 626 626 261 230 27 26 3

2 Kunar Kunar 57 54 89 91 15 10 0

3 Laghman Laghman 229 229 230 230 31 26 1

4 Nuristan Nuristan 40 37 20 20 0 0 0 5 Paktya Gardez 46 46 41 41 6 6 4

6 Paktika Sharan 16 14 18 18 1 1 0

7 Khost Khost 51 45 45 45 7 7 5

8 Ghazni Ghazni 56 56 95 95 11 11 4

9 Kundoz Kundoz 546 466 857 784 87 87 1

10 Baghlan Pul-e-khumri 466 466 784 784 83 87 2

11 Badakhshan Faizabad 107 107 180 180 20 20 6

12 Takhar Taleqan 210 210 353 354 39 39 1

13 Kandahar Kandahar 1089 1089 446 401 34 45 4

14 Nimroz Zaranj 96 93 152 157 15 17 3 15 Helmand Lashkargha 211 211 373 355 40 39 2

16 Zabul Qalat 54 54 93 91 12 10 0

17 Balkh Mazarisharif 1223 1223 500 450 90 50 5

18 Faryab Maimana 211 211 394 355 20 39 1

19 Sar-e-Pul Sar-e-Pul 76 76 142 128 20 14 4

20 Samangan Aybak 101 101 189 170 20 19 6

21 Jawzjan Sheberghan 288 288 250 484 54 54 1

22 Kabul Kabul 6491 6233 2051 2076 208 255 1

23 Parwan Charikar 154 153 256 257 35 29 4

24 Kapisa Mehmood Raqi 190 137 106 230 24 26 3

25 Punjshir Bazarak 48 48 90 80 0 9 0 26 Bamyan Bamyan 25 25 13 13 23 23 8

27 Logar Pul-e-Alam 7 7 75 75 9 9 5

28 Herat Heart 1340 1340 548 493 50 55 6

29 Farah Farah 89 89 166 149 10 17 5

30 Badghis Qala-e-Naw 54 54 101 91 10 10 3

31 Ghore Chughcharan 19 19 36 32 10 4 1

Total Actual 24768 Planned 24936 14216 13807 8954 8959 1011 1044 4


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Reliability and validity

At several points in the study reliability and validity concerns were identified and

addressed. These include:

Translation and Interpretation

Problems with translation from English to Dari and Pashto arose throughout the study.Semantic and translation difficulties occurred during study questionnaire development,

training of enumerators, enumeration and data cleaning.

Motivation

Even though the enumerators were MOLSAMD staff working in their home provincethey were provided with a small stipend in recognition of the extra, and quite onerous,

work load they were asked to do, and in the hope that faithful reporting was maintained.

Concerns relating to tax information collection

Because the household questionnaire asked about incomes, some of the respondents

thought they had cause to reply incorrectly. This was probably because they were

worried about taxes etc. The local, and known, MOLSAMD staff enumerators were

trained address this concern but inevitably some responses were influenced by it.

Expectations of support

Whenever a survey is conducted in Afghanistan, some of the surveyed population has

raised expectations that perhaps some kind of financial or other support might be

forthcoming, which it sometimes does. On the other hand, many people have been

disappointed when some expected benefit, perhaps implied by enumerators, is notforthcoming. For both situations, population groups exist who are either unwilling to

answer survey questions, or answer them falsely.

Methodological approach to handling data

Collection

The collection procedure was designed and then tested in Charikar and in districts of

Kabul. A training manual was written and the supervisors and controllers were trained

by the LMIAU Manager and Advisor. This training cascaded as the supervisors trained

the enumerators and each trained enumerator was given a copy of the manual in their

own language. This gave a consistent approach to data collection.

Data entry

Training and evaluation of data entry clerks was rigorous. Every day the entered data was

sample checked for errors and any data entry personnel who continuously inputted bad


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data was released. Prizes were issued on a periodic basis for the best data entry clerks, for

the given period.

The flow chart below details the main stages of the study.

All efforts were made to ensure that the integrity of the data collection and data entry

process was maintained throughout the study. However, in employing and building the

capacity of staff having very limited experience and no previous training, and in havingto maintain a very tight time schedule, inevitably a number of enumeration and data entry

errors were found.

After numerous queries based on the evidence emerging when the report charts emerged

from the database it is hoped that the majority of errors have been corrected or

eliminated.

All data collected by this study resides with the LMIAU, which is currently linked to the

NSDP at the MOLSAMD. This data is freely available to any individual or agency

requesting it.


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Findings

Household data

Approximately 2% of all the urban households in the 31 provincial capitalswere surveyed.

The average urban household consists of 5.6 people.

47.1% of all Individuals are employed but many would like to work morehours per week, suggesting there is a significant level of underemployment.

