A Modified Audit Production Framework: Evaluating the Relative Efficiency of Audit Engagements

TLDR

The study develops a Data Envelopment Analysis model of audit production, using labor cost as input and evidence‑gathering hours as output to assess assurance levels. The model incorporates client characteristics as exogenous factors and is applied to a sample of U.S. engagements from an international accounting firm.

Abstract

We develop a model of audit production based on Data Envelopment Analysis (DEA) using labor cost as input and hours spent on evidence-gathering activities that determine the level of assurance as output. Client characteristics are considered exogenous factors that affect audit production as a whole. We apply the model to a sample of U.S.-based engagements from an international accounting firm. Results indicate that a constrained DEA model using variable returns to scale is appropriate for modeling audit production. We find that audits are more efficient for clients that are larger, have a December year-end, and are highly automated. Audits are less efficient when the auditor relies on internal control, tax services are provided, and the client has subsidiaries. We also find that a well-specified regression-based production model can control for factors that influence auditor efficiency. Finally, we find that inefficiencies are impounded in fees for some industries and firm offices.