{"title":"Determinants of audit fees: Evidence from Compustat database from 2009-2019","authors":"Vusumuzi Malele, M. E. Letsoalo, M. Mafu","doi":"10.23919/fusion49465.2021.9626872","DOIUrl":null,"url":null,"abstract":"The firm’s financial characteristics affecting the audit fees are determined based on the 2099 firms listed on the Compustat database from 2009-2019. A more comprehensive view of this subject is provided by analyzing fundamental financial, statistical, and market information from thousands of companies worldwide based on the database. The best set of predictor variables are identified using descriptive statistics, correlation matrices, and exploratory data analysis. A regression model is built to test and measure the relationship and significance between these predictor variables and audit fees. Notably, results confirm that the firm financial characteristics ACT, INVT, LCT, AT, EBIT, EBITDA, and CEQ determine audit fees. Furthermore, the audit fees are negatively and significantly related to PIFO, FYEAR, EMP, and GVKEY. Previously, studies focused on determinants such as firm size, status of the audit firm, and corporate complexity. Thus, this work integrates an international financial perspective in the determination of audit fees.","PeriodicalId":226850,"journal":{"name":"2021 IEEE 24th International Conference on Information Fusion (FUSION)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 24th International Conference on Information Fusion (FUSION)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/fusion49465.2021.9626872","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The firm’s financial characteristics affecting the audit fees are determined based on the 2099 firms listed on the Compustat database from 2009-2019. A more comprehensive view of this subject is provided by analyzing fundamental financial, statistical, and market information from thousands of companies worldwide based on the database. The best set of predictor variables are identified using descriptive statistics, correlation matrices, and exploratory data analysis. A regression model is built to test and measure the relationship and significance between these predictor variables and audit fees. Notably, results confirm that the firm financial characteristics ACT, INVT, LCT, AT, EBIT, EBITDA, and CEQ determine audit fees. Furthermore, the audit fees are negatively and significantly related to PIFO, FYEAR, EMP, and GVKEY. Previously, studies focused on determinants such as firm size, status of the audit firm, and corporate complexity. Thus, this work integrates an international financial perspective in the determination of audit fees.