The average income of an individual employed Afghan, nationally (urban),was found to Afs. 4,989.

The average income of females is Afs. 3,139 and the average income

nationally (urban) of males is Afs. 5,256. The average percentage of males vocationally trained nationally (urban) is

2.6%, and females 2.1%.

Age distribution nationwide (urban)

Chart 1 illustrates the current age distribution nationwide (urban) from the household

data. As captured in the provincial data given in the annexes, there appears to be an

under-reporting of the number of females in the Pushtoon Belt. In other parts of

Afghanistan a more equal distribution was reported.

Chart 1


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Education

Chart 2a shows the distribution of the levels of education in urban areas nationwide

(urban) (KILM 14)

Chart 2a

Chart 2b shows the same information gender disaggregated.

Chart 2b


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Those that consider themselves literate have been disaggregated by where they acquired

their literacy skills.

It is interesting to note that the percentage of individuals acquiring literacy from themosque is higher than that acquired from literacy in training programs.

For education level province wise see Annex 2a

About five times as many women gained literacy in the mosque as compared to in a

training centre. For men it is twice as many.

It appears that one in two hundred Individuals become literate through attending some

vocational training course. InAnnex 2b this information is duplicated for each skill areawithout gender breakdowns.

In most skill areas, even engineering, there is a significant number of only basically-literate people working in this sector. This could be explained by the fact that in

Afghanistan the titles of Engineer and Doctor are sometimes given to people who do nothave recognized academic credentials.

There are three patterns related to literacy in the different skill areas.

The first, and most common, is typified by Animal Husbandry. This skill area has a largenumber of basically-literate people and a low number of people with higher levels of

education. Other, women-dominated skills, including Kitchen Gardening, are among the

first group.

The second is typified by Auto Mechanics who mainly comprise basically-literatepractitioners, a significant percentage of primary and secondary educated practitioners

and a small percentage of fully literate or university educated practitioners. Some of theskills in the second group are dominated by women, such as Beauty Parlor worker, Bag

Making and Bead Sewing.

As expected, there is a good correlation between more education and the need for highertechnical competency.

The third pattern has an added peak of one particular education level, such as secondary

school graduates in Photography or university graduates in Engineering.

Rose Petal Essence Making which was traditionally dominated by Hindus shows a large

percentage of workers with some primary school (29.6%). In some cases this reflects the

fact that a particular skill area needs certification of some kind or access to information

which a higher level of education facilitates.

There are several skill areas that conform to these three expected patterns although others

appear contradictory. For example, Puncture Repair, which belongs to the third pattern,

involves a large percentage of secondary school graduates (11%). Several ideas havebeen proposed for this but it maybe that the ease of learning this skill, the flexible hours

and decent income, attracts secondary school graduates needing temporary employment

while looking for permanent work.


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22

Incomes

Average incomes by occupation

Charts 3a and 3b shows the number of individuals sampled and their average monthly income byoccupation (SeeAnnex 3Province wise)

22


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23

High income earners include engineers/technicians, medical doctors, wholesale traders

and goldsmiths.

In some provinces (see Annex 4) NGO workers, florists, car sellers, shop keepers,construction site painters, car sellers and, in one case, a large dairy farmer, are also well

paid well paid being a relative term depending on the province and the demands for the

trade/service within the province.

The low end of well paid ranges from Afs. 2,000 in Bamyan to Afs. 13,000 in Kabul.

In some provinces there are occupations with very few people working in them and with

a few people having high incomes. This skews the average income for that occupation.

The charts 4a and 4b below provide an overview of the top 50 occupations for male and

top 30 for females respectively.


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Note:The data pertaining to agriculture in chart 4a and chart 4b does not represent this sector nationwide due to thecover rural areas where agriculture labor can be reached.

Chart 4a

Percentage of Male Working in Each Occuaption Natiionwide

from the sampled Population

0.4 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.6 0.6 0.6 0.7 0.7 0.8 0.8 0.8 0.8 0.8 0.9 0.9 0.9 0.9 0.9 1.1 1.2 1.3 1.3 1.4 1.5 1.6 1.7 1.8 1.8 1.8 1.8 1.9

0

5

10

15

20

Electr

onicR

epairing

Florist

Dairy

Produ

ctWorki

ng

Embroide

ry

Radio

Repairi

ng

AriCo

nditione

r

Mobile

/Tele

phon

eRepa...

