Article type
Abstract
"Background:
The environment plays a crucial role in the sustainable development of human society. However, the rapid pace of industrialization has led to heightened environmental pollution, drawing global attention to the imperative of effective environmental governance. To enhance the ecological environment and elevate human health and well-being, the implementation of environmental regulations is deemed necessary. Yet, it is essential to acknowledge that such regulations may elevate enterprise costs and alter employment structures. Consequently, a key concern among scientists and the public alike revolves around the potential impact of environmental regulations on employment.
Objectives/aims：
The purpose of this study is to systematically assess the comprehensive impact of environmental regulations on employment
Methods：
Initially, computers systematically queried databases such as EBSCO, WOS, JSTOR, and Google Scholar to compile empirical research regarding the influence of environmental regulations on employment. Subsequently, following meticulous literature screening and data extraction, StataMP 16.0 facilitated meta-analysis to determine the comprehensive effect value of environmental regulations on employment. This process included delineating characteristics of empirical analyses in sample data selection, model design, and estimation methods. Furthermore, funnel plots and forest plots were employed to detect and illustrate any potential publication bias.
Main findings：
In this paper, 16 literatures meeting the requirements of meta-regression analysis were selected, and 48 conclusions were extracted from them. According to the meta-regression results, environmental regulations have a comprehensive impact on employment (effect size=-0.008,95%, CI: -0.014, -0.002). We found a significant publication bias in the study sample.
Conclusions:
In the short term, heightened environmental regulations lead to a modest reduction in employment. Moreover, the impact on employment is contingent on the characteristics of diverse sample data and indicator construction."
The environment plays a crucial role in the sustainable development of human society. However, the rapid pace of industrialization has led to heightened environmental pollution, drawing global attention to the imperative of effective environmental governance. To enhance the ecological environment and elevate human health and well-being, the implementation of environmental regulations is deemed necessary. Yet, it is essential to acknowledge that such regulations may elevate enterprise costs and alter employment structures. Consequently, a key concern among scientists and the public alike revolves around the potential impact of environmental regulations on employment.
Objectives/aims：
The purpose of this study is to systematically assess the comprehensive impact of environmental regulations on employment
Methods：
Initially, computers systematically queried databases such as EBSCO, WOS, JSTOR, and Google Scholar to compile empirical research regarding the influence of environmental regulations on employment. Subsequently, following meticulous literature screening and data extraction, StataMP 16.0 facilitated meta-analysis to determine the comprehensive effect value of environmental regulations on employment. This process included delineating characteristics of empirical analyses in sample data selection, model design, and estimation methods. Furthermore, funnel plots and forest plots were employed to detect and illustrate any potential publication bias.
Main findings：
In this paper, 16 literatures meeting the requirements of meta-regression analysis were selected, and 48 conclusions were extracted from them. According to the meta-regression results, environmental regulations have a comprehensive impact on employment (effect size=-0.008,95%, CI: -0.014, -0.002). We found a significant publication bias in the study sample.
Conclusions:
In the short term, heightened environmental regulations lead to a modest reduction in employment. Moreover, the impact on employment is contingent on the characteristics of diverse sample data and indicator construction."