Purpose This study investigates how China's judicial independence reform curbs local protectionism, thereby enhancing the efficiency and rational allocation of governmental resources, particularly among state-owned enterprises (SOEs) and local SOEs. Design/methodology/approach Based on the quasi-natural experiment of China's 2014–2019 judicial management reform, this study employs a difference-in-differences (DID) model to empirically examine the impact of judicial independence on the efficiency of government subsidies. To ensure robustness, a series of validation methods are applied, including alternative sample tests, cross–fixed effects estimation, controlling for confounding events (circuit courts), placebo tests and parallel trend tests. Findings The reform curbs local protectionism and significantly reduces government subsidies to SOEs, especially local SOEs. Three mechanisms explain this outcome: (1) eliminating resource allocation barriers, (2) enhancing resource allocation efficiency and (3) intensifying regulatory scrutiny towards resource allocation. Although R&D subsidies and expenditures declined, innovation outputs increased, indicating improved efficiency of innovation resource allocation. Furthermore, the reform generates positive abnormal stock returns around subsidy announcements, reflecting enhanced investor confidence in judicial impartiality and improved fiscal transparency. Originality/value This study makes three main contributions. First, it integrates judicial independence into the analytical framework of government subsidy allocation, emphasizing institutional quality as a determinant of fiscal efficiency. Second, it reveals a novel mechanism linking judicial reform to corporate innovation through subsidy restructuring, offering new insights into law–finance–innovation interactions. Third, it identifies the market announcement effect of judicial reforms, demonstrating how enhanced judicial impartiality fosters investor confidence and enterprise value.

Rural roads in narrowing regional income inequality: A quasi-natural experiment from China

Minority shareholders protection and the incremental textual information in analysts' reports: A quasi-natural experiment in China

Driving digital innovation through quality incentives: Evidence from Chinese cities in the digital transformation era

Does urban agglomeration policy improve urban land use efficiency? A quasi-natural experiment based on 281 Chinese cities

Human presence in protected forests impacts wildlife, but investigating such impacts is challenging because it is rare to isolate human presence from other anthropogenic factors. The COVID-19 lockdowns in 2020 provided a quasi-natural experiment that reduced human activity on Barro Colorado Island, a tropical forest isolated from most human footprints in Panamá. We used trail-based camera trap data from mammal species to compare a lockdown period (April-July 2020) versus non-lockdown (2019). For all observed species, we tested the hypotheses that human presence impacts activity level for 14 species, and for focal species we also tested diel activity, predator-prey dynamics, group cohesiveness, scent-marking, foraging, and vigilance. To assess lockdown effect, we analyzed our data using negative binomial, logistic and recurrent event analysis, and we contrasted null and alternative models. We also estimated diel activity patterns and used confidence intervals to examine lockdown effects. Based on camera trap observations, human presence on BCI forest was 9 times lower, while 16.2 times lower based on safety book records. Results showed no significant changes in activity level(rate of events) and diel activity for any species; in foraging duration of agouti, collared-peccary, red-brocket deer, and white-nosed coati; in predator-prey dynamic between agouti and ocelot; and in scent-marking of agouti. However, group cohesiveness and vigilance of white-nosed coati and collared-peccary were higher during lockdown. Overall, under lockdown, animal activity and diel activity patterns remained unchanged, although agouti, peccary, coati, and ocelot's diel activity slightly increased during typical human-active hours. Our results indicate that mammals, living on a managed forest with low anthropogenic impact and disturbance, can tolerate non-consumptive human presence.

ABSTRACT This paper uses China’s New Asset Management Rules as the policy shock and tests whether passageway business regulation affects stock price crash risk. The results indicate that treated firms experience a marked decline in crash risk after the regulation. Mechanism tests suggest that this effect is associated with better information disclosure, stronger focus on core operations, and reductions in both explicit and hidden debt. Additional tests document positive short-window market reactions, with stronger effects among firms with greater bad-news hoarding incentives, in regions with more developed financial systems, and among firms with higher capital dependence. The results also hold for both legitimate and regulation-evading passageway business. Overall, the findings provide firm-level evidence that targeted financial oversight is linked to lower downside risk and more disciplined use of financial resources.

