Pub Date : 2025-01-02DOI: 10.1016/j.chieco.2024.102340
Zihao Chen , Xu Tian
We examine the impact of the relaxation of birth control policies on women's income. By leveraging variations in birth control polices in China following the implementation of the Universal Two-Child Policy in 2016, we find that the relaxation of birth control significantly reduces women's income and further exacerbates the intra-household income gap. Further investigation into potential mechanisms reveals that the negative impact of the UTC policy on women's income may be primarily due to the motherhood penalties associated with having a second child, as well as labor market discrimination stemming from perceived fertility intentions and increased familial responsibilities. Our study provides crucial insights for policymaking concerning fertility growth and the refinement of fertility support measures.
{"title":"The relaxation of birth control policies adversely affects women's income: Evidence from China's universal two-child policy","authors":"Zihao Chen , Xu Tian","doi":"10.1016/j.chieco.2024.102340","DOIUrl":"10.1016/j.chieco.2024.102340","url":null,"abstract":"<div><div>We examine the impact of the relaxation of birth control policies on women's income. By leveraging variations in birth control polices in China following the implementation of the Universal Two-Child Policy in 2016, we find that the relaxation of birth control significantly reduces women's income and further exacerbates the intra-household income gap. Further investigation into potential mechanisms reveals that the negative impact of the UTC policy on women's income may be primarily due to the motherhood penalties associated with having a second child, as well as labor market discrimination stemming from perceived fertility intentions and increased familial responsibilities. Our study provides crucial insights for policymaking concerning fertility growth and the refinement of fertility support measures.</div></div>","PeriodicalId":48285,"journal":{"name":"中国经济评论","volume":"90 ","pages":"Article 102340"},"PeriodicalIF":5.2,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143128291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-31DOI: 10.1016/j.chieco.2024.102339
Meng Tang
This paper examines how the abolition of agricultural tax contributes to local industrialization in China through the local government's responses. Based on difference-in-differences analysis, this paper demonstrates that the agricultural tax abolition significantly increases the county-level secondary sector's share in GDP and firm-level industrial output. Furthermore, the mechanism analysis reveals that the local governments play a crucial role in supporting industrial growth by expanding bank credits and land provisions. This paper also finds that the agricultural tax abolition positively affects firm entry, TFP, and human capital investment.
{"title":"Industrialize with tax structure change: Agricultural tax abolition and local industrial growth in China","authors":"Meng Tang","doi":"10.1016/j.chieco.2024.102339","DOIUrl":"10.1016/j.chieco.2024.102339","url":null,"abstract":"<div><div>This paper examines how the abolition of agricultural tax contributes to local industrialization in China through the local government's responses. Based on difference-in-differences analysis, this paper demonstrates that the agricultural tax abolition significantly increases the county-level secondary sector's share in GDP and firm-level industrial output. Furthermore, the mechanism analysis reveals that the local governments play a crucial role in supporting industrial growth by expanding bank credits and land provisions. This paper also finds that the agricultural tax abolition positively affects firm entry, TFP, and human capital investment.</div></div>","PeriodicalId":48285,"journal":{"name":"中国经济评论","volume":"90 ","pages":"Article 102339"},"PeriodicalIF":5.2,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143128299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-22DOI: 10.1016/j.chieco.2024.102312
Feng Huang , Haichun Ye , Jing Zhang
This study examines the persistent impact of historical Chinese clan culture on contemporary female labor force participation. Using the hand-collected genealogy data from China, we find that traditional clan-based gender biases significantly suppress women's employment, with the husband's clan heritage strongly influencing the wife's work decisions. The gender bias embedded in Chinese clan culture is the primary driver linking clan heritage to reduced female labor force participation. While women from clan-oriented backgrounds exhibit labor market advantages, these are primarily driven by self-selection into the workforce rather than direct causal effects.
