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Action ‘ESSnet on the harmonisation and implementation of a European socio-economic classification (ESeG)’

WP2 - Expertise of the basic variables

Technical report

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1. Introduction..................................................................................................................................3

2. Results of a NSIs consultation on data collection and coding in the LFS, Eu-Silc and Aes........5

2.1 Potential sources of non sampling errors on the variable occupation..................................5

2.2 Potential sources of non sampling errors on the variable ‘economic activity’..................13

3. Some troublesome areas of Isco08 and Nace rev.2....................................................................16

4. The Italian experience to assess and improve data accuracy on occupation..............................19

5. The difficult areas of Nace rev2 and the quality assessment on the coding activity.................24

6. Some coding tools for occupation: the Dutch experience..........................................................30

7. Time comparability of the occupation series in the LFS............................................................32

8. Time comparability: the Dutch experience................................................................................34

9. Time comparability: the French, Italian and Danish results......................................................42

10. Cross-comparison of the ISCO-88 and ISCO-08: the Czech experience...............................44

Appendix 1. Target variables.............................................................................................................49

Appendix 2. Questionnaire to ESS NSIs in the framework of the ESSnet on the European socio-economic groups (ESeG)....................................................................................................................50

Appendix 3 - Differences on the Percentages of the Occupation by Major Groups according to Isco08 and Isco88 (3rd quarter 2011-2010).......................................................................................56

Appendix 4 - Isco08 Major groups: incoming (from Isco88) and outgoing (to Isco08) unit groups.60

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1. Introduction

The aim of the report is to document the quality of the main variables potentially involved in the ESeG prototype, with a particular emphasis on the quality of ISCO2008.

In fact, as cited at pag. 31 of the grant agreement, the first of the four specific objectives of the action is to ‘test the quality and the strength of the core variables which will be the basis of the Socio-economic classification’.

To reach this objective, a specific Work package was scheduled within the action, that is Wp2 ‘Expertise on the basic variables’.Table 1 lists the target variables potentially used for the ESeG construction whose quality might be under evaluation and the national surveys that might produce data on target variables.

Table 1 – Target variables and statistical processes potentially used in the ESeG construction and validation (see the details in Appendix 1)

Target variables potentially used for Esec Social Statistical processes Status in employment Occupation in employment Economic sector in employment

1. Labour force survey2. Eu-silc3. Household budget survey (HBS)4. Adult education survey (AES)5. ICT usage in households and by individual (ICT)6. European health interview survey (EHIS)7. Time use survey (TUS)8. Census9. Structure of earnings survey (SES)

The quality evaluation proposed by WP2 has to tackle two different issues depending on the type of variables considered. In fact, on the one hand we deal with variables such as the status in employment that are/should be:

- strongly harmonized and consolidated within and between the surveys;- relatively simple to answer for a respondent;- with a relatively small set of answers to choose.

On the other hand, dealing with occupation or economic activity variables generally means to face with:

- a relatively huge set of answers to choose (Isco08 proposes 436 unit groups to choose, Nace rev2 615 4th digit codes);

- classifications that may leave room for a slight different interpretation of their objects, even though they seek to avoid it;

- coding processes (i.e. the way in which individual responses are brought back into a classification scheme) that might affect the results but that nevertheless have not been harmonized between NSI and between the surveys.

This lead us to think that the quality evaluation of data stemming from the use of a classification needs a supplementary set of metadata in order to give a more realistic ‘state of the art’ of data quality.Moreover, both the Nace and the Isco classification have recently gone under an updating process and this may be the cause of some inconsistencies on the time series that is worthwhile documenting.

When dealing with the setting-up of an evaluation study on data quality the general framework proposed by Eurostat (see Table 2) is surely the guideline.

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Table 2- Eurostat framework to assess the quality of statistical processes and their outputs

Quality Dimensions Definition1. Relevance degree to which statistics meet current and potential users’ needs2. Accuracy the closeness of estimates to the exact or true values3.1 Timeliness The length of time between its availability and the event or phenomenon it

describes3.2 Punctuality time lag between the date of the release of the data and the target date (the

date by which the data should have been delivered)4. Accessibility and

clarityRefer to the physical conditions in which users can obtain data and whether data are accompanied with appropriate metadata, illustrations such as graphs and maps

5. Coherence statistics originating from different sources convey coherent messages6. Comparability extent to which differences between statistics are attributed to differences

between the true values of the statistical characteristic7. Confidentiality the privacy of data providers (households, enterprises,

administrations and other respondents), the confidentiality of the information they provideand its use only for statistical purposes

In this report we will concentrate on 3 out of the 7 dimensions that are: accuracy, coherence and comparability.As far as accuracy is concerned we will try to give different types of contribution. On the one hand we would like to give (see par. 2) the results of a consultation with NSIs who were asked to give information on some possible sources of measurement errors, which can eventually contribute to a lack of accuracy on the estimates. Moreover in par. 3, we will try to put light on specific areas of Isco08 which seem to be more problematic.On the other hand, we will present (see par.4) the Italian experience who have set up a monitoring system to assess and improve data quality of occupation in terms of accuracy. Paragraph 5 is devoted to Nace rev.2 presenting the more troublesome areas and the monitoring system developed to assess data quality.Finally in par. 6 we will present the rationale of the software Cascot implemented by Statistics Netherlands for coding occupations in social surveys.

Regarding the time comparability, paragraph 7 will give elements to assess the impact of the new Isco08 on data distribution. More precisely par. 8 will widely present the Dutch experience and par.9 the results of three countries: Denmark, France and Italy. As far as coherence is concerned we will take under consideration the estimates produced by three different statistical processes, such as the labour force survey, the Structure of Earnings Survey and the Adult education survey and we will present how they convey a consistent message. In particular, paragraph 10 presents the Czech analysis devoted to the cross-comparison between the results of 2010 Labour Force Survey and the provisional results of 2010 Structure of Earnings Survey according both to Isco08 and to ISCO-88.

The accuracy dimension

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2. Results of a NSIs consultation on data collection and coding in the LFS, Eu-Silc and Aes

In May 2012 a consultation among the National Statistical Institutes was carried out in order to get a general background on how the variables ‘occupation’ and ‘economic activity’ are collected and coded within three main statistical surveys: the Labour Force Survey (LFS), Statistics on income and living conditions (EU-Silc) and Adult Education Survey (AES).

The idea beyond the consultation was that getting information on the type of question wording used to collect data, on the way in which the coding activity is performed and on the way in which the national classification is converted into the international one, can help in understanding the potential sources of non sampling errors, which can eventually contribute to a lack of accuracy on the estimates.

A short questionnaire (see Appendix 2) was developed in order to document the NSIs practices on data collection and treatment. The questionnaire was sent to the 27 EU countries, to the 4 EFTA countries and to the 7 CC/PCC countries. We got the replies of 26 out of 27 EU countries (Greece didn’t reply), 2 out of four Efta countries (Liechtenstein and Iceland didn’t reply) and 5 out of 7 CC/PCC countries (Serbia and Montenegro didn’t reply).

2.1 Potential sources of non sampling errors on the variable occupationAs suggested by ILO, <<…for an accurate coding to any level of Isco08 and related national classifications, information is needed on the following:

Name or title of occupation Main tasks or duties usually performed in the job.>>

Hence, one of the first metadata we would like to get is the type of data collected by the different surveys in the different countries in order to come up with information on occupation.

As far as the Labour force survey is concerned, 28 out of 33 countries follow Ilo suggestions, asking both the name and the main tasks or duties performed.

Moreover, three out of these countries (Germany, France and Spain) ask, and use to code occupation, additional information related to the firm size and skill (France), the complexity of the tasks performed and leadership/supervisory functions (Germany), the qualification requested for the position, professional status, supervisory responsibilities (Spain).

No country mentioned the type of economic activity of the establishment or whether or not the main aim of the activity is own consumption, which are listed by ILO as useful additional information. Five countries (Switzerland, Luxembourg, Finland, Austria and Ireland) collect only the job title.

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Figure 1 - Type of data collected to code occupation in the LFS (percentage values of answers given by 33 countries )

15%

76%

9%

only job titles

job titles and the workactivities titles, activities andother variables

If we move to EuSilc, 14 out of 31 countries1 don’t use the same question wording of the LFS (Belgium will have harmonized them by 2013). The main reasons of the difference are:

1. reference to a different concept (Austria for instance refers to the occupation (“Beruf”) in the LFS, while in SILC to employment in general (“Erwerbstätigkeit”); Spain asks in LFS “What is the occupation or type of job which you carry out?” (“¿Cuál es la ocupación o el tipo de trabajo que desempeña?”) and in EU-SILC: “In your main job, what occupation, profession or trade do you carry out?” (“En su empleo principal ¿cuál es la ocupación, profesión u oficio que desempeña?”);

2. fewer questions (for instance only the job title or only the main activities performed or);

3. different time reference period.

A similar situation is registered for AES, conduced by 27 of the 33 countries2, where 12 countries use a different question wording for the same reasons expressed for Silc.

Moreover, some countries (Denmark and Norvegia) prefill the question on occupation with register data and ask respondents to confirm or correct the information. Respondents for whom register data

1 Two of the responding countries don’t carry out the survey (Albany and Bosnia Herzegovina)

2 Macedonia, Croazia, Albania, Bosnia Herzegovina, United Kingdom and Switzerland don’t carry out the survey6

on occupation are not available, and respondents for which the register data is incorrect, are asked questions that are identical to the LFS.

We have analysed another aspect that can have an impact on data quality: the coding process.

When, by whom is it carried out? Is it supported by some IT tools?

These are the questions that have been asked to the countries for the three surveys.

Most of the countries (18 out of 33) perform the coding activity of the Labour force survey always after the interview process, that means without the possibility, if needed, to get more details from the respondent, while two countries (Germany and Ireland) do that always during the interview.

The countries who perform the coding activity both during and after the interview process have given an estimate of the coding percentage performed during the interview. This percentage has a wide range, going from 5% in Spain to 97% in Switzerland. However, in most of the cases it is not possible to determine whether the coding has been performed during or after the interview.

The practice adopted by Eusilc and Aes reflects the one of the LFS. Over one third of the countries perform the coding activity both during and after the interview process, sometimes (Poland and Luxemburg) recalling respondents for further information.

Despite that, 8 countries choose different coding strategies across the three surveys.

(n.a. refers to the countries that don’t perform the survey or that don’t perform the coding activity as they use registers)

7

0

5

10

15

20

25

only during theinterview

only after theinterview

both during and afterthe interview

N.A.

LFS

EUSILC

AES

Figure 2 - When is the occupation coding performed? (Answers of the 33 countries)

Moving to the subject who performs the coding activity, all the three surveys more frequently make use of experts.

This result goes together with the previous one, related to the great number of countries that performs the coding after the interview. When the surveys make use of more than one kind of coder (the mixed mode), the most common situation is the use of Capi/cati interviewer together with experts.

Figure 3 - By whom is the occupation coding performed? (percentage values of answers given by 33 countries)

0,0

10,0

20,0

30,0

40,0

50,0

60,0

Capi/Catiinterviewers

Papi interviewers Experts Mixed mode(a)

LFS

EUSILCAES

(a) Mixed mode means Capi/cati interviewers and experts (8 countries use this mode for the LFS, 7 countries for Eusilc and 5 for Aes) or Papi and experts (1 country uses this mode for the LFS, 2 countries for Eusilc and 2 for Aes) or Capi/Cati interviewers and Papi (2 countries use this mode for the LFS, 1 country for Eusilc and 1 for Aes)

Just in a few countries (Bulgaria, Czech Republic, Germany, Hungary, Latvia, Poland and Slovakia) Papi interviewers are involved in the coding process, while only Luxemburg and the Netherlands relay on respondents for AES occupational data coding.