ABSTRACT This study provides city-level causal evidence on the economic effects of data trading infrastructure. Treating the staggered establishment of data trading platforms (DTPs) across Chinese cities between 2014 and 2023 as a quasi-natural experiment, we estimate a multi-period difference-in-differences model using a balanced panel of 298 prefecture-level cities from 2000 to 2023. The baseline estimate indicates that DTP establishment increases night-time light intensity – our primary proxy for urban economic vitality – by 3.610 units, robust across all sensitivity specifications. Event-study analysis validates parallel trends, and a randomization-inference placebo test yields an empirical p-value below 0.001. A Bartik instrumental variable strategy produces a 2SLS estimate of 9.421 (p < 0.05), which we interpret as complementary given a moderately relevant first stage (F = 2.71). Mechanism tests reveal that DTPs promote innovation and digital economy employment. A dose–response analysis shows that each additional year of platform operation increases vitality by 0.876 units on average, but the marginal effect turns negative in cities with below-median internet penetration. These findings establish that DTPs can serve as effective institutional vehicles for data factor marketization, but their economic returns are contingent on complementary digital infrastructure investments.

The construction of the National Agricultural Green Development Pioneer Zone represents a crucial strategic direction for promoting green transformation in agriculture and advancing high-quality agricultural development. This paper treats the green agricultural development pilot zone initiative as a quasi-natural experiment, selecting A-share agricultural listed enterprises from 2005 to 2024 as the research sample, and employs the staggered difference-in-differences (DID) method to empirically examine the impact of the green agricultural development pilot zone policy on agricultural enterprise total factor productivity (TFP). The findings reveal that: (1) The green agricultural pilot zone policy effectively enhances agricultural enterprise TFP, and this conclusion remains robust after conducting a series of robustness tests including parallel trends test, placebo test, and PSM-DID test. (2) Heterogeneity analysis demonstrates that the policy effects are more pronounced in asset-light enterprises, enterprises in central regions, and major grain-producing areas. (3) Mechanism analysis indicates that the policy operates through three pathways: increasing government subsidies, enhancing technological innovation, and promoting industrial agglomeration. This study evaluates policy effects from the enterprise micro-level perspective, providing empirical support and policy implications for China's continued advancement of green agricultural development and improvement of the agricultural support policy system.

ABSTRACT Amid the imperative for global climate governance and sustainable development, green technological innovation is a vital path for firms to overcome resource constraints and improve development quality. By bridging firms and capital markets, environmental, social, and governance (ESG) ratings improve the external information environment and establish a market-based governance framework aligned with green innovation incentives. Leveraging SynTao Green Finance’s inaugural publication of ESG ratings as a quasi-natural experiment, this article examines the effect of these ratings on green technological innovation, using a time-varying difference-in-differences approach on Chinese A-share listed firms from 2009 to 2021. We find that favourable ESG performance significantly promotes green technological innovation, a result confirmed by extensive robustness checks. Three transmission channels are identified: alleviating financing constraints, raising innovation efficiency, and amplifying market attention. The promotional effect is particularly salient in growth-stage, eastern-region, high-tech, and highly competitive firms. Further analysis shows that ESG ratings strengthen the intertemporal continuity of corporate green innovation and that CEOs’ green professional background positively moderates this relationship. Regulators should accelerate the standardization of China’s ESG disclosure framework and broaden its coverage. Firms should strengthen internal controls and non-financial reporting so that improved ESG performance translates into substantive green innovation.

ABSTRACT This paper examines whether macro competition policy improves firm total factor productivity by mitigating financial frictions. Using the implementation of China’s Anti-Monopoly Law as a quasi-natural experiment, we employ a difference-in-differences approach based on Chinese listed firms from 2006 to 2023. The results show that the Anti-Monopoly Law significantly increases firm total factor productivity. Mechanism analyses further indicate that the policy alleviates financial frictions by reducing resource misallocation and easing financing constraints, thereby improving resource allocation efficiency. Heterogeneity analyses show that the positive effect is more pronounced among high-tech firms, non-heavily polluting firms, firms in eastern China, and non-state-owned firms. The findings suggest that macro competition policy can promote firm productivity through the mitigation of financial frictions.