{"title":"Off the books, away from the market: Clan culture and female labor force participation","authors":"Feng Huang , Haichun Ye , Jing Zhang","doi":"10.1016/j.chieco.2024.102312","DOIUrl":"10.1016/j.chieco.2024.102312","url":null,"abstract":"<div><div>This study examines the persistent impact of historical Chinese clan culture on contemporary female labor force participation. Using the hand-collected genealogy data from China, we find that traditional clan-based gender biases significantly suppress women's employment, with the husband's clan heritage strongly influencing the wife's work decisions. The gender bias embedded in Chinese clan culture is the primary driver linking clan heritage to reduced female labor force participation. While women from clan-oriented backgrounds exhibit labor market advantages, these are primarily driven by self-selection into the workforce rather than direct causal effects.</div></div>","PeriodicalId":48285,"journal":{"name":"中国经济评论","volume":"89 ","pages":"Article 102312"},"PeriodicalIF":5.2,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-20DOI: 10.1016/j.chieco.2024.102311
Lifang Zhang , Jiusheng Zhu
Egalitarian gender role attitudes are crucial for empowering women across household, labor market, and political spheres; however, the evolution of these attitudes remains underexplored. This study examines the impact of higher education on gender role attitudes using a quasi-natural experiment based on China's higher education expansion. The data are obtained from the China Family Panel Studies. Our results reveal that this expansion considerably enhanced higher education attainment for men and women; however, the effects on gender role attitudes are asymmetric. While higher education positively influences women's career-related gender norms, it does not substantially impact their marriage-related attitudes or men's gender role attitudes. Moreover, attaining higher education also improves women's career-related gender equality behaviors. Further analysis indicates that these divergent impacts are attributable to patriarchal Confucian culture, educated women's superior labor market performance, and the lack of gender equality education. We also consider the role of marriage-matching patterns, whereby women tend to marry partners with higher education and greater earnings, which reinforces traditional gender roles in marriage.
{"title":"Can higher education improve egalitarian gender role attitudes? Evidence from China","authors":"Lifang Zhang , Jiusheng Zhu","doi":"10.1016/j.chieco.2024.102311","DOIUrl":"10.1016/j.chieco.2024.102311","url":null,"abstract":"<div><div>Egalitarian gender role attitudes are crucial for empowering women across household, labor market, and political spheres; however, the evolution of these attitudes remains underexplored. This study examines the impact of higher education on gender role attitudes using a quasi-natural experiment based on China's higher education expansion. The data are obtained from the China Family Panel Studies. Our results reveal that this expansion considerably enhanced higher education attainment for men and women; however, the effects on gender role attitudes are asymmetric. While higher education positively influences women's career-related gender norms, it does not substantially impact their marriage-related attitudes or men's gender role attitudes. Moreover, attaining higher education also improves women's career-related gender equality behaviors. Further analysis indicates that these divergent impacts are attributable to patriarchal Confucian culture, educated women's superior labor market performance, and the lack of gender equality education. We also consider the role of marriage-matching patterns, whereby women tend to marry partners with higher education and greater earnings, which reinforces traditional gender roles in marriage.</div></div>","PeriodicalId":48285,"journal":{"name":"中国经济评论","volume":"88 ","pages":"Article 102311"},"PeriodicalIF":5.2,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-19DOI: 10.1016/j.chieco.2024.102300
Randolph Luca Bruno , Maria Cipollina , Silvia Dal Bianco
China has been an important trade partner for many African countries, and in particular for South Africa, whose trade volume with China has increased significantly over the past decades. Changes of global trade and Global Value Chains (GVCs) dynamics as response of increasing trade sanctions bring substantial economic challenges for both countries directly involved and countries not directly involved by sanctions. On the one hand, trade sanctions have direct effects on sanctioned countries. On the other, sanctions can have significant indirect effects on countries not involved, as a consequence of trade diversion, changes in comparative advantages, and geopolitical realignment. The paper provides an empirical assessment of Global Value Chains’ re-organization by China and African countries in the age of trade sanctions. It explores and quantifies the intertwined relationship between trade sanctions, GVCs participation, and Revealed Comparative Advantage (RCA), with a focus on the dyad China–South Africa in a comparative perspective vis-á-vis other Chinese trade partners. The analysis is based on a purpose-built dataset covering GVCs participation indexes on 66 origin and destination countries for 68 industries (ISIC Rev.4) over the period 2005–2018. A simplified evolutionary model shows how the indirect effect of sanctions on forward GVCs could be positive and sizable, the mechanism being the displacement of (heterogeneous) inefficient firms with (heterogeneous) more efficient ones; while the indirect effect of sanctions on backward GVCs is indeterminate. By zooming onto the China–South Africa relations, the paper sheds new light on the consequences of sanctions, as perceived from both buyer’s (backward) and seller’s (forward) perspective, in a so-called South–South trade partnership.
