Journal ArticleDOI
Propensity Score Matching in Accounting Research
Reads0
Chats0
TLDR
Propensity score matching (PSM) has become a popular technique for estimating average treatment effects (ATEs) in accounting research as mentioned in this paper, however, studies often oversell the capabilities of PSM, fail to disclose important design choices and/or implement PSM in a theoretically inconsistent manner.Abstract:
Propensity score matching (PSM) has become a popular technique for estimating average treatment effects (ATEs) in accounting research. In this study, we discuss the usefulness and limitations of PSM relative to more traditional multiple regression (MR) analysis. We discuss several PSM design choices and review the use of PSM in 86 articles in leading accounting journals from 2008–2014. We document a significant increase in the use of PSM from zero studies in 2008 to 26 studies in 2014. However, studies often oversell the capabilities of PSM, fail to disclose important design choices, and/or implement PSM in a theoretically inconsistent manner. We then empirically illustrate complications associated with PSM in three accounting research settings. We first demonstrate that when the treatment is not binary, PSM tends to confine analyses to a subsample of observations where the effect size is likely to be smallest. We also show that seemingly innocuous design choices greatly influence sample composi...read more
Citations
More filters
Journal ArticleDOI
Do Client Characteristics Really Drive the Big N Audit Quality Effect? New Evidence from Propensity Score Matching
TL;DR: It is shown that it is premature to suggest that propensity score matching (PSM) eliminates the Big N effect, and random combinations of PSM design choices that achieve covariate balance and four commonly used audit quality measures find that this finding may be affected by PSM’s sensitivity to its design choices and/or by the validity of the auditquality measures used in the analysis.
Journal ArticleDOI
Entropy-balanced accruals
TL;DR: In this article, a multivariate matching approach (entropy balancing) was employed to adjust for determinants in place of relying on a linear model, which significantly improves accrual model specification by reducing coefficient bias relative to linear and propensity-score matched models.
Journal ArticleDOI
Proxies and Databases in Financial Misconduct Research
TL;DR: In this paper, the authors examine the causes and effects of financial misconduct based on samples drawn from four popular databases that identify restatements, securities class action lawsuits, and Accounting and Auditing Enforcement Releases (AAERs), and show that the results from empirical tests can depend on which database is accessed.
Journal ArticleDOI
Is the SEC captured? Evidence from comment-letter reviews
TL;DR: This article found that firm political connections positively predict comment letter (CL) reviews and substantive characteristics of such reviews, including the number of issues evaluated and the seniority of SEC staff involved.
Journal ArticleDOI
Influential Observations and Inference in Accounting Research
TL;DR: Two widely used approaches to address influential observations as discussed by the authors were proposed to deal with the extreme values of observations with extreme values that can influence coefficient estimates and inferences in accountancy studies.
References
More filters
Journal ArticleDOI
Sample Selection Bias as a Specification Error
TL;DR: In this article, the bias that results from using non-randomly selected samples to estimate behavioral relationships as an ordinary specification error or "omitted variables" bias is discussed, and the asymptotic distribution of the estimator is derived.
Journal ArticleDOI
The central role of the propensity score in observational studies for causal effects
TL;DR: The authors discusses the central role of propensity scores and balancing scores in the analysis of observational studies and shows that adjustment for the scalar propensity score is sufficient to remove bias due to all observed covariates.
Journal ArticleDOI
Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches
TL;DR: In this article, the authors examine the different methods used in the literature and explain when the different approaches yield the same (and correct) standard errors and when they diverge, and give researchers guidance for their use.
Posted Content
Mostly Harmless Econometrics: An Empiricist's Companion
TL;DR: The core methods in today's econometric toolkit are linear regression for statistical control, instrumental variables methods for the analysis of natural experiments, and differences-in-differences methods that exploit policy changes.