We propose a new adaptive hypothesis test for inequality (e.g., monotonicity, convexity) and equality (e.g., parametric, semiparametric) restrictions on a structural function in a nonparametric instrumental variables (NPIV) model. Our test statistic is based on a modified leave‐one‐out sample analog of a quadratic distance between the restricted and unrestricted sieve two‐stage least squares estimators. We provide computationally simple, data‐driven choices of sieve tuning parameters and Bonferroni adjusted chi‐squared critical values. Our test adapts to the unknown smoothness of alternative functions in the presence of unknown degree of endogeneity and unknown strength of the instruments. It attains the adaptive minimax rate of testing in L 2 . That is, the sum of the supremum of type I error over the composite null and the supremum of type II error over nonparametric alternative models cannot be minimized by any other tests for NPIV models of unknown regularities. Confidence sets in L 2 are obtained by inverting the adaptive test. Simulations confirm that, across different strength of instruments and sample sizes, our adaptive test controls size and its finite‐sample power greatly exceeds existing non‐adaptive tests for monotonicity and parametric restrictions in NPIV models. Empirical applications to test for shape restrictions of differentiated products demand and of Engel curves are presented.

I show that cash distributions through cash mergers, dividend payments, and stock buybacks are, in principle, similar to investor fund flows in generating demand for investable assets. Abnormal returns on certain assets can be forecasted because delegated investors predictably reinvest cash returns toward certain holdings. Novel measures of stock-level demand constructed using proportional reinvestments by mutual funds predict abnormal returns and issuances in noncash-paying stocks. These results highlight an alternative and substantial source of price fluctuations in the cross section of equities.

Using hand-collected data on financial asset portfolios and exploiting the 2014 oil price crisis as an exogenous cash flow shock, we investigate financial risk-taking at distressed firms. We find that distressed firms, with high debt rollover risk proxied for by short-term liabilities, substantially increase their investments in risky financial assets, including corporate debt, equity, and mortgage-backed securities. The effects are stronger for unhedged firms with low collateral assets. Overall, we provide new evidence that distressed firms take risk using financial assets camouflaged as cash reserves, which, compared to real assets, are less visible and carry lower transaction costs and accelerated payoffs.

This study proposes that naming a firm eponymously is a mechanism that small private firms can use to signal their superior financial performance and commitment to fulfill debt contract obligations. Using 621,614 small private firms in Europe over the period 2008–2018, we find that small private eponymous firms pay significantly lower interest on their debts and have more long-term debt than non-eponymous firms. Our findings are robust to various controls and placebo tests. Additional analyses show that eponymy lowers the cost of debt and facilitates long-term debt via reputation signaling and private information. We also document that the effect of eponymy on debt contracting is most pronounced when there is less financial development and when firms’ dependence on external financing is low, consistent with the idea that high-quality firms opt for eponymy when they consider less external financing.

How prior trust moderates investor responses to restatements is unknown. We examine how societal trust affects the changes in institutional investors’ shareholdings around a restatement. We consider two competing hypotheses based on the erosion of trust and confirmatory bias. We find the change in institutional investors’ shareholdings around a restatement is more negative for investors from high trust areas compared to low trust areas, consistent with an erosion of trust where high trust institutional investors view the restatement as a violation of trust. Further analyses show that our findings vary with the regulatory or economic environment, type of institution, and type of restatement. Our results are also robust to different tests that address endogeneity and use alternative societal trust measures. Overall, we contribute to the literature by examining the role of societal trust in a dynamic setting where investors’ trust-based beliefs about the credibility of accounting information are not realized. Data Availability: GSS Sensitive Data Files are not available from the authors. Persons interested in obtaining these data should contact the GSS at [email protected]. Other data are available from the public sources cited in the text.

I examine whether employee‐initiated lawsuits against an audit office adversely affect its ability to attract high‐quality talent and deliver quality audits. I posit that employee lawsuits erode prospective employees’ perceptions of an office, diminishing their willingness to join. Using a comprehensive data set of individual auditor profiles, I find a decline in the quality of newly hired auditors following an employee lawsuit. Cross‐sectionally, the adverse effect of employee lawsuits on talent acquisition is more pronounced when an office is undergoing higher growth and when a case receives greater media attention. Conversely, this adverse effect is less pronounced when an audit office is larger or offers more competitive wages within the local area. When an audit office is unable to recruit high‐quality talent, its audit quality is likely to suffer. Consistent with this, I find a deterioration in audit quality provided by an office following an employee lawsuit. Overall, this study underscores the importance of human capital management and employer reputation for audit offices that operate in competitive labor markets.

Carbon trading is an important market mechanism to achieve carbon neutrality. This study explores the possible impact of carbon markets on the stock market performance of listed companies using data from 2013 to 2022 in China's carbon trading pilot regions. Using the event shock of delayed trading in the Chinese carbon market, we attempt to answer the question of the role of green innovation hidden under the compliance event. Results show that a 1% increase in carbon market turnover leads to an average decrease of CNY 0.123 in the company's stock price. Large-scale companies that have been listed for a short time and have poor green innovation capabilities are more vulnerable to the carbon market. Under delayed trading, firms with high green innovation capability will be profitable. By contrast, profitability is not reflected in low green innovation firms. Companies with low green innovation can reduce stock market performance owing to the carbon market's undersupply situation. Our study reveals the stock performance of different carbon trading entities under delayed trading, providing a realistic basis for firms to choose green innovation while helping to improve carbon trading market dynamics.

This paper proposes a novel approach to estimating the probability weighting function (PWF) of investors in the option market. We match observed option prices to the option pricing bounds under stochastic dominance rules. Using 1-month S&P 500 index option data, we find that investors could subjectively employ an inverse S-shaped probability weighting function, which increases the weights on extreme returns and asymmetrically assigns greater weights to extremely low returns than to extremely high returns. Our findings suggest that the inverse S-shaped nature of the PWFs is robust across various estimation specifications, such as adopting an alternative methodology to construct the return distribution, and employing option data with different times to maturity.