In more than 80% countries3 the coding process is supported by IT tools (that is, for instance, software to look for job title codes). In 23 countries this practice is common to all the three surveys; on the contrary, 4 countries make no use of IT tools and 6 countries relay on them for at least one of the surveys.

3 Six countries (Croatia, Albania, Cyprus, Malta, Romania, Luxembourg) declare not to use IT tools in the LSF, two of these (Croatia and Cyprus) instead make use of IT tools in Eusilc; Macedonia, Denmark, Malta, Poland, Romania and Luxembourg don’t use IT tools in the Eusilc; Malta, Poland, Romania, Hungary and Luxembourg don’t use IT tools in the AES.

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Here in the following we propose a summary of the IT tools/procedures used in the 3 surveys by the responding countries. The tools are quite different as far as their complexity level is concerned:

Excel files containing a list of job titles with the corresponding occupational codes; these lists are often integrated in the data entry program and sometimes include hints on the basis of auxiliary variables;

Use of the software Blaise to search for a text string; Routine for trigram search or hierarhical search; Combo box with a list of job titles and related codes; Electronic list of job titles /activities and synonyms with a search engine integrated in the

data entry program; Cascot (see par. 5 for more detail); Routine proposing alternative codes to a given keyword: coders write the job title and the

computer automatically searches for a suitable code; if computer finds several codes, the coder is expected to choose the most appropriate one;

Software to look for names and description of occupations, to browse the classification and read the main duties and activities performed, or know the mapping of the specific occupational unit to Isco 08 code.

We also asked if any consistency checks between occupations and other variables are performed and, if yes, when these checks are done.

For the LFS and EUsilc, more than 60% of the responding countries declare to perform consistency checks, while this percentage is quite lower (48.1%) for AES. In this survey, all the checks are

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Figure 4 - Countries supporting the coding process with IT tools

(percentage values on the number of countries that conduct the survey)

80,0

80,2

80,4

80,6

80,8

81,0

81,2

81,4

81,6

81,8

82,0

LFS EUSILC AES

performed after the interview process; that means without the possibility to solve with the interviewed the inconsistencies. As far as LFS and EUsilc are concerned, 7 countries (Austria , Croatia, Italy , Latvia, Poland, Spain and Turkey) perform consistency check both during and after, so more than 70% of the countries do it only after the interview process.

Table 2 - Do you perform consistency checks between occupation and other variables? (percentage values on the number of countries that conduct the survey)

NO YES

If yes, do you perform them during or after the interview

After the interview

Both during and after

LFS 36,4 63,6 71,4 28,6

EUSILC 32,3 67,7 80,0 20,0

AES 51,9 48,1 100,0 0,0

The type of consistency checks performed by the responding countries are different. They control for instance the plausibility between occupation and:

- education levels and NACE, as some combinations are impossible;- performed work activities, educational attainment, economic activity, size of the workplace, supervisory responsibilities;- firm size (or size of the exploitation for farmers), tasks, skill, public/private, level of education;- occupation registered at previous interviews;- level of income.

Some countries have developed soft and hard rules within the questionnaire routine to give the interviewer warnings on the type of inconsistency he/she has to try to solve with the help of the respondent.

Moreover, we have asked the countries if they perform other checks on the quality of the occupation coding, to assess for instance if there is coherence between the job title and the chosen code.

Approximately half of the countries perform this kind of quality checks for the LFS, while this percentage is 42% for Eusilc and 26% for Aes.

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Figure 5 - Countries performing checks on the occupation quality (percentage values on the number of countries

that conduct the survey)

0,0

10,0

20,0

30,0

40,0

50,0

60,0

LFS EUSILC AES

The most common practice is to compare the given job title and job description with the one given by the classification to the chosen code. Some countries also perform longitudinal control in order to check, whenever a person didn’t change the job, the time coherence of the occupation code. One country (Malta) perform an independent double coding, while Slovenia compare data on occupation with the Statistical Register of Employment. In Sweden reconciliation is used.

The main complaint of the countries regarding this activity is the scarce information stemming from the collected data. In fact, respondents seem to give very generic hints that are difficult to translate into a specific occupational code.

Asked for the more problematic occupational areas to code, countries seem to converge on the following:

- job titles that refer to ‘managerial occupations’ could actually be coded into MG 1, 2 or 3. The available information is frequently insufficient to make a proper choice;

- it is not straightforward to figure out if an occupation is a skilled or unskilled one (especially in the agricultural area) and consequently to choose for the 6 th or 9th MG is not a trivial matter;

- with the available information it may be difficult to identify the border between a process control technician (to classify in 3rd MG) and a plant and machine operator (8th MG).

Is Isco08 directly used to collect data or are data collected and first coded making use of the national classification and then converted into Isco08?

33% of countries directly use Isco08 to collect data for the LFS, while the same percentage is more than 35% for Eusilc and 48% for AES.

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Some countries collect data using a list of job title which has a double code, one into Isco08 and the other into the national classification.

Figure 6 - Countries making a direct use of Isco08 to collect data (percentage values on the number of countries that

conduct the survey)

0,0

10,0

20,0

30,0

40,0

50,0

60,0

LFS EUSILC AES

Countries that first use the national classification and then convert it into Isco08 mainly use conversion tables as a method; Netherlands and France have developed conversion routines that make use of ancillary variables (for instance the size of enterprise and level of education).

Finally, for some countries the national classification is identical to ISCO-08 up to the 4 th digit level, hence the conversion into Isco is not required.

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2.2 Potential sources of non sampling errors on the variable ‘economic activity’

What kind of data do you collect with the LFS questions on economic activity?

In the LFS approximately 45% of countries collect the name of the economic activity performed and/or a full description of the goods and services produced in the local unit and relay on this information to attribute a code; the others look to the name and the address of the local unit and get its Nace code from business register.

The same question wording as LFS is used by twenty-one out of 31 countries who perform eusilc and by 16 out of 27 countries who perform AES.

The main reason why countries use a different wording is to make it simpler, even though this means collecting less information.

Most of the countries perform the coding activity after the interview process and this practice could explain the great percentage of countries who delegate the coding to the experts rather than to the interviewers. Almost one third of the countries relay on more than one kind of coders (mixed mode) in all the three surveys; the favourite combination is Capi/Cati interviewers and experts.

0

2

4

6

8

10

12

14

16

18

Capi/Catiinterview ers

Papi interview ers Experts Respondents Mixed mode(a)

LFS

EUSILCAES

Figure 6 - By whome is the economic activity coding performed? (percentage values of answers given by 33 countries)

(a) mixed mode means Capi/cati interviewers and experts (6 countries use this mode for the LFS, 5 countries for Eusilc and 3 for Aes) or Papi and experts (1 country uses this mode for the LFS, 1 country for Eusilc and 3 for Aes) or Capi/Cati interviewers and Papi (3 countries use this mode for the LFS, 1 country for Eusilc and 1 for Aes)

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For the AES, three countries (Finland, The Netherland and Luxembourg) give the respondent the duty to choose the code.

Most of the countries support the coding activity with IT tools; the type of tools is quite different, as it was the case already seen for the occupation.

Figure 7 - Countries supporting the coding process with IT tools (percentage values on the number of countries that

conduct the survey)

64,0

66,0

68,0

70,0

72,0

74,0

76,0

78,0

80,0

82,0

84,0

LFS EUSILC AES

They are, for instance:

Combo box with a list of activity to choose Use of the software Blaise to search for a text string; Routine for trigram search or hierarhical search Search-engine upon a list of economic activity titles, and a choice of Business Register Engine to make a full text search of the enterprise by name or by street Cascot electronic list of activities and synonyms with a search engine Software to look activity codes and their short definition corresponding to classification

If we look at the LFS and Eusilc, more than half countries (percentage is lower for AES) perform consistency checks between economic activity and other variables like: status in employment (for instance workers in public administration must be employees), occupation (for instance agriculture versus agricultural related occupations, education versus teaching occupations; health versus medical occupations), public versus private sector, type of contract (for civil servants), place of work, enterprise dimension and level of education. Checks are mainly carried out after the interview

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process; only 7 countries (Austria , Croatia, Italy, Latvia, Poland, Spain and Turkey) perform them both during and after the interview in LFS and Eusilc surveys.

Table 3- Do you perform consistency checks between economic activity and other variables? (percentage values on the number of countries that conduct the survey)

NO YES

If yes, do you perform them during or after the interviewDuring the interview

After the interview

Both during and after

LFS 42,4 57,6 5,6 66,7 27,8EUSILC 48,4 51,6 0,0 73,3 26,7AES 59,3 40,7 0,0 100,0 0,0

Some countries also perform longitudinal checks or comparison with administrative data.

Additional checks are performed to assess the coding quality. Hence, the description given by the respondent on the economic activity is analysed by some countries in order to evaluate if the chosen code is correct. Other countries test whether the chosen code is coherent with the code given to the enterprise in the statistical registers.

Figure 8 - Countries performing checks on the quality of economic activity (percentage values on the number of

countries that conduct the survey)

0,0

10,0

20,0

30,0

40,0

50,0

60,0

LFS EUSILC AES

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3. Some troublesome areas of Isco08 and Nace rev.2

The coding process of occupations is not simple and requires continuous support given to people involved. First of all, the occupation is a multidimensional concept and interviewees could focus on different aspects making the data incomparable. Moreover, coding this variable generally means to face with a relatively huge set of answers to choose (Isco08 proposes 436 unit groups). Some errors stem from the difficulty to capture the detailed information needed to recognize the job specificity or the skill level; so, for example, a geometer and a bricklayer can be easily recognized, but to discriminate a building structure cleaner from an elementary cleaner might be a rather difficult business. In the same way, it isn’t easy to distinguish an administrative technician from an employee with specific tasks in administrative field.

Regarding the contents of the new occupation taxonomy (Isco08), the Italian coding experience proposes quite large number of problematic areas, the most relevant are:

ManagersThe Italian productive system is dominated by small enterprises. Generally the workers that manage small enterprises are involved in productive activities. In these cases, workers who divide their daily time between the company management and the production of goods or services shouldn’t be classified in the first major group but in the appropriate categories of the fifth, sixth or even seventh major group. Only the workers who manage the enterprises and are occasionally involved in the productive activities may be classified among the managers of the first major group.

The interviewers should be careful put these questions to the interviewees in order to understand if workers are involved or not in the productive activities and choose the correct codes.

The job titles linked to the first major group codes are mainly ‘entrepreneur’, ‘farm owner’, ‘administrator’, etc. but a small minority (13%) focuses on the productive activities carried out by the workers (‘locksmith’, ‘electrician’, ‘produces cakes’ ‘chimney builder’, etc.) instead of the enterprise management.

ExecutivesMany people that direct enterprises use to define ‘executives’ themselves while to be properly called ‘executive’ they should at least have responsibility for and makes decision about one of the following criteria:

a. the budget;b. the overall strategic and operational direction of enterprise;c. hire or fire workers.

The interviewers have to check these criteria before coding a worker as executive. Also in this case, some job titles - as ‘office coordinator’, ‘computer center manager of a bank’ or ‘public administration consultant’ – could ignore the executives’ prerogatives.

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Supervisors Supervisors in many productive sectors take a great relevance in the new classifications. Hence, it is important the interviewers know how identify supervisory tasks and the degree of autonomy they require.

