Economic Analysis and Policy最新文献

This research aims to empirically investigate the relationship between bank digital transformation and lending distance. In traditional financial geography theory, banks have a natural geographical proximity preference in their credit decision-making, which might lead to suboptimal credit allocation. Can the rapid development of digitalization improve the situation that banks are only capable of undertaking ex ante due diligence and ex post monitoring of proximate borrowers, given that fintech has greatly improved the overall efficiency of the financial industry? Using bank loan data of listed enterprises in China from 2013 to 2021, this paper finds that the digital transformation of banks can significantly extend the lending distance between banks and enterprises. The moderating effect analysis suggests that distance extending effect of bank digitalization is more pronounced for firms with poor information quality and in competitive banking sector. Further, digital transformation extends the lending distance without increasing risk preferences, as evidenced by the empirical finding that the non-performing loan ratio remains unaffected by the increased distance. Also, geographical expansion in lending distance reduces loan concentration. The research in this paper supports the conclusion that banks' digital transformation positively impacts corporate credit allocation and is beneficial to achieving financial stability by improving loan performances.

This paper investigates the impact of banking competition on corporate labor income share in China. Utilizing hand-collected unique data on bank branches within a certain distance of firms and a large sample of Chinese A-share list firms spanning the period 2000–2022, we find that banking competition significantly boosts corporate labor income share. A 10 percent increase in banking competition, the corporate labor income share increases by 0.06 percent on average. The results remain robust after replacing proxies, changing estimation methods, controlling for other shocks, and addressing endogenous concerns. Easing financing constraints, improving investment efficiency, and enhancing human capital are three essential channels through which banking competition promotes corporate labor income share. We also find that the impact of banking competition on corporate labor income share is more pronounced for firms with higher external financing dependence, higher financing gaps, more investment opportunities, higher governance efficiency, and higher information asymmetry. Our findings highlight the significance of enhancing banking competition to promote income distribution, foster common prosperity, and drive high-quality economic development.

Although most national innovation policy aim to promote urban innovation, their impact on technological specialization and diversification has not been thoroughly explored. This paper examines the impact of the National Innovation City Pilot Policy (NICPP) on technological specialization and diversification in Chinese cities, utilizing data from 282 cities between 2006 and 2019, and employing the difference-in-differences (DID) method. The results indicate that NICPP increases technological specialization while decreasing diversification in cities. The pathways to these outcomes include innovation path dependence, agglomeration effects, and a reduction in breakthrough innovations. Additionally, the policy's spatial spillovers contributed to technological specialization in peripheral areas. The study highlights the heterogeneity of policy effects, suggesting that cities with higher levels of initial specialization are more significantly impacted by these policies, while differences in resource endowment, geographical location, and city size lead to varying patterns of specialization. Moreover, the study verifies the synergistic effect of NICPP with other policies, where initiatives promoting high technology and environmental regulation work in conjunction with NICPP to enhance specialization in corresponding industries. This study offers a comprehensive analysis of the multifaceted impacts of NICPP, delivering theoretical insights and empirical evidence for strategic policy deployment, enhancing regional cooperation, and fostering synergies among policies.

This study examines whether enhanced minority shareholder voting influences corporate liquidity management. Using China's Rules for the Implementation of Online Voting (Rules) as a natural experiment, we find that increased minority shareholder participation leads to a significant reduction in corporate cash hoarding. By enabling their active participation, the Rules curtails tunneling activities, especially in firms with excess cash reserves, thereby mitigating expropriation by controlling shareholders. This effect is notably stronger in firms with weaker external monitoring mechanisms. Our findings also reveal that empowered minority shareholders contribute to more efficient cash allocation, reflected in higher market valuations of cash holdings and a quicker adjustment toward optimal cash levels. Overall, this study highlights the economic benefits of strengthened minority voting rights in mitigating agency problems and promoting value-enhancing liquidity management strategies.

This paper investigates if the complexity of a country's productive structure can help explain variations in income inequality. We use country panel data on 126 countries from 1995 to 2018 and approximate a country's productive structure through the Economic Complexity Index and income inequality from the World Income Inequality Database. Our results found that the relationship between economic complexity and income inequality is not homogenous across countries and, that at the world level, is not linear. Instead, when the level of complexity of the economy is low, increases in complexity mainly lead to an increase in economic inequality. At higher levels of economic complexity, its effect on income inequality becomes negative. This means that economic complexity improves equality after certain thresholds, which seems to reflect the situation of high-income economies.