TV/V

CRRe

pairing

BarBend

ing

Shoe

Making

Wood

Working

Food

Processi

ng

Punc

tureR

epairing

House

Wiring

HairD

ressing

Vehic

leWiring

Comp

uterS

oftware

Artist

Retired

Auto

Pena

lBeating

Doctor

Plumbing

Tinsmith

Farmer

Photo

graphy

Carpe

tWeavi

ng

Blacksmith

ry

Motor

cycleM

echanic

Shee

tMeta

lFabrica

tor

Cooki

ng/D

omest

icServic

e

Policem

an

Engineer

ing

Kitche

nGarden

ing

Anim

alHusband

ry

Buildi

ngPaint

ing

Orch

ardKeepi

ng

NonG

ovtE

mployee

Bake

ry&C

onfec

tionary

Carp

A u

Occupation

Percentage


25/225

Chart 4b

Percentage of Female Working in Each Occupation NationawideFrom Sampled Population

0.2 0.2 0.2 0.2 0.2 0.2 0.4 0.4 0.4 0.4 0.5 0.5 0 .7 0. 8 1.1 1 .2 1.3 1.3 1.4 1.6 2.1 2.2 2.3

0

5

10

15

20

25

30

Salm

a&SataraW

orking

SilkProd

uctio

n

Artifi

cialFlow

erMaking

EggPro

ducer

Rose

Petal

EssenceM

aking

Utensil

Make

r

Tablo

Maker

/Calligra

phy

Doctor

Engine

ering

Kitchen

Gardening

F

lorist

Policem

an

Comp

uterSof

tware

Food

Processing

Bake

ry&Co

nfectionary

Shopkeepe

r

BagMaking

NonG

ovt Emp

loyee

Bead

Sewing

/Makro

na

Anim

alHusb

andry

BeautyP

arlor

Handicr

aftArtist

GovtEmp

lo y

Occupation

Percentage


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Employment to population ratio

Chart 5 relates to KILM 2 - Employment to Population Ratio.

Chart 5

57.6% of the core working age population (25 to 54 years) is employed nationwide(urban).

47.1% of the working age population (age 15+) is employed, nationwide (urban).

Except for the 15 to 25 year-olds (32.2% employed) it seems that there isnt much

variation in employment as the population ages. 60.1% of the 35 to 54 age group is

employed and 51.0% of the 65+ age group is employed.

Nationwide (urban), and in each of the provinces, the least employed and most numerousof the working age groupings are the 15 to 24 year olds. The fact that they represent the

largest group doing little work is one of the most serious socio-economic and political

problems for Afghanistan to solve. The lack of employment opportunity for this group is

likely to lead to both higher criminal activity and recruitment by undesirable agencies.

(SeeAnnex 5for provincial data.)

Methods of finding work

Chart 6shows the percentage of the sample population and the methods used to find

work.

26


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27

Chart 6

As is the case in many countries, the most common way of finding work in Afghanistan

is through contact with relatives and friends/neighbours.

In 21 provinces (see provincial Charts inAnnex 6), the most common way to find work is

through family connections. In 8 provinces (Farah, Ghazni, Kapisa, Kunar, Kundoz,

Laghman, Nangrahar and Paktika) the most common method of finding work is through

friends/neighbours. In all provinces both these methods rate either as first or second.

Other ways of finding a job were stated as:

The Employment Service Centres (approximately 9%)

Contacting Employers directly. (3%)

Through contacts at the Mosque. (3%)

Newspapers (2%)

The Internet (


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28

In fifty-five occupations the mean hours willing to work is lower than the mean hours

working. In thirteen they are the same and in seventeen the mean hours per week workingare fewer than those willing to work. This latter figure is indicative of significant levels

of underemployment.

Weekly hours worked in only sixteen occupations average fewer than thirty.

(Goldsmiths, averaging fifty-five hours of work per week, have the highest salary but

stated that they want to work fewer hours.)

Sheet metal work, bar bending and auto mechanics all take significant physical effort and

that may account for why the practitioners of these trades also stated that they wanted to

work fewer hours.

There can be many explanations for this desire to work less and further studies are

needed in order to obtain a clearer picture.

Several practitioners of female-dominated and/or handicraft-related occupations statedthat they also want to work fewer hours. These occupations are lace production,

salma/satara (ornate embroidery for clothes) production, silk production and silk worm

rearing, and artificial flower making.

It is possible that women-dominated trades are often the ones done at home and the

women practitioners may feel they are overloaded and desire more free time to make

more social contacts or to do other kinds of work, time for themselves, time for their

children and other household activities.

Other women, such as those working in trades such as makrona (ornate embroidery for

non-clothing items), want to work the same number of hours, or more.


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Chart 7a


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Chart 7b


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31

Informal business data

Data from the Informal business survey is shown in Charts 8 through 17.

A total of 8,570 informal business owners and 1,011 laborers were interviewed thisrepresenting approximately 2% of the informal businesses/informal workers in the 31

provincial capitals surveyed.

