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Daniel J. Taylor

Other affiliations: Stanford University
Bio: Daniel J. Taylor is an academic researcher from University of Pennsylvania. The author has contributed to research in topics: Insider trading & Insider. The author has an hindex of 27, co-authored 66 publications receiving 4943 citations. Previous affiliations of Daniel J. Taylor include Stanford University.


Papers
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Posted Content
TL;DR: The authors review and evaluate the methods commonly used in the accounting literature to correct for cross-sectional and time-series dependence and find that the extant methods are not robust to both forms of dependence.
Abstract: We review and evaluate the methods commonly used in the accounting literature to correct for cross-sectional and time-series dependence. While much of the accounting literature studies settings where variables are cross-sectionally and serially correlated, we find that the extant methods are not robust to both forms of dependence. Contrary to claims in the literature, we find that the Z2-statistic and Newey-West corrected Fama-MacBeth do not correct for both cross-sectional and time-series dependence. We show that extant methods produce misspecified test statistics in common accounting research settings, and that correcting for both forms of dependence substantially alters inferences reported in the literature. Specifically, several findings in the cost of equity capital literature, the cost of debt literature, and the conservatism literature appear not to be robust to the use of well-specified test statistics.

1,099 citations

Journal ArticleDOI
TL;DR: The authors review and evaluate the methods commonly used in the accounting literature to correct for cross-sectional and time-series dependence and find that the extant methods are not robust to both forms of dependence.
Abstract: We review and evaluate the methods commonly used in the accounting literature to correct for cross‐sectional and time‐series dependence. While much of the accounting literature studies settings in which variables are cross‐sectionally and serially correlated, we find that the extant methods are not robust to both forms of dependence. Contrary to claims in the literature, we find that the Z2 statistic and Newey‐West corrected Fama‐MacBeth standard errors do not correct for both cross‐sectional and time‐series dependence. We show that extant methods produce misspecified test statistics in common accounting research settings, and that correcting for both forms of dependence substantially alters inferences reported in the literature. Specifically, several findings in the implied cost of equity capital literature, the cost of debt literature, and the conservatism literature appear not to be robust to the use of well‐specified test statistics.

946 citations

Posted Content
TL;DR: In this paper, the authors examined when information asymmetry among investors affects the cost of capital in excess of standard risk factors and found that the degree of market competition is an important conditioning variable to consider when examining the relation between information asymmetrized and costs of capital.
Abstract: This paper examines when information asymmetry among investors affects the cost of capital in excess of standard risk factors. When equity markets are perfectly competitive, information asymmetry has no separate effect on the cost of capital. When markets are imperfect, information asymmetry can have a separate effect on firms’ cost of capital. Consistent with our prediction, we find that information asymmetry has a positive relation with firms’ cost of capital in excess of standard risk factors when markets are imperfect and no relation when markets approximate perfect competition. Overall, our results show that the degree of market competition is an important conditioning variable to consider when examining the relation between information asymmetry and cost of capital.

320 citations

Journal ArticleDOI
TL;DR: In this paper, the authors show that if the manager is risk-averse and misreporting increases both equity values and equity risk, the sensitivity of the manager's wealth to changes in stock price (portfolio delta) will have two countervailing incentive effects: a positive "reward effect" and a negative "risk effect".

281 citations

Journal ArticleDOI
TL;DR: In this article, the authors examined when information asymmetry among investors affects the cost of capital in excess of standard risk factors and found that the degree of market competition is an important conditioning variable to consider when examining the relation between information asymmetrized and costs of capital.
Abstract: This paper examines when information asymmetry among investors affects the cost of capital in excess of standard risk factors. When equity markets are perfectly competitive, information asymmetry has no separate effect on the cost of capital. When markets are imperfect, information asymmetry can have a separate effect on firms’ cost of capital. Consistent with our prediction, we find that information asymmetry has a positive relation with firms’ cost of capital in excess of standard risk factors when markets are imperfect and no relation when markets approximate perfect competition. Overall, our results show that the degree of market competition is an important conditioning variable to consider when examining the relation between information asymmetry and cost of capital.

278 citations


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Book
01 Jan 2009

8,216 citations

Journal ArticleDOI
01 May 1981
TL;DR: This chapter discusses Detecting Influential Observations and Outliers, a method for assessing Collinearity, and its applications in medicine and science.
Abstract: 1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

4,948 citations

Journal ArticleDOI
TL;DR: The authors proposed a variance estimator for the OLS estimator as well as for nonlinear estimators such as logit, probit, and GMM that enables cluster-robust inference when there is two-way or multiway clustering that is nonnested.
Abstract: In this article we propose a variance estimator for the OLS estimator as well as for nonlinear estimators such as logit, probit, and GMM. This variance estimator enables cluster-robust inference when there is two-way or multiway clustering that is nonnested. The variance estimator extends the standard cluster-robust variance estimator or sandwich estimator for one-way clustering (e.g., Liang and Zeger 1986; Arellano 1987) and relies on similar relatively weak distributional assumptions. Our method is easily implemented in statistical packages, such as Stata and SAS, that already offer cluster-robust standard errors when there is one-way clustering. The method is demonstrated by a Monte Carlo analysis for a two-way random effects model; a Monte Carlo analysis of a placebo law that extends the state–year effects example of Bertrand, Duflo, and Mullainathan (2004) to two dimensions; and by application to studies in the empirical literature where two-way clustering is present.

2,542 citations

Posted Content
TL;DR: The authors study whether managers use real activities manipulation and accrual-based earnings management as substitutes in managing earnings and find that managers trade off the two earnings management methods based on their relative costs.
Abstract: I study whether managers use real activities manipulation and accrual-based earnings management as substitutes in managing earnings. I find that managers trade off the two earnings management methods based on their relative costs and that managers adjust the level of accrual-based earnings management according to the level of real activities manipulation realized. Using an empirical model that incorporates the costs associated with the two earnings management methods and captures managers’ sequential decisions, I document large sample evidence consistent with managers using real activities manipulation and accrual-based earnings management as substitutes.

1,422 citations

Journal ArticleDOI
TL;DR: In this paper, the authors examine whether socially responsible firms behave differently from other firms in their financial reporting, and they find that firms that exhibit corporate social responsibility also behave in a responsible manner to constrain earnings management, thereby delivering more transparent and reliable financial information to investors.
Abstract: This study examines whether socially responsible firms behave differently from other firms in their financial reporting. Specifically, we question whether firms that exhibit corporate social responsibility (CSR) also behave in a responsible manner to constrain earnings management, thereby delivering more transparent and reliable financial information to investors as compared to firms that do not meet the same social criteria. We find that socially responsible firms are less likely (1) to manage earnings through discretionary accruals, (2) to manipulate real operating activities, and (3) to be the subject of SEC investigations, as evidenced by Accounting and Auditing Enforcement Releases against top executives. Our results are robust to (1) controlling for various incentives for CSR and earnings management, (2) considering various CSR dimensions and components, and (3) using alternative proxies for CSR and accruals quality. To the extent that we control for the potential effects of reputation and financial performance, our findings suggest that ethical concerns are likely to drive managers to produce high-quality financial reports.

1,284 citations