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What do we learn from two new accounting-based stock market anomalies?

Journal of Accounting and Economics 2004 38, 333-348 open access
Hirshleifer et al. (J. Account. Econom. 38 (2004)) and Taffler, Lu and Kausar (J. Account. Econom. 38 (2004)) document large and statistically significant abnormal returns from trading on balance sheet data and audit opinions. However, the statistical tests ignore high transactions costs, especially for selling short, that would likely make the trading strategies unprofitable. The accounting anomalies literature is adding little to what we know about how and why markets operate more or less efficiently. I identify some research questions and opportunities, highlighting those with accounting and auditing implications.

The conservatism principle and the asymmetric timeliness of earnings1

Journal of Accounting and Economics 1997 24(1), 3-37
I interpret conservatism as resulting in earnings reflecting ‘bad news’ more quickly than ‘good news’. This interpretation implies systematic differences between bad news and good news periods in the timeliness and persistence of earnings. Using firms’ stock returns to measure news, the contemporaneous sensitivity of earnings to negative returns is two to six times that of earnings to positive returns. I also predict and find that negative earnings changes are less persistent than positive earnings changes. Earnings response coefficients (ERCs) are higher for positive earnings changes than for negative earnings changes, consistent with this asymmetric persistence. ¢ 1997 Elsevier Science B.V. All rights reserved.

The misuse of regression-based x-Scores as dependent variables

Journal of Accounting and Economics 2024 77(2-3), 101643 open access
Researchers often use regression-based x-Scores (e.g., conservatism C-Score , misstatement F-Score ) from a stage 1 model as a dependent variable in stage 2. We argue that this x-Score analysis can cause coefficient biases and interpretation problems because (1) x-Score does not capture new sources of variation, and (2) the estimates often hinge on unacknowledged technical assumptions. Instead, we recommend that researchers include the test variables and the relevant controls in stage 1, obviating the need for an x-Score . In replication analyses, some important published findings change after we remove the coefficient bias caused by the use of x-Score as a dependent variable.

Modeling the determinants of meet-or-just-beat behavior in distribution discontinuity tests

Journal of Accounting and Economics 2019 68(2-3), 101266
We develop new distribution discontinuity tests conditional on multiple explanatory variables for analyzing meet-or-just-beat behavior around benchmarks. These tests combine Burgstahler and Dichev's (1997) meet-or-just-beat intuition with a flexible statistical model that addresses important limitations of the existing tests. Our method considerably outperforms logit-based tests of distribution discontinuity determinants and changes the interpretation of a major finding in the earnings discontinuity literature. As a secondary benefit, it also has slightly higher statistical power than histogram-based tests of distribution discontinuity existence. Our method is robust, easy to implement using our publicly available Stata command, and could benefit researchers in many fields.

Loss function assumptions in rational expectations tests on financial analysts’ earnings forecasts

Journal of Accounting and Economics 2004 38, 171-203
Prior research concludes that financial analysts do not process public information efficiently in generating their earnings forecasts. The ordinary least squares (OLS) regression-based tests used in prior studies assume implicitly that analysts face a quadratic loss function. In contrast, we argue that analysts likely face a linear loss function, and hence, try to minimize their absolute forecast errors. We conduct and compare rational expectations tests using these two alternative loss functions. We reproduce most prior findings of forecast inefficiency with OLS regressions, but find virtually no evidence of forecast inefficiency with least absolute deviation regressions, where we explicitly assume a linear loss function.

Director–Liability–Reduction Laws and Conditional Conservatism

Journal of Accounting Research 2019 57(4), 889-917
ABSTRACT We study nonofficer directors’ influence on the accounting conservatism of U.S. public firms. Between 1986 and 2002, all 50 U.S. states enacted laws that limited nonofficer directors’ litigation risk but often left officer directors’ litigation risk unchanged. We find that conditional conservatism decreased after the staggered enactments of the laws, which we attribute to less nonofficer director monitoring of financial reporting in affected firms. Conservatism fell less when shareholder or debtholder power was high, consistent with major stakeholders moderating the influence of nonofficer directors. We verify that our results stem from reductions in the asymmetric timeliness of accruals and, specifically, its current assets components. We also show that affected firms switched away from Big N auditors more often, which reduced these firms’ commitment to conservative financial reports.

Asymmetric loan loss provision models

Journal of Accounting and Economics 2020 70(2-3), 101359
Large net loan charge-offs are frequently associated with large decreases in nonperforming loans and large increases in loan loss provisions, inducing a V-shaped relation between loan loss provisions and nonperforming loan changes. Failure to model the asymmetry attributable to net loan charge-offs can change inferences about the presence of earnings management and the effects of delayed loan loss recognition in prior papers that assumed linearity. Future researchers should either include net loan charge-offs in linear models of loan loss provisions or explicitly model the asymmetry induced by omitting net loan charge-offs.

Walking the walk? Bank ESG disclosures and home mortgage lending

Review of Accounting Studies 2022 27(3), 779-821 open access
We show that banks with high environmental, social, and governance (ESG) ratings issue fewer mortgages in poor localities—in number and dollar amount—than banks with low ESG ratings. This lending disparity happens at both the county and census tract level, worsens in disaster areas of severe hurricane strikes, is robust to alternative ESG ratings (including using only the social (S) component), and cannot be explained by banks’ differential deposit networks. We find no difference in mortgage default rates between high- and low-ESG banks, rejecting an alternative explanation based on differential credit screening quality. We report a complementary, not substitution, relation between high-ESG banks’ mortgage lending and their community development investments (like affordable housing projects) in poor localities. Loan-application-level analyses confirm that high-ESG banks are more likely than low-ESG banks to reject mortgage loans in poor neighborhoods. The evidence hints at social wash: banks deploy prosocial rhetoric and symbolic actions while not lending much in disadvantaged communities, the social function they arguably ought to perform. Community Reinvestment Act (CRA) examinations partially undo the social wash effect.