Supervisors plan, organize, coordinate, control and direct the work done by others, but they don’t have the same responsibility and authority to make decisions as managers and executives have. At the same time, they usually have experience as workers in one or more of the occupations they supervise, but they don’t carry out the occupational activities monitored.

A slight percentage of job titles (7%) incorrectly refers to executives and managers (‘direction of work’, ‘quarry manager’, ‘director construction site’, etc.) or don’t recall the supervision but the real productive activity carried out in the enterprise (‘footwear worker’, ‘clerical support worker’, ‘plastic assembler’, etc.).

Chefs and cooksThe new classification separates ‘chefs’ from ‘cooks’ and ‘fast food preparers’. The boundaries between these occupations are sometimes difficult to get. Interviewers have to distinguish these workers according to their activities:

a) Chefs plan and develop recipes and menus, create dishes and oversee the preparation and cooking of meals;

b) Cooks plan, organize, prepare and cook a range of dishes, they do so according to recipes or under the supervision of chefs;

c) Fast food preparers prepare and cook a limited range of foods or beverages involving simple preparation processes and a small number of ingredients.

In the Italian labour force data we find a very small percentage (2%) of ‘chefs’ classified in the fifth major group together with the cooks and a much larger percentage (11%) of ‘cooks’ classified in the third major group with the chefs. In both cases respondents combine the tasks of both occupations forcing the interviewers to choose the most suitable code according to a prevalence criterion or to the higher skill required.

These cases underline the importance to favor the activities actually carried out by the workers rather than the job titles.

Plant operatorsThe classification puts in the third major group some technical figures employed as plant operators in the continuous processes. These occupations check, through automated systems, organize and manage the operations and the safety of the processes. They usually work in remote control rooms using electronic or computerized control panels.

Interviewers have to focus on the productive context and on the control systems to recognize technicians plant operators. The problems raised by the plant operators confirm once again the complexity of coding process. This cannot be only based on the job title and must be preceded by a careful analysis of the type and the context of work as well as of the skills required to perform the occupations’ tasks.

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Personal care workers Personal care workers provide routine personal care and assistance with activities of daily living to persons who are in need of such care due to the effects of ageing, illness or other physical or mental condition. In the classification these workers are coded in the fifth major group between the qualified personal care occupations, while the domestic helpers are coded in the ninth major group among the elementary occupations. The difference between these occupations is based on the goal of their caring activity: people rather than houses.

In Italy many personal care workers are also used to take care of the house of their clients, washing clothes and dishes, preparing and serving meals. This causes problems for coding, forcing the interviewers to recognize the prevalent tasks carried out by their interviewees or to refer to the more qualified activities.

As in the case of ‘chefs’ and ‘cooks’ even for ‘personal care providers’ and ‘housekeepers’, the labour force data present a miscellaneous situation. In particular, a very large percentage of ‘personal care providers’ are classified in the ninth major group between the elementary occupations (7%), probably because in these cases the home care is clearly prevalent on personal care activities.

Agricultural, forestry and fishery workersRegarding agricultural occupations, problems may arise on the criterion for distinguishing between skilled workers (major group 6) and unskilled workers (major group 9). The first generally perform a wide range of tasks typically involving skills acquired through extensive experience and/or training, while the latter perform simple and routine tasks requiring limited training or experience. In some cases the occupation titles alone may be sufficient to distinguish between skilled and elementary farm workers. For example occupation titles where the key noun is ‘farmer’, ‘grower’, ‘shearer’, ‘pruner’ etc, would all indicate occupations that involve the performance of a wide range of tasks or highly specialized skills. Similarly, occupation titles such as ‘farm labourer’, ‘fruit picker’ or ‘cane cutter’ would indicate routine or repetitive tasks requiring limited training or initiative.

The combination of occupation title and task information or other qualifying information may therefore be useful to the interviewers in order to choose the more appropriate codes.

Postman and post runnerThe new classification recognizes a difference between postman and post-runner. The first has a wide range of performing, sorting, recording and delivering tasks related to the mail services. The postman’s job is mainly office based and it has to be classified among the executive office occupations. The post-runner carries out his job on the road, delivering packs or mail by scooter or small van. His tasks are limited and not particularly qualified. For this reason the interviewers have to code this occupation in the ninth major group. Currently eight per cent of the postmen are classified in the ninth major group without any recognition of their office activity.

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4. The Italian experience to assess and improve data accuracy on occupation

The troublesome areas listed above suggest the importance to recall some specific issues of the classification analysing it both by major groups and by economic activity sectors. The analysis by major groups allows to better understand the features and the requirements of the occupations classified in each taxonomical level. The economic activity sectors analysis allows to detail the differences in tasks and responsibilities among occupations that operate in the same context but at different levels.

Training is essential to obtain high quality data as well as to equip the interviewers with the best skills to capture the relevant information and to orientate themselves in the classification. The courses have to be planned in order to focus on several aspects:

the cognitive purpose of the questions, in other words what we mean for ‘occupation’ or ‘economic activity’;

the data collection and what we need to capture to code properly;

the classification framework, the criteria to order occupations or economic activities and to distinguish them;

the coding process, that is how to merge all the information and choose the correct code.

Training courses should be as interactive as possible and share good practices between the interviewers. The Italian experience teaches, moreover, that it’s crucial to assess the actual understanding of the topics also with the use of coding tests and interview simulations. The followings figures present a couple of examples of activities proposed during the training activity.

Figure 9 - Example of coding tests

Instructions to the interviewers to carry out the exercise:

- Work in pairs and simulate the interview- You have been given a script as a respondent containing relevant, irrelevant and misleading information- Come up with the right code selecting the useful pieces of information

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Example of statements to understand and to code:

Occupation description Code

“I usually prepare payroll, sometimes compile statistical data or perform transaction in the bank”

Economic activity description Code

“Manufacture homeopathic preparations”

Figure 10 - Example of exercise regarding the practice of interview

Instructions for the interviewers to carry out the exercise:

- Work in pairs and simulate the interview- Identify the questions needed to get more detail information in order to come up with the code- The answer of respondent is: ‘I deal with statistics’

Example of questions to ask the respondent in order to come up with a code:

First questionFirst answer

Second question Second answer

Final code

Where?

At University

What role do you play?

I'm a Professor 26160

I'm a researcher 26260

ElsewhereWhich are your tasks/duties?

Develop statistical concepts, theories and operational models 21132

Assist Statisticians in planning and performing statistical analysis 31130

Compute elementary statistic elaborations 43240

Nevertheless training is not enough. It is important to get a feedback on the training effectiveness to be aware whether the messages arrived correctly. Hence, monitoring the interviewers’ activities, evaluating their performance and eventually reinforce the main messages is the natural corollary to the training activity.

The monitoring on coding process of occupations in the labour force survey is carried out as follows. Twice a year a sample of first interviews is selected and analysed in order to evaluate the

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occupation codes. The evaluation takes into account the consistency between the code chosen by the interviewer for the specific occupation and a set of variables including the status in employment, the economic activity, the supervising position, the educational level, the size of enterprise and other categories.

The results of the monitoring activity give evidence of the improvements or suggest the possible need to plan new training sessions in order to explain some unclear criteria of the classification or the correct way to fill in the questionnaire. In each case, the interviewers receive a report (Figure 11) with their individual performance compared with the national average and some examples of coding errors or forms filled in incorrectly.

Figure 11 – Example of report sent to the interviewers

Second semester 2010

Monitoring quality LFS

ID Coder 00326

% correct codes % wrong codes

% generic descriptives

Id coder 00326 70.0 10.0 20.0

Total 78.9 7.8 13.3

Some exemples of wrong codes Correct codes

Police officer (93110) 54831

Some exemples of generic job titles Comments

Construction worker It's necessary to specify the tasks carried out and the skill level

Farmer it’s necessary to specify the type of cultivation.

The report suggests that a single coding can be evaluated as:

0 = correct and accurate code;

1 = incorrect and inaccurate code;

2 = insufficient information to obtain a unique code (i.e. generic job titles or descriptions not related to the occupational activity carried out by the interviewee).

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Of course the case ‘2’ is not as severe as the case ‘1’ even though it points out a potential critical situation. In fact, whenever the coding activity is not performed during the interview but at a later time, the lack of information might compromise the coding quality.

The table below shows the trend of the Italian labour force survey interviewers over the last three years.

Table 3 – Performances of the Italian labour force survey interviewers on the coding activity of Isco (2009 – 2012) –

2009 2010 2011 2012

0 - correct codes 69.0 78.9 81.7 84.3

1 - incorrect codes 9.5 7.8 7.9 8.0

2 - insufficient information 21.5 13.3 10.4 7.7

The trend shows a significant improvement in interviewers’ performances although, in the last year, there is a slight increase in coding errors due to the introduction of the new classification of occupations (The national classification CP11 linked to Isco08).

Regarding the situation of ‘insufficient information’, here in the following examples are listed:

1. job titles related to the economic activity sector (“Extraction of natural gas”, “Postal activities”, “Cleaning”, etc.)

2. job titles linked to the names of the organizations/enterprises where the interviewee works (“Fiat”, “Local Health Unit”, “Municipality of Rome” etc.)

3. job titles related to the role or to the status in employment (“Clerk”, “Head of unit”, “Coordinator”, etc.)

4. indefinite job titles that prevent the assignment of even the first digit (“Worker”, “Advisor”, “Bank worker”, etc.)

5. indefinite job titles that prevent the assignment of more than one-digit code (“Engineer”, “Breeder”, “Electrician”, “Employer”, etc.)

6. detailed but not work relevant job titles (“Social cooperative member”, "Worker in archaeological excavations", "Moroccan seller”, etc.).

Whenever we find these types of job titles or description, it is important to outline to the interviewers the need to capture relevant and detailed information about the work, focusing on the activities actually carried out. In order to improve the quality of coding an automatic procedure has been implemented aimed to delivering to the interviewers, by email, a list of their generic or not properly exploited descriptions. In this way the interviewers are able to recognize opportunely their mistakes and to focus on the correct information they would have to collect.

The following list shows some examples of generic descriptions that have been selected and sent to the interviewers with an apposite training message.

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Cleaner > it’s necessary to specify the type of cleaning and the place where the working activity is carried out

Farmer > it’s necessary to specify the type of cultivation

Street vendor > it’s necessary to specify the type of good sold

Driver > it’s necessary to specify the type of vehicle driven

Carpenter > it’s necessary to specify the processed material in the working activity

Electrician > it’s necessary to specify the place where the working activity is carried out

Plumbers > it’s necessary to specify the place where the working activity is carried out

Teacher > it’s necessary to specify the school and the subject taught

Bricklayer > it’s necessary to specify the processed material in the working activity

Policeman > it’s necessary to specify the working activities and the rank in the police force

The Italian experience in the labour force survey shows the benefits that may result from a continuous exchange with the interviewers, not only to improve their performances but also to improve the classification and the survey tools. To pursue this aim it is relevant to set up a feedback system to collect, examine, select and introduce the suggestions coming from the field into the ‘tools’, i.e. the questionnaire, the classification dictionary, etc. In recent years, it has been implemented a real time support for the interviewers. They can contact the Institute by email o by phone during the interview or in the post-coding phase in order to get advice on how to handle difficult cases. The exchange with the coders is mutual and allows to incorporate new job titles and to improve the descriptions of the taxonomy.

Of course, the face to face exchanges remain the most effective way to support coders. For this reason the Italian Institute organize periodically debriefing sessions with the interviewers in order to analyze the most common coding errors, recall the training contents and share the best practices to improve data quality.