{"title":"Trade sanctions and Global Value Chains: A China–South Africa perspective","authors":"Randolph Luca Bruno , Maria Cipollina , Silvia Dal Bianco","doi":"10.1016/j.chieco.2024.102300","DOIUrl":"10.1016/j.chieco.2024.102300","url":null,"abstract":"<div><div>China has been an important trade partner for many African countries, and in particular for South Africa, whose trade volume with China has increased significantly over the past decades. Changes of global trade and Global Value Chains (GVCs) dynamics as response of increasing trade sanctions bring substantial economic challenges for both countries directly involved and countries not directly involved by sanctions. On the one hand, trade sanctions have direct effects on sanctioned countries. On the other, sanctions can have significant indirect effects on countries not involved, as a consequence of trade diversion, changes in comparative advantages, and geopolitical realignment. The paper provides an empirical assessment of Global Value Chains’ re-organization by China and African countries in the age of trade sanctions. It explores and quantifies the intertwined relationship between trade sanctions, GVCs participation, and Revealed Comparative Advantage (RCA), with a focus on the dyad China–South Africa in a comparative perspective vis-á-vis other Chinese trade partners. The analysis is based on a purpose-built dataset covering GVCs participation indexes on 66 origin and destination countries for 68 industries (ISIC Rev.4) over the period 2005–2018. A simplified evolutionary model shows how the indirect effect of sanctions on forward GVCs could be positive and sizable, the mechanism being the displacement of (heterogeneous) inefficient firms with (heterogeneous) more efficient ones; while the indirect effect of sanctions on backward GVCs is indeterminate. By zooming onto the China–South Africa relations, the paper sheds new light on the consequences of sanctions, as perceived from both buyer’s (backward) and seller’s (forward) perspective, in a so-called South–South trade partnership.</div></div>","PeriodicalId":48285,"journal":{"name":"中国经济评论","volume":"89 ","pages":"Article 102300"},"PeriodicalIF":5.2,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study investigates the phenomenon of household consumption rising and then dropping after payday, even in the absence of liquidity constraints. Utilizing data from a large bank, we document two findings that jointly provide a rationale for such payday consumption cycle. First, we find that consumption surges around payday only among groups exhibiting strong present bias. Second, we identify the presence of mental budget constraints, where a plausibly exogenous payday surge in consumption predicts a decrease in consumption three and four weeks later, even in the absence of liquidity constraints. These findings suggest that present bias together with mental budget constraints provide an explanation for the payday consumption cycle.
