I study whether the demand for monitoring explains the scope for renegotiation in private debt contracts. Theory suggests that renegotiation trades off the benefits of enhanced monitoring with the costs of creditor intervention. Consistent with this tradeoff, I show that monitoring demand proxies bear a positive association with renegotiation intensity. In contrast, the costs of creditor intervention are associated with less frequent renegotiations. I also find that contractual monitoring mechanisms, such as covenants and concentrated syndicate structures, are positively related to renegotiation intensity. Furthermore, renegotiations transmit new information to the market, in line with private creditors discovering information during renegotiations.

Do accruals-based earnings provide better information about future operating cash flows than do operating cash flows themselves, as predicted by the Financial Accounting Standards Board's conceptual framework (FASB, 1978)? While this is a foundational issue in accounting, because it addresses the information added by accrual accounting methods, testing it remains unsettled. We show that when comparing the predictive ability of operating cash flows with that of an equivalent earnings measure calculated on an accrual basis, earnings outperform operating cash flows. The result becomes more pronounced when allowance is made for cross-sectional differences in the relation between firms' earnings and future cash flows. In fact, even “bottom line” earnings then have similar explanatory power as operating cash flows.

To what extent does the narrative context surrounding the numbers in financial statements alter the informativeness of these numbers, that is, contextualize them? Answering this question empirically presents a methodological challenge. Leveraging recent advances in deep learning, we propose a method to uncover the value of contextual information learned from the (deep) interactions between numeric and narrative disclosures. We show that the contextualization of accounting numbers makes them substantially more informative in shaping beliefs about a firm's future, especially when numeric data are less reliable. In fact, the informational value of interactions dominates the direct informational value of the narrative context. We corroborate this finding by showing that stock markets and financial analysts incorporate the interactions between narrative and numeric information when making forecasts. We also demonstrate the value of our approach by identifying rich firm‐year–specific heterogeneity in earnings persistence. We discuss a number of avenues for future research.

We explore revealed preferences for the contractual treatment of changes to GAAP in a large sample of private credit agreements issued by publicly held U.S. firms. We document a significant time‐trend toward excluding GAAP changes from the determination of covenant compliance over the period from 1994 to 2012. This trend is positively associated with proxies for standard setters’ shift in focus toward relevance and international accounting harmonization. At the firm level, borrowers facing higher uncertainty are more likely to write contracts that include GAAP changes, but these firms also show a more pronounced time‐trend toward excluding GAAP changes. While this evidence is broadly consistent with an efficiency role for GAAP changes in debt contracting, it is also consistent with a shift in standard setters’ focus offering a partial explanation of why fewer contracts rely on GAAP changes in 2012 than in 1994.

Building on contract theory, we argue that financial covenants control the conflicts of interest between lenders and borrowers via two different mechanisms. Capital covenants control agency problems by aligning debt holder–shareholder interests. Performance covenants serve as trip wires that limit agency problems via the transfer of control to lenders in states where the value of their claim is at risk. Companies trade off these mechanisms. Capital covenants impose costly restrictions on the capital structure, while performance covenants require contractible accounting information to be available. Consistent with these arguments, we find that the use of performance covenants relative to capital covenants is positively associated with (1) the financial constraints of the borrower, (2) the extent to which accounting information portrays credit risk, (3) the likelihood of contract renegotiation, and (4) the presence of contractual restrictions on managerial actions. Our findings suggest that accounting‐based covenants can improve contracting efficiency in two different ways.

The new accounting standard requires that financial institutions estimate expected credit losses on their loan portfolios. The predictability of long-term losses, however, remains an open question. We develop a model that predicts long-term loan losses and incorporates adjustments for macroeconomic forecasts. The model combines cross-sectional predictions with a high-dimensional dynamic factor model that tracks aggregate losses over the business cycle. The model predicts long-term losses out-of-sample with significantly greater accuracy than the Harris et al. (2018) model and several other alternatives. It is also more effective at detecting bank failures. We use the model to estimate the present value of expected losses and the expected loss overhang for a given bank-quarter. The estimated present values subsume information in reported allowances and in fair value disclosures about long-term losses; the evidence is also consistent with loss overhang distorting banks' decisions. The model provides a useful benchmark to study loan loss provisioning.

A substantial literature investigates conditional conservatism, defined as asymmetric accounting recognition of economic shocks (“news”), and how it depends on various market, political, and institutional variables. Studies typically assume the Basu [1997] asymmetric timeliness coefficient (the incremental slope on negative returns in a piecewise‐linear regression of accounting income on stock returns) is a valid conditional conservatism measure. We analyze the measure's validity, in the context of a model with accounting income incorporating different types of information with different lags, and with noise. We demonstrate that the asymmetric timeliness coefficient varies with firm characteristics affecting their information environments, such as the length of the firm's operating and investment cycles, and its degree of diversification. We particularly examine one characteristic, the extent to which “unbooked” information (such as revised expectations about rents and growth options) is independent of other information, and discuss the conditions under which a proxy for this characteristic is the market‐to‐book ratio. We also conclude that much criticism of the Basu regression misconstrues researchers’ objectives.

This paper reviews theoretical and empirical work on financial contracting that is relevant to accounting researchers. Its primary objective is to discuss how the use of accounting information in contracts enhances contracting efficiency and to suggest avenues for future research. We argue that incomplete contract theory broadens our understanding of both the role accounting information plays in contracting and the mechanisms through which efficiency gains are achieved. By discussing its rich theoretical implications, we expect incomplete contract theory to prove useful in motivating future research and in offering directions to advance our knowledge of how accounting information affects contract efficiency.

The concept of conditional conservatism (asymmetric earnings timeliness) has provided new insight into financial reporting and stimulated considerable research since Basu (1997). Patatoukas and Thomas (2011) report bias in firm-level cross-sectional asymmetry estimates that they attribute to scale effects. We do not agree with their advice that researchers should avoid conditional conservatism estimates and inferences from research based on such estimates. Our theoretical and empirical analyses suggest the explanation is a correlated omitted variables problem that can be addressed in a straightforward fashion, including fixed-effects regression. Correlation between the expected components of earnings and returns biases estimates of how earnings incorporate the information contained in returns. Further, the correlation varies with returns, biasing asymmetric timeliness estimates. When firm-specific effects are taken into account, estimates do not exhibit the bias, are statistically and economically significant, are consistent with priors, and behave as a predictable function of book-to-market, size, and leverage. Data Availability: Data are publicly available from sources identified in the article.