Differential Audit Quality, Propensity Score Matching and Rosenbaum Bounds for Confounding Variables

43 Pages Posted: 5 Jul 2012

See all articles by Michael J. Peel

Michael J. Peel

Cardiff University - Cardiff Business School

Gerry Makepeace

Cardiff University; IZA Institute of Labor Economics

Date Written: June/July 2012

Abstract

Via propensity score matching (PSM) and Rosenbaum Bounds (RB), this paper reports new evidence on the premiums charged by big 4 and the top 4 mid‐tier (mid 4) auditors relative to their smaller counterparts in the private corporate market. The results demonstrate that big 4 and mid 4 premiums are in accord with theoretical predictions on auditor quality differences; and that these premiums are relatively insensitive to potential hidden bias when gauged by the RB method for appraising confounding variables under bounded uncertainty. Given the limitations of conventional methods, PSM is being increasingly adopted in accounting studies to estimate treatment effects. Employing paired and simultaneous multi‐sample PSM premium estimates, we provide a comprehensive evaluation and illustration of the RB method, together with the advantages and limitations of PSM, on which RB is predicated, when compared to alternative estimators. We demonstrate that PSM, when coupled with RB, provide novel empirical evidence for premiums estimated across three different matched audit quality tiers, to those estimated in prior studies which employ Heckman methods, to hidden bias equivalents and to the sensitivity of the bounds parameters to the omission of covariates employed in the study. New evidence on premiums across size quartiles, and quantile regression estimates over audit fee percentiles, support the PSM findings.

Keywords: auditor premiums, Rosenbaum Bounds, propensity score matching, selection bias, multi‐sample matching, quantile regression, Heckman methods

Suggested Citation

Peel, Michael J. and Makepeace, Gerald H, Differential Audit Quality, Propensity Score Matching and Rosenbaum Bounds for Confounding Variables (June/July 2012). Journal of Business Finance & Accounting, Vol. 39, Issue 5‐6, pp. 606-648, 2012, Available at SSRN: https://ssrn.com/abstract=2100697 or http://dx.doi.org/10.1111/j.1468-5957.2012.02287.x

Michael J. Peel (Contact Author)

Cardiff University - Cardiff Business School ( email )

Cardiff
United Kingdom

Gerald H Makepeace

Cardiff University ( email )

Economics Section
Cardiff Business School
Cardiff, Wales CF10 3EU
United Kingdom

IZA Institute of Labor Economics

Schaumburg-Lippe-Str. 7 / 9
Bonn, D-53072
Germany

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