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5. The difficult areas of Nace rev2 and the quality assessment on the coding activity

A similar investment in data quality has been made for another target variable potentially involved in the Esec prototype: the economic sector in employment. In this case several activities of training on the new classification and of monitoring on coding process in labour force survey have also been carried out. As for the occupation, in fact, the coding process of economic activity is difficult and requires continuous support given to people involved.

The new Italian economic activity classification (Ateco_2007) uses the same four-digit of the international NACE_Rev 2 and presents several differences from previous version (Ateco_2002). New concepts at the highest level of the classification have been introduced and new detail has been created to reflect different forms of production and emerging new industries. The following table compares the structure of NACE Rev.1.1 to NACE Rev.2.

Table 4 – Comparison between the structures of NACE Rev.1.1 and Rev.2.

NACE Rev.1.1 NACE Rev.2 Difference

All sectionsSections 17 21 4Divisions 62 88 26Groups 224 272 48Classes 514 615 101Manufacturing sectionSections 1 1 -Divisions 23 24 1Groups 103 95 -8Classes 242 230 -12Other sectionsSections 16 20 4Divisions 39 64 25Groups 121 177 56Classes 272 385 113

It is important to note that the structure of new classification has considerably increased. NACE Rev. 2 is more detailed than NACE Rev.1.1 since more than one hundred classes have been added.

The main changes that characterize the new version of classification are described below.

The previous sections for agriculture and fishing have been combined in the new one ‘Agriculture, forestry and fishing’; this section is more detailed in the lower level of classification.

New divisions in manufacturing, representing important new industries or old industries that have increased their economic or social relevance, have been created, such as division 21 ‘Manufacture of basic pharmaceutical products and pharmaceutical preparations’ and division 26 ‘Manufacture of computer, electronic and optical products’.

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Repair and installation of machinery and equipment, which was formerly classified under manufacturing of the corresponding type of equipment, is now identified separately in division 33.

A new section E (‘Water supply, sewerage, waste management and remediation activity’) has been created, which includes the ‘sanitation’ activities in NACE Rev 1.1 division 90, water collection and distribution activities in previous NACE division 41 and material recovery activities, which largely correspond to previous NACE division 37. The concept of ‘specialized construction activities’ has been introduced in the new classification, replacing the logic of the previous version based largely on the stage of the construction process.

A new section J (‘Information and communication’) has been created, combining activities involving production and distribution of information and cultural products, provision of the means to transmit or distribute these products, as well as data or communications, information technology activities and the processing of data and other information service activities.

The NACE Rev 1.1 section for ‘Real estate, renting and business activities’ has been split up into three different sections in the new NACE.

In section P (‘Education’) have now been included specialized sports, cultural and other educational services and also specialized support services.

The focus in section Q (‘Human health and social work activities’) has been narrowed since it includes only human health activities.

Substantial components of NACE Rev. 1.1 section O (‘Other community, social and personal service activities’) have been moved to NACE Rev. 2 sections E (‘Water supply, sewerage, waste management and remediation activities’) and J (‘Information and communication’).

The new classification was adopted since the first quarter 2011 LFS, while before this date the Rev1.1 was used and trans-coded into the Rev.2 version.

In the first period after the introduction of the new classification the coding evaluation activity was reinforced in order to check the interviewers’ activity and improve their comprehension of the new taxonomy.

The monitoring activity on coding process in the labour force survey is carried out taking into account the consistency between the codes chosen by the interviewers for the specific economic activities and the other linked variables, first of all the occupations of the respondents. The coherence between all the variables linked to work activities (the status in employment, the educational level, the size of enterprise, etc.) is an important element to assess the quality of the chosen code.

As general result, it is clear that for the respondents is much easier to give information on occupation rather than on the economic activity. The information isn’t always well known especially in the case of large organizations with several goods or services produced. Many respondents may be unsure on the kind of economic activity carried out by their organization. Many others may fail to recognize the main economic activity in presence of multiple tasks. This is the case for instance of the workers in the social cooperatives, which perform different type of activities; the workers are hardly able to recognize the economic activity which mostly contributes to the added value of their local unit. Moreover, some respondents mix up their specific working activity with the enterprise activity. So, for instance, a marketing manager who prepares advertising

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campaigns in a car industry might say that economic activity of his organization is ‘Advertising agencies’ instead of ‘Manufacture of motor vehicles’.

In synthesis, we may conclude that the main difficulty for the LFS interviewers is to collect the right information and to focus on the main economic activity of the local unit, avoiding ancillary activities, rather then choose the correct code.

Regarding the NACE contents, the main difficulties met by the LFS interviewers when coding the economic activities are listed below:

some interviewers continue to classify ‘Repairing’ or ‘Installing’ activities - which are now identified in a specific division in the new classification - under ‘Manufacturing’ of the corresponding type of machine or equipment;

on the contrary, some interviewers think that activities such as remodelling or renovating existing residential structures have to be code under the new division 43 (‘Specialised construction activities’), rather then under the same old division 41 (‘Construction of building’);

for many farms, interviewers tend to neglect ‘Growing of grapes’ or ‘Growing of oleaginous fruits’ as potential main economic activities since these enterprises are also devoted to the wine or oil production;

on the contrary, some industrial activities related to the agricultural products - like slaughtering, packaging or selling - are sometimes coded in the agricultural sector (div.01);

often the education activities carried out by public organizations (for example, schools administered by the central or local government) are coded under the section O (‘Public administration and defence’) rather then under the correct section P (‘Education’);

similarly, human health activities are sometime classified into the public administration, when they are performed by the national health service structures, instead of the appropriate section Q (‘Human health and social work activities’).

finally, it happens that the activities of day nurseries for pupils was coded under the section ‘Education’ instead of ‘Social activities’.

In general, many interviewers make mistakes in coding the economic activity of large enterprises, with several productive phases, forgetting the traditional prevalence rules, such as the following:

Manufacturing/Production > Trade

Manufacturing/Production > Repairing/Installation

Farming > Trade/Harvesting

Wholesale trade > Retail trade > Repairing/Installation

As for occupation, the monitoring activity found several generic or not informative answers also for the economic activity variable. Hence, the main source of inaccuracy places before the coding process, when the respondents have to describe their local unit economic activity with a great detail.

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The most effective actions to improve data quality should be placed at the first phases of the survey. The development of inconsistencies rules between the variables is undoubtedly one of the most important action.

Once introduced within the CAPI software, the rules might alert the interviewer on the quality of the answers given by the respondents and eventually prevent some errors. In the Italian LFS questionnaire there are two types of rules:

hard rules that require corrections by the interviewer; in other words the interview doesn’t proceed if the inconsistency is not resolved by the interviewer modifying a previous code;

soft rules that don’t require any intervention by the interviewer but suggest a further reflection on the answers chosen.

As far as the variables on work activities are concerned, the inconsistency rules consider mainly the coherence between occupation, status in employment and economic activity. Here in the following some examples are listed:

SOFT A self-employed usually doesn’t carry out occupations of the fourth major group (Clerical support workers).

SOFT A non-executive employee usually doesn’t carry out occupations of the first major group (Managers).

SOFT An executive usually doesn’t carry out occupations of the fourth (Clerical support workers), sixth (Skilled agricultural, forestry and fishery workers), seventh (Craft and related trades workers), eighth (Plant and machine operators and assemblers) and ninth (Elementary occupations) major groups.

HARD Self-employed workers can not carry out Armed forces occupations.

HARD People working for the Armed forces can not be coded in a section that is not O (Public administration), P (Education), Q (Human health and social work activities) or U (Activities of extraterritorial organisations and bodies).

HARD Self-employed can not be coded in section O (Public administration and defence) of economic activities.

HARD Self-employed can not be coded in division 97 (Activities of households as employers of domestic personnel) of economic activities.

SOFT Mining and quarrying managers should be coded in section B (Mining and quarrying) of economic activities.

SOFT Manufacturing managers should be coded in section C (Manufacturing) of economic activities.

SOFT Electricity, gas, steam and air conditioning supply managers should be coded in section D (Electricity, gas, steam and air conditioning supply) of economic activities.

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SOFT Water supply managers should be coded in section E (Water supply) of economic activities.

SOFT Construction managers should be coded in section F (Construction) of economic activities.

SOFT Wholesale and retail trade managers should be coded in section G (Wholesale and retail trade) of economic activities.

SOFT Accommodation and food service activities managers should be coded in section I (Accommodation and food service activities) of economic activities.

SOFT Financial, insurance and real estate activities managers should be coded in section K (Financial and insurance activities) or L (Real estate activities) of economic activities.

SOFT Shopkeeper and shop sales assistants should be coded in division 46 (Wholesale trade) or 47 (Retail trade) of economic activities.

SOFT Teachers of elementary school should be coded in group 852 (Primary education) of economic activities.

SOFT Teachers of secondary school should be coded in group 853 (Secondary education) of economic activities.

SOFT University researchers should be coded in group 854 (Higher education) of economic activities.

This kind of rules represent a further support to the interviewers since they alert them on possible errors and suggest a way to solve them directly with the respondent’s help. When the interviewer combines a pair of inconsistent codes, in fact, the software shows a warning message about the kind of potential error and suggests a list of possible correct codes.

The performance of the Italian labour force survey interviewers on the coding activity of Nace in the last two years is quite similar to the Isco performance (Table 5). The correct codes are increasing, while there are still many generic descriptions.

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Table 5 – Performances of the Italian labour force survey interviewers on the coding activity of Nace (2011 – 2012)

2011 2012

0 - correct codes 82,5 86,5

1 - incorrect codes 7,1 5,2

2 - insufficient information 10,4 8,3

Regarding the situation of ‘insufficient information’, here in the following some examples are listed:

1. The description does not specify the type of main activity (manifacturing, growing, retail trade, wholesale), but it only refers to the good (“varnish”, “clothing”, “glasses”, etc;

2. The description does not specify the type of goods produced or the material used (“soles”, “doors”, “machinery” etc.);

3. The description is a copy of the code from the navigator;

4. The description does not specify whether the figures as a plumber, a construction painter, a mason are employed or self-employed;

5. The description contains the name of the job title instead of the activity;

6. The description does not specify the location of the activity (hotels, farm holidays, crops in the ground or in a greenhouse, transport by road or rail or inland waters).

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6. Some coding tools for occupation: the Dutch experience 4

In 2012 Statistics Netherlands implemented a new system for coding occupations in social surveys. The system uses Cascot and is suitable for implementation in the CAPI, CATI and CAWI modes. Cascot is a computer program designed to make the coding of text information to standard classifications possible. It is not an interactive tool, the answers are collected first and are automatically coded afterwards.

Using this system we developed a coding process that can be split up into 4 steps:

Step 1

In the first step the answers of respondents to the question on occupation that can be directly converted into ISCO-codes are coded automatically. In these cases no extra information is needed. For example the answer ‘primary teacher’ can directly be coded 2341, Primary school teachers. For this step a search file is used containing the job titles that can be linked directly to a 4 digit ISCO08-code. To build up this search file we used data with answers of respondents to questions on their occupation and the main tasks of four years of the Labour Force Survey (2004 until 2008). This database contains approximately 700 000 records. During the process of building up the search file priority was given to the most frequently occurring answers of respondents in order to maximize the proportion of data that can be coded automatically.

Step 2

For some frequently occurring job titles it was obvious that extra information was needed in order to determine the correct ISCO-code. In these cases we added the answer to the question on the job title to the answer to the question on the main tasks performed in the job. The combined answers served as input for automatic coding in Cascot. The same search file is used in both steps and the file was optimized to achieve a more effective use of the answer on main tasks in automatic coding.

