This study examines whether and how earnings quality, measured as accruals quality (AQ), affects the cost of equity capital. Using two-stage cross-sectional regression tests, we find that the AQ risk factor is significantly priced, after controlling for low-priced stocks. This result is robust in tests using individual stocks, various portfolio formations, and different beta estimations. Furthermore, we show that AQ and its pricing effect systematically vary with business cycles and macroeconomic variables. In particular, this pricing effect is prominent in total AQ and innate AQ but not in discretionary AQ. The risk premium associated with AQ exists only in economic expansion but not in recession periods. Poorer AQ firms are more vulnerable to macroeconomic shocks. The risk premium and the dispersion of AQ are also related to future economic activity. Overall, our results suggest that AQ contributes to the cost of equity capital and that its pricing effect is associated with fundamental risk.

Recent research has documented the failure of market beta to capture the crosssection of expected returns within the context of a two-pass estimation methodology. However, the two-pass methodology suffers from the errors-in-variables (EIV) problem that could attenuate the apparent significance of market beta. This article provides a new correction for the EIV problem that is robust to conditional heteroscedasticity. After the correction, I find more support for the role of market beta and less support for the role of firm size in explaining the cross-section of expected returns. VVhile the EIV correction leads to a diminished role of firm size, the size variable remains a significant force in explaining the cross-section of expected returns. RECENT FINDINGS BY FAMA and French (1992) suggest that market beta has verylimited ability to explain the cross-section of average stock returns, while firm size and the book-to-market equity ratio have considerable power. These findings cast doubt on the validity of the capital asset pricing model (CAPM) of Sharpe (1964), Lintner (1965), and Black (1972). However, the Fama and French findings are subject to the errors-in-variables (EIV) problem of the traditional two-pass estimation methodology: In the first-pass, beta estimates are obtained from separate time-series regressions for each asset, and in the second-pass, gammas are estimated cross-sectionally by regressing asset returns on the estimated betas. Therefore, the explanatory variable in the cross-sectional regression (CSR) is measured with error. The EIV problem results in an underestimation of the price of beta risk and an overestimation of the other CSR coefficients associated with variables observed without error (such as firm size or the book-to-market equity ratio). Hence, it is very important to determine whether the weak relation between average stock returns and market beta is the result of the misspecification of the asset pricing model or is simply a consequence of the EIV problem.Several methods have been proposed to address the EIV problem. Litzenberger and Ramaswamy (1979) suggest a correction that involves a weighted least squares version of the CSR estimator with a modified design matrix. * Department of Finance, Rutgers University School of Business. I am grateful for helpful discussions and comments from Steve Brown, Eric Chang, Cheng-few Lee, Edward Nelling, Jay Shanken, William Taylor, and especially Gikas Hardouvelis. I am also particularly grateful to an anonymous referee and Ren6 Stulz (the editor) for their help in improving the article. Financial support for this research was provided by the Research and Sponsored Programs at Rutgers University. All errors remain my responsibility. 1605 1606The Journal of Finance However, their corrected estimator can be obtained only when security residual variances are exactly known. Shanken (1992) modifies the traditional two-pass procedure and derives an asymptotic distribution of the CSR estimator within a multifactor framework in which asset returns are...

No abstract

No abstract