This paper examines how potential disruptions from generative artificial intelligence (AI) to firms' core businesses affect their cross-industry acquisition decisions. Using data on Chinese A-share listed firms, we employ a large language model to assess the potential positive and negative effects of generative AI on core businesses and construct a measure of net AI risk exposure. We measure cross-industry M&A using the semantic distance between acquirers' and targets' business descriptions. A difference-in-differences analysis exploiting the commercial diffusion of generative AI shows that more exposed firms acquire more distant targets, with an effect equivalent to 8.2% of the sample mean and robust to alternative specifications. The effect is stronger among firms with narrower innovation boundaries and more concentrated business portfolios, consistent with innovation capability reconfiguration and strategic risk diversification. It is also stronger among firms with smaller market shares, in more competitive industries, and in more marketized regions. Further analyses show that high-exposure firms acquire targets with higher AI patent shares and receive more favorable announcement-day market reactions to distant acquisitions. Our findings suggest that potential AI-related disruptions shape acquisition target selection and firms' business boundaries.

This study evaluates whether electric vehicles (EVs) in China have delivered on their “green” promise by improving air quality and reducing private ownership costs. Combining city–month data on EV adoption and air pollution with detailed vehicle-level transaction records, we find little evidence that rising EV adoption reduces concentrations of major pollutants or greenhouse gases. Both the traditional instrumental variable (IV) and the Bartik IV estimations show that the null effects persist after addressing potential endogeneity. The limited environmental gains are largely attributable to the continued dominance of coal in electricity generation and to a sizable rebound effect whereby lower operating costs increase vehicle usage. On the private side, although EVs reduce energy expenditures by roughly CNY 16,747, their faster depreciation leads to an average net loss of about CNY 18,175 over the ownership period relative to fuel vehicles (FVs). Counterfactual simulations show that EVs match the emissions of fuel vehicles when the coal share falls to about 55%, deliver measurable benefits below 49%, and require a reduction to around 31% once higher utilization is considered. The results show that the environmental benefits from EV adoption depend on a transition toward cleaner electricity generation.

This paper studies the unintended spillover effects of China's 2020 "Three Red Lines" policy – a macroprudential intervention aimed at deleveraging real estate developers – on employment in the upstream manufacturing firms. Exploiting variation in industries' exposure to the real estate sector via input-output linkages and employing a generalized difference-in-differences (DID) design on panel data of listed manufacturing firms (2017-2022), we find a significant decline in employment among upstream suppliers, while there is no substantial effect on downstream firms. We identify two transmission channels: a demand propagation channel, evidenced by falling sales and inventory overhang, and a balance sheet contagion channel, where liquidity strain is passed upstream via extended payables and a shift to riskier short-term debt. Furthermore, we show that downward nominal wage rigidity shaped the adjustment, as firms resorted to layoffs rather than wage cuts for ordinary workers. From a regional labor market perspective, the employment losses represent a net reduction at the aggregate level, as displaced workers are not absorbed by other local firms in the same city or province. Our study reveals a significant real economic cost of sectoral macroprudential regulation and clarifies how such shocks propagate through production networks and interact with labor market frictions.

Mergers and acquisitions (M&A) are widely regarded as a critical instrument for industrial consolidation and capacity rationalization. Utilizing a dataset of China’s major national and regional steel enterprises from 1998 to 2013, this study empirically evaluates the efficacy of M&A in resolving over1capacity. We document a striking heterogeneity in outcomes: while M&A generally alleviates overcapacity, this effect is exclusively driven by inter-provincial transactions; intra-provincial mergers show no significant impact. Mechanism analysis reveals that inter-provincial M&A facilitates the transfer of control rights, effectively insulating firms from local government intervention. In contrast, intra-provincial mergers are undermined by local intervention through mechanisms of "internal control" and "external defense." Furthermore, despite the reduction in capacity, we find that inter-provincial mergers suffer from incomplete post-merger integration. There is a persistent lack of governance coordination, and no convergence in capacity management performance is observed between the merging entities over time. These findings offer critical policy implications for mitigating local protectionism and enhancing integration efficiency to resolve industrial overcapacity.

This paper explores the impact of the Integrated Government Service Platform (IGSP) reform, a large-scale digital regulatory initiative in China, on firms’ investment efficiency. Using a firm-level panel dataset of Chinese listed firms, we find that the IGSP reform significantly enhances firms’ investment efficiency. Mechanism analyses indicate that the IGSP enhances firms’ investment efficiency by improving governance service quality and convergence of governance services across cities within a province, thereby reducing economic policy uncertainty and reinforcing market expectations. The heterogeneity analyses reveal that the effect is more pronounced for firms without political connections, those operating in high business volatility and high-tech industries, and regions with stronger informal institutions. Finally, the IGSP encourages firms to expand their investment activities to other cities within the same province. This finding is fully consistent with the underlying mechanisms identified in this study. Our findings provide novel evidence on the economic consequences of digital regulatory integration and offer policy implications for advancing service-oriented and efficiency-driven governance in developing economies.