Since the study focused on urban capitals, farms and rural production facilities are notrepresented. (Fewer than 100 agricultural businesses were covered)

The businesses were sampled from the myriad of small and mostly unregistered

enterprises which makes up the majority of Afghanistans non-rural economy.

Chart 8 breaks down the total informal businesses sampled into sectors. (Annex 8contains the same breakdown for each province.)

Percentage of informal businesses by sector

Chart 8

The largest sector nationwide (urban), and in twenty-two of the provinces sampled, is

services. In the nine remaining provinces it is second. It represents almost half the

businesses sampled nationwide (urban) (>3,700). The only provincial capital with an

unusually low number of businesses in the service sector is Nuristan.

The next largest sector is construction, which represents more than one-quarter of thebusinesses nationwide (urban). It is about half the size of the service sector. Only in

Badghis, Helmand, Kandahar, Khost, Nimroz and Paktika is the construction sector


32/225

32

significantly less than the service sector. These provinces include those in the unstable

Southern region and construction activity is less in these areas compared to the rest of thecountry.

Badakhshan, Bamiyan, Faryab, Ghor, Herat, Juzjan, Kabul, Logar, Nangahar, Nuristan

and Samangan have large construction sectors.

Nationally (urban), the business and commerce sector is a little smaller than the

construction sector with Badghis, Badakhshan, Farah, Faryab, Ghazni, Ghor, Helmand,

Herat, Kandahar, Nuristan, Panjshir, Takhar and Zabul being representative provinces.

All of these, except Ghor, border other countries and so the business and commerce

sector is expected to be relatively large. Every province that is between Kabul and Heraton the Ring Road built by the Soviets is also in this group.

Total numbers of employees by sector

Chart 9a is a breakdown of total employees by sector for 1386 and Chart 9b is the same

breakdown for 1387.

Chart 9a


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33

Chart 9b

Projected and stated future staff needs by sector

Chart 10 is a projection of the percent of future staff needs broken down by sector.

(Annex 10gives the breakdown for stated staffing needs province wise)

Chart 10


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34

Average incomes

Chart 12a shows the average income (using summed midpoints of ranges), by type of

business stated as net profit.

(For average monthly income province wise seeAnnex 13a)


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Chart 12b shows the percentages of businesses with incomes (stated net profit) greater than

20,000 Afs per month, by type of business.(SeeAnnex 13bfor each province)

Chart 12b

Chart 12c shows the percentage of respondents with incomes less than 10,000 Afs per month,

by type of business.

36


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37

Chart 12c

The overlap between the higher and lower earning enterprises indicates that these businesses

are very common and practiced on both a large and small scale.

Those enterprises having the most significant overlap are general stores; mechanics

workshops, metal workshops, carpentry workshops, restaurants, and tailoring - those tradesbeing in demand and satisfying the Services and Construction sectors.

(See annex 12a for each province)


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38

Number of people employed

Chart 13 shows the stated number of employed people last year (1386) and the number of

employed people this year (1387), by province.

Chart 13

It appears that in some provinces the employment rate in the informal sector has actually fallen

this year compared with last. In most provinces it appears to have remained static.

Employment of women and those having disability in urban-based informal enterprises

In Afghanistan almost no women are employed directly in urban-based informal businesses.

However, 9.6% of employers stated that they would be willing to employ women and 29.9%

stated that they would be willing to employ people with disabilities.

Acquiring skills for employment

Chart 14 illustrates the ways the workers employed in the informal sector learn their skills.

(Annex 16shows this for individual provinces.)


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39

Chart 14

As expected for Afghanistan, and as is the case for the majority of developing countries having

a large informal sector economy, the vast majority of workers learn their skills on the job

through informal apprenticeships. These data appear to confirm this, finding that on average

around 95% of workers learn their skills on the job.

In Farah, Khost and Nuristan, government short courses were stated as being the second most

common method of learning skills for employment with approximately 8% of workers learning

in this manner. Logar appears unusual with 28% stating that they learned an employable skill

through a government course. In Kunar and Laghman the second most common method,

covering approximately 8% of workers sampled, is through an NGO course. (See Annex 16 on

provincial level data)

Day labor pick-up-point data

The following data refers to carpenters, electricians, masons, laborers, painters and plumbers

who were interviewed at labor pick-up points. These groups represent the most numerous and

statistically significant groups and work in the buoyant construction sector.

The following data gives the number of days worked per week, months worked per year, and

the average weekly wage for these key skills areas (KILM 16).

(Note that in cases where the original data appeared inconsistent and could not re-check, the

province has been omitted. Note also that the sample size in approximately 50% of provincialtowns is small. This reflects the fact that approximately 50% of Afghanistans urban centers

are indeed very small, having fewer than fifty small businesses.)

