Economic Analysis and Policy最新文献

Government intervention in industrial development is prevalent across both developed and developing nations. This paper evaluates the efficacy of Chinese government intervention in high-tech industries in fostering economic development. Methodologically, we assess government intervention's effectiveness by examining the heterogeneity of agglomeration effects in high-tech industries across various locations before and after policy interventions. Our study reveals several key findings: (1) Overall, high-tech industry agglomeration yields positive intra-industry and local spillover effects. (2) Agglomeration effects exhibit significant spatial and temporal variations. Before 2013, government intervention was limited, and high-tech industries predominantly clustered in the eastern region due to market forces, resulting in significantly positive agglomeration effects. However, post-2013, government intervention became evident, particularly driven by competitive dynamics in less-developed regions and central government support for these areas. Consequently, high-tech industries in these regions generated positive intra-industry and local spillover effects, leading to a shift in the distribution of high-tech industry hubs towards the central and western regions. Nonetheless, agglomeration effects diminished in these regions, signaling distortions. (3) Not all high-tech industries exert positive impacts; for instance, the ICT manufacturing sector, characterized by general technology, demonstrates the most pronounced effects, whereas the aerospace manufacturing industry shows relatively weaker agglomeration effects. (4) High-tech industries primarily enhance industrial profitability by refining intermediate inputs and foster local total factor productivity and green total factor productivity through knowledge spillovers. Consequently, policy interventions should aim to effectively facilitate intermediary mechanisms. These findings offer valuable insights into how governments can judiciously intervene in high-tech industries to promote sustainable economic development.

The digital economy has introduced new ideas and methods for the high-quality development of agriculture, becoming a driving force for enhancing agricultural production efficiency. This manuscript utilizes balanced panel data from 1,503 counties and employs the three-stage DEA-Malmquist method to measure agricultural total factor productivity (hereinafter referred to as ATFP). Fixed effect models and mediation models are used to explore the impact and mechanisms of digital rural development on ATFP. The research findings indicate that both ATFP and digital rural development are increasing, although regional disparities exist. The eastern region has higher levels of digital rural development and ATFP compared to the central and western regions. Analysis using fixed effect models and mediation models shows that digital rural development has a significant positive effect on ATFP during the sample period, with rural inclusive finance and human capital playing a mediating role. The impact of digital rural development on ATFP varies across regions. It is more prominent in main grain-producing and main grain-consuming areas, and less significant in balanced production and consumption areas. Geographically, the impact is stronger in the eastern region than in the central and western regions. When categorized by the type of agricultural production, the impact is significant in livestock areas, while relatively smaller in planting industry areas. Based on these findings, it is recommended that local areas tailor their approach to digital rural construction and formulate agricultural production policies that leverage regional strengths and address weaknesses. Additionally, promoting the development of rural inclusive finance, cultivating digital talent, improving talent introduction policies, and expanding the rural digital talent pool are suggested to build momentum for agricultural development.

The global climate issue is becoming increasingly serious, and studying the energy transition (ET) has proven to be an effective solution to this problem. The essence of climate mitigation is to address the issue of ensuring the public health (pH) of human beings. Still, the definitions of ET in existing literature are inconsistent, and Many researches overlook the definitions of ET in official documents and discuss the relationship between ET and pH. Therefore, this research utilizes panel data from 107 countries over the period 2000–2020 to construct an energy transition indicator based on the definition from the World Economic Forum (WEF). It also examines the link between ET and pH using a two-way fixed effects regression. In the current turbulent international environment, this paper also investigates this link in the context of composite risk control (CRC), financial risk control (FRC), economic risk control (ERC), and political risk control (PRC). The results show that ET can significantly improve pH, a conclusion that remains significant after being subjected to a range of robustness tests. The study exploring the mechanism impact on the relationship between ET and pH shows that CRC, FRC, ERC, and PRC all strengthen the effect of ET on pH, and the mechanism effect varies considerably between high-income and low- and middle-income countries (LMICs); ET is more significantly affected by the mechanism in LMICs than in high-income countries. Furthermore, this paper illustrates that ET does not differ by gender in improving pH among infants, while there are gender differences in adults by using the instrumental variable regression and GMM regression to mitigate the endogenous and heteroscedasticity issue for heterogeneity test. The study in this paper can not only inspire policy researchers on which aspects to promote ET, but also provide a direction for improving pH.

Corporate environmental information disclosure (EID) is an important green signal. While prior literature well documents that the leading officials’ accountability audit of natural resources assets (AANRA) can effectively enhance the environmental regulatory pressure of local governments, little is known about whether this pressure can promote corporate EID. Utilizing panel data of 2,073 Chinese industrial listed enterprises from 2008–2021, we employ a staggered difference-in-difference-in-differences approach and identify the causal effect of AANRA on corporate EID. The results show that the EID quality of heavily polluting enterprises in AANRA cities increases by 3.28 % after the implementation of AANRA, and this effect persists. Meanwhile, AANRA does not trigger selective disclosure of enterprises, and its improvement of negative EID is more effective. Our mechanism analysis suggests that AANRA improves corporate EID through environmental incentive effect, environmental, social and governance (ESG) engagement effect and cost constraint effect. Moreover, the effect of AANRA varies with firms, industries, and regions, and it is more pronounced in non-state-owned firms, small firms, growing and mature firms, highly competitive firms, high-tech firms, and firms located in the eastern region, high audit intensity region and better institutional region. Our findings highlight the role of government environmental regulatory pressure in corporate EID, providing new insights into green transformation for enterprises in developing countries like China.

