In this study, we use cross‐sectional regressions to estimate the value of the debt tax shield. Recognizing that debt is correlated with the value of operations along nontax dimensions, we estimate reverse regressions in which we regress future profitability on firm value and debt rather than regressing firm value on debt and profitability. Reversing the regressions mitigates bias and facilitates the use of market information to control for differences in risk and expected growth. Our estimated value for the debt tax shield is approximately 40 percent (10 percent) of debt balances (firm value), net of the personal tax disadvantage of debt.

We examine the valuation performance of a comprehensive list of value drivers and find that multiples derived from forward earnings explain stock prices remarkably well: pricing errors are within 15 percent of stock prices for about half our sample. In terms of relative performance, the following general rankings are observed consistently each year: forward earnings measures are followed by historical earnings measures, cash flow measures and book value of equity are tied for third, and sales performs the worst. Curiously, performance declines when we consider more complex measures of intrinsic value based on short‐cut residual income models. Contrary to the popular view that different industries have different “best” multiples, these overall rankings are observed consistently for almost all industries examined. Since we require analysts’ earnings and growth forecasts and positive values for all measures, our results may not be representative of the many firm‐years excluded from our sample.

Estimating expected credit losses on banks' portfolios is difficult. The issue has become of increasing interest to academics and regulators with the FASB and IASB issuing new regulations for loan impairment. We develop a measure of the one-year-ahead expected rate of credit losses (ExpectedRCL) that combines various measures of credit risk disclosed by banks. It uses cross-sectional analyses to obtain coefficients for estimating each period's measure of expected credit losses. ExpectedRCL substantially outperforms net charge-offs in predicting one-year-ahead realized credit losses, and reflects nearly all the credit loss-related information in the charge-offs. ExpectedRCL also contains incremental information about one-year-ahead realized credit losses relative to the allowance and provision for loan losses and the fair value of loans. It is a better predictor of the provision for loan losses than analyst provision forecasts, and is incrementally useful beyond other credit risk metrics in predicting bank failure up to one year ahead.

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Cite View This Citation Add to Citation Manager Citation Nahum D. Melumad, Doron Nissim, SARAH E. McVAY; Line-Item Analysis of Earnings Quality. The Accounting Review 1 May 2010; 85 (3): 1121–1122. https://doi.org/10.2308/accr.2010.85.3.1121 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentThe Accounting Review Search Advanced Search