Against the backdrop of the global COVID-19 pandemic and the deepening structural changes in the Chinese economy, this study presents a four-sector dual Dynamic Stochastic General Equilibrium (DSGE) model that incorporates households, heterogeneous firms, capitalists, and the government, taking into account the current domestic "dual economic structure." The model is used to simulate and analyze the impacts of fiscal policies and technological progress on diverse economic entities during the pandemic. The study reveals several key findings: (1) the pandemic outbreak has a significant short-term impact on the economy, disproportionately affecting small and microenterprises but with higher natural recovery rates compared with large and medium-sized enterprises; (2) unbiased fiscal policies have positive effects on output and capital, with larger output recovery effects observed for large and medium-sized enterprises, while capital recovery effects are less favorable; (3) technological progress contributes to rapid and stable economic growth, yielding overall benefits for large and medium-sized enterprises, but leading to significant crowding-out effects on small and microenterprises; and (4) solely increasing tax support for small and microenterprises, assuming constant tax revenue sources, does not enhance the overall resilience of the economy. These research findings provide policymakers with a dynamic microeconomic foundation within a macroeconomic framework, thereby enhancing the efficacy and precision of policies.

The rising digital economy has reshaped social and economic forms, exerting a profound impact on the industrial structure development. However, few studies have linked digital economy with industrial agglomeration. This paper studied the panel data of 30 provinces in China from 2011 to 2020, constructed the corresponding indicator measurement system to analyze the scale level of China's digital economy and the level of industrial agglomeration. It put forward three hypotheses of the mechanism of digital economy affecting industrial agglomeration, including spatial spillover effect and threshold effect, spatial SDM model with two-way fixed effect and threshold regression model were used to make an empirical analysis. It is found that the digital economy inhibits the industrial agglomeration in the local area and has a positive spatial spillover effect on the surrounding areas, whose impact on the industrial agglomeration is regional heterogeneity. Digital economy has non-linear threshold effect on industrial agglomeration, which exists industry heterogeneity.

Using the Smart City Pilot (SCP) policy as a quasi-experiment, we evaluate the causal effect of place-based information technology policy on digital finance development with a difference-in-differences (DID) approach. Our DID estimates indicate that the SCP policy significantly boosts digital financial inclusion (DFI) in China. Relative to non-pilot cities, this policy increases the DFI index by 1.44 in pilot cities. This increase in the DFI index is mainly driven by the deepened usage of digital finance. Heterogeneity analyses show that the implementation of the SCP policy exerts larger influences on digital finance development in eastern cities, cities with high administrative levels or more education resources, and non-resource-based cities. Furthermore, the stimulated development of the information industry and the improved business environment are two important channels to explain the positive impact of the implementation of this place-based information technology policy on digital finance development.

Global climate change and its subsequent impact on energy demand present pressing issues for policymakers. Existing literature presents various determinants of energy demand, but the intricate relationship between energy demand and climate policy uncertainty (CPU) remains underexplored. Utilizing the Fourier-augmented ARDL (FA-ARDL) model and drawing from monthly data spanning March 1995 to August 2022, we investigate the impact of CPU on energy demand in China. Our study finds a significant long-run co-integration between climate policy uncertainty (CPU) and renewable energy demand. The FA-ARDL analysis shows that CPU negatively impacts renewable energy demand in both the short and long term, as it leads to higher renewable energy prices. These increased prices deter stakeholders from investing in or adopting renewable technologies, making renewables less competitive compared to traditional energy sources. Our findings are helpful for policymakers to communicate the climate objectives since mitigating climate-related uncertainties would substantially drive renewable energy consumption.

This paper develops a simple model to explore whether a higher detection probability of tax evaders—e.g., because of improved exchange of information between countries and/or due to digitalization of tax administrations—renders it optimal for governments to introduce a voluntary disclosure program (VDP) and, if so, under what terms. We find that if the VDP is unanticipated, it is likely to be optimal for a revenue-maximizing government to introduce a VDP with relatively generous terms, i.e., a low or even negative penalty. When anticipated, however, the VDP is neither incentive compatible nor optimal, as it induces otherwise compliant taxpayers to evade tax. A VDP can then only be beneficial if tax evasion induces an external social cost beyond the direct revenue foregone, e.g., due to adverse effects on overall tax morale. In contrast to the common view that VDPs should come along with additional enforcement effort, we find that governments should relax enforcement if the VDP itself provides more powerful incentives to come clean.