This paper investigates the implications of fiscal policy for labor income inequality through two causal channels. First, I estimate how fiscal policy reacts to negative income shocks happening at different points on the labor income distribution, to examine whether fiscal policy responds differently when there are changes in income for low-income earners, versus median-income earners or high-income earners. Secondly, I estimate the impact that various fiscal policies have on labor market income at the low, median, and high ends. I consider eight different fiscal policy variables, including four types of government transfer variables shown to be countercyclical, government consumption and government investment, and personal versus corporate tax revenue. Embedding each fiscal policy variable into a Bayesian structural vector autoregression, I estimate both the reaction of each fiscal policy variable to shocks to labor income at three points of the labor income distribution, and the impact of shocks to each fiscal policy variable on labor income along the same three points of the distribution. Impulse response functions show most fiscal policies are more responsive to shocks to the low end of the income distribution. The impulse response functions also show that it is often the median and upper-end of the income distribution that benefit most from fiscal expansions, leading to greater income inequality. The results also reveal that the fiscal policies most effective for boosting income at low income levels also lead to the largest increases in income inequality. Finally, I find that the fiscal policies most effective for stimulating labor income are also the least responsive to labor income shocks.

This paper studies the housing sector of Hong Kong and the role of collateral constraint in modelling Hong Kong economy, through the lens of a small open economy DSGE model with a currency board exchange rate commitment. By estimating and evaluating the model by Indirect Inference over the sample period of 1994Q1–2018Q3, it is found that the collateral model can match data behaviour. Comparing with the tests generated from the model without collateral, collateral model can match the housing price data better, while the model without collateral fits the general price better. Since collateral constraint acts like an additional transmission channel, it enhances the impact from shocks and housing price is highly determined by housing demand. We further investigate LTV policy, finding it could be applied as macroprudential policy, especially when addressing the problem caused by increase in the US interest rate and the burst in the domestic housing demand, but the government should watch closely to the crowding out effect from export to housing demand and housing investment.

Few studies have explored the impact of heterogeneous government investment on corporate bond ratings from the perspective of government social capital allocation. This paper examines the bond market's response to government social capital allocation, utilizing empirical data from the bond ratings of listed companies issued between 2008 and 2020. The analysis begins with a rational explanation, conceptual definition, and index construction of government social capital. The empirical research finds that government social capital allocation significantly enhances corporate credit ratings. Mechanism tests reveal that local governments provide “government support” signals through short-term and long-term borrowing, enabling firms to secure more long-term loans and reduce their default risk. These signals are captured by rating agencies, which then influence the rating outcomes. Heterogeneity tests indicate that the positive impact of government capital allocation on ratings is more pronounced during periods of corporate financial distress. Furthermore, foreign rating agencies are better able to capture signals of government social capital allocation, and their independence confirms that high ratings are not the result of rating inflation.

This study examines the problem of enterprise energy consumption intensity from the perspective of executive environmental protection experience using data for China's A-share listed enterprises from 2007 to 2021. It is revealed that executive environmental protection experience has negatively impact on the enterprise energy consumption intensity. Moreover, the negative effect of executive environmental protection experience on enterprise energy consumption intensity is particularly pronounced in non-state-owned and low-energy consuming enterprises. According to mechanism study, the three primary approaches are low-carbon technology innovation, enterprise environmental protection investment, and recruiting green investors. In addition, media attention positively moderates the relationship between executive environmental protection experience and enterprise energy consumption intensity. The conclusions help to understand the influence mechanism of executive environmental protection experience on the enterprise energy consumption intensity at the micro level and have implications for pushing enterprise to save energy.

Urban pollution governance requires the joint participation of government, society, and enterprises, with the environmental information disclosure policy serving as a novel tool to promote multi-stakeholder engagement. This study aims to delve into the impact of the environmental information disclosure policy on regional environmental quality by using data from Chinese cities. Through analysis, the study gets the following conclusions. Firstly, the environmental information disclosure policy not only effectively reduces urban environmental pollution but also exhibits an apparent spatial spillover effect. The impact of this policy on air pollution in neighboring cities shows an inverted U-shaped pattern of first rising and then falling, with the optimal radius of this external effect estimated at 250 km. Secondly, the results of the mechanism test indicate that government regulatory efforts and clean industry alternatives are essential channels for curbing urban environmental pollution. Lastly, the heterogeneity test shows that the inhibitory effect of the environmental information disclosure policy on environmental pollution is more pronounced in civilized cities, cities in the “two control zones”, sulfur dioxide control zones, and cities with high Pollution Information Transparency Index scores.

In the context of a global economic slowdown and structural shifts, comprehending labor market stability is crucial for devising effective macro-employment strategies. This research introduces an innovative framework to analyze employment resilience in the wake of China's smart city pilot policy. Utilizing data from 275 prefecture-level cities across China, spanning 2008 to 2020, the study delves into the beneficial effects of the smart city pilot policy on employment resilience. It employs a dual approach, integrating the Differences-in-Differences method (DID) with robustness analysis. Findings indicate that employment resilience in smart city pilot cities is approximately 0.58% higher compared to non-pilot cities. Factors such as location, size, and city type exhibit varying influences on this outcome. The research further reveals that entrepreneurial activities significantly mediate the link between smart city policies and employment resilience. Additionally, the concentration of manufacturing and productive services, along with their interplay, demonstrates notable moderating effects. This investigation broadens the economic research scope regarding smart cities and offers fresh empirical insights into the labor market impacts of smart city pilot policies, serving as a valuable guide for policymakers in managing employment markets.