[In the last two decades of accounting research, many studies have investigated the relation between accounting variables and risk-adjusted security returns. The earliest studies (e.g., Ball and Brown 1968) used simple, nonparametric methods and focused mainly on the question of whether accounting earnings are associated with residual equity returns. Subsequent studies made methodological refinements in both the measurement and the statistical techniques. One important statistical refinement was the "unexpected earnings response regression model" (UERRM), a linear statistical model that uses the unexpected earnings variable as a regressor to explain risk-adjusted returns. The UERRM has become well-known, and many recent studies (e.g., Cornell and Landsman 1989, 686; Daley et al. 1988, 580; Doran et al. 1988, 392; Landsman and Damodaran 1989, 107; McNichols 1989, 15) have used some form of it as a "benchmark" model, against which to compare more complicated models. In one paradigm (so popular that it has become almost standard practice), various accounting variables are added to the UERRM, and their "incremental information content" is assessed by testing the statistical significance of their coefficients. The inferences derived from this procedure are, of course, conditional on the degree to which the UERRM is correctly specified. A critical problem caused by using a misspecified UERRM is that its least squares estimator can lead to erroneous inferences in the research design. Despite the UERRM's popularity, researchers have expressed concerns regarding its specification. For example, Lev (1989) recently surveyed a large number of research papers that used some form of an UERRM and found that for the most part R2 s were low and often bordered on "the negligible." His table 1, which includes statistics from 19 studies, indicates that most reported R2 s are less than 10 percent. Although low R2 s are not proof of major specification problems, Lev does suggest that they are a cause for concern and may be the result of specification problems. Investigation of multiple specification problems is an important aspect of the present study because the various specification issues are interrelated. For example, nonnormality can be associated with nonlinearity, which, in turn, can be associated with heteroscedasticity or variation in the coefficients (Judge et al. 1985, 455, 814, 839). Thus, ad hoc tests for a single specification problem can be misleading and can fail to identify the fundamental problems. To our knowledge, no studies have comprehensively and formally evaluated the specification of the cross-sectional, ordinary least squares model that relates unexpected earnings to risk-adjusted security returns. Therefore, the purpose of this study is to test such a model systematically and empirically for specification problems. Specifically, this study tests for nonlinearity, heteroscedasticity, residual nonnormality, omitted variables, and interfirm systematic and random coefficient variation. Also, when appropriate, adjusted R2 -statistics are included to indicate the degree of misspecification-information that is not directly observable from the tests themselves. A high degree of generality is obtained by using three samples of earnings forecasts as proxies for expected earnings. These were obtained from IBES financial analyst consensus forecasts, Value Line financial analyst forecasts, and COMPUSTAT-based time-series forecasts. Daily and monthly security returns are considered for short and long event-windows, respectively. In addition, one study recently published in The Accounting Review (Cornell and Landsman 1989) is replicated. The findings from all of the samples and the replication indicate that the specification error is large enough to affect conclusions regarding economic relationships. For example, in the replication, the specification problems are shown to lead to substantial instability in inferences from the model.]

Recent research provides evidence that the operating cash flows-to-price ratio subsumes accruals in explaining future annual returns. This suggests that the accrual anomaly is part of the overall value-glamour anomaly and does not represent the mispricing of earnings. We extend the literature by using multiple measures of abnormal accruals and separate analyses of future annual returns and future earnings announcement returns. The results reveal that the operating cash flows-to-price ratio does not subsume abnormal accruals in explaining future annual returns or future announcement returns. We also find that the operating cash flows-to-price ratio does not subsume total accruals in explaining future announcement returns. These results are not consistent with accruals being a manifestation of the value-glamour anomaly. Our study contributes to the current debate on the existence and the extent of the (abnormal) accrual anomaly. Moreover, the methodology employed can help researchers in exploring mispricing phenomena.

Does accounting regime play a role in the well-documented phenomenon of overbidding in M&As? The 2001 regulatory change from a goodwill amortization to a non-amortization regime (SFAS 142) affords us a quasi-experimental setting for testing the consequences of M&A accounting rules for acquirers' bidding decisions. Relying on a novel approach to modeling optimal bidding, our primary finding indicates a significant increase in overbidding in the post-2001 period, suggesting that M&A accounting has real consequences for bidding decisions, and that this result is robust to a battery of sensitivity tests. In addition, supplementary tests show that overbidding is more pronounced in pooling versus purchase transactions, and that the accounting regime's implications for overbidding and acquisition premium are distinct. Overall, our findings shed light on the role accounting plays in shaping managerial decisions—and, ultimately, shareholder wealth—in an important corporate setting. They may thus inform researchers, corporate boards, and standards setters. Data Availability: Data are available from the public sources cited in the text.

