Final Report

Methodology

The purpose of our project is to determine whether there is an association between the geographic location of industry leaders in an auditing firm and the auditing pricing and quality of that same auditing firm’s industry clients. Professor Reidenbach and I mainly focused on the Big Four accounting firm: Deloitte, EY, KPMG and PwC. I collected office location, industries served, services provided, the individuals leading each respective industry, and these leaders’ office locations information from these four accounting firms. It was quite challenging to determine the names of the industry leaders within each firm since they are not available within a database and are not always easily located on the audit firms’ websites. Then, we used the Wharton Research Data Services (WRDS) and picked the audit analytics dataset to collect audit pricing/fee and audit opinion data using excel format and SAS Windows_32 dataset format. Professor Reidenbach used the software application and the sets of data we have collected to come up with results for our study.

Research summary/ Accomplishments

We defined the major controlled variables for the regression analysis that Professor Reidenbach performed. The controlled variables are Log of Total Assets, Ratio of Long Term Debt over Total Assets, Ratio of EBIT over Total Assets, Qualified Audit Opinion, Inventory Record, Joint Leader (City and Nation), National Leader, City Leader, Leader CBSA (which means that the client company’s headquarter location is the same as the industry leaders’ offices) and groups of industries such as Oil and Gas, Retail and Utilities that we believe will have an impact on the result. We performed a two-tailed t test and used 0.05 as the significance level. For one of the most important controlled variables, Leader CBSA, we got the p-value as 0.2687, which is way greater than 0.05. This leads us to conclude that there is no association between industry leaders’ office locations and audit fee even when the office locations are headquarter locations. After discussing with Professor Reidenbach, we believe that one possible cause is missing data for certain industries. There is a major system called Standard Industry Code (SIC) that Professor Reidenbach used to pick out the industry data used to run the regression analysis. It is a coding system that experts created on breaking down various industries accounting firms work with and there are 99 groups broken down.  Therefore, this will be the main task for us to work on for finishing up the project.

Reflection

So far, working with Professor Reidenbach has been a great opportunity for me to get the initial exposure of research in auditing. This study provides additional insight into the way that the auditor industry specialization construct works in practice. It also has shown me an interesting insight into whether the way audit firms structure their industry leadership and their market share are related. There is definitely more depth we could research further for the topic, which we will continue working on.

Blog 2

The purpose of our research is evaluating whether an industry leaders’ office location is associated with changes in audit pricing. Our main focus is the Big Four accounting firms: Deloitte, KPMG, PwC and EY. I collected the following data from these four firms: office locations, industries served, services provided, the individuals leading each respective industry, and these leaders’ office locations. The most challenging step from collecting this set of data is determining the names of the industry leaders within each firm since they are not available within a database and are not always easily located on the audit firms’ websites. Professor Reidenbach and I then used the Wharton Research Data Services (WRDS) and picked the audit analytics dataset to collect audit pricing/fee and audit opinion data using excel format and SAS Windows_32 dataset format. Professor Reidenbach used the software application and the sets of data we have collected to come up with results for our study.

We defined the major controlled variables for the regression analysis that Professor Reidenbach performed. The controlled variables are Log of Total Assets, Ratio of Long Term Debt over Total Assets, Ratio of EBIT over Total Assets, Qualified Audit Opinion, Inventory Record, Joint Leader (City and Nation), National Leader, City Leader, Leader CBSA (which means that the client company’s headquarter location is the same as the industry leaders’ offices) and groups of industries such as Oil and Gas, Retail and Utilities that we believe will have an impact on the result. We performed a two-tailed t test and used 0.05 as the significance level. For one of the most important controlled variables, Leader CBSA, we got the p-value as 0.2687, which is way greater than 0.05. This leads us to conclude that there is no association between industry leaders’ office locations and audit fee even when the office locations are headquarter locations. After discussing with Professor Reidenbach, we believe that one possible cause is missing data for certain industries. This will be the main task for us to work on before finishing up the project.

The key information I have learnt so far is all the technical terms within the accounting industry and the coding system that experts created on breaking down various industries accounting firms work with. The system is called Standard Industry Code (SIC) and there are 99 groups broken down. It is also a major system that Professor Reidenbach used to pick out the industry data used to run the regression analysis.

Currently, the major exciting task for us is to gather a more precise set of data and to rerun the regression analysis to explore the final results for the final report I am going to post.

Blog 1 – Beginning of our Auditing Research

The title of our research is Audit Firm Industry Leader Location and Its Effect on Audit Fees and Quality. Our main goal of the project is to determine whether there is an association between the geographic location of an auditing firm’s industry leader and the audit fee and audit quality of that same auditing firm’s industry clients. Meanwhile, this is a great opportunity for me to get the initial exposure of research in auditing. We believe that this study would provide additional insight into the way that the auditor industry specialization construct works in practice. It also would provide an interesting insight into whether the way audit firms structure their industry leadership and their market share are related. Eventually, Professor Reidenbach and I would hope to present our results at the American Accounting Association’s Faculty-Student Collaborations in Accounting Conference in Chicago next summer.

Currently, I am focusing on collecting data from the top 10 accounting firms, such as national office locations, industry leaders and industry audit, tax and advisory services leaders. As we move further for the project, I am going to use Wharton Research Data Services (WRDS) to collect archival audit pricing, audit quality, financial data and analyze the factors influence industry audit fees and quality in national locations. I would like to find out all the influences drive the fluctuation of audit fees and qualities in different locations from studying this project.