ANALYZING EMPLOYMENT BY OCCUPATION ACROSS SECTORS IN GREEK LABOR MARKET

In this paper we investigate the trends in the number of employees by occupational category across the economy's main sectors. For the purpose of our study we use mixed-fixed and random coefficient modeling, taking unemployment, gross value added, employee compensation, and proxies for labor fo...

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Bibliographic Details
Published in:Economics & sociology 2022-04, Vol.15 (2), p.24-40
Main Authors: Karamanis, Kostas, Kolias, Giorgios
Format: Article
Language:English
Subjects:
Classification
Econometrics
Employees
Employment
Estimates
Forecasting
Labor economics
Labor force
Labor force participation
Labor market
Literature reviews
Longitudinal studies
Macroeconomics
Occupational mobility
Occupations
Population
Productivity
Random effects
Scarcity
Sovereign debt
Trends
Unemployment
Value added
Variables
Workforce
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Summary:In this paper we investigate the trends in the number of employees by occupational category across the economy's main sectors. For the purpose of our study we use mixed-fixed and random coefficient modeling, taking unemployment, gross value added, employee compensation, and proxies for labor force participation rate as the determining factors. Using annual data from 2000 to 2018, we examine the effects of the determining factors on the share of workers by sector and occupation. Our econometric research shows that the regression coefficients vary between sectors and categories of occupation and the proposed model correctly estimates the dependent variable and the heterogeneous variation of the random effects. Our model can be used to identify occupations with current and future shortages across sectors as well as for assessment and anticipation of employment needs. This study's main contribution is the provision of a flexible and innovative econometric tool, with minimal data requirements, for investigating and assessing employment across economic activities over time. Moreover, in conjunction with other forecasting macroeconomic models, it can offer accurate forecasts for future levels and trends in employment.
ISSN:2071-789X
2306-3459
DOI:10.14254/2071789X.2022/15-2/2