This study examines differences in finance research productivity and influence across 661 academic institutions over the five‐year period from 1989 through 1993. We find that 40 institutions account for over 50 percent of all articles published by 16 leading journals over the five‐year period; 66 institutions account for two‐thirds of the articles. Influence is more skewed, with as few as 20 institutions accounting for 50 percent of all citations to articles in these journals. The number of publications and publication influence increase with faculty size and academic accreditation. Prestigious business schools are associated with high publication productivity and influence.

Earnings nonresponse in household surveys is widespread, yet there is limited knowledge of how nonresponse biases earnings measures. We examine the consequences of nonresponse on earnings gaps and inequality using Current Population Survey individual records linked to administrative earnings data. The common assumption that earnings are missing at random is rejected. Nonresponse across the earnings distribution is U-shaped, highest in the left and right tails. Inequality measures differ between household and administrative data due in part to nonresponse. Nonresponse biases earnings differentials by race, gender, and education, particularly in the tails. Flexible copula-based models can account for nonrandom nonresponse.

A new information aggregation mechanism (IAM), developed via laboratory experimental methods, is implemented inside Intel Corporation in a long-running field test. The IAM, incorporating features of pari-mutuel betting, is uniquely designed to collect and quantize as probability distributions dispersed, subjectively held information. IAM participants’ incentives support timely information revelation and the emergence of consensus beliefs over future outcomes. Empirical tests demonstrate the robustness of experimental results and the IAM’s practical usefulness in addressing real-world problems. The IAM’s predictive distributions forecasting sales are very accurate, especially for short horizons and direct sales channels, often proving more accurate than Intel’s internal forecast.

This paper evaluates the impact of three different performance incentive schemes using data from a social experiment that randomized 88 Mexican high schools with over 40,000 students into three treatment groups and a control group. Treatment 1 provides individual incentives for performance on curriculum-based mathematics tests to students only, treatment 2 to teachers only, and treatment 3 gives both individual and group incentives to students, teachers, and school administrators. Program impact estimates reveal the largest average effects for treatment 3, smaller impacts for treatment 1, and no impact for treatment 2.

To what extent do U.S. consumers change their purchase behavior or, in the extreme, boycott companies based on negative information about corporate tax activities? Practitioner publications and academic research identify consumers as a key corporate tax stakeholder. But we have limited empirical evidence whether information about corporate tax activities influences consumer actions. We undertake a comprehensive study of this question, triangulating across several settings. First, a representative sample of consumers suggests they rarely boycott in response to corporate tax activities. Next, an analysis of granular retail scanner data fails to provide compelling evidence of consumer purchase responses to negative tax news. An analysis of individual foot traffic at retail establishments around negative tax news again fails to suggest U.S. consumers change their shopping activities in response to negative tax news. The combined evidence suggests consumers do not meaningfully alter their purchase behavior in response to negative tax news.

In the absence of random treatment assignment, the selection of appropriate control variables is essential to designing well-specified empirical tests of causal effects. However, the importance of control variables seems under-appreciated in accounting research relative to other methodological issues. Despite the frequent reliance on control variables, the accounting literature has limited guidance on how to select them. We evaluate the evolution in the use of control variables in accounting research and discuss some of the issues that researchers should consider when choosing control variables. Using simulations, we illustrate that more control is not always better and that some control variables can introduce bias into an otherwise well-specified model. We also demonstrate other issues with control variables, including the effects of measurement error and complications associated with fixed effects. Finally, we provide practical suggestions for future accounting research. Data Availability: All data used are publicly available from sources cited in the text.

Consulting service revenues recently surpassed audit revenues as the primary income source for the largest accounting firms. Since SOX limits the provision of consulting services to audit clients, this shift in revenues implies that firms and many clients likely choose between audit and consulting relationships. We explore the implications of this by developing and validating a measure of client-level consulting needs that can likely be fulfilled by accounting firms, which we refer to as “consulting opportunities.” As predicted, we find that consulting opportunities relate positively to auditor switches. We also find that consulting opportunities relate negatively to subsequent Big 4 auditor selection—the firms focusing most on consulting—but we fail to find evidence that consulting opportunities relate to deteriorations in audit quality. Together, our results suggest that legislation limiting firms' ability to deliver consulting services to audit clients may have reduced audit market concentration without discernably impacting quality. Data Availability: All data used are publicly available from sources cited in the text.

In this study, we examine whether investors' actions to acquire accounting information are predictive of future firm performance because these actions partially reveal investors' private expectations of this performance. Using a database of EDGAR downloads, we find some evidence that information acquisition of accounting reports by EDGAR users is, on average, predictive of future firm performance. We then determine the identity of the EDGAR user and examine whether different users' private expectations will be relatively more predictive of subsequent performance. We find that the information acquisition activities of more sophisticated institutional users (e.g., hedge funds, investment banks) are more strongly associated with future performance than are those of less sophisticated retail users. Finally, we find that information acquisition by sophisticated institutions is a leading indicator of their equity holdings. In summary, this study provides evidence of predictive information embedded in sophisticated investors' actions to acquire accounting information.

This study examines the tax avoidance behavior of firms prior to the issuance, and following the resolution, of SEC tax comment letters. We find that firms that appear to engage in greater tax avoidance are more likely to receive a tax-related SEC comment letter. We also find that firms receiving a tax-related SEC comment letter, relative to firms receiving a non-tax comment letter, subsequently decrease their tax avoidance behavior consistent with an increase in expected tax costs. Additionally, we document evidence consistent with other firms that do not receive a comment letter reacting to multiple publicly disclosed tax-related comment letters within their industry by increasing their reported GAAP ETR, consistent with an indirect effect of regulatory scrutiny on certain types of tax avoidance.