Step 3

In the third step some specific job titles that cannot be coded in either step 1 or step 2 are converted into ISCO-codes by using additional variables. We use the following additional variables:

Economic activity

Managerial tasks: the answers to the following 5 questions:

1. Q: Do you supervise workers or personnel? A: yes / no2. Q: Do you exclusively supervise or do you also perform the same tasks as the personnel you

supervise? A: exclusively / besides supervision also the same tasks as the personnel supervised

3. Q: What do your main tasks exist of? A: supervision / other tasks4 This paragraph was written by Sue Westerman, Statistics Netherlands

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4. Q: Are you authorized to make decisions on personnel matters such as appointment of staff or wage increase? A: yes / no

5. Q: Are you authorized to make decisions on the overall strategic and financial policy of the organization, such as budgets or long-range plans? A: yes / no

The chosen variables and values depend on the type of occupation. We only use these variables in this automatic coding step in the cases where the respondents description of the job and main tasks are not informative enough to provide a code in step 1 or 2 and where on the basis of the test files we are able to verify that automatic coding will for the majority of cases produce an accurate code.

The variables on managerial tasks are used in job titles containing the word manager, but where management is often not the main task. Examples of these job titles are: sales manager, product manager, marketing manager, service manager. By using the information on the managerial tasks performed the distinction between Major Group 1 and Major Group 2 or 3 could be properly made.

The variables on managerial tasks are also used in combination with economic activity for the distinction between the different types of managers within Major Group 1 or the different types of supervisors. An example of a job title where we use these variables in automatic coding is the job title ‘team leader’. Here we assume that in the majority of cases where team leader is the only answer and the economic activity is in retail or whole sale trade, and where the answers to questions on managerial tasks show that supervision is their main task, ISCO08-code 5222 Shop supervisors would apply. The remaining cases with the job title ‘team leader’ are then coded manually by a coding expert in step 4.

An example of a job title where we only used economic activity to assign a code automatically is ‘machinist’ this job title is used for 8311 Train engine drivers, 3151 Ships engineers and several other occupations within Major Group 8. Here we use economic activity either to code 8311 or 3151, the remaining cases are coded manually. Another example is the job title ‘leidster’ (feminine form of leader). In most cases this is used in the occupation 5311 Child care workers, but also in the occupation 3412 Social work associate professional.

Step 4

Not all job titles can be converted by using the additional variables into codes of the ISCO-08. The answers that cannot be coded in steps 1, 2 or 3 will be coded manually.

Comparability

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7. Time comparability of the occupation series in the LFS

As required by the Commission Recommendations (EC) 29/10/2009, and the derived Commission Regulation, from 2011 on the LFS will have to send data according to the new Isco085.

Hence, starting from the first quarter of 2011 Eurostat is receiving LFS data according to the new Isco08. So it is important to highlight its difference from Isco88 in order to better understand the time series on occupations.

In fact even though the first hierarchical level of the two classifications maintains the same number (ten) and name, the elements they are made up have changed. From Table 5, which compares the two Isco structures, we can only partially comprehend the trend of the series (see for instance the figures in Appendix 3)

Table 6 - Isco88 and Isco08 structure

Major group - IscoSubmajor group Minor group Unit group

Isco88 Isco08 Isco88 Isco08 Isco88 Isco08I- Managers 3 4 8 11 33 31II- Professionals 4 6 18 27 55 92

III- Technicians and associate professionals 4 5 21 20 73 84

IV- Clerical support workers 2 4 7 8 23 29

V- Service and sales workers 2 4 9 13 23 40

VI- Skilled agricultural, forestry and fishery workers 2 3 6 9 17 18

VII- Craft and related trades workers 4 5 16 14 70 66VIII- Plant and machine operators and assemblers 3 3 20 14 70 40

IX- Elementary occupations 3 6 10 11 25 33

X- Armed forces occupations 1 3 1 3 1 3Total 28 43 116 130 390 436

5 Similarly, the Commission Regulation No 1893/2006 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 20 December 2006 established that Member States' statistics should be produced using NACE Rev. 2 or a national classification derived therefrom.

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http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2009:283:0003:0004:EN:PDF

Indeed, almost all Major groups were reshuffled with some occupations moving from one major group to another (see Appendix 4 for a list of the incoming occupations (from Isco88) and outgoing (to Isco08 ones) and only MG 0 - Armed forces remained with the same composition in the 2 versions of the classification.

To better understand the impact of the new Isco on the series distribution it is important to estimate the magnitude of the "entrant" and "leaving" occupations in each Major Group.

To reach this aim we have followed two alternative strategies:

1- for a given year (2010) get the double coding (according to Isco88 and Isco08) of the same occupation (France, Italy, the Netherland);

2- select the longitudinal LFS sample of individual who didn't change job between 2010 and 2011 and compare the different code Denmark.

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8. Time comparability: the Dutch experience6

The method used for coding occupations in the Dutch Labour Force Survey until the year 2011 made it possible to deliver data for the year 2011 according to Isco88 and Isco08.

The aim of this paragraph is to present the double coding of the same occupation of the employed persons of the Dutch labour force according to ISCO88 and ISCO08 for the year 2011. The results are presented together with an explanation on the major flows and the method used for double coding.

Method used for double coding

The method used for double coding data on occupation to codes of ISCO-08 and ISCO-88 was developed in the early nineties and was used until 2011. In this method two steps are used for assigning classification codes to occupational information from surveys.

The first step is to assign the so-called provisional occupational codes. These provisional codes are not the same as the classification codes: there are more provisional codes than categories in the classification (approximately 2100 provisional codes and 1211 and 390 codes in the National Standard Classification of Occupations 1992 and ISCO-88 respectively). These provisional codes are used to reduce the information on occupations into categories which contain linguistically similar information. Assigning provisional occupational codes is in part a manual process. Both in the manual and the automatic coding process information on the job title, main tasks and economic activity is used.

In the second step these provisional codes are converted into definite occupational codes of the occupational classifications. In a decision table most of the provisional codes are directly converted into codes of the occupational classification. Some conversions however require additional information, such as the employment status (wage earning, self-employed or unpaid family worker), the educational level and field and the number of subordinates. In the decision tables all provisional codes are defined and for some code values of these conditional variables are specified. The decision tables are automatically called up in the case of provisional codes. For each classification a separate decision table was designed.

The design of the decision table that was used to convert the provisional codes into codes of the ISCO-08 was based on the decision table for conversion into ISCO-88. The codes of ISCO-88 were converted into codes of ISCO-08 by means of the correspondence table (ISCO-88 ISCO-08) of the ILO. In cases of multiple suggestions for ISCO-08-codes we decided which ISCO-08 unit group to be most appropriate and what additional variables should be used to achieve a correct conversion of the provisional codes.

In case a provisional code could not be converted to one ISCO unit group we decided which more aggregated level of the ISCO-08 would be appropriate. Our aim was to convert to 4 digit ISCO-codes, but for some cases this was not feasible. 6 This paragraph was written by Sue Westerman, Statistics Netherlands

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In the decision table for conversion into ISCO we used the following ancillary variables: attained level and field of education, a variable giving information on managerial tasks and the number of employees supervised, the size of the company and the economic activity. Economic activity was used as an extra ancillary variable to make a distinction between different groups in ISCO-08 where the provisional occupational codes were not detailed enough. Economic activity was not used in the decision table for conversion into ISCO-88. The decision table is available from the authors.

Data of the Labour Force Survey of the year 2011 was used for analysis of the double coding according to ISCO-88 and ISCO-08. A selection was made of the employed persons in the labour force according to the international definition of 2009. Of this selection 1,5% of the cases the ISCO-88 code was unknown, these cases were filtered out because they are not relevant for the analysis of the double coding.

Table 1 - Flows of employees among Major Groups of ISCO-88 and ISCO-08ISCO-88 Major Group

ISCO-08 Major Group %ISCO-88 %ISCO-08

0 0 100 1001 1 63 922 2 93 843 3 69 794 4 85 975 5 97 746 6 91 517 7 99 888 8 77 999 9 93 99

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Table 2 - Flows of employees among Major Groups of ISCO-88 and ISCO-08ISCO-88 Major Group

ISCO-08 Major Group %ISCO-88 %ISCO-08

3 2 17,1 14,11 3 12,6 8,34 5 12,1 7,48 3 12,1 4,01 6 11,8 48,83 5 11,4 11,38 7 11,1 6,81 5 8,0 4,66 5 7,9 0,69 5 5,1 2,32 3 3,6 4,51 2 3,1 1,44 3 2,7 1,92 1 2,6 7,35 3 2,1 1,83 7 1,6 3,39 7 1,5 1,57 3 1,4 0,71 7 0,7 0,86 9 0,6 0,13 4 0,6 1,15 9 0,5 1,02 4 0,5 1,01 4 0,5 0,59 8 0,4 0,84 2 0,2 0,13 1 0,2 0,51 8 0,1 0,34 8 0,1 0,27 9 0,1 0,19 3 0,1 0,08 9 0,1 0,09 6 0,1 0,27 1 0,0 0,05 1 0,0 0,07 8 0,0 0,0

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Table 3 Distribution of the Major Groups of the ISCO-08 presented in terms of percentage of a Major Group of ISCO-88.ISCO-88 ISCO-08 0 1 2 3 4 5 6 7 8 9 Total 0 100 1001 63 3 13 0 8 12 1 0 1002 3 93 4 0 1003 0 17 69 1 11 2 1004 0 3 85 12 0 1005 0 2 97 1 1006 8 91 1 1007 0 1 99 0 0 1008 12 11 77 0 1009 0 5 0 2 0 93 100Total 0 7 23 16 10 19 3 9 4 8 100

Table 4 Distribution of the Major Groups of the ISCO-88 presented in terms of percentage of a Major Group of ISCO-08.ISCO-88 ISCO-08 0 1 2 3 4 5 6 7 8 9 Total 0 100 01 92 1 8 0 5 49 1 0 112 7 84 4 1 213 0 14 79 1 11 3 194 0 2 97 7 0 125 0 2 74 1 146 1 51 0 17 0 1 88 0 0 88 4 7 99 0 59 0 2 0 1 1 99 9Total 100 100 100 100 100 100 100 100 100 100 100

An explanation is given for the flows between ISCO-88 and ISCO-08 that represent at least 1% of all cases coded in a given ISCO-88 major group (table 2).

Major Group 3 Major Group 2

In total 68 different provisional occupational codes that were coded ISCO-88 Major Group 3 are now coded ISCO-08 Major Group 2. 5 provisional occupational codes represent three quarters of the flow of Major Group 3 to Major Group 2, these are: 84901 system-, network administrators, 76201 physiotherapists, 339401 investment advisor bank, credit advisor, analysts and evaluators, 162202 advertisements-, graphic designers and book illustrators, 79201 speech therapists.

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In total 82 different provisional occupational codes that were coded ISCO-88 Major Group 1 are now coded ISCO-08 Major Group 3. 78% of the employed that were coded with Major Group 1 move to Minor Group 312 Mining, manufacturing and construction supervisors (70%) or to 3341 office supervisors (8%). They move not on the basis of the number of employees supervised, but on the basis of the job titles that belong to these provisional occupational codes. The remaining cases move to Major Group 3 based on the job title in combination with information on ancillary variables. In these cases the assumption is made that below a certain number of employees supervised it is not likely that management will be the main task. For example, a self employed manager of a restaurant with no personnel or only 1 employee is coded 3434 chefs.


In total 11 different provisional occupational codes that were coded ISCO-88 Major Group 4 are now coded with ISCO-08 Major Group 5. 82% of the cases concern cashiers that are now coded with ISCO-08 5230 (cashiers and ticket clerks), the remainder includes mainly provisional occupational codes for commercial administrative workers (mainly sales activities) and call centre salespersons that are coded with ISCO-08 unit group 5244 contact centre salespersons.


