In this paper, we investigate the availability of external finance for state-owned enterprises (SOEs) and private enterprises (PEs) across all manufacturing industries in China. Employing a disequilibrium model, we find that SOEs are generally less financially constrained than PEs, but the difference is of small magnitude and has been steadily declining over time. We also reveal a positive relation between the advantage of SOEs in accessing external funds and the level of SOE monopoly at the industry level. In general, while SOEs and PEs are equally constrained in competitive downstream industries, we find a significant comparative advantage in accessing external finance for SOEs in monopolized mid- and upstream industries. The policy implication is straightforward: to finance PEs better, the Chinese government should consider breaking the existing monopolies or near monopolies of SOEs in certain industries further, rather than encouraging banks to favor PEs in their lending.

We study how alternative data influences investors’information acquisition and market efficiency from both short-term and long-term perspectives. Using the exogenous introduction of online sales data on a major Chinese financial information platform, we find that such disclosure enhances investors’information processing capacity. In the short term, firms covered by online sales data exhibit weaker market reactions to unexpected earnings, reflecting more accurate earnings expectations. In the long term, online sales disclosure strengthens the link between earnings and stock returns, indicating higher earnings value relevance. These results are robust to a series of endogeneity tests and robustness checks. Cross-sectional analyses indicate that these effects are more pronounced for firms with lower institutional ownership, higher earnings volatility, and greater reliance on online sales. Mechanism analyses show that short-term effects operate through improved analyst forecast accuracy, while long-term effects are jointly driven by higher firms' earnings quality and enhanced analyst performance. These findings offer new perspectives on market efficiency and fresh evidence on investor information processing.

In automobile markets where consumers attach social recognition to car ownership, how does the introduction of a lower-cost alternative influence the market outcomes of traditional internal combustion engine vehicles (ICEVs)? Leveraging high-frequency sales data covering China's entire automobile market from 2018 to 2022, we examine heterogeneous market responses to the emergence of electric vehicles (EVs) across different price segments. Overall, the rise of EVs is associated with lower ICEV sales but higher total automobile sales. More importantly, while EV penetration is negatively correlated with ICEV sales in the lowand mid-end segments, it is positively correlated with ICEV sales in the high-end segment. Further evidence suggests that the rise of EVs amplifies the symbolic value of high-end ICEVs, boosting sales of ICEV models with strong social recognition.

This paper examines the effects of China's 2016 coal capacity reduction policy on firms, local labor markets, and crime. We find that the policy substantially reduced the asset size and employment of coal firms in treated cities while simultaneously increasing their profitability and lowering debt. Policy-induced layoffs generated adverse spillovers in local labor markets, reducing residents' incomes, worsening public perceptions of job opportunities, and increasing divorce rates. These labor market effects were most pronounced among older and less-educated individuals. Employment also shifted away from the mining sector toward wholesale and retail trade and real estate-related industries. In addition, the policy led to an increase in crime, driven primarily by property offenses committed by individual offenders, while violent crime remained largely unchanged. A back-of-the-envelope calculation suggests that the increase in coal firms' profits exceeded the fiscal resources required for worker resettlement.

Using Chinese A-share listed firms from 2007 to 2024, this study examines whether supply chain shareholding (SCS) affects stock price synchronicity. We find that SCS significantly reduces stock price synchronicity. This finding remains robust to a series of robustness and endogeneity tests. Mechanism tests provide evidence consistent with information asymmetry and agency costs as two channels linking SCS to lower stock price synchronicity. Heterogeneity analyses show that the effect is more pronounced among firms with low supply chain concentration and those operating in unfavorable business environments. Overall, these findings identify SCS as a relationship-based governance arrangement that improves capital market information efficiency, particularly where relational governance and informal institutional substitution are more valuable.

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.

We study how expanding access to intellectual property (IP)-backed credit affects firm innovation and aggregate total factor productivity (TFP). Exploiting China's IP-backed financing pilot as a quasi-natural experiment, we use difference-indifferences estimates to show that the policy increases R&D participation, raises firm-level productivity, and reduces capital misallocation. To interpret these effects and quantify their aggregate implications, we develop a dynamic model of heterogeneous firms that borrow subject to collateral constraints backed by tangible assets and IP, and choose R&D investment and the accumulation of wealth. R&D raises future productivity and creates collateralizable IP. We estimate the model by the method of simulated moments, using the policy-induced shift in R&D participation to identify the change in IP pledgeability. The estimated model implies that a nationwide adoption of IP-backed financing would raise long-run TFP by 14%, with roughly two-thirds coming from static gains due to improved capital allocation and the remainder from dynamic gains driven by higher innovation that accumulate over time. Relative to a comparable expansion of lending backed by tangible collateral, IP-backed financing delivers larger productivity gains by easing constraints for high-productivity but low-wealth firms and by strengthening incentives to accumulate IP as collateral for future borrowing.

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.