In the last two decades of accounting research, many studies have investigated the relation between accounting variables and risk-adjusted security returns. The earliest studies (e.g., Ball and Brown 1968) used simple, nonparametric methods and focused mainly on the question of whether accounting earnings are associated with residual equity returns. Subsequent studies made methodological refinements in both the measurement and the statistical techniques. One important statistical refinement was the "unexpected earnings response regression model" (UERRM), a linear statistical model that uses the unexpected earnings variable as a regressor to explain risk-adjusted returns.' The UERRM has become well-known, and many recent studies (e.g., Cornell and Landsman 1989, 686; Daley et al. 1988, 580; Doran et al. 1988, 392; Landsman and Damodaran 1989, 107; McNichols 1989, 15) have used some form of it as a "benchmark" model, against which to compare more complicated models. In one paradigm (so popular that it has become almost standard practice), various accounting variables are added to the UERRM, and their "incremental information content" is assessed by testing the statistical significance of their coefficients. The inferences derived from this procedure are, of course, conditional on the degree to which the UERRM is correctly specified. A critical problem caused by using a misspecified UERRM is that its least squares estimator can lead to erroneous inferences in the research design. Despite the UERRM's popularity, researchers have expressed concerns regarding its specification. For example, Lev (1989) recently surveyed a large number of research papers that used some form of an UERRM and found that for the most part R2s were low and often bordered on "the negligible." His table 1, which includes statistics from 19 studies, indicates that most reported R²s are less than 10 percent. Although low R²s are not proof of major specification problems, Lev does suggest that they are a cause for concern and may be the result of specification problems. Investigation of multiple specification problems is an important aspect of the present study because the various specification issues are interrelated. For example, nonnormality can be associated with nonlinearity, which, in turn, can be associated with heteroscedasticity or variation in the coefficients (Judge et al. 1985, 455, 814, 839). Thus, ad hoc tests for a single specification problem can be misleading and can fail to identify the fundamental problems. To our knowledge, no studies have comprehensively and formally evaluated the specification of the cross-sectional, ordinary least squares model that relates unexpected earnings to risk-adjusted security returns. Therefore, the purpose of this study is to test such a model systematically and empirically for specification problems Specifically, this study tests for nonlinearity, heteroscedasticity, residual nonnormality, omitted variables, and interfirm systematic and random coefficient variation. Also, when appropriate, adjusted R²-statistics are included to indicate the degree of misspecification information that is not directly observable from the tests themselves. A high degree of generality is obtained by using three samples of earnings forecasts as proxies for expected earnings. These were obtained from IBES financial analyst consensus forecasts, Value Line financial analyst forecasts, and COMPUSTAT-based time-series forecasts. Daily and monthly security returns are considered for short and long event-windows, respectively. In addition, one study recently published in The Accounting Review (Cornell and Landsman 1989) is replicated. The findings from all of the samples and the replication indicate that the specification error is large enough to affect conclusions regarding economic relationships. For example, in the replication, the specification problems are shown to lead to substantial instability in inferences from the model.

This paper examines the impact of hedge fund activism on corporate tax avoidance. We find that relative to matched control firms, businesses targeted by hedge fund activists exhibit lower tax avoidance levels prior to hedge fund intervention, but experience increases in tax avoidance after the intervention. Moreover, findings suggest that the increase in tax avoidance is greater when activists have a successful track record of implementing tax changes and possess tax interest or knowledge as indicated by their Securities and Exchange Commission (SEC) 13D filings. We also find that these greater tax savings do not appear to result from an increased use of high-risk and potentially illegal tax strategies, such as sheltering. Taken together, the results suggest that shareholder monitoring of firms, in the form of hedge fund activism, improves tax efficiency. JEL Classifications: G32; G34; H26. Data Availability: Data are available from sources identified in the text.

This study examines whether politicians exhibit hometown favoritism in assigning preferential corporate income tax rates. We find that firms with hometown connections to incumbent provincial leaders experience favorable tax treatment. This effect is more pronounced when those leaders have strong hometown preferences and weaker when they have a strong incentive to seek promotion, suggesting that social incentives are the primary drivers of the effects on corporate tax benefits of hometown favoritism by politicians. Moreover, this effect is intensified when members of senior management have personal connections with the provincial leader. The mechanism test reveals that the provincial governments tend to qualify connected firms for preferential tax policies under their jurisdictions. Overall, our results suggest that hometown favoritism by politicians promotes tax benefits for business entities. Data Availability: Data are available from the public sources cited in the text.