{"title":"Present bias, mental budget constraint, and the payday consumption cycle","authors":"Yonghao Xu , Juanjuan Meng , Yu Zhang , Jeffrey Koo","doi":"10.1016/j.chieco.2024.102306","DOIUrl":"10.1016/j.chieco.2024.102306","url":null,"abstract":"<div><div>This study investigates the phenomenon of household consumption rising and then dropping after payday, even in the absence of liquidity constraints. Utilizing data from a large bank, we document two findings that jointly provide a rationale for such payday consumption cycle. First, we find that consumption surges around payday only among groups exhibiting strong present bias. Second, we identify the presence of mental budget constraints, where a plausibly exogenous payday surge in consumption predicts a decrease in consumption three and four weeks later, even in the absence of liquidity constraints. These findings suggest that present bias together with mental budget constraints provide an explanation for the payday consumption cycle.</div></div>","PeriodicalId":48285,"journal":{"name":"中国经济评论","volume":"89 ","pages":"Article 102306"},"PeriodicalIF":5.2,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-17DOI: 10.1016/j.chieco.2024.102266
Yueling Wei , Hongsheng Zhang , Zihan Zhao
Drawing on OECD Inter-Country Input-Output Database and Carbon Dioxide Emissions Embodied in International Trade Database from 2000 to 2018, this study measures the level of industrial digitalization of 44 industries in South Africa from the input side and empirically analyzes the effect of industrial digitalization on CO2 emissions. The results show that industrial digitalization significantly reduces the intensity of CO2 emissions in production. The effect of industrial digitalization on CO2 emissions exhibits more prominent for the tertiary industry and those industries with high digital skills. The digital inputs from foreign countries have a greater impact on CO2 emissions than domestic digital inputs. Industrial digitalization reduces CO2 emissions through two mechanisms: increasing productivity and optimizing the factor input structure. Furthermore, we compare South Africa with other four BRICS countries and find that significant emission reduction effects are observed through industrial digitalization in Brazil, South Africa and China. These findings carry important practical implications for industrial digital transformation and sustainable development in developing countries, particularly in promoting eco-friendly production and enhancing the quality of economic development in African nations.
{"title":"Digitalization and pollution: Evidence from South Africa","authors":"Yueling Wei , Hongsheng Zhang , Zihan Zhao","doi":"10.1016/j.chieco.2024.102266","DOIUrl":"10.1016/j.chieco.2024.102266","url":null,"abstract":"<div><div>Drawing on OECD Inter-Country Input-Output Database and Carbon Dioxide Emissions Embodied in International Trade Database from 2000 to 2018, this study measures the level of industrial digitalization of 44 industries in South Africa from the input side and empirically analyzes the effect of industrial digitalization on CO2 emissions. The results show that industrial digitalization significantly reduces the intensity of CO2 emissions in production. The effect of industrial digitalization on CO2 emissions exhibits more prominent for the tertiary industry and those industries with high digital skills. The digital inputs from foreign countries have a greater impact on CO2 emissions than domestic digital inputs. Industrial digitalization reduces CO2 emissions through two mechanisms: increasing productivity and optimizing the factor input structure. Furthermore, we compare South Africa with other four BRICS countries and find that significant emission reduction effects are observed through industrial digitalization in Brazil, South Africa and China. These findings carry important practical implications for industrial digital transformation and sustainable development in developing countries, particularly in promoting eco-friendly production and enhancing the quality of economic development in African nations.</div></div>","PeriodicalId":48285,"journal":{"name":"中国经济评论","volume":"88 ","pages":"Article 102266"},"PeriodicalIF":5.2,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-17DOI: 10.1016/j.chieco.2024.102307
Changbiao Zhong , Chao Zhang
Empowering urban innovation is particularly crucial in the new development paradigm. The capacity of data elements to drive urban innovation is a significant issue that warrants exploration. Based on the panel data of Chinese cities from 2011 to 2021, we empirically estimate the effect of data elements on urban innovation using a two-way fixed-effects panel model and analyze the influencing mechanism using a mediated-effects model. The study finds that data elements significantly enhance urban innovation capacity, and this conclusion remains valid after a series of rigorous tests for robustness. The results of the mechanism analysis indicate that data elements can boost urban innovation capacity by promoting the integration of manufacturing and service industries, increasing urban entrepreneurial activity, and enhancing urban digital finance. Heterogeneity analysis reveals that data elements have a more significant impact on enhancing the innovation capacity of cities in eastern China, high-level cities, and cities with high levels of science and education. The findings of this study provide valuable guidance for formulating policies aimed at promoting the data elements market and enhancing urban innovation vitality.
