Class Overview
Why is this important?
Understanding the economics of audit is crucial for grasping how and why companies invest in these services, particularly in relation to risk management and regulatory compliance. By examining real-world data and applying analytical tools, students will gain insights into the cost structures of audit services, factors influencing pricing, and the broader implications for financial transparency. This skill set is valuable not only for audit professionals but also for anyone involved in corporate governance, accounting, or financial analysis.
What will we do?
This class delves into the economic principles underlying audit services, focusing on understanding the factors that influence audit fees across different firms. Building on our earlier discussions on the economics of disclosure and audit, we will explore hypotheses that explain audit fees, utilizing statistical methods such as t-tests, correlation, and regression analysis to test these ideas. Through a combination of case-based discussions and data-driven exercises, students will develop a framework for analyzing firm characteristics that contribute to variations in audit fees.
How this relates to other classes:
We have briefly discussed the economics of disclosure and audit in Class 1. We will continue this discussion and propose hypotheses about which firm features explain audit fees. These hypotheses will be discussed in a way in which we could test them using data, the tools we will discuss are those using statistical methods including t-tests, and correlation and/or regression analysis.We shift from technical audit tools to understanding the broader economic landscape that impacts audit practices
Materials and Preparation
Class Materials
- Case: EconomicsOfAudit
- Slides: PowerPoint or PDF
- Analytics Tools: Git and GitHub, Alteryx
- Suggested in-class seating: discussion teams
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Suggested Pre-Class Preparation
- If you have not read the Economics of Audit Case yet, please read it before class.
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Class Plan
- We will review the material presented in our first class, this will be largely done on PollEverywhere.
- After the review we will begin working on the case, for the first half of class we will discuss the case in discussion teams and use the warm call technique to report back to class.
- Our goal is to test our predictions against real world data, specifically, what do we think helps explain why some companies pay more in audit fees than other companies, as an example Microsoft paid $61,402,000 in audit fees in 2023 and Apple paid $25,403,329 (you can find information about audit fees either in 10-Ks or Def14A filings known as Proxy Statements see: MSFT and AAPL ).
- In the second half of class, working in discussion teams, I will first demonstrate an Alteryx workflow to prepare the data and test the prediction that audit fees are higher for larger companies.
- Discussion teams will then test another prediction about a firm characteristic that helps explain audit fees that is incremental to the size of the company.
- To conclude class, discussion teams will be given time to present their findings and explain their prediction and data choices.
Required Deliverables
| Deliverable | Due Date | Canvas Submission Portal |
|---|---|---|
| Professionalism (individual): Audit Fee Prediction Q&A | September 25th, 2025 | Upload to Canvas |