ABSTRACT This study uses hand-collected data to investigate the impact of state-level political uncertainty and corruption on corporate investment in India. We use a panel of 1,666 firms with 16,869 firm-year observations from 2001 to 2022. We find that the interaction between political uncertainty and corruption negatively affects firm-level investments, and that firms close to political power face greater political uncertainty. These findings are consistent across multiple robustness checks. We further validate the results by employing a Difference-in-Differences (DID) framework and using the 2018 Prevention of Corruption (Amendment) Act as a quasi-natural experiment to check investment patterns. The strong anti-corruption measures helped alleviate the negative impact of political uncertainty and corruption. Overall, the study highlights the adverse effect of state-level political uncertainty and corruption on firm-level investments.

ABSTRACT In responding to supply chain disruptions, logistics infrastructure investment and institutional standardization reforms are often implemented separately, yet whether their coordinated implementation translates into stronger firm-level supply chain resilience remains unclear. Using a panel of Chinese A-share listed manufacturing firms from 2011 to 2023, this paper exploits the staggered rollout and policy overlap of the National Circulation Node City policy and the Logistics Standardization Pilot City policy as a quasi-natural experiment, and applies a difference-in-differences framework to identify the incremental effect of joint implementation relative to either policy alone. We find that coordinated implementation significantly enhances firm-level supply chain resilience, with effects exceeding those of each policy in isolation. Mechanism analyses show that the synergy operates through improved operational efficiency, reduced supply chain concentration, and expanded cross-regional operations. The effects are more pronounced for large firms, state-owned enterprises, and firms located in more segmented markets, and are amplified by local digital infrastructure and firms’ digital transformation, while also varying with the sequence of policy adoption. These findings highlight the complementarity between infrastructure connectivity and institutional standardization, and provide firm-level evidence for policy designs aimed at strengthening supply chain resilience through coordinated governance.

Networked power infrastructure, energy transition, and supply chain resilience: Evidence from China's ultra-high voltage transmission.

ABSTRACT This study examines how China’s Green Finance Reform and Innovation Pilot Zones affect urban biodiversity using city-level bird observation data from 2012 to 2020. Adopting a quasi-natural experiment and difference-in-differences method, we assess the policy’s impacts. The results show that green finance policies notably raise overall bird species richness. Such ecological gains mainly stem from sustainable agriculture development, industrial green upgrading and rising public environmental awareness.Policy effects differ across bird species: common and migratory birds benefit greatly, whereas endangered species see no significant changes. This reveals general green finance policies have limited effects on protecting vulnerable wildlife, calling for targeted financial tools. Overall, the study proves financial policies incorporating biodiversity goals bring tangible ecological benefits, offering references for balancing economic growth and biodiversity conservation.

ABSTRACT This paper exploits China’s Environmental Protection Tax Reform (CEPTR) as a quasi-natural experiment to examine whether market-based environmental regulation can simultaneously enhance productivity and reduce pollution. Using panel data on A-share listed firms over the period 2012–2024 and a difference-in-differences (DID) framework, we evaluate the reform’s impact on firms’ total factor productivity (TFP) and pollutant emissions. The results reveal a clear ‘double dividend’ effect: CEPTR significantly increases TFP while simultaneously reducing emissions. Mechanism analyses indicate that these effects are primarily driven by three channels: the promotion of green innovation, increased R&D investment and the alleviation of financing constraints. Heterogeneity analysis shows that firms in moderately polluting industries experience the most pronounced improvements in both productivity and emission reduction, suggesting that the reform is particularly effective where regulatory pressure is neither too weak nor excessively stringent. Overall, the findings provide firm-level evidence supporting the Porter Hypothesis in the context of a major developing economy and highlight the role of environmental taxation as an effective policy instrument for achieving coordinated economic and environmental gains.