Based on the provisional occupational codes different types of operators that were coded with ISCO-88 Sub major Group 81 stationary-, plant and related operators were coded with ISCO-08 Minor Group 313 Process control technicians. Constituting 90% of all cases that move from Major Group 8 to major group 3 can be explained by this flow.


This flow consists mainly of farmers, crop growers etc. that were coded as agricultural managers in Major Group 1 in the ISCO-88 and are now coded with Major Group 6 in ISCO-08.


Label provisional occupational code Provisional occupational code

ISCO-88 ISCO-08 Cum % of Total flow 32

systeem-, netwerkbeheerder 84901 3121 2520 39%

fysiotherapeut, heilgymnast-masseur (geen leerling en assistent) 76201 3226 2264

52%

beleggingsadviseur bank, kredietadviseur, -analist, -beoordelaar ed 339401 3411 2410

62%

reclame-ontwerper, boekillustrator ed grafische ontwerpers 162202 3471 2166

71%

logopedist 79201 3229 2266 75%

38

80% of all cases that move from Major Group 3 to Major Group 5 can be explained by one provisional occupational code 72301 ziekenverzorgende (caretaker of the sick) that was coded as nursing associate professionals (3231) in ISCO-88. According to the definitions of ISCO-08 and the job titles we found with this code, the ISCO-08 Minor Group 532, Personal care workers in health services was chosen as a more appropriate group. Other provisional occupations moving to Major Group 5 are technical teachers aides, driving instructors and pedicures.


30 different provisional occupational codes explain the flow of Major Group 8 to Major Group 7. The majority of cases (85%) move from ISCO-88 Sub Major Group 82 machine operators and assemblers to three different unit groups in ISCO-08, namely 7322 printers, 7523 and 7223, the wood- and metalworking machine tool setters and operators.


This flow can be explained by the shop managers that were coded in Major Group 1 in ISCO-88 and are now coded with unit group 5221, shop keepers (67% of the cases) mostly based on the job titles found with these provisional occupational codes alone. For some provisional occupational codes where on the basis of the job titles Major Group 1 or Major Group 5 could be relevant, information on ancillary variables on managerial tasks was used. Self-employed with no personnel or only 1 person being supervised, or the non self-employed with less than 5 persons under supervision are coded with 5221.

The remaining cases flow from Major Group 1 into unit groups 5222 shop supervisors, 5211 Stall and market salespersons and 5151 Cleaning and housekeeping supervisors in offices, hotels and other establishments.


All cases of this flow can be explained by the job titles that belong to ISCO-08 unit group 5164 pet groomers and animal care workers that were coded with ISCO-88 6129 Market-oriented animal producers and related workers not elsewhere classified.


90% of all cases of this flow consisted of the building caretakers that were coded with 9141 in ISCO-88 and with 5153 in ISCO-08 (66%) and by the street food vendors (27%) that were coded with 9111 in ISCO-88 and with 5212 in ISCO-08.


Several provisional occupational codes make up the flow of the cases from Major Group 2 into Major Group 3. 50% of the cases can be explained by a provisional occupational code that is used for social workers that assist (groups of) clients that staying youth centres or residents under supervision. Dependent on the level of educational attainment these jobs were coded as a professional or associate professional in the ISCO-88. In the conversion table we use for coding to ISCO-08 we decided not to use the level of educational attainment because based on the

39

information on the main tasks we found for these provisional occupational codes ISCO-08 unit group 3412 social work associate professionals to be most appropriate.

Another 20% of the cases can be explained by the government tax and excise officers that were coded 2411 in ISCO-88 and belong to 3352 in ISCO-08.

Other job titles that are classified in Major Group 3 are inspectors civil engineering, health inspectors, environmental inspectors, interior designers and ambulance paramedics.


This flow can be explained by a large range of job titles of which we think below a certain number of employees supervised it is no longer plausible that the majority of time is spent on supervision or where based on the tasks belonging to a job title alone we think management will not be the main component of the work performed. Job titles that on the basis of this ancillary information were coded in Major Group 2 are head nursing department, head of a IT-company, head of a company dealing with marketing and advertisement activities, head of a company dealing with recruitment. Examples of job titles where ancillary information on the number of employees supervised was used in the decision rules for ISCO-88 and not in the current decision rules for ISCO-08 are legal advisors, inspectors of education, pharmacists, system programmers and analysts, coordinators, advisors in the field of education and organization analysts.

In summary this flow can be explained because in the use of the ancillary information on managerial tasks (number of employees supervised) the criterion that management should be the major component of the tasks performed was rather strictly implemented.


The majority of cases can be explained by 2 provisional occupational codes. One of them is used for workers that check implementation of regulations and rules and where the tasks have an administrative component. In the ISCO-88 these cases were coded 4190 Other office clerks. In the ISCO-08 we coded them 335 Regulatory government associate professionals, since these employees are in most cases working for the government and their main tasks suit the description of this ISCO-08 Minor Group.

The other provisional occupational code in the flow of cases from Major Group 4 to Major Group 3 is code 321302 ‘secretaries (excluding medical and executive secretaries)’. Since this code includes legal secretaries we used economic activity as a proxy to make a distinction between legal secretaries coded ISCO-08 3342 and the general secretaries coded ISCO-08 4120.


A large proportion of the cases (60%) that move to Major Group 1 can be explained by cases that were coded with provisional occupational codes for directors or heads of governmental institutions or of departments within a governmental institution. Below 50 employees supervised these cases were coded with ISCO-88com 2470, Public service administrative professionals. In the ISCO-08 we decided Sub Major Group 11 would be more appropriate regardless of the number of employees supervised.

40

Another 23% of the cases that move to Major Group 1 can be explained by the provisional occupational codes that are used for directors of educational institutions. In ISCO-08 they were coded in Sub Major Group 13 without considering the number of employees supervised.


The chef cooks and dental assistants explain 97% of the cases that flow from Major Group 5 to Major Group 3. Chef cooks (36%) move from ISCO-88 5122 Cooks to ISCO-08 3434 Chefs, the dental assistants (61%) move from ISCO-88 5132 Institution-based personal care workers to ISCO-08 3251 Dental assistants and therapists.


60% of the cases that flow from Major Group 3 to Major Group 7 can be explained by a rather vague provisional occupational code with the description ‘technician, specialization unknown, education attainment level lower/secondary’. In the coding of ISCO-88 educational level was used to code them ISCO-88 Minor Group 311 in the cases where level of educational attainment was secondary or higher. In the coding of ISCO-08 we decided for with Minor Group 723 based on the job titles and main tasks that occurred with this provisional occupational code.

Another 20% of the cases that flow from Major Group 3 to Major Group 7 can be explained by the provisional occupational code that is used for flower arrangers. They were coded ISCO-88 3471 Decorators and commercial designers and are now coded ISCO-08 7549 Craft and related workers not elsewhere classified according to the definitions of ISCO-08-manual.


This flow contains provisional occupational codes used for product graders and testers, specialization unknown, no metal or electronics. They were coded with ISCO-88 932 manufacturing laborers and are now coded with Sub Major Group 75 Food processing, wood working, garment and other craft and related trades workers, because based on the provisional occupational codes it is not possible to distinguish between food (751) and non-food (754) testers and graders.


63% of this flow consists of dental technicians and medical instrument makers and repairers (excl. electro technical) that were coded with ISCO-88 7311 Precision-instrument makers and repairers and were coded with ISCO-08 3214 Medical and dental prosthetic technicians. Another 23% can be explained by the job titles used for the stage, studio and lighting technicians that were coded ISCO-88 7137 Building and related electricians and are coded ISCO-08 3521 Broadcasting and audio-visual technicians.

41

9. Time comparability: the French, Italian and Danish results

France - Double codingIsco88 Isco08 0 1 2 3 4 5 6 7 8 90 85.1 0.6 0.0 0.0 0.0 14.3 0.0 0.0 0.0 0.01 0.0 72.2 0.6 4.1 0.0 23.0 0.0 0.0 0.0 0.02 0.0 3.2 96.7 0.0 0.0 0.0 0.0 0.0 0.0 0.03 0.0 0.9 11.5 85.8 0.0 1.8 0.0 0.0 0.0 0.04 0.0 0.0 0.0 9.5 82.5 8.0 0.0 0.0 0.0 0.05 0.0 0.0 0.0 2.4 3.5 86.8 0.0 0.0 0.0 7.36 0.0 0.3 3.5 1.4 0.0 0.0 81.1 0.9 0.0 12.87 0.0 0.1 0.0 13.4 0.0 0.0 0.0 69.0 5.8 11.58 0.0 0.0 0.0 11.3 0.0 0.0 0.0 9.3 74.2 5.19 0.0 0.0 0.0 0.0 1.7 14.6 0.0 0.0 1.0 82.7Total 0.9 7.0 16.1 20.5 10.1 16.2 2.9 8.3 6.9 11.1 Italy - Double codingIsco88 Isco08

0 1 2 3 4 5 6 7 8 9

0 100.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

1 0.0 84.4 0.0 0.0 0.0 9.2 6.4 0.0 0.0 0.0

2 0.0 0.7 98.5 0.8 0.0 0.0 0.0 0.0 0.0 0.0

3 0.0 0.0 14.2 85.7 0.0 0.0 0.0 0.0 0.0 0.0

4 0.0 0.0 0.0 0.0 99.3 0.7 0.0 0.0 0.0 0.0

5 0.0 0.0 0.0 0.0 0.4 96.8 0.0 1.0 0.0 1.9

6 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 0.0 0.0

7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 99.9 0.1 0.0

8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0

9 0.0 0.0 0.0 0.0 2.0 8.0 0.0 0.0 0.0 89.9

Total 1.0 4.3 12.7 16.7 11.2 17.3 2.9 16.2 8.1 9.6 Denmark - Longitudinal people with the same job titleIsco88 Isco08 0 1 2 3 4 5 6 7 8 90 50.0 0.0 0.0 50.0 0.0 0.0 0.0 0.0 0.0 0.01 0.0 47.9 22.5 22.5 0.0 4.2 0.0 1.4 0.0 1.42 0.0 4.8 81.1 12.7 1.1 0.3 0.0 0.0 0.0 0.03 0.2 4.6 44.5 40.5 4.0 3.6 0.2 1.2 0.2 1.04 0.0 0.5 1.6 25.7 66.5 4.2 0.5 0.5 0.5 0.05 0.0 0.8 0.8 2.4 0.4 90.9 0.0 0.0 0.0 4.76 0.0 0.0 0.0 0.0 0.0 0.0 90.0 0.0 0.0 10.07 0.0 0.8 0.0 7.0 0.8 0.8 0.0 86.8 2.3 1.68 0.0 0.0 0.0 3.1 1.6 0.0 1.6 4.7 84.4 4.79 0.0 0.7 0.0 0.7 2.2 14.6 0.7 1.5 2.2 77.4Total 0.1 4.5 30.6 19.3 9.0 16.1 2.3 7.1 3.5 7.5

42

Table - Flows in employees among MGs of ISCO-88 and ISCO-08 - France -

Isco88 Major groupIsco08 Major group %Isco88 %Isco08

1 5 23.0 1.09 5 14.6 8.70 5 14.3 1.07 3 13.4 7.26 9 12.8 4.17 9 11.5 11.43 2 11.5 13.58 3 11.3 4.64 3 9.5 5.38 7 9.3 9.34 5 8.0 5.75 9 7.3 8.77 8 5.8 9.28 9 5.1 3.91 3 4.1 1.86 2 3.5 0.85 4 3.5 4.62 1 3.2 6.65 3 2.4 1.53 5 1.8 2.19 4 1.7 1.66 3 1.4 0.29 8 1.0 1.5Italy3 2 14.2 21.71 5 9.2 2.29 5 8.0 4.81 6 6.4 0.19 4 2.0 1.95 9 1.9 3.35 7 1.0 1.02 3 0.8 0.54 5 0.7 0.57 8 0.1 0.3 - Denmark0 3 50.0 0.33 2 44.5 43.04 3 25.7 14.41 2 22.5 3.01 3 22.5 4.79 5 14.6 7.12 3 12.7 13.22 1 4.8 21.35 9 4.7 9.03 1 4.6 30.0

43

10.Cross-comparison of the ISCO-88 and ISCO-08: the Czech experience7

This aim of this paragraph is to practically examine one aspect of the quality of the ISCO classification as a root of ESeG – coherence – as well as to be a theoretical guideline for the other countries. The described situation in the Czech Republic should serve as an example.

