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COMPLEMENTING DATA GAPS ON WAGES IN THE LABOUR FORCE SURVEY DATA SET: EVIDENCE FROM POLAND

Economics

COMPLEMENTING DATA GAPS ON WAGES IN THE LABOUR FORCE SURVEY DATA SET: EVIDENCE FROM POLAND

Name and surname of author:

Wojciech Grabowski, Karol Korczak

Year:
2020
Volume:
23
Issue:
3
Keywords:
LFS, SES, microeconometrics, mixed-effects model, data gaps
JEL clasification:
C21 - Single Equation Models - Single Variables: Cross-Sectional Models - Spatial Models - Treatment Effect Models - Quantile Regressions, C50 - Econometric Modeling: General, J01 - Labor Economics: General
DOI (& full text):
https://doi.org/10.15240/tul/001/2020-3-001
Anotation:
The European Union Labour Force Survey (EU LFS) is a widely used source of information on the participation in the labour force of citizens from the countries of the European Union. The LFS data set contains quarterly collected, anonymized data on individuals representing various industries and occupations. The data are collected using common classifications, concepts and definitions. In each country, the same set of characteristics is collected. Despite common standards for data collection, the use of the unified LFS data set may sometimes encounter various difficulties. First of all, from the very beginning of the LFS, there have been numerous methodological changes in sampling (Kerr & Wittenberg, 2015), definitions and classifications (European Commission, 2018). These changes make it difficult to compare data with previous years. Secondly, different cross-national classification rules may produce various problems.
The European Union Labour Force Survey (EU LFS) is a widely used source of information on the participation in the labour force of citizens from the countries of the European Union. The LFS data set contains quarterly collected, anonymized data on individuals representing various industries and occupations. The data are collected using common classifications, concepts and definitions. In each country, the same set of characteristics is collected. Despite common standards for data collection, the use of the unified LFS data set may sometimes encounter various difficulties. First of all, from the very beginning of the LFS, there have been numerous methodological changes in sampling (Kerr & Wittenberg, 2015), definitions and classifications (European Commission, 2018). These changes make it difficult to compare data with previous years. Secondly, different cross-national classification rules may produce various problems.
Section:
Economics
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