In Kabul, the province with the most interviews per skill, the average number of days per week

worked is a bit less than four. In general, masons, carpenters and laborers work more than in other

skills. Underemployment is likely to be related to the intense competition in the provincial cities,

but it has also been reported that there is great reluctance on the part of artisans such as carpenters

to negotiate and accept a lower daily rates.

The data also reflects seasonal variation with many artisans working fewer than nine months per

year. In the winter months construction site activity lessens, and in the summer months, especiallyin the more fertile provinces, alternative livelihood opportunities are likely to be available.


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40

Carpenters

Chart 15a

Chart 16a


41/225

41

Chart 17a

Chart 18a


42/225

42

Electricians

Chart 15b

Chart 16b


43/225

43

Chart 17b

Chart 18b


44/225

44

Masons

Chart 15d

Chart 16d


45/225

45

Chart 17d

Chart 18d


46/225

46

Painters

Chart 15e

Chart 16e


47/225

47

Chart 17e

Chart 18e


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48

Plumbers

Chart 15f

Chart 16f


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49

Chart 17f

Chart 18f


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50

Number of years worked by day laborers

Chart 19 shows, respectively, the numbers sampled and percentage of urban day laborers by

the number of years they have worked in their current skill area.

Chart 19

In most skill areas there is a bulge in numbers in the 1-10 year experience age range followed

by a diminishing number in the 10-25 year experience range and again followed by a another

peak in the >25 year experience range.

This is consistent with a post conflict, conflict and pre-conflict labor market situation.

Before 1983 the security situation made it easier to learn a trade and find consistent work, and

this older age group are still working and have >25 years of experience.

After 1983 and during the period of conflict, the construction sector to which these trades

belong stagnated and/or contracted and hence the demand for labour stagnated or contracted.

The optimism of 2002-2004 created a large construction boom in many places and attracted a

large number of people to the construction trades. This is seen in the increased numbers in the

experience age range 1-10.

For painters, masons and carpenters, there appears to be a fall in the number of having only

recent experience and is, perhaps, indicative of a tailing off of optimism in the construction

sector and/or saturation of the market.


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51

Education levels and age distribution of day laborers

Chart 20a breaks down the education level of the respondent day laborers (KILM 14 but only

for day workers).

Chart 20

Overall, a majority of day laborers consider themselves as not literate (57.2%). This is more

than twice as large as for the general male population (22.5%).

Chart 20a breaks down the age distribution of day laborer into four age groups.

Chart 20a

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

45.0%

Percentage

14-25 25-34 35-54 55-70

Age group

Skilled day laborer by age group


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52

Formal business data

444 formal (registered) businesses filled out their questionnaires. This is about 2% of those

listed as members of AICC or registered at AISA. (The formal sector questionnaire was self-

administered.)

The chart 21 shows the percentage of employees, by sector in the formal sector

Chart 21

Percentage of employees by sector for the formal sector

0

10

2030

40

50

60

Manufucturing Construction Commerce Agriculture Services

Sectors

Percentage

Male

Female

Chart 22 is a breakdown of the percentage of total employees by sector and by occupation

types. (Management/Administrative, Professional/Technical, Skilled, Unskilled and Other,respectively) (KILM 4).

Chart 22

While all sectors are dominated by men, the Business and Commerce Sector has the most

gender equity. Manufacturing has the high percentage of skilled employees. As expected, an

overwhelming majority of workers in Manufacturing and Construction are male.


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53

Future staff demand in the formal sector

The questionnaire asked formal-sector business owners to express their future staff demand,

disaggregated by sector and employee types Management /Administrative,

Professional/Technical, Skilled, and Unskilled, respectively.

The responses indicated that for the Agriculture, Construction, Manufacturing and Services

sectors, there was still a significant demand for more unskilled workers. It was not clear from

the responses whether employers were finding it difficult to recruit unskilled workers. For the

Commerce and Services sector, employers stated that they would like to recruit more

professional and technical workers. This is likely to cover financial and administrative skills.

Export activity

Chart 23 shows the percent of enterprises in each sector that exports some products.

Chart 23

The percentage of formal businesses in agricultural sector that export is greater than in other

sectors, despite the urban nature of this survey. The primary recipients of the agricultural

products are in Pakistan and Iran.


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54

Employment of foreigners

Chart 24 shows the percentage of enterprises in each sector which hire foreigners. The

Construction and Services sectors hire most foreigners. In both of these sectors many

Pakistani, Chinese, Indian, and Iranian workers employed, and most are skilled and semi-

skilled. Further study is needed in this area to ascertain more precisely why Afghan workersare not being hired. A previous rapid study held by the NSDP indicated that it was not so mu

ch a question of Afghans not having the required skills, but more a question of immigrant

workers being managed more closely and housed in low cost hostel accommodation. In some

cases it was stated that immigrant construction workers had more specific and more finely

honed skills than Afghans.