This study is the first to estimate the effects of unemployment insurance (UI) benefit contractions on mental health. We leverage a unique quasi-natural experiment: early termination of the Federal Pandemic Unemployment Compensation (FPUC) and Pandemic Unemployment Assistance (PUA) programs across more than 20 states during the summer of 2021. Using high-frequency data from the Census Bureau's Household Pulse Survey (HPS), our difference-in-differences estimates suggest that early withdrawal from FPUC and PUA increases the probability of reporting anxiety symptoms among working-age adults without a college degree, a group particularly vulnerable to unexpected income shocks. The adverse effects are more pronounced among racial and ethnic minorities, older individuals, and women. However, the increase in anxiety symptoms is short-lived, persisting for about 1month after the benefit cessation. Finally, we find evidence that financial hardship is a likely mechanism underlying these findings.

Against the backdrop of carbon peaking, carbon neutrality, and digital economy development, exploring the pathways through which artificial intelligence (AI) applications in manufacturing enterprises empower green transformation is of great significance. Using panel data on Chinese A-share listed manufacturing companies from 2005 to 2024 and a difference-in-differences (DID) model, this study examined the impact of the National Artificial Intelligence Innovation and Application Pilot Zones (AI Pilot Zones) policy on corporate green innovation. The results showed that the establishment of AI Pilot Zones significantly promoted green innovation among manufacturing enterprises, and this conclusion remained robust after parallel trend tests, PSM-DID estimation, and alternative variable measurements. Mechanism analysis revealed that financing constraints served as a key mediating channel, and that AI policies promoted green innovation through a serial mediation mechanism involving fintech development and the alleviation of financing constraints. Moderation analysis indicated that both human capital and digital transformation enhanced the policy effect. Heterogeneity analysis suggested that the policy’s impact was more pronounced among non-state-owned enterprises, large enterprises, and firms located in eastern regions. This study provides empirical evidence on the effectiveness of AI Pilot Zones in promoting green innovation among manufacturing firms and clarifies the underlying mechanisms.

ABSTRACT This study evaluates the causal effect of public data openness on urban total factor productivity (TFP) and explores its mechanisms through government governance and transaction costs. Using panel data of Chinese prefecture-level cities from 2000 to 2023, we treat the launch of government data open platforms as a quasi-natural experiment and employ a multi-period difference-in-differences (DID) approach. TFP is measured via the two-step Solow residual method, with robustness verified by instrumental variable estimation, PSM-DID, placebo tests, and green TFP. Baseline regressions show that public data openness significantly enhances urban TFP. Mechanism analysis reveals that improved government governance and reduced transaction costs are the primary drivers. Heterogeneity analysis indicates stronger policy effects in non-Yangtze River Economic Belt regions and areas with lower financial development, exhibiting a ‘timely assistance’ characteristic. This study provides city-level causal evidence, identifies concrete transmission channels, expands research on data factor economic value, and offers empirical support for differentiated data openness policies and inclusive growth.

ABSTRACT Amid the wave of the digital revolution, the openness of public data served as a crucial measure to advance the construction of Digital China and promote enterprise digital transformation. Based on data from A-share listed enterprises between 2007 and 2023, this study employed the quasi-natural experiment of local governments launching public data platforms. Using a staggered difference-in-differences (DID) model and drawing on innovation ecosystem theory, the study explored the relationship between public data openness and enterprise digital transformation. The findings indicated that public data openness facilitated enterprise digital transformation, and this effect remained robust after various tests. The innovation ecosystem functioned as an important intermediary in this relationship. Specifically, public data openness promoted digital transformation by encouraging enterprises to increase innovation resource investment, optimise the innovation environment, and strengthen innovation collaboration. Further analysis revealed that absorptive and adaptive capacities reinforced the positive impact of public data openness on digital transformation, with the effect of absorptive capacity being more pronounced. Additionally, the promotion effect was stronger among non-state-owned enterprises and firms with lower operational efficiency. Public data openness was also found to promote digital transformation from multiple dimensions, with a greater effect on the transformation of underlying technological applications than on the application of digital technologies. Among these, cloud computing transformation benefited the most. Finally, the digital transformation driven by public data openness simultaneously enhanced enterprises’ economic performance and optimised their ESG ratings. The research findings contributed to a deeper understanding of the value creation role of public data openness in facilitating enterprise digital transformation.