This article examines the link between foreign institutional holdings and firms’ efficiency in labor investment in the setting of Chinese markets. We find that foreign institutional investors enhance firms’ labor investment outcomes primarily through mitigating asymmetric information and by strengthening internal governance. Specifically, the influence of foreign institutional investors on a firm’s labor investment efficiency is stronger when the firm faces greater labor adjustment frictions. This effect is more evident when foreign institutional investors are originated from countries or areas with stronger cultural connections to China, stronger governance quality, common law traditions, or stronger bargaining power in the firms’ governance. Our paper contributes to the literature in that it documents the monitoring role of foreign institutional investors from the perspective of firms’ labor investment decisions, and adds to the literature on the drivers of firms’ labor investment choices.

This paper studies missing firm characteristics in the Chinese stock market and their implications for empirical asset pricing. Relative to the U.S. market, missing firm characteristics in China remain underexplored despite substantial differences in data availability and disclosure environments. Using a dataset of 106 firm characteristics from 1992 to 2021, we document a pronounced cliff-shaped pattern in missingness, with missing rates falling sharply after 2000. We then compare expectation-maximization (EM) and mean imputation (MN) in both univariate characteristic-sorted portfolios and machine-learning applications that combine many predictors. Results indicate that, in univariate analysis, the two methods produce very similar return spreads because they assign largely the same stocks to the extreme deciles. In machine-learning applications, however, EM-imputed data generally produce better-performing prediction-sorted portfolios than mean-imputed data. These findings provide new evidence on missing firm characteristics in a major emerging market and highlight the importance of imputation choices in machine-learning asset-pricing applications.

Investors and forecasters often extrapolate from past returns, but whether this reffects behavioral bias or efficient information processing remains unclear. We address this questionby inferring Chinese mutual fund managers’ market expectations from textual analysis oftheir commentaries and linking them to portfolio choices and performance. Extrapola-tion is state-dependent: it is stronger when growth is above trend and idiosyncratic riskis relatively more important. It is associated with weaker market timing and strongerstock picking, leaving overall performance unchanged. Our findings support a rational-inattention model of expectation formation, in which managers shift scarce attentionbetween aggregate and stock-speciffc information as the relative importance of differentrisks change.

冯静仪

We revisit cross-asset time-series momentum (XTSM) and single-asset time-series momentum (TSM) in China's stock and bond markets. With a fixed-effects model, we find a positive momentum from bonds to stocks and a negative momentum from stocks to bonds, with both momentum persisting for no more than six months. By employing a cross-grouping method, we find that the choice of lookback periods and asset signals impacts the performance of XTSM and TSM. A comparison between XTSM, TSM, and time-series historical (TSH) portfolios reveals that XTSM outperforms in small/midcap stocks and government bonds, while its performance is weak in large-cap stocks and corporate bonds. A spanning test confirms that XTSM generates excess returns that other pricing factors can not explain. XTSM is more prone to momentum crashes. Increased market stress has similarly adverse effects on XTSM and TSM. Furthermore, Market illiquidity, IPO counts, new investor accounts, and consumer confidence index positively correlate with the returns of XTSM and TSM portfolios, while IPO first-day return and turnover rate correlate negatively. The effects of these sentiment indicators exhibit heterogeneity.

Forming diversified global supply chains (GSC) is an important approach to improving economic resilience. When firms expand their oversea suppliers for such purposes, information friction is a major challenge, and internetization may help firms cope with it by more efficient communication of information. We introduce a dynamic discrete choice model for firms’ searching for new supplier sources estimated with structural methods, and construct counterfactual studies to analyze the internetization effects on Chinese firms’ GSC diversification. Our quantitative studies reveal that internetization relieves information friction, which reduces firms’ searching costs by 13.4%, and thus significantly diversifies firms’ GSC. It also raises firms’ productivity by 0.5% through efficient communication of information. Reductions in searching costs are revealed as the main channel of such effects of internetization, while the productivity channel is less significant. Moreover, the internetization effects on diversifying GSC are persistent over time, and are biased towards high-productivity and importing firms.

We study the influence of investor attention on mutual fund investors' fund selection and fund managers' portfolio choice. Using the Google Search Volume Index to measure investor attention on individual stocks, we find fund investors tend to direct more capital to mutual funds holding more high-attention stocks; fund managers tend to perform window-dressing trading to increase the portfolio holdings of high-attention stocks displayed to investors. Our results suggest that funds, particularly those with strong incentives, strategically trade on stock attention to attract investor flows. This strategic trading behaviour is also associated with fund underperformance and leads to larger non-fundamental volatility of holding stocks.

A second-tier patent system with relatively low protectability standards has been adopted by many countries, but empirical evidence on how it is used by firms israre. Using Chinese patent data, we exploit “parallel filings” – where a second-tierpatent is filed simultaneously with an invention patent – to shed light on its usein practice. The data indicate that while parallel filings appear to be inventionswith a narrower scope, they are cited more frequently in the early years and morelikely to be licensed or transferred compared to inventions protected by standardpatents. We provide evidence that parallel filing is likely a strategic choice forshort-life-cycle technologies that achieve high value early in their lifetime but decayfast. The rapid issuance of the second-tier patent facilitates knowledge diffusionand technology transfer, thereby helping the patentees capitalize on the value of fast-moving technologies. This study provides some much-needed empirical evidenceon how the quick procedure of the second-tier patent system serves short life-cycletechnologies.

Portfolio underdiversification is one of the most costly losses accumulated over a household’s life cycle. We provide new evidence on the impact of financial inclusion services on households’ portfolio choice and investment efficiency using 2015, 2017, and 2019 survey data for Chinese households. We hypothesize that higher financial inclusion penetration encourages households to participate in the financial market, leading to better portfolio diversification and investment efficiency. The results of the baseline model are consistent with our proposed hypothesis that higher accessibility to financial inclusion encourages households to invest in risky assets and increases investment efficiency. We further estimate a dynamic double machine learning model to quantitatively investigate the non-linear causal effects and track the dynamic change of those effects over time. We observe that the marginal effect increases over time, and those effects are more pronounced among low-asset, less-educated households and those located in non-rural areas, except for investment efficiency for high-asset households.

We develop an information choice model where information costs are sticky and co-move with firm-level intrinsic uncertainty as opposed to temporal variations in uncertainty. Incorporating analysts' forecasts, we predict a negative relationship between information costs and information acquisition, as proxied by the predictability of analysts' forecast biases. Finally, the model shows a contrasting pattern between information acquisition and intrinsic and temporal uncertainty, where intrinsic uncertainty strengthens return predictability of analysts' biases through the information cost channel, while temporal uncertainty weakens it through the information benefit channel. We empirically confirm these opposing relationships that existing theories struggle to explain.