Chart 24

Business expansion and contraction

Chart 25 reports respondents ideas concerning whether their businesses expanded or

contracted in the past two years.

Chart 25

While more enterprises in the Business and Commerce sector, and the Manufacturing sector

have contracted, the majority of enterprises questioned stated that they plan to expand their

businesses in the next two years


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55

Data from vocational training centers

143 urban-based Vocational Training Centre (VTC) managers/service providers were

interviewed.

In the sample almost 50% of the VTCs were managed by NGOs. 40% are privately managedand 10% government managed.

Courses being taken

Chart 26a and 26b shows the percentage of the total, male and female trainees, respectively, in

training in each course type.

Chart 26a

Percentage of Male Students Enrolled in Vocational Courses

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0 .2 0.30 .3 0.3 0 .3 0.4 0.4 0 .4 0.40 .4 0.40 .5 0.6 0.7 0.7 0.7 0.7 0.8 0.8 0.9 1.1 1.1 1.2 1.5 1.6 1.8 1.92.6 3.1 3.5

5.7 6.68.6

19.8

28.5

0.05.0

10.015.020.025.030.0

Drivin

gCourse

BagK

nittin

g

Comp

uterH

ardwa

re

Blacksmith

ry

BeeK

eepin

g

Drawing

Miniatur

e

Sculptur

eMaking

Swee

pMaking

Tajwe

ed

Vehic

leWirin

g

DariL

anguage

FruitD

rying

Archite

cturing

Agriculture

Generat

orRe

pairin

g

Maths

Mana

geme

nt

Quran

Mem

orizin

g

Motor

cycle

Rep

airing

Anim

alHu

sban

dry

Vehic

lePa

inting

Masonry

Lathe

Working

Auto

PenalB

eatin

g

TVRepairing

Mobil

eRep

airng

Tinsmith

ry

Embro

idery

Child

ernRigh

t

HealthE

ducatio

n

Metal

Work

Islamic

Jurispro

dence

Weldi

ngWorking

HouseW

iring

Plumbing

Carpe

ntry

Carpe

tWeavin

g

Auto

Mechanic

Scho

olSubje

cts

Tailo

ring

Vocatio

naltr

aining

English

Comp

uterS

oftwa

re

Name of Courses

Percentage

ofStuden

ts

Chart 26b

Percentage of Female Students Enrolled in Vocational Courses

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.3 0.3 0.3 0.3 0.3 0.4 0.4 0.4 0.5 0.5 0.7 0.7 0.7 0.7 0.7 1.2 1.7

3.5 4.57.6

9.0 10.611.0

13.5

26.0

0.0

5.0

10.0

15.0

20.0

25.0

30.0

BagK

nitting

Confe

ctiona

ry

Food

Proc

essing

Agric

ulture

BeeK

eepin

g

Salm

aSata

rawo

rking

Swee

pMaki

ng

Maine

ture

Sculp

tureM

aking

Caligr

aphy

DariL

angu

age

RugW

eavin

g

Curta

inWe

aving

BagW

eavin

g

CapW

eavin

g

Cotto

nWea

ving

Draw

ing

Lace

Work

ingMa

ths

Beed

Wea

ving

Hand

Embro

idery

Beau

tyPa

rlor

Jacke

tKnitt

ing

String

Wea

ving

Childe

rnRig

ht

House

Wirin

g

Jam

Makin

g

Healt

hEdu

cation

Islami

cJuri

sprod

ence

FruitD

rying

Weavi

ng

Scho

olSub

jects

Voca

tional

trainin

g

Carpe

tWea

ving

Embro

idery

Comp

uterS

oftwa

re

Tailor

ing

Englis

h

Name of Courses

Percentage

ofStudents

In every province close to 30% of enrolled students are taking computer software and English

courses and the second largest element among male and female is English and tailoring

respectively.

Computer software and English skills are likely to be in demand across the urban areas of

Afghanistan, as are most construction sector skills, but at present it is known that most

vocational training centers are not carrying out local labor market surveys or tracer studies and

so the course supply, in general, is unlikely to reflect the demand in the labor market. In the

case of tailoring and embroidery, and other skills which are often performed by women, there

is likely to be an oversupply of trainees and a consequent high rate of underemployment.


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56

Curriculum source

Chart 27 shows that most vocational training providers use their own curriculum and materials

(about 45%).

Chart 27

Although the NSDP is starting the process of developing standards, and supporting the

establishment of a modern, levels-based and competency-based Qualifications Framework for

Technical and Vocational Education and Training (TVET), it will take a number of years

before skills development institutions adopt modern approaches and have available to them

more relevant curriculum, and a cross-sector accreditation and certification system.