Statistical sources to be used for the ESeG are essentially:Labour Force Survey (LFS)Statistics on Income and Living Conditions (SILC)Adult Education Survey (AES)and other household surveys using “core variables” plus the Structure of Earnings Survey (SES) which is an enterprise survey.

The coherence means eo ipso both the quantitative comparison of results of the above mentioned surveys and the explanation of the differences found.

Second important aspect of this exercise is dealing with the occupational classification changeover: the ISCO-88 has been changed to the ISCO-08 in 2011. For time-series data analyses or the possibility of back-casting the ESeG series, we have to have in mind the way how to abridge this shift. For this reason, beside the comparison between sources, we also need to investigate differences between these two versions.

In order to analyse the coherence, we generally have to make three steps:1) to prepare outputs of all the sources in the same form (or as much similar as possible);2) to depict the whole coding process in which the information on ISCO is gathered, in the most detailed form;3) to evaluate the discrepancies in the results and compare them with the divergences in the methodology or coding practice; and to synthesize.

For the first task, we had to define the united form, see Attachment 1. There is a need to indicate i) the data source, ii) the reference year and iii) the version of classification used, see the heading. Survey results are broken down by major group and sex. Other cross-comparisons are possible, but for the first look this would suffice. Graphic comparison seems the quickest way to asses the coherence.

In the Czech Republic, a comparison was done among the LFS and the SILC and provisional results of the Structure of Earnings Survey for reference year 2010.

Note: We face a problem that more up-to-date results are recently available only for the LFS, they also use ISCO-08. It means that real comparison must be based on the old version of occupational classification ISCO-88. Or we have to wait until June 2012 when the 2011 results should became accessible.

7 This paragraph was written by Dalibor Holy, Czech Statistical Office44

Figure 1

Figure 2

The comparison of LFS and SILC shows great similarity, even broken down by sex, see figure no 1 and 2. It is understandable because of national practise in the household surveys: the same field-workers do the both surveys with the same training as for the ISCO coding. In 2010, there were still divergences concerning coding practice, i.e. the SILC used only 2digit level of ISCO-88 and the LFS required 4digit codes. Also, there was poor support for ISCO coding in the SILC questionnaire. Since 2011, after implementation of the new ISCO-08, all household surveys have been utilizing universal tools implanted to BLAISE electronic questionnaire where the codes are presented on the 5digit level of national ISCO classification8. Therefore,

8 The Czech statistics implemented an occupational classification based on the UN international standard known as ISCO since the beginning of the 1990s under abbreviation KZAM. The Labour Force Survey used this 4-digit national classification, coded directly

45

we expect even more similar results now and in future. On the other hand, there are still discrepancies between weighting systems of LFS and SILC, resulting in the different totals in number of household and persons.Obviously, there will be no need to search on for differences between household surveys in the Czech Republic when they are all carried by the same people and with the same practice. The coherence has to be virtually perfect; the deviations are expected to be under the limit of sampling error. The discrepancies between household survey and enterprise one could tell more.

The Structure of Earnings Survey (SES) is a semi-administrative source on the wages and salaries of employees in the Czech Republic. It covers enterprises with 10+ employees and all organizations of non-business sphere. Occupational classification has been coded on the most detailed level (5digits of national ISCO classification), since 2011 it uses ISCO-08. Coding is provided by the enterprise, it means HR experts, mostly without any help from statisticians. For the older data, 2010 in particular, there was necessary to use a transition key for both surveys.For the SES covers only employees - not the self-employed persons, the result of household survey was also limited to employees in order to make the comparison as close as possible.As we can see on the following figures, in contrast with the data of two household surveys, there are remarkable differences between the LFS and SES results.

Figure 3

The comparison was made on the data for whole year 2010 in which data were gathered in ISCO-88. For the reason of comparison, the results of both surveys were converted to ISCO-08 by transition keys.

As regards the LFS data, the transition key was derived from double-coded panel population 2010 Q4 – 2011 Q1; it covered 80 % of total LFS sample as the rotating scheme changes by 20 % in every quarter. As

by interviewers during the interview. Since 2011, all statistical sources use the same list of occupations based strictly on the new ISCO-08. An enhanced version of the international classification has been created; it has one additional level, so it has finally 5-digit codes, it is named CZ-ISCO. As for the 4-digit level, the CZ-ISCO is the most precise translation of English ISCO-08 to Czech language.The interviewers have been trained and made familiar with the new version as much as possible. They should code all the interviewees to the CZ-ISCO classification just during the interview or almost immediately after it. Also the CAPI software for this household survey (in BLAISE) has been adapted to new CZ-ISCO.

46

regards the SES data, the transition key was created artificially from the most detailed classification (5digits of ISCO) using bottom-up method and historical empirical SES data.

Figure 4

The great gap in the Major Group 5 (MG5) is supposed to be on account of national SES deficiency in the small services, as this survey does not cover enterprises with 1-9 employees.

The worse situation is for the MG1 and MG2 where no such significant methodological differences exist. The LFS data show much smaller part of employees there. On the other hand, MG3 and MG4 show higher proportions. A only explanation at hand is that our interviewers are more strict during the coding as for the distinction whether the respondent has managarial or expert position than the firms’ HR people which code the SES data. If this hypothesis is confirmed, it has consequences for both the ESeG construction and its subsequent use.

According to both sources, the most occupied Major Group is 3 – Technicians and associate Professional, followed by 7 - Craft and related trades workers and 8 - Plant and machine operators and assemblers with similar sizes. Conversely, MG0 and MG6 are very small, on the border of the sampling error of the survey.

After recoding to ISCO-08, the proportions would change, see Figure No 4. Plainly, the flows among MGs happened, from one to another, in various directions. For example, the MG3 is still the most populated MG, but with lower percentage and the difference between LFS and SES changes – it means that the changeover of the occupational classification has been described differently by source there.

On the other hand, the disproportion in MG5 seems untouched, which commend the assumption on the influence of exclusion of small services in the SES. Also, the other discrepancies (MG1 and MG2 and MG4) where the cause is not so clear look still pretty same.

47

What to do next? All in all, we cannot reject data from both kinds of sources, but more care and additional analyses are needed on their quality and suitability for specific purpose as the ESeG has actually been. Similar analyses are needed to be done in other countries. Methodology of the occupational classification varies as well as national practice of coding. Especially the household surveys should be investigated in depth as they would be the elementary sources for the ESeG. All discrepancies have to be explained by the NSI experts who work on these particular surveys.

48

Appendix 1. Target variables Status in employment

The variable collects the professional status of employed persons (employees or self-employed) with a breakdown for employees with permanent or temporary contracts.Codes Labels10 Self-employed20 Employee21 with a permanent job or work contract of unlimited duration22 with temporary job/work contract of limited duration

Status in employment is associated with life chances in a number of important ways. People who are self-employed benefit directly from the level of profit made by the business or enterprise. On the other hand, they are generally more exposed than employees to economic risk, in that their remuneration is tied more directly to the level of profit.

Occupation in employmentThis variable provides information on the occupation in the main job.

Codes labels

36 positions according to ISCO 88 (COM)

The basis for the classification in the ISCO scheme is the nature of the job itself and the level of skill required. It is generally recognised that the type of work performed can have a great influence on the living conditions of the individual and household. Hence, “social stratification” and “social mobility” researchers pay attention to the type of job as a central element in studies of inequalities of opportunities and results, and their reproduction over life cycles and generations.

Economic sector in employment

This core variable is defined as the economic activity of the local unit where the respondent is employed (incl. Self-employed). The economic activity of the enterprise can serve as a proxy where information at local unit cannot be collected or is not available.The scope is limited to persons currently in employment, excluding persons seeking a job.The activity sector in which people are employed is a key descriptor for labour market analysis (including issues linked to skills, mobility of workers, quality of the job, etc.) and together with the occupation (ISCO) and the type of contract is very useful to describe the socio economic status of individuals.

Codes Labels (according to Nace rev1)

1 Agriculture, hunting and forestry; fishing and operation of fishhatcheries and fish farms2 Industry, including energy3 Construction4 Wholesale and retail trade, repair of motor vehicles and householdgoods, hotels and restaurants; transport and communications5 Financial, real-estate, renting and business activities6 Other service activities

49

Appendix 2. Questionnaire to ESS NSIs in the framework of the ESSnet on the European socio-economic groups (ESeG)

Data collection on Occupation and Economic activity in the Labour Force Survey (LFS), EUSILC and Adult Education Survey (AES)

The questionnaire is made up of 18 questions and it is divided into 2 parts: the first one (question from 1 to 10) is devoted to data collection on occupation, the second part (question from 11 to 18) to data collection on economic activity.

Questions from 2 to 9 and questions from 12 to 18 refer to three surveys, the Labour Force survey (LFS), EUSILC and the Adult Education Survey (AES). Please give an answer for each of them.

NSI and country :

Reference person:

Email address :

Occupation

1. What kind of data do you collect with the LFS questions on occupation? - only job titles |_|- both job titles and the work activities performed |_| - only the work activities performed |_|- something else, please explain

|________________________________________| |_|

2. Do EUSILC and AES use the same question wording of the LFS to collect data on occupation?

Yes NO, please explain the differences

- EUSILC |_|

- AES |_|

50

3. When is the occupation coding performed in the LFS, EUSILC and AES respectively?

Only during the interview

Only after the interview process (*)

Both during and after the interview process →

If both during and after, please give an estimate of the coding percentage performed during the interview

- LFS |_| |_| |_| →- EUSILC |_| |_| |_| →- AES |_| |_| |_| →

(*) this means without the possibility, if needed, to get more details from the respondent

4. By whom is the occupation coding performed (more than one answering item is possible)

interviewers experts respondents

- LFSCapi/Cati |_|

Papi |_||_| |_|

- EUSILCCapi/Cati |_|

Papi |_||_| |_|

- AESCapi/Cati |_|

Papi |_||_| |_|

5. Is the coding process supported by IT tools (for instance software to look for job title codes).

No Yes → If yes, please give a short description

- LFS |_| |_| →- EUSILC |_| |_| →

- AES |_| |_| →

6. Do you perform consistency checks between occupation and other variables (for instance the level of education, occupational status)?

