The endurance of empire in China over much of the past two millennia contrasts starkly with the political fragmentation in Europe since the fall of Rome. To explain the persistence of China’s empire, we analyze the role of keju, the imperial civil service examination system. We argue that the systematic implementation of keju from the Song dynasty onward tied local elites to the imperial state, sustaining political integration and reducing secessionist conflicts. Exploiting panel data covering 4,243 grid cells and 22 centuries, we find robust evidence that areas producing more jinshi – the top exam passers – experienced significantly fewer secessionist wars. Our study shows how the examination system created the political incentives for imperial durability.

This study examines whether China’s Industrial Internet pilot policy (2017–2023) enhances firm innovation and explores the underlying mechanisms. Exploiting the staggered rollout of the policy across provinces as a quasi-natural experiment, we find that Industrial Internet adoption significantly increases firms’ innovation output. Mechanism tests show that the policy promotes knowledge accumulation, strengthens innovation persistence, and improves human capital allocation. We also document positive economic consequences, as treated firms earn higher returns to innovation. The effects are stronger for capital-intensive firms, those located in regions with advanced digital infrastructure, and firms undertaking joint or substantive innovation activities. Overall, the evidence highlights the Industrial Internet as an effective catalyst for firm innovation by deepening R&D capability and facilitating cross-industry knowledge flows.

This paper examines how profits from mutual funds’ participation in initial public offerings (IPOs) shape fund performance, investor flows, and market stability in China. Using comprehensive fund–IPO matched data from 2016 to 2023, we decompose fund returns into an IPO-lottery component and residual performance. At the aggregate level, IPO allocations add 2.05% to annualized excess returns; net of IPOs, excess return is −0.35% per year. At the individual level, the contribution of IPO profits varies substantially across funds and is most pronounced among mid-sized funds, inflating perceived managerial skill. Funds with higher IPO-driven gains attract greater inflows despite the absence of performance persistence, leading to capital misallocation. At the market level, IPO-profit-induced trading (PIT) predicts short horizon price run-ups that dissipate and reverse over subsequent months, while raising both total and idiosyncratic volatility. Overall, IPO profits temporarily enhance reported performance but erode market stability by propagating non-fundamental shocks through secondary markets.

We construct a stock learning index in China A-share market, which is based on a theoretical model of information and investment choice. The higher the learning index value, the more thoroughly the individual stock is learned. Our study shows that a stock with a high learning index will have a lower expected future return compared to a stock with a low learning index. Additionally, decomposition of predictive power shows that the predictive power of the learning index mainly comes from the persistence of its own predictive power, while the rest cannot be explained by changes in the volume of news (proxy for information flow). Moreover, the learning index can explain many market anomalies in China A-share market.

This study focuses on the relationship between individual stocks’ systemic tail risk and future returns. Analyzing data from China's A-share market, we document an abnormal negative crosssectional relationship between stocks’ systemic tail risk and returns, which cannot be explained by firm-specific characteristics. We show that the joint effect of investor expectation of stock return persistence and investor sentiment contributes to the systemic tail risk anomaly. Investors tend to underestimate the loss persistence of stocks that have suffered large losses in the most recent period and overprice such stocks, leading to a strong negative relationship between stock systemic tail risk and return. In addition, constraints on short selling exacerbate individual stocks’ systemic tail risk and also explain the systemic tail risk anomaly.

We study the role of marriage for women's intergenerational mobility during the Ming-Qing (1368-1911) period. Using status information based on the timing of marriage from family histories in Central China, already in the early 1500s it is the case that daughters from rich families attain higher status over their lifetime than daughters from poorer families. This intergenerational status persistence is partly due to marital sorting because daughters from highstatus families tend to become the wives of sons who themselves come from rich families. Quantitatively, the correlation of 0.6 between the status of biological and in-law families means that marriage accounts for more than one third of total intergenerational status transmission, while not accounting for marriage overestimates mobility by more than 20 percent. Further underscoring the importance of marriage, typically the status of the in-law family plays a larger role for intergenerational status transmission than the child's biological grandparents. Over the period 1500 to 1900, the degree of marital sorting falls, as does intergenerational persistence. Lower investments in the marriage market to find a good match for a daughter go hand in hand with the fall in the returns to son education due to the decline of China's civil service examination.

This paper proposes the two-component realized EGARCH model with dynamic jump intensity (hereafter REGARCH-C-DJI model) to model and forecast stock market volatility. The key feature of our REGARCH-C-DJI model is its ability to exploit the high-frequency information as well as to capture the long memory volatility and jump dynamics. An empirical application to Shanghai Stock Exchange Composite (SSEC) index data shows the presence of high persistence of volatility and dynamic jumps in China’s stock market. More importantly, the REGARCH-C-DJI model dominates the GARCH, EGARCH, REGARCH and REGARCH-C models in terms of out-of-sample forecast performance. Our findings highlight the importance of accommodating the realized volatility, volatility components and jump dynamics in forecasting stock market volatility.

This paper is the first study to systematically discuss the predictive power of crosssectional asset pricing anomalies on aggregate market excess return time series in the Chinese A-share market. The paper summarizes the anomalies and uses linear methods with different shrinkage techniques to extract predictive information from highdimensional long-short anomaly portfolio returns datasets. We find that long-short anomaly portfolio returns show highly significant out-of-sample predictive power of aggregate market excess returns, both statistically and economically. Unlike similar studies on U.S. stocks, the predictive power stems from stronger limits of arbitrage in the short-leg when using bid-ask spread as a proxy but from stronger limits of arbitrage in the long-leg when idiosyncratic volatility or market capitalization is used as proxies.

We uncover a signiffcant relationship between the persistence of marketing and investment skills among U.S. mutual fund companies. Using regulatory filings, we calculate the share of marketing-oriented employees to total employment and reveal alarge heterogeneity in its level and persistence. A framework based on costly signaling and learning helps explain the observed marketing decision. The model features a separating equilibrium in which fund companies’ optimal marketing employment share responds to their past performance differently, conditional on the skill level. We confirm the model prediction that the volatility of the marketing employment share negatively predicts the fund companies’ long-term performance.

We provide an easy method to identify purchases and sales initiated by retail investors using recent, widely available U.S. equity transactions data. Individual stocks with net buying by retail investors outperform stocks with negative imbalances by approximately 10 basis points over the following week. Less than half of the predictive power of marketable retail order imbalances is attributable to order flow persistence; contrarian trading (a proxy for liquidity provision) and public news sentiment explain little of the remaining predictability. There is suggestive (but only suggestive) evidence that retail marketable orders contain firm-level information that is not yet incorporated into prices.