## 1. Introduction

Conservatism has been a central accounting principle for centuries (Watts and Zimmerman [1986], Basu [1997], Watts [2003a]). Basu ([1997, p. 7] defines conservatism as “the accountant's tendency to require a higher degree of verification to recognize good news as gains than to recognize bad news as losses,” a definition that is consistent with the adage “anticipate no profits but anticipate all losses.” In an efficient market, stock return reflects all new public information, and thus is a valid proxy for economic shocks to value. Then, in a piecewise-linear regression of accounting income on fiscal-period stock return, the incremental coefficient on negative return (the proxy for negative shocks, or “bad news”) is assumed to be a valid measure of asymmetrically timely loss recognition.1 Basu predicts and finds that the incremental coefficient indeed is positive, indicating timelier incorporation of negative economic shocks than positive shocks.2

Under this definition of conservatism, how accounting income incorporates shocks to firm value depends on their sign, so Ball and Shivakumar [2005] and Beaver and Ryan [2005] term it *conditional* conservatism. This contrasts with defining conservatism as reporting unconditionally low earnings or book value of equity. The key difference between these concepts is that conditional conservatism carries new information.3 Basu's formulation of conservatism in this fashion was an important breakthrough in our understanding of financial reporting rules and practices.

In a comparatively short period of time, the Basu [1997] piecewise-linear regression of accounting income on stock return has become one of the principal models of the financial accounting literature. The range and importance of these applications is testimony to the pervasiveness of conservatism as a property of financial reporting, and also to researchers’ confidence in the validity of their estimates of it.4 Furthermore, these studies regularly report differences in conditional conservatism that are consistent with plausible hypotheses, which provides added confidence in the validity of the estimates.

Nevertheless, researchers have assumed that the Basu regression produces valid measures of conditional conservatism due largely to its intuitive appeal, without rigorous analysis.5 The need for formal econometric analysis is heightened by claims that the Basu asymmetric timeliness coefficient is not a valid measure of conservatism (Dietrich, Muller, and Riedl [2007]); that it is unduly affected by variables, such as the book-to-market ratio (Pae, Thornton, and Welker [2005], Givoly, Hayn, and Natarajan [2007], Roychowdhury and Watts, [2007]); and that the Basu coefficients should be avoided by researchers (Patatoukas and Thomas [2011]).

We build our analysis on a model of the relation between accounting income and economic income that captures the salient properties of income recognition as it is practiced. We then use the model to derive and analyze the Basu earnings asymmetric timeliness coefficient. The model addresses shocks to firm value that arise from different types of information, and, consequently, our analysis is conducted entirely in the context of “news” and its incorporation in earnings. In particular, we ignore variation in expected returns across both time and firms. This framework allows a formal derivation of the Basu measure of conservatism, and also improves our understanding of how that measure interacts with characteristics of a firm's information environment.

The model distinguishes four components of information that financial reporting rules and practices cause to be incorporated in accounting income at different points in time. One information component is incorporated contemporaneously. The second information component is incorporated contemporaneously or with a lag, depending on its sign or magnitude. This earnings component is the source of conditional conservatism, which arises because negative news about future cash flows is subject to a lower accounting verification threshold than positive news. The third information component in our model always is incorporated with a lag, such as news about “unbooked” rents or growth options. The first three information components are assumed to be reflected in security prices, even when they are not recognized in current earnings. The model also has accounting income incorporating “noise,” for example, due to random errors in counting inventory or in valuing accounts receivable, that reverses over time. We believe this model incorporates the salient properties of accounting recognition rules and practices.

The primary result in this paper is that the Basu regression provides econometrically valid estimates of conditional conservatism. In particular, we show that, holding other things constant, the Basu regression identifies conditional conservatism only when it exists. The model also allows us to pursue the secondary goal of this paper, which is to show how conditional conservatism is a function of the relative importance of the various information components. Consequently, we are able to formalize and extend the results in Roychowdhury and Watts [2007] on the relation between conditional conservatism and market-to-book ratios. We also address the Dietrich, Muller, and Riedl [2007] claim that return endogeneity and sample truncation lead to biased Basu regression estimates.

Section 'A Framework for Interpreting Regressions of Earnings on Returns' outlines the model of the income–return relation that incorporates salient properties of accounting income. Section 'Econometrics of the Basu Regression' then proceeds with a formal analysis of the Basu regression in the context of that model. Section 'Conditional Conservatism, Firm Characteristics, and Empirical Implications' analyzes the relation between timeliness and firm characteristics, the role of the market-to-book ratio, and other empirical implications. Section 'Return Endogeneity and Sample Truncation' addresses return endogeneity and sample truncation. A short summary and our conclusions appear in section 'Summary and Conclusions'.