This paper compares China's parallel and sequential admissions mechanisms under the dummy-quota policy that limits how many applicants each college can screen. Although neither mechanism is stable or strategy-proof, their weaknesses are structurally different. Under the parallel mechanism, priority violations and profitable deviations are confined to a policy-determined buffer: students routed into colleges' screening pools by exam-score priority but rejected when colleges finalize admissions based on their preferences. The size of this buffer is bounded by the gap between screening and admission capacities. Under the sequential mechanism, by contrast, violations are driven by the round-by-round structure and can expand sharply with congestion and preference concentration. We derive tight upper bounds that characterize these exposures and quantify their magnitudes in calibrated simulations. The results reveal a clear distinction: institutional risk is capped ex ante by design under the parallel mechanism, whereas under the sequential mechanism it scales with market pressure-providing a complementary explanation for China's transition from sequential to parallel admissions.

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.

Our study examines dynamic innovation through the U.S.-Sino industrial-chain networks and its asset-pricing and financial-fundamental implications amid U.S.-China network disruptions. Innovation synergy captures similarity between firms’ learned innovation processes, in which firm characteristics and network information are used to predict patent output. Using an annually reconstructed joint network of Chinese and U.S. firms, we form peer-return, peer-R&D, and peer-patent measures and estimate their associations separately in the two markets. The annual R&D- and patent-based measures are positively associated with firms' own R&D intensity in both markets, their gross-profitability associations are stronger for large firms, and tangible-asset associations become more positive after 2017. The R&D- and patent-based long–short portfolios have positive Fama–French three-factor alphas in both markets, while the return-based signal is stronger in China than in the United States.

Entry of arbitrageurs need not increase with larger mispricing. Arbitrageurs trade mispriced assets and close positions once mispricing is corrected, seeking to minimize carry cost (shadow value of trading capital). More deployed arbitrage capital shortens the wait, lowering carry costs but also payoffs. Discretionary entry is profitable only in a “Goldilocks” region, where deployed capital is neither too low nor too high: enough capital is deployed to accelerate correction, while profits remain. The region’s upper bound follows from the condition that every sequence of entrants has a last entrant who cannot rely on subsequent discretionary entry.

Less informative strategic advice can produce more informative prices. We study an informed adviser who both trades on his own account and receives compensation linked to the post-report price. Holding private information fixed, we show how promotion can restrain manipulation motivated by trading profits. At sufficiently high reputation, raising compensation enough to eliminate false bad news used to buy cheaply improves market price informativeness in every equilibrium, even though the strategic adviser’s report becomes uninformative. Under further sufficient conditions, always-favourable strategic reporting yields the most informative current prices among equilibria at every interior reputation. We also derive analytical sufficient conditions under which higher reputation lowers the adviser’s expected payoff and worsens prices within the same equilibrium. Financial influencers motivate the joint incentives: a reward for higher prices can counteract the incentive to depress prices before buying, while greater credibility need not benefit its holder.

This study examines the role of artificial intelligence (AI) adoption in the market for corporate control using a sample of Chinese listed firms from 2011 to 2021. We construct a novel firm-level AI Index through textual analysis of annual reports and find that AI adoption significantly enhances both the likelihood of becoming an acquisition target and the valuation premiums commanded in M&A transactions. Specifically, a one-standard-deviation increase in the AI Index is associated with a significant increase in the probability of being acquired and higher deal premiums measured by price-to-earnings multiples. We identify two channels through which AI adoption creates value recognized by the M&A market: an efficiency channel, whereby AI reduces agency costs and improves profitability, and an innovation channel, evidenced by increased high-quality patent output. The persistence of these effects over time further suggests that AI adoption generates substantive improvements in firm fundamentals rather than serving as a transitory informational signal. Importantly, we document significant heterogeneity across ownership structures: the positive effects of AI adoption are substantially weaker for State-Owned Enterprises (SOEs) than for non-SOEs. Our findings contribute to the literature on digital transformation and corporate finance by demonstrating that AI adoption serves as a value-relevant firm attribute that shapes outcomes in the market for corporate control.

How do market-design reforms affect secondary-market liquidity in an emerging equity market? We examine China’s ChiNext reform, which combined registration-based IPO issuance with changes in secondary-market trading rules. Using firm-month observations and high-frequency order-book data, we compare incumbent ChiNext firms with Main Board firms in a difference-in-differences framework. The results show that the reform significantly improves secondary-market liquidity, with consistent evidence across alternative DID estimators and liquidity measures. Dynamic estimates show comparable pre-reform movements and increasingly favorable liquidity outcomes after implementation. Cross-sectional analysis indicates stronger liquidity improvements among larger and more profitable firms. Microstructure results show narrower quoted spreads, broadly stable displayed depth, and a shift in order flow toward buyer-initiated trading. Overall, the findings demonstrate that the integrated ChiNext reform package improved secondary-market liquidity and reshaped the cross-sectional distribution of liquidity gains, highlighting the market-quality consequences of institutional reform in emerging equity markets.

We find that firm-specific social media tone influences leveraged trading. A more positive tone predicts greater next-day net margin purchasing, driven predominantly by sentiment. High margin purchasing following positive social media tone consistently yields inferior performance over both short and long horizons. Short sellers are collectively more sophisticated. They capitalize on fluctuations in social media tone, both positive and negative, through strategies that adjust to different tone windows and holding periods. While experienced, rational short sellers can swiftly profit from temporary negative sentiment, high short selling following persistently high social media tone is highly profitable over longer horizons.

This study investigates the impact of employee ownership on firms’ investment responsiveness to stock market feedback. Using data from Chinese listed firms, we find that employee ownership significantly enhances the sensitivity of corporate investment to Tobin’s q. This effect is more pronounced in firms with higher information asymmetry, greater labor intensity, weaker corporate governance, and higher financial distress risk. While employee ownership is linked to increased subsequent profitability volatility, it also mitigates financial mismatch and downside operating risk. Our findings also suggest that employee ownership drives a shift in corporate strategy, leading to more aggressive approaches and improved risk preferences. These results highlight the role of employee ownership in mitigating agency problems and enhancing firms’ ability to incorporate market information into investment decisions.

We interpret industry discount rates as proxies for value investment, grounded in Q theory, while capturing gambling preferences through salience theory. Integrating these perspectives, we propose a novel asset pricing model (ST-ICAPM) that unifies value investment and salience factors, evaluating its pricing efficacy across Chinese industries from 2004 to 2023. Empirical results show that investment factors tend to negatively predict future returns, while growth factors command risk premia. However, profitability factors exhibit limited explanatory power. Investor expectations are primarily driven by profit growth, emphasizing the need to enhance profit stability for a value-oriented market. Salience intensity, especially when measured via eigenvector centrality within industry networks, serves as a strong negative predictor of returns, emphasizing the importance of conceptual connections over purely economic linkages in shaping investor behavior. Robust tests confirm that the ST-ICAPM outperforms benchmark models (FF3, CARHART4, FF5, ICAPM, and STCAPM) in terms of pricing power. Our findings emphasize the need to promote value investing and restrain gambling behavior as essential strategies to cultivate a resilient capital market in China.