{"title":"Can data elements enhance urban innovation? Evidence from China","authors":"Changbiao Zhong , Chao Zhang","doi":"10.1016/j.chieco.2024.102307","DOIUrl":"10.1016/j.chieco.2024.102307","url":null,"abstract":"<div><div>Empowering urban innovation is particularly crucial in the new development paradigm. The capacity of data elements to drive urban innovation is a significant issue that warrants exploration. Based on the panel data of Chinese cities from 2011 to 2021, we empirically estimate the effect of data elements on urban innovation using a two-way fixed-effects panel model and analyze the influencing mechanism using a mediated-effects model. The study finds that data elements significantly enhance urban innovation capacity, and this conclusion remains valid after a series of rigorous tests for robustness. The results of the mechanism analysis indicate that data elements can boost urban innovation capacity by promoting the integration of manufacturing and service industries, increasing urban entrepreneurial activity, and enhancing urban digital finance. Heterogeneity analysis reveals that data elements have a more significant impact on enhancing the innovation capacity of cities in eastern China, high-level cities, and cities with high levels of science and education. The findings of this study provide valuable guidance for formulating policies aimed at promoting the data elements market and enhancing urban innovation vitality.</div></div>","PeriodicalId":48285,"journal":{"name":"中国经济评论","volume":"88 ","pages":"Article 102307"},"PeriodicalIF":5.2,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-15DOI: 10.1016/j.chieco.2024.102297
Ye Chen , Cagri S. Kumru , Yurui Zhang
This paper analyzes the optimal tax combination using a model that incorporates differential mortality and human capital accumulation. We calculate the optimal combinations of the capital income tax, consumption tax, and progressive labor income tax rates for the Chinese economy under four different model settings: a standard life-cycle model without human capital accumulation (NHC), an NHC model with differential mortality (NHC+DM), a life-cycle model with human capital accumulation (HC), and an HC model with differential mortality (HC+DM). Our results of implementing the optimal capital income tax rates in the Chinese economy are 8.1%, 7.9%, 2.6%, and 15.4%, respectively. The optimal labor income tax includes a 41.6% marginal tax rate with a 98,010 yuan fixed deduction, a 21.0% marginal tax rate with a 97,253 yuan deduction, a 3.1% marginal tax rate with a 96,225 yuan deduction, and an 18.5% marginal tax rate with a 97,535 yuan deduction, respectively. In a nutshell, we find that the optimal tax bundles under each model are different for China. It would be better to incorporate both human capital accumulation and differential mortality for a more comprehensive model for optimal taxation analysis in China.
{"title":"Optimal taxation, differential mortality, and endogenous human capital accumulation in China","authors":"Ye Chen , Cagri S. Kumru , Yurui Zhang","doi":"10.1016/j.chieco.2024.102297","DOIUrl":"10.1016/j.chieco.2024.102297","url":null,"abstract":"<div><div>This paper analyzes the optimal tax combination using a model that incorporates differential mortality and human capital accumulation. We calculate the optimal combinations of the capital income tax, consumption tax, and progressive labor income tax rates for the Chinese economy under four different model settings: a standard life-cycle model without human capital accumulation (NHC), an NHC model with differential mortality (NHC+DM), a life-cycle model with human capital accumulation (HC), and an HC model with differential mortality (HC+DM). Our results of implementing the optimal capital income tax rates in the Chinese economy are 8.1%, 7.9%, 2.6%, and 15.4%, respectively. The optimal labor income tax includes a 41.6% marginal tax rate with a 98,010 yuan fixed deduction, a 21.0% marginal tax rate with a 97,253 yuan deduction, a 3.1% marginal tax rate with a 96,225 yuan deduction, and an 18.5% marginal tax rate with a 97,535 yuan deduction, respectively. In a nutshell, we find that the optimal tax bundles under each model are different for China. It would be better to incorporate both human capital accumulation and differential mortality for a more comprehensive model for optimal taxation analysis in China.</div></div>","PeriodicalId":48285,"journal":{"name":"中国经济评论","volume":"88 ","pages":"Article 102297"},"PeriodicalIF":5.2,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-15DOI: 10.1016/j.chieco.2024.102308
