绿色的代价:中国环保税的就业效应

IF 5.2 1区 经济学 Q1 ECONOMICS 中国经济评论 Pub Date : 2024-07-18 DOI:10.1016/j.chieco.2024.102244
Shuling Lu, Qijing Yang
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引用次数: 0

摘要

与指令性法规相比,人们对环境税对劳动力市场的影响知之甚少。本研究考察了 2018 年环境保护税(EPT)对就业的影响。运用三重差分框架,我们实证确定了 EPT 的就业抑制后果,主要归因于产出减少和绿色技术进步。此外,我们的分析凸显了企业为应对不断攀升的环境成本而采取的与规模相关的策略:小型企业选择缩小生产规模,而大型企业则倾向于加大对技术减排措施的投资。异质性分析表明,失业效应在面临更高的财务约束和更大的公众环境关注的公司中更为明显,低技能工人首当其冲,尽管工资不平等现象并不明显。此外,我们还发现,政府的绿色补贴可以抑制这种减少就业的效应。我们的研究揭示了中国环境政策成本对劳动力的意外影响,并强调了全面的政策评估。
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Price of going green: The employment effects of the environmental protection tax in China

Compared with command-and-control regulations, it is less known about the labor market consequences of environmental taxes. This study examines the employment impact of the 2018 Environmental Protection Tax (EPT). Applying a triple-difference framework, we empirically establish the employment-suppressing consequence of EPT, which is primarily attributable to output reductions and green technological advances. Moreover, our analysis highlights a size-dependent strategy adopted by companies to navigate the escalating environmental costs: while small companies opt for production downsizing, larger counterparts tend to invest more in technical abatement initiatives. Heterogeneity analysis reveals that the unemployment effect is more pronounced in companies facing higher financial constraints and greater public environmental attention, with low-skilled workers bearing the brunt, albeit without significant wage inequality. Further, we find that government green subsidies can mute this job-reduction effect. Our study illuminates an unintended incidence of environmental policy costs on labor in China and underscores comprehensive policy evaluation.

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来源期刊
中国经济评论
中国经济评论 ECONOMICS-
CiteScore
10.60
自引率
4.40%
发文量
380
期刊介绍: The China Economic Review publishes original works of scholarship which add to the knowledge of the economy of China and to economies as a discipline. We seek, in particular, papers dealing with policy, performance and institutional change. Empirical papers normally use a formal model, a data set, and standard statistical techniques. Submissions are subjected to double-blind peer review.
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