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57

References

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Afghanistan Information Management System, Kabul District Maps,Afghanistan Information

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The Asia Foundation (2007),Afghanistan in 2007: A Survey of the Afghan People,The Asia

Foundation, Kabul, Afghanistan

Beall, J. & Schutte, S., (June 2006), Urban Livelihoods in Afghanistan, Afghanistan Research

and Evaluation Unit, Kabul Afghanistan.

Central Statistical Office (2003),Estimated Population of Afghanistan, Transitional IslamicState of Afghanistan

Gray, L. et al. (1993),Reducing the cost of technical and vocational education: a report to the

Overseas Development Administration,ODA Education Paper No.3

Gray, L., Warrender, A.M., Davies, P., Hurley, G, (1996).Labour Market Signals &

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International Labour Organization (1982)Resolution concerning statistics of the economically

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thirteenth International Labour Conference of Statisticians.

International Labour Organization (1987),Resolution concerning the revision of the

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Labour Conference of Statisticians.

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the informal sector, adopted by the fifteenth International Labour Conference of Statisticians.

International Labour Organization (1998).Resolution concerning the measurement of

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International Labour Organization (2008),Afghanistan: Towards a Resuscitated Labour

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59

Annexes

Annexes

Annex Name

Annex 1 Manual for enumerators on Questionnaires

Annex 1a Household questionnaire

Annex 1b Formal businesses questionnaire

Annex 1c Informal businesses questionnaire

Annex 1d Individual skilled labor questionnaire

Annex 1e Vocational training centres questionnaire

Annex 2a Education levels province wiseAnnex 2b Education levels with gender breakdown province wise

Annex 3 Number of people working, by occupation, province wise

Annex 5 KILM2-Employment to population ratio in provinces

Annex 6 Methods of finding work province wise

Annex 7a Average hours working per week by occupation province wise

Annex 7b Average hours willing to work per week by occupation province wise

Annex 8 Informal business by sector for each province

Annex 10 Informal business, stated staffing needs, province wiseAnnex 12a Low earners province wise

Annex 13a Average monthly income province wise

Annex 13b Percentage at the 122 informal enterprise type earning more than

AFS.20, 000 per month province wise

Annex 16 How do your workers learn their skills, province wise


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Annex 1

Islamic Republic of AfghanistanMinistry of Labor, Social Affairs, Martyrs and Disable

National Skills Development ProgramLabor Market Information Analysis Unit

Enumerators

Manual


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2

Objectives of the project: Collection, processing, analysis and disseminating information in regards to thestatus of supply and demand in the labor market in the 34 provincial centers of the

country.

Developing technical and administrative capacities for implementing surveys andlabor market studies in the future.

Definitions:

Who is the enumerator?

With respect to this survey, an enumerator is a person who is collecting data through

conducting interviews after being trained and assigned by the Programme. It is worth

mentioning that in this survey besides the face to face interview the self administeredmethod will also be utilized. In self Administrated method the survey forms will be

delivered to interviewees and they will be asked to fill it themselves. The enumerator

goes back and collects the completed forms.

Enumerators are playing key roles in the survey and their impact in quantity and quality

of the data is considered significant.

Responsibilities of the enumerators

1. Keeping the confidentiality of the collected data is one of the main responsibilitiesof the surveyors. The enumerators under no circumstances and conditions can reveal or

disclose the collected data to any organization or individual.2. The usage of the collected data for personal or business purposes is highlyrestricted.

3. To hand over the survey forms to the project's assigned staff and obtain its receipt.4. Before returning questionnaires to the office, surveyors should make sure that theforms are thoroughly filled out, if any question have remained unanswered, the

enumerator should try to complete that.5. The enumerator must write the exact answers of the interviewee and without anychanges in the questionnaire. However, spellings correction is allowed.

6. The enumerator should respect and observe the values, beliefs and traditions ofthe interviewees and avoid raising any issues that cause political, social and security

conflict.

What is an interview and how it should be held?

With respect to this survey, interview refers to the conversation held between the

enumerator and the interviewee. During the interview enumerator seeks response to thequestions asked in the questionnaire.


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The Enumerator must take the following points into consideration:

1. After greetings, the enumerator should show his/her identity card to theinterviewee and politely illustrate the purpose of the survey in order to attract theinterviewees trust.

2. Efforts should be made to conduct the interview in native language of theinterviewee.

3. The way dressed, body language, and speaking determined the first impression,therefore enumerators shall try to avoid wearing unusual dress and do not use impolite

words and gestures.

