Analyzing employment by occupation across sectors in Greek labor market

K. Karamanis, Giorgios Kolias
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Abstract

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.
分析希腊劳动力市场各部门的就业情况
在本文中,我们调查了经济主要部门按职业类别的雇员人数的趋势。本文采用固定系数和随机系数混合模型,将失业率、总增加值、员工薪酬和劳动力参与率作为决定因素。使用2000年至2018年的年度数据,我们按部门和职业检查了决定因素对工人比例的影响。我们的计量经济学研究表明,回归系数在行业和职业类别之间存在差异,所提出的模型正确地估计了因变量和随机效应的异质性变异。我们的模型可用于识别当前和未来各部门短缺的职业,以及评估和预测就业需求。本研究的主要贡献是提供了一种灵活和创新的计量经济学工具,以最少的数据要求来调查和评估一段时间以来经济活动中的就业情况。此外,结合其他预测宏观经济模型,它可以对就业的未来水平和趋势提供准确的预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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