Assessment of the Impact of Green Economy Development on Employment

\nThe relevance of this study is due to the growing attention to the development of green economy and its potential impact on employment. The purpose is to evaluate how green economic development affects employment in Russia, using panel data from 82 regions spanning the period from 2016 to 2020. To analyze the data, we use generalized linear regression models such as OLS, random effects, and fixed effects models. The final fixed effects model explains about 25% of the total variation in unemployment rates across different regions. However, evidence of cross-sectional dependence in the residuals suggests potential challenges, such as the omission of relevant variables that capture unobserved heterogeneity and inadequate consideration of spatial clustering within specific regions. The main results show that expenditure on environmental protection and maintenance of protected areas are positively linked with unemployment. This suggests that these expenditures may not directly lead to job creation. There could be several reasons for that: administrative costs, the delayed effect of environmental investments, or regional disparities in infrastructure and skilled labor availability.\n

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-10-02
DOI
https://doi.org/10.1051/e3sconf/202457407003/pdf
Primary Topic
Sustainable Development and Policies
Type
article
Field-Weighted Citation Impact
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article

Assessment of the Impact of Green Economy Development on Employment

Springer Link (Chiba Institute of Technology)
Sustainable Development and Policies
article

Assessment of the Impact of Green Economy Development on Employment

article en

Abstract

\nThe relevance of this study is due to the growing attention to the development of green economy and its potential impact on employment. The purpose is to evaluate how green economic development affects employment in Russia, using panel data from 82 regions spanning the period from 2016 to 2020. To analyze the data, we use generalized linear regression models such as OLS, random effects, and fixed effects models. The final fixed effects model explains about 25% of the total variation in unemployment rates across different regions. However, evidence of cross-sectional dependence in the residuals suggests potential challenges, such as the omission of relevant variables that capture unobserved heterogeneity and inadequate consideration of spatial clustering within specific regions. The main results show that expenditure on environmental protection and maintenance of protected areas are positively linked with unemployment. This suggests that these expenditures may not directly lead to job creation. There could be several reasons for that: administrative costs, the delayed effect of environmental investments, or regional disparities in infrastructure and skilled labor availability.\n

Springer Link (Chiba Institute of Technology)
Decent work and economic growth
Openalex Percentile: Top 50%
Sustainable Development and Policies
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