4. The interviewees should be assured that the information collected will beconfidential. Interviewees shall clearly understand that the information they provide is forthe sole purpose of statistical studies.

5. Once the interviewee is ready for the interview, then the enumerator can startasking questions. In order to an interviewee understand the questions, enumerator shallspeak slowly and clearly.

6. After finishing the interview, the enumerator should review all the questions andanswers to assure that all the questions are answered and none of them left unanswered.

7. After the interview is completed, the interviewer must extend his/her specialthanks to the interviewee and leave the place.

Questionnaire in this Survey:

With respect to this survey, the questionnaire is composed of one or more pages through

which the information and data of labor market is being collected.

In this survey four questionnaires have been designed and prepared. The usage andcontents of each questionnaire will be discussed in more detailed.

Informal Sector:

The most important characteristic of businesses include in this sector is that the

government is not involved in that business, or in other words, one or more person start abusiness without government being involved.

Household:

One or more people live under one roof and have common income and expenditure iscalled a household.

Formal Sector:

Contrary to the informal sector, this type of business is formally registered with the

government, or in other words, the government is involved in this kind of business.


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Publicly Listed Companies:

Publicly listed Companies are the establishments that earn their capital through the sale

of shares issued to the public. The ownership of such companies belong to theindividuals, employers and investor institutions.

Cooperative Business:

The ownership of this business belongs to its members.

Sole Proprietorship:

In Sole Proprietorship one person is the owner of the business.

Vocational Training Centers:

Vocational Training Centers are those kinds of Centers that provide vocational trainingand education for their beneficiaries. These centers are administrated by government,

NGOs, private institutions and people. The expenditures of such centers are funded by

government, NGOs, international aids and by people through paying fees.

Corporation Companies:

It is a legal entity owned by individuals and shareholders

Limited Companies:

It is a legal form of business offering limited liability to its owner


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Chapter 2

Guideline for Questionnaires

A) Informal Sector Business QuestionnaireB) Technical & Vocational ET Center QuestionnaireC) Formal Sector Enterprises QuestionnaireD) Household QuestionnaireE) Individual( Tradesman ) QuestionnaireA) Informal Sector Business QuestionnaireThis questionnaire has been planned to collect information about Informal Organization.

How to fill the form?

1.1Name of Organization:Write the complete name of Organization clearly/legibleDate of started: The date organization has practically started its work.

1.2Owner name:The answer to this question is optional. If the interviewee does not like to mention his/her

name in the questionnaire, the enumerator shall skip this question.

1.3Province:Write down the name and code number of the province in which the business is located.

The complete list of provinces code-number is included in the annex number ( ) of thisguideline.

1.4City:Write down the name and code number of the city where the business is located in. For

filling the city code number please refer to the annex number ( ).

2.0 Basic data:

2.1 Number of current and last year full time staff/employees including owner

2.1.1 Number of male employees (write the number)

2.1.2 Number of female employees (write the number)

How many of the employees are family members of the enterprise owner? Write the

number.


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Total of Employees:

The total number of employees should be written in figures.

2.2 Last year employees2.2.1The Number of male employees should be written in figures.

2.2.2 The number of female employees should be written in figures.

2.2.3 The total number of last year employees should be written in figures.

2.3 Job title and salary range of the above employees

2.3.1 Job title:

In this row you can ask about the number of employees whom were given information inthe previous question. For example: You go to a panel beating workshop and have

interview with owner of the workshop. You ask the owner that how many employees

does he/she have? He/she answers that I have 4 employees. Then you will ask him/herthat what are they doing or what are their Job titles? He/she tells you that one person is a

panel beater second one is a welder, third one is doing wiring and the fourth one is apainter. Now what you do is to write in the box ( 2.3.2) theirs job title. Then you ask the

interviewees that the monthly wages/salary of his/her panel beater fall in to which one of

the following five categories? (Please read out each category) Suppose the answer is

(7500 Afs per month) now you write (x) in the box of 2.3.2 under the row of more than6100/m .you use the same method with the welder, wiring man and painter.

2.4 How many more employees do you require?

Write the number beside the question. What skills considered most important for your employees? Write (x) for one ofthe four given answers.

If the answer is out of the three mentioned categories then write your specified answer.

Would you be interested in taking apprentices?

Write (x) for yes or no answer

Would you consider employing a woman?Write (x) for yes or no answer

Do you need other staff?Write (x) for yes or no answer

Would you consider employing disables?Write (x) for yes or no answer

If the answer is no, then the reason should be asked. One of the reasons of not employing

disables will be: because this job needs physical activities and the disables will not be

able to afford it.

8/12/2019 An Urban Area Primary Source Study of SupplyDemand in the Labor Mark

An Urban Area Primary Source Study of SupplyDemand in the Labor Market(en)

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