Zhenhua Zhang , Yunpeng Zhang , Huangbin Wu , Shunfeng Song , Yuxi Pan , Yanchao Feng
The “technology dividend” brought by the development of artificial intelligence (AI) can optimize the allocation of resource within enterprises, provide a new model for enterprises to achieve sustainable development, and create a new power source for enterprise economic development and pollution reduction. Although the advantages and disadvantages of AI have been widely discussed, few studies have explored whether it can play the dual effects on economy and environment from the perspective of enterprises. Considering the difficulty of measuring AI indicators, this paper attempts to explore the impact of automation, as a key underlying technology of AI, on enterprise economic performance and environmental performance, and rationally infer the dual impact of AI. We use panel data from China's Shanghai and Shenzhen A-share listed companies from 2009 to 2021 to reveal the dual effects of automation. The benchmark regression results show that automation can boost both enterprise economic and environmental performance. The result is still credible after a series of robustness tests and causal identification. Moreover, we find that the economic performance is stronger in non-heavily polluted enterprises. The dual effects of automation are more significant in areas with low environmental regulations and areas with high levels of industrial digitalization and digital industrialization. The mechanism analysis results show that automation can play the dual effects through the cost-effectiveness channel, the capital-labor substitution channel, and the energy-saving and emission reduction channel.
人工智能（AI）发展带来的 "技术红利 "可以优化企业内部资源配置，为企业实现可持续发展提供新模式，为企业经济发展和污染减排创造新的动力源。虽然人工智能的优缺点已被广泛讨论，但很少有研究从企业角度探讨人工智能能否发挥经济和环境的双重效应。考虑到人工智能指标难以衡量，本文试图探讨作为人工智能关键底层技术的自动化对企业经济绩效和环境绩效的影响，合理推断人工智能的双重影响。我们利用 2009 年至 2021 年中国沪深 A 股上市公司的面板数据，揭示了自动化的双重影响。基准回归结果表明，自动化可以同时提升企业的经济绩效和环境绩效。经过一系列稳健性检验和因果识别后，结果仍然可信。此外，我们还发现，非重度污染企业的经济绩效更强。自动化的双重效应在环境法规较少的地区以及工业数字化和数字工业化水平较高的地区更为显著。机理分析结果表明，自动化可以通过成本效益渠道、资本-劳动力替代渠道和节能减排渠道发挥双重效应。
{"title":"Dual effects of automation on economy and environment: Evidence from A-share listed enterprises in China","authors":"Zhenhua Zhang , Yunpeng Zhang , Huangbin Wu , Shunfeng Song , Yuxi Pan , Yanchao Feng","doi":"10.1016/j.chieco.2024.102308","DOIUrl":"10.1016/j.chieco.2024.102308","url":null,"abstract":"<div><div>The “technology dividend” brought by the development of artificial intelligence (AI) can optimize the allocation of resource within enterprises, provide a new model for enterprises to achieve sustainable development, and create a new power source for enterprise economic development and pollution reduction. Although the advantages and disadvantages of AI have been widely discussed, few studies have explored whether it can play the dual effects on economy and environment from the perspective of enterprises. Considering the difficulty of measuring AI indicators, this paper attempts to explore the impact of automation, as a key underlying technology of AI, on enterprise economic performance and environmental performance, and rationally infer the dual impact of AI. We use panel data from China's Shanghai and Shenzhen A-share listed companies from 2009 to 2021 to reveal the dual effects of automation. The benchmark regression results show that automation can boost both enterprise economic and environmental performance. The result is still credible after a series of robustness tests and causal identification. Moreover, we find that the economic performance is stronger in non-heavily polluted enterprises. The dual effects of automation are more significant in areas with low environmental regulations and areas with high levels of industrial digitalization and digital industrialization. The mechanism analysis results show that automation can play the dual effects through the cost-effectiveness channel, the capital-labor substitution channel, and the energy-saving and emission reduction channel.</div></div>","PeriodicalId":48285,"journal":{"name":"中国经济评论","volume":"88 ","pages":"Article 102308"},"PeriodicalIF":5.2,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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