OLS estimates of linear regression models become imprecise when distributional assumptions about the regression errors are not strictly met. Such situations frequently arise in applied research due to the heavy-tailed distributions of dependent variables. Using simulated data and replication settings, we show how robust regression estimation can produce more policy-relevant inferences by increasing the precision of estimates, improving test power, and tightening confidence intervals. We provide guidance to researchers on when and how to apply robust estimation as alternative to OLS and how to combine robust regression estimators with fixed effects and clustered standard errors. Given the non-random nature of observations typically downweighted by robust regression estimators, we also illustrate the importance of inspecting the robust regression weights and discuss how these weights can provide useful insights about heterogeneity in treatment effects or relations of interest.

This paper examines why private firms choose to be financially transparent or opaque by conducting a field experiment with more than 25,000 firms in Germany. We inform a randomly chosen set of firms about a disclosure option that allows eligible firms to restrict access to their otherwise publicly available financial statements. We also vary the messaging in subtle ways to induce experimental variation in the probability that firms take transacting (capital providers or customers and suppliers) versus non‐transacting stakeholders (competitors or general interest parties) into consideration when making their filing decision. Based on each firm's actual filing decision, we find that treated firms are 15% more likely to restrict access to their financial statements. This intention‐to‐treat effect is persistent and concentrated among firms that should derive lower net benefits from disclosure (smaller, more mature firms in less capital‐intensive industries). These findings indicate that informational constraints affect firms’ disclosure practice. Additionally, we show that the treatment effect is almost 40% larger for firms that have a higher, exogenously induced, probability of considering non‐transacting stakeholders when making their disclosure decision. By analyzing subsequent firm activity and complementary survey evidence, we also provide suggestive evidence that disclosure requirements put an undue burden on very small private firms.

This paper demonstrates that measures of stock price synchronicity based on market model R 2 s are predictably biased downward as a result of stock illiquidity, and that previously employed remedies to correct market model betas for measurement bias do not fix R 2 . Using a large international sample of firm‐years, we find strong negative and nonlinear relations between illiquidity and R 2 across countries, across firms, and over time. Because variables of interest frequently relate to illiquidity as well, we illustrate the consequences of not controlling for illiquidity in synchronicity research. More generally, we demonstrate the importance of using nonlinear control variable methods. Overall, we conclude that the illiquidity‐driven measurement bias in R 2 provides an explanation for why prior research finds low‐ R 2 firms to have weak information environments, and suggest future research carefully evaluate the sensitivity of its results to nonlinear controls for illiquidity.

We examine how investment professionals assess the usefulness of financial accounting information depending on their information acquisition objectives and preparers' earnings management incentives. We conduct a survey experiment based on face-to-face interviews with investment professionals and document two main results. First, we find that, compared with investment professionals assigned a firm valuation objective, those assigned a managerial performance evaluation objective assess accounting information as significantly less useful. Second, we find no systematic evidence that preparers' earnings management incentives negatively affect investment professionals' assessments of accounting information usefulness. To elucidate this second finding, we conduct a large-scale follow-up online experiment. Our results continue to offer no support for the effect of earnings management incentives on investment professionals' assessments of accounting information usefulness, irrespective of preparers' corporate governance quality. Instead, we find that poor corporate governance, by itself, reduces the usefulness of accounting information to investment professionals.

This paper reports the results of a field experiment investigating how attributes of carbon footprint information affect consumer choice in a large dining facility. Our hypotheses and research methods were preregistered via the Journal of Accounting Research ’s registration‐based editorial process. Manipulating the measurement units and visualizations of carbon footprint information on food labels, we quantify effects on consumers’ food choices. Treated consumers choose less carbon‐intensive dishes, reducing their food‐related carbon footprint by up to 9.2%, depending on the treatment. Effects are strongest for carbon footprint information expressed in monetary units (“environmental costs”) and color‐coded in the familiar traffic‐light scheme. A postexperimental survey shows that these effects obtain although few respondents self‐report concern for the environmental footprint of their meal choices. Our study contributes to the accounting literature by using an information‐processing framework to shed light on the information usage and decision‐making processes of an increasingly important user group of accounting information: consumers.