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Collection of data on occupations for Finnish Employment Statistics

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Presentation on theme: "Collection of data on occupations for Finnish Employment Statistics"— Presentation transcript:

1 Collection of data on occupations for Finnish Employment Statistics
Workshop on data collection on occupation, Pajunen Airi Employment Statistics Statistics Finland

2 Contents 1 Introduction
2 Collection and sources for occupational data in Finnish Employment Statistics (ES) 3 Coherence with Labour Force Survey (LFS) 4 The reasons for differences between ES and LFS Pajunen - Finnish Employment Statistics

3 Introduction (1/2) Collection of data on occupations with several surveys : HBS, Time Use Survey, Income Distribution Survey etc. Two statistics publish data on numbers in each occupational category: Labour Force Survey (sample survey, >) Employment Statistics (total statistics, >) Pajunen - Finnish Employment Statistics

4 Introduction (2/2) Data on occupations on the entire employed labour force have been produced at five-year intervals in connection with the population census (1980,1985,1990,1995, 2000) The importance of occupational data has grown After 2004 data on occupations have been produced annually in Employment Statistics Most of population census data have been produced annually since 1987 The reason for the late start: the production requires a lot of combining different data sources Pajunen - Finnish Employment Statistics

5 Collection and sources for occupational data in ES (1/2)
In the whole process, the basic rule is that first we define the main employment realtionships in the last week of the year to the each person.. Then we select to each person the occupation which best describes the main employment relationship. Some employed person may get several codes from registers and the inquire and some persons may get none For those employed persons for whom we get no suitable, proper occupational data . We estimated occupational codes from background information. We use backgroud information such as exact industry of their workplaces, education, income, former occupation. And also for all entrepreneurs occupational codes are estimated from data on exact industry of companies and size of their companies. Pajunen - Finnish Employment Statistics

6 Collection and sources for occupational data in ES (2/2) Data sources in the production of occupational data 2005, % Pajunen - Finnish Employment Statistics

7 Coherence (1/2) Employed by occupational major group according to LFS and ES, 2005
Pajunen - Finnish Employment Statistics

8 Coherence (2/2) Differences in employed persons at 3- and 4-digit level
Pajunen - Finnish Employment Statistics

9 Reasons for differences between LFS and ES (1/3)
Differences in concepts employed, entrepreneur, etc. Differences in reference points of time LFS: survey week, ES: last week of the year Differences in nature of data LFS: sample survey, based on the respondents’ own reporting and coded on the basis of job titles ES: total data, collected mainly from administrative registers, coded largely on the basis of job titles. An exception of Employers organisations’ data: coded at first on the basis of job task Differences in coding practices separate coding applications occupations of entrepreneurs Pajunen - Finnish Employment Statistics

10 Employment Statistics:
Reasons for differences (2/3): Differences in coding practices: Occupations of Entrepreneurs Labour Force Survey: entrepreneurs are often coded as managers: the rule is that entrepreneurs have to have at least one hired employee Employment Statistics: Only entrepreneurs with companies at least five employees are classified as managers. The rest are coded according to the industry of their companies Pajunen - Finnish Employment Statistics

11 Reasons for differences (3/3): Differences in coding practices Entrepreneurs by occupational major group in LFS and ES, 2005 29% 3% Entrepreneurs: LFS: FES: Pajunen - Finnish Employment Statistics

12 Future Statistics Finland intends to harmonise the occupational data of the LFS and the Employment Statistics Differences can not be totally eliminated but can be diminished, for instance, by unifying the practices on the coding of entrepreneurs by increasing co-operation between LFS and ES We hope that the new updating classification gives help for this task Thank you ! Pajunen - Finnish Employment Statistics


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