In business research, firm size is both ubiquitous and readily measured. Complexity, another firm-related construct, is also relevant, but difficult to measure and not well-defined. As a result, complexity is less frequently incorporated in empirical designs. We argue that most extant measures of complexity are one-dimensional, have limited availability, and/or are frequently misspecified. Using both machine learning and an application-specific lexicon, we develop a text solution that uses widely available data and provides an omnibus measure of complexity. Our proposed measure, used in tandem with 10-K file size, provides a useful proxy that dominates traditional measures.

We create a lexicon of 45 capital budgeting terms and document manager language usage in earnings conference calls during 2010-2020. A sharp contrast between prior survey evidence and capital budgeting terms actually spoken by managers during conference calls is reported. Although surveys suggest that many managers use sensitivity analysis and real options for capital budgeting decisions, these terms almost never occur in any conference calls. Managers of large firms generating more positive financial performance tend to talk more about capital budgeting in earnings calls. Finally, we find that companies that mention payback rather than net present value are smaller in size, have less R&D expenses, and are younger in age.

[A theoretical model that explicitly incorporates the relation between investment banker and auditor is developed to provide a framework for testing the effect of auditor selection in the initial market for unseasoned equity issues. The theoretical model generates a number of testable propositions. Consistent with stylized facts, the theory suggests that high reputation investment bankers will more frequently use high reputation auditors, and that both investment banker and auditor reputation help to reduce underpricing. As either reputational variable increases, the model predicts that the impact of the other variable will diminish. The empirical results confirm this more complex relation. The structure of the model documented in this research may explain the difficulties of previous studies in identifying an empirical relation between auditor reputation and underpricing.]

Measuring the extent to which a firm is financially constrained is critical in assessing capital structure. Extant measures of financial constraints focus on macro firm characteristics such as age and size, variables highly correlated with other firm attributes. We parse 10-K disclosures filed with the U.S. Securities and Exchange Commission (SEC) using a unique lexicon based on constraining words. We find that the frequency of constraining words exhibits very low correlation with traditional measures of financial constraints and predicts subsequent liquidity events, such as dividend omissions or increases, equity recycling, and underfunded pensions, better than widely used financial constraint indexes.

An intertemporal general equilibrium model relates financial asset returns to movements in aggregate output. The model is a standard neoclassical growth model with serial correlation in aggregate output. Changes in aggregate output lead to attempts by agents to smooth consumption, which affects the required rate of return on financial assets. Since aggregate output is serially correlated and, hence, predictable, the theory suggests that stock returns can be predicted based on rational forecasts of output. The empirical results confirm that stock returns are a predictable function of aggregate output and also support the accompanying implications of the model.

This study tests the reaction of security returns to anticipated and unanticipated inflation using SFAS 33 data to stratify firms cross-sectionally by inflation sensitivity. The cross-sectional stratification allows for the distributive effects of inflation and provides a unique means of assaying the accounting disclosures. The results confirm the significant negative impact of unanticipated inflation on security returns for the 1980-82 period. The market measure of inflation sensitivity, however, does not appear to be related in any way to accounting measures of inflation sensitivity based on SFAS 33 data.

A theoretical model that explicitly Incorporates the relation between investment banker and auditor is developed to provide a framework for testing the effect of auditor selection in the Initial market for unseasoned equity Issues. The theoretical model generates a number of testable propositions. Consistent with stylized facts, the theory suggests that high reputation Investment bankers will more frequently use high reputation auditors, and that both Investment banker and auditor reputation help to reduce underpricing. As either reputational variable Increases, the model predicts that the Impact of the other variable will diminish. The empirical results confirm this more complex relation. The structure of the model documented in this research may explain the difficulties of previous studies in Identifying an empirical relation between auditor reputation and underpricing.

An intertemporal general equilibrium model relates financial asset returns to movements in aggregate output. The model is a standard neoclassical growth model with serial correlation in aggregate output. Changes in aggregate output lead to attempts by agents to smooth consumption, which affects the required rate of return on financial assets. Since aggregate output is serially correlated and hence predictable, the theory suggests that stock returns can be predicted based on rational forecasts of output. The empirical results confirm that stock returns are a predictable function of aggregate output and also support the accompanying implications of the model.