NO YES → If yes, do you perform them during or after the interviewDuring the interview (*) After the interview

- LFS |_| |_| → |_| |_|

-EUSILC |_| |_| → |_| |_|

- AES |_| |_| → |_| |_|

(*) for instance with warnings to the interviewer

51

7. If you perform consistency checks, can you please briefly describe them?

Please describe the consistency checks between occupation and other variables (*)

- LFS

- EUSILC

- AES

(*) for instance give the list of variables involved and the types of checks

8. Do you perform other checks on the quality of the occupation coding? (for instance checks on the coherence between the job title and the chosen code or between the codes given by different IT tools)

NO YES → If yes, are there specific areas which seem more problematic to code?Please list them

- LFS |_| |_| →

-EUSILC |_| |_| →

- AES |_| |_| →

9. Do you make a direct use of Isco08 for data collection or do you first code answers with the national classification and then convert them into Isco08?

Direct use of Isco08 Use of national classification and then conversion into Isco08- LFS |_| |_| -EUSILC |_| |_|

- AES |_| |_|

10. If you use a national classification, how do you convert it into Isco08?- using conversion tables that link the national codes to the Isco08 ones |_| - using a job title list coded both in the national classification and in ISCO08 |_|- using conversion routines that make use of ancillary variables (for instance the size of enterprise, level of education) |_|- with other procedures, please explain

|_____________________________________________________| |_|

52

Economic activity

11. What kind of data do you collect with the LFS questions on economic activity?

- only the economic activity titles |_|- both the economic activity titles and a full description of the goods or services produced |_|- only full description of the goods or services produced |_|- name and address of local unit (getting its NACE code from the business register) |_|- something else, please explain |_______________________| |_|

12. Do Eu-silc and Aes use the same question wording of the LFS to collect data on economic activity?

Yes NO, please explain the differences

- EUSILC |_|

- AES |_|

13. When is the economic activity coding performed in the LFS, Eu-Silc and AES respectively?

during the interview after the interview process (*)- LFS |_| |_|- EUSILC |_| |_|- AES |_| |_|

(*) this means without the possibility, if needed, to get more details from the respondent

14. By whom is the economic activity coding performed? (more than one answering item is possible)

interviewers experts respondent

- LFSCapi/Cati |_|

Papi |_||_| |_|

- EUSILCCapi/Cati |_|

Papi |_||_| |_|

- AESCapi/Cati |_|

Papi |_||_| |_|

53

15. In their coding process do the coders use IT tools? (for instance software to look for activity codes).

No Yes → If yes, please give a short description- LFS |_| |_| →- EUSILC |_| |_| →

- AES |_| |_| →

16. Do you perform consistency checks between economic activity and other variables (for instance the occupation, occupational status)?

NO YES → If yes, do you perform them during or after the interviewDuring the interview (*) After the interview

- LFS |_| |_| → |_| |_|

-EUSILC |_| |_| → |_| |_|

- AES |_| |_| → |_| |_|

(*) for instance with warnings to the interviewer

17. If you perform consistency checks, can you please briefly describe them?

Please describe the consistency checks between economic activity and other variables

- LFS

- EUSILC

- AES

18. Do you perform other checks on the quality of the economic activity coding? NO YES → If yes, are there specific areas which seem more problematic

to code?Please list them

- LFS |_| |_| →

-EUSILC |_| |_| →

- AES |_| |_| →

Thank you very much for your cooperation!

54

Appendix 3 - Differences on the Percentages of the Occupation by Major Groups according to Isco08 and Isco88 (3rd quarter 2011-2010)

I MG

-7

-6

-5

-4

-3

-2

-1

0

1

II MG

-4

-2

0

2

4

6

8

10

III MG

-10

-8

-6

-4

-2

0

2

4

6

56

Figure continue- Differences on the Percentages of the Occupation by Major Groups according to Isco08 and Isco88 (3rd quarter 2011-2010)

IV MG

-3-3-2-2-1-101122

V MG

-4

-2

0

2

4

6

8

VI MG

-3

-2

-2

-1

-1

0

1

1

2

57


VII MG

-3

-2

-1

0

1

2

3

4

5

VIII MG

-4

-3

-2

-1

0

1

2

IX MG

-3

-3-2-2

-1-1

0

11

2

58


X MG

-100000000011

59

Appendix 4 - Isco08 Major groups: incoming (from Isco88) and outgoing (to Isco08) unit groups

ISCO08I- Managers

enters from Isco88

exits the occupation previously coded in this major group

now coded in Isco08

Health and age care service managers 2230 Film, stage and related directors and producers 2654 Construction supervisors 3123 Other artistic and cultural associate professionals 3485 Shopkeepers 5221 managers from: Field crop and vegetable growers 6111 Tree and shrub crop growers 6112 Gardeners, horticultural and nursery growers 6113 Mixed crop growers 6114 Livestock and dairy producers 6121 Poultry producers 6122 Mixed crop and animal producers 6130 Forestry and related workers 6210 Aquaculture workers 6221 Inland and coastal waters fishery workers 6222 Deep-sea fishery workers 6223II- ProfessionalsSafety, health and quality inspectors 3152 Nursing and midwifery professionals 134Farming and forestry advisers 3213 Nursing and midwifery professionals 322Medical assistants 3221 Business professionals not elsewhere classified 3339Sanitarians 3222 Dieticians and nutritionists 3223 Optometrists and opticians 3224 Physiotherapists and related associate professionals 3226

Modern health associate professionals (except nursing) not elsewhere classified 3229

Traditional medicine practitioners 3241 Primary education teaching associate professionals 3310

Pre-primary education teaching associate professionals 3320

Special education teaching associate professionals 3330

Other teaching associate professionals 3340 Securities and finance dealers and brokers 3411 Technical and commercial sales representatives 3415

Technical and commercial sales representatives 3415

Decorators and commercial designers 3471 Radio, television and other announcers 3472 Street, night-club and related musicians, singers and dancers 3473

60

Clowns, magicians, acrobats and related associate professionals 3474

III- Technicians and associate professionalsProduction and operations department managers in construction 1223 Radio, television and other announcers

26Production and operations department managers not elsewhere classified 1229 Decorators and commercial designers

216Nursing and midwifery professionals 2230 Physiotherapists and related associate professionals 226Business professionals not elsewhere classified 2419 Modern health associate professionals (except nursing)

not elsewhere classified 226Stenographers and typists 4111 Other teaching associate professionals 235Word-processor and related operators 4112 Technical and commercial sales representatives 243

Data entry operators 4113 Street, night-club and related musicians, singers and dancers 265

Calculating-machine operators 4114 Farming and forestry advisers 2132Secretaries 4115 Traditional medicine practitioners 2230Accounting and bookkeeping clerks 4121 Medical assistants 2240Statistical and finance clerks 4122 Safety, health and quality inspectors 2263Stock clerks 4131 Sanitarians 2263Production clerks 4132 Dieticians and nutritionists 2265Transport clerks 4133 Optometrists and opticians 2267Library and filing clerks 4141 Primary education teaching associate professionals 2341

Mail carriers and sorting clerks 4142 Pre-primary education teaching associate professionals2342

Coding, proof-reading and related clerks 4143 Special education teaching associate professionals 2352Other office clerks 4190 Securities and finance dealers and brokers 2412

Receptionists and information clerks 4222 Clowns, magicians, acrobats and related associate professionals 2659

Telephone switchboard operators 4223 Cooks 5122 Institution-based personal care workers 5132 Metal processing plant operators 812 Chemical-products machine operators 822 Rubber and plastic-products machine operators 823 Textile-, fur- and leather-products machine operators 826 Food and related products machine operators 827 Assemblers 828 Miners and quarry workers 7111 Building frame and related trades workers not elsewhere classified 7129

Precision-instrument makers and repairers 7311 Mining-plant operators 8111 Paper-pulp plant operators 8142 Papermaking-plant operators 8143 Chemical-heat-treating-plant operators 8152 Chemical-filtering- and separating-equipment operators 8153

Chemical-still and reactor operators (except petroleum and natural gas) 8154

Petroleum- and natural-gas-refining-plant operators 8155

61

Chemical-processing-plant operators not elsewhere classified 8159

Power-production plant operators 8161 Incinerator, water-treatment and related plant operators 8163

Automated-assembly-line operators 8171 Industrial-robot operators 8172 Machine-tool operators 8211 Wood-products machine operators 8240 Printing-machine operators 8251 Bookbinding-machine operators 8252 Paper-products machine operators 8253 Other machine operators and assemblers 8290 IV- Clerical support workers

Travel consultants and organisers 3414 Office supervisors, legal and medical secretaries from: 334Travel attendants and travel stewards 5111 Stenographers and typists Word-processor and related operators Data entry operators Calculating-machine operators Secretaries Accounting and bookkeeping clerks Statistical and finance clerks Stock clerks Production clerks Transport clerks Library and filing clerks Mail carriers and sorting clerks Coding, proof-reading and related clerks Other office clerks Receptionists and information clerks Telephone switchboard operators Coding, proof-reading and related clerks 3252 Cashiers and ticket clerks 5230 V- Service and sales workersGeneral managers in wholesale and retail trade 1314

Institution-based personal care workers3258

Other teaching associate professionals 3340 Cooks 3434Cashiers and ticket clerks 4211 Cooks 9411Market-oriented animal producers and related workers not elsewhere classified 6129

Travel attendants and travel stewards4221

Door-to-door and telephone salespersons 9113 Door-to-door and telephone salespersons 9113 Doorkeepers, watchpersons and related workers 9152 Building caretakers 9141 Street food vendors 9111 VI- Skilled agricultural, forestry and fishery workersGeneral managers in agriculture, hunting, forestry and fishing 1314

Market-oriented animal producers and related workers not elsewhere classified 5164

Gardeners, horticultural and nursery growers 9214 Inland and coastal waters fishery workers 7541

62

VII- Craft and related trades workersSafety, health and quality inspectors 3152 Miners and quarry workers 3121Inland and coastal waters fishery workers 6152 Miners and quarry workers 8111Machine-tool operators

8211Building frame and related trades workers not elsewhere classified 3123

Printing-machine operators 8251 Precision-instrument makers and repairers 3214Bookbinding-machine operators 8252 Photographic and related workers 8132Wood-products machine operators 8240 Weavers, knitters and related workers 8152VIII- Plant and machine operators and assemblersMiners and quarry workers 7111 Mining-plant operators 3121Weavers, knitters and related workers 7432 Metal processing plant operators 3135Photographic and related workers 7344 Paper-pulp plant operators 3139 Papermaking-plant operators 3139 Chemical-heat-treating-plant operators 3133 Chemical-filtering- and separating-equipment operators 3133

Chemical-still and reactor operators (except petroleum and natural gas) 3133

Petroleum- and natural-gas-refining-plant operators 3134

Chemical-processing-plant operators not elsewhere classified 3133

Power-production plant operators 3131 Incinerator, water-treatment and related plant operators 3132 Automated-assembly-line operators 3122 Automated-assembly-line operators 3139 Industrial-robot operators 3122 Industrial-robot operators 3139 Machine-tool operators 3122 Machine-tool operators 7211 Machine-tool operators 7223 Chemical-products machine operators 3122 Rubber and plastic-products machine operators 3122 Wood-products machine operators 3122 Wood-products machine operators 7521 Wood-products machine operators 7523 Printing-machine operators 3122 Printing-machine operators 7322 Bookbinding-machine operators 3122 Bookbinding-machine operators 7323 Paper-products machine operators 3122 Textile-, fur- and leather-products machine operators 3122 Food and related products machine operators 3122 Assemblers 3122 Other machine operators and assemblers 3122IX- Elementary occupationsCooks 5122 Street food salespersons 5212Gardeners, horticultural and nursery growers 6113

Door-to-door and telephone salespersons5243

Door-to-door and telephone salespersons 5244 Building caretakers 5153 Doorkeepers, watchpersons and related workers 5414

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