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.

This study investigates the impact of analysts' information source diversity on forecast bias and investment returns. We combine the GPT-4o model and text similarity, to extract the names of information sources from the text of analyst in-depth reports. Using 349,200 sources, we calculate information diversity scores based on the variety of data sources to measure analysts’ ability of selecting relevant information. The findings reveal that higher information diversity significantly reduces forecast bias and enhances portfolio returns. The effect is particularly pronounced for large companies, state-owned enterprises, those with low analyst coverage, low firm-specific experience, and reports with positive forecast revisions. Institutional investors recognize the value of this skill, while retail investors remain largely unaware, which contributes to financial inequality. This study highlights the critical role of information diversity in analyst performance.

Why do firms appoint expired independent directors? How do expired independent directors affect corporate governance and thus impact investment decisions? By taking advantage of the sharp increase in expired independent directors’ re-employment in China caused by exogenous regulatory shocks, Rule No. 18 and Regulation 11, this paper adopts a PSM-DID design to test the impact of expired independent directors on CSR performance. We find that firms experience a significant decrease in CSR performance after re-hiring expired independent directors and the effect is stronger for CSR components mostly related to internal governance. The results of robustness tests show that the main results are robust to alternative measures of CSR performance, an extended sample period, alternative control groups, year-by-year PSM method, and a staggered DID model regarding Rule No. 18 as a staggered quasi-natural experiment. We address the endogeneity concern that chance drives our DID results by using exogenous regulatory shock, an instrumental variable (the index of regional guanxi culture), and placebo tests. We also find that the negative relation between the re-employment of expired independent directors and CSR performance is more significant for independent directors who have more relations with CEOs and raise less objection to managers’ decisions, and for firms that rely more on expired independent directors’ monitoring roles (e.g., a lower proportion of independent directors, CEO duality, high growth opportunities, and above-median FCF). The mediating-effect test shows that the re-employment of expired independent directors increases CEOs’ myopia and thus reduces CSR performance. In addition, we exclude the alternative explanation that the negative relation is caused by the protective effect brought by expired independent directors’ political backgrounds. Our study shows that managers may build reciprocal relationships with expired independent directors in the Chinese guanxi culture and gain personal interest.

How does executive authority affect household behavior? I develop a model in which the executive branch of the government is partially constrained. These constraints credibly limit intervention under normal conditions but can be overridden when a sufficiently large fraction of the population is in distress. Households anticipate this and strategically coordinate their financial risks through public markets, creating collective distress that compels government bailouts. Weaker constraints lower the threshold for intervention, making implicit guarantees more likely. The model explains why implicit guarantees are prevalent in China and predicts that such guarantees may discontinuously emerge elsewhere as executive constraints gradually weaken.

This study identifies an incentive-compatible mechanism to foster individual environmental engagement. Utilizing a dataset comprising 100,000 randomly selected users of Ant Forest—a prominent personal carbon accounting platform embedded within Alipay, China's leading BigTech super-app—we provide causal evidence that individuals strategically engage in eco-friendly behaviors to enhance their credit limits, particularly when approaching borrowing constraints. These behaviors not only illustrate the green nudging effect of BigTech but also generate value for the platform by leveraging individual green actions as soft information, thereby improving the efficiency of credit allocation. Using a structural model, we estimate an annual green value of 427.52 million US dollars generated by linking personal carbon accounting with BigTech credit. We also show that the incentive-based mechanism surpasses green mandates and subsidies in improving consumer welfare and overall societal welfare. Our findings highlight the role of an incentive-aligned approach, such as integrating personal carbon accounts into credit reporting frameworks, in addressing environmental challenges.

This paper employs a proprietary data set on commodity producers’ profit margins (PPMG) and establishes a robust positive relationship between commodity producers’ profitability growth and future returns of commodity futures. The spread portfolio that longs top-PPMG futures contracts and shorts bottom-PPMG futures contracts delivers a statistically significant average weekly return of 36 basis points. We further demonstrate that profitability is a strong SDF factor in commodity futures market. We theoretically justify our empirical findings by developing an investment-based pricing model, in which producers optimally adjust their production process by maximizing profits subject to aggregate profitability shocks. The model reproduces key empirical results through calibration and simulation.

This paper investigates the impact of curation algorithms through the lens of stock market dynamics. By innovatively incorporating the dynamic interactions between social media platforms, investors, and stock markets, we construct the Social-Media-augmented Artificial Stock marKet (SMASK) model under the agent-based computational framework. Our findings reveal that curation algorithms, by promoting polarized and emotionally charged content, exacerbate behavioral biases among retail investors, leading to worsened stock market quality and investor wealth levels. Moreover, through our experiment on the debated topic of algorithmic regulation, we find limiting the intensity of these algorithms may reduce unnecessary trading behaviors, mitigates investor biases, and enhances overall market quality. This study provides new insights into the dual role of curation algorithms in both business ethics and public interest, offering a quantitative approach to understanding their broader social and economic impact.

We provide a novel explanation for the geographic dispersion of borrower-lender relationships based on information frictions rather than competition. Firms may strategically select distant banks to increase lenders’ information production costs, securing larger loans under information-insensitive contracts. Our model predicts that higher-quality firms prefer distant lenders for information-insensitive contracts, while lower-quality firms use local lenders with information-sensitive terms. Using transaction-level data from a major Chinese bank, we find strong empirical support: higher-rated firms exhibit greater propensity for distant borrowing; local loans show stronger negative correlation between amounts and interest rates; and distant loan pricing demonstrates weaker sensitivity to defaults.

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.

Reputation is widely regarded as a stabilizing factor in financial institutions, reducing capital constraints and enhancing firm resilience. However, in the insurance industry, where capital requirements are shaped by solvency regulations and policyholder behavior, the effects of reputation on capital management remain unclear. This paper examines the unintended consequences of reputation in insurance asset-liability management, focusing on its impact on capital allocation. Using a novel reputation risk measure based on large language models (LLMs) and actuarial models, we show that reputation shifts influence surrender rates, altering capital requirements. While higher reputation reduces surrender risk, it increases capital demand for investment-oriented insurance products, whereas protection products remain largely unaffected. These findings challenge the conventional wisdom that reputation always eases capital constraints, highlighting the need for insurers to integrate reputation management with capital planning to avoid unintended capital strain.