This paper studies the role of the soft budget constraint in shaping firm dynamics and long-run economic growth. We develop a Schumpeterian model with two sectors: consumption and investment, and two types of firms: state-owned enterprises (SOEs) and privately owned enterprises (POEs). Within this framework, multi-product firms require fixed inputs of investment goods to operate — a resource that is also crucial for firm expansion, and the soft budget constraint allows subsidized firms to continue operating on loss-making product lines. This distortion raises the price of investment goods, suppresses firm dynamics, and dampens aggregate growth. To quantify the mechanism, the model is calibrated using Chinese firm-level data. Our quantitative exercise shows that eliminating the SOE soft budget constraint friction reduces the price of investment goods by 9.82 percent, increases the overall TFP growth rate by 0.12 percentage points, and generates a welfare gain of 4.94 percent.

This paper examines how traditional informal institutions shape preferences for old-age support and the emergence of initiative-based long-term financial planning. Using data from the China Health and Retirement Longitudinal Study combined with clan genealogy records, we estimate the causal impact of exposure to clan culture on old-age support preferences. We find that stronger exposure to clan culture in early life is associated with a higher likelihood of adopting modern preferences for old-age support, characterized by greater reliance on self-initiated savings and pension participation rather than dependence on children. The results are robust to instrumental variable estimation and placebo test. Importantly, the effect operates exclusively through exposure to clan culture during early life, while clan culture encountered in adulthood has no significant influence, particularly among individuals who relocate later in life. Mechanism analysis suggests that peer effects, generalized trust, income growth, and financial literacy jointly mediate the relationship between clan culture and old-age support preferences. We further show that the expansion of the formal pension system complements, rather than crowds out, the influence of clan culture, consistent with a process of co-evolution between informal and formal institutions. The effects are stronger among individuals with favorable attitudes toward clans, rural residents, and men. Finally, modern preferences induced by clan culture translate into higher pension participation and larger financial asset holdings. Overall, the findings highlight how informal institutions can shape economic preferences and facilitate the adoption of formal financial arrangements.

Enhancing the performance of corporate green supply chain management (GSCM) represents a critical enabler for delivering on the central imperatives of the global low-carbon transition. Using panel data of Chinese listed companies from 2003 to 2022, this study employs a staggered difference-in-differences (DID) approach to examine the impact of the Low-Carbon City Pilot (LCCP) policy on firms' GSCM performance. The results show that the LCCP policy significantly improves firms' GSCM performance, and this effect remains robust across a range of sensitivity tests. Mechanism analyses reveal that the policy operates primarily by stimulating green innovation and increasing investment in environmental protection equipment. Furthermore, financial constraints play a significant moderating role: the positive effect of the policy on GSCM performance is stronger when firms face fewer financing constraints. Heterogeneity analysis indicates that the policy effects are more pronounced among non-heavy-polluting enterprises, those located in resource-dependent cities, and ISO 14001-certified enterprises. This study provides novel micro-level evidence on the environmental governance effects of place-based climate policies, and offers key policy implications for scaling up low-carbon city pilots and promoting corporate supply chain decarbonization.

This paper exploits China’s culture-oriented institutional reform as a quasinatural experiment to examine the impact of cultural policies on water pollution. Using a difference-in-differences approach with city-level panel data from 2003 to 2020, we find that the reform leads to a significant reduction in water pollution in pilot cities. Heterogeneity analysis indicates that the effect is more pronounced in cities with better economic performance, higher administrative status, richer tourism resources, and more abundant human capital. The reform prompts a shift in local industrial structure toward less-polluting sectors, with a marked contraction in pollution-intensive activities. It also strengthens local environmental regulation and enhances green innovation, thereby contributing to pollution reduction. Our findings highlight the spillover environmental effects of policies not explicitly designed for environmental purposes.

Against the backdrop of escalating global carbon emission reduction urgency and China’s "dual carbon" goals, individual carbon trading (ICT) has emerged as a key measure to tap into consumer-side emission reduction potential. However, the current ICT mechanism remains in the exploratory stage, plagued by limited access to formal trading channels, strict entry barriers, and low public penetration, only 5 carbon exchanges in China allow individual participation, with fewer than 10,000 total participants. Focusing on mechanism integrity and integrating the carbon inclusive system, this study explores the influencing factors of ICT operation and constructs targeted optimization strategies. Based on Mechanism Design Theory, the Theory of Planned Behavior, and Value-Belief-Norm Theory, a theoretical model covering five core ICT components was established. Using data from 1,200 questionnaires across 15 Chinese cities, multiple linear regression and hierarchical regression were employed to analyze the impacts of institutional fairness, technical usability, social atmosphere, and individual cognition. Results show: (1) Institutional fairness increases quota compliance by 38% through transparent rules; (2) User-friendly technical tools boost engagement by 1.8x, enhancing accounting accuracy and platform efficiency; (3) Social atmosphere moderates the effect of individual cognition on incentive conversion, particularly strongly in rural areas; (4) Individual cognition mediates the relationship between social atmosphere and trading platform efficiency. Additionally, optimizing mechanism components is more critical for long-term operation than single incentives. This study proposes a multi-dimensional optimization framework, providing theoretical and policy references for improving ICT integrity and advancing "dual carbon" goals.