Challenges in Assessing Effective Company Tax Rates
Carol Anne Matchett
Building: Holme Building
Room: Cullen Room
Date: 2016-07-20 03:30 PM – 05:00 PM
Last modified: 2016-07-01
Abstract
This presentation is based on research, still in progress, that is designed to identify if large public companies pay less tax than smaller companies in Australia. The extant literature has identified the relationships between company size and effective tax rates with varying degrees of consistency. We consider that large companies in industries with high levels of political power, while affected by political costs, may still pay relatively less tax as they increase in size. We test this hypothesis by using the raw data on companies listed in the Australian Stock Exchange from Thomas Reuters DataStream and extracted relevant information from these companies’ annual reports for the financial year ending 2000 to 2012.
Challenges have occurred during the data collection and collation component of the research. First, we are unable to include companies with net operating losses in the analysis because econometric analyses do not permit negative logs i.e. positive size and negative income. Second, existing data is focused on financial analysis of individual companies for commercial use which limits the details captured and requires considerable manipulation of publically available data to meet research requirements. This presentation will describe the logic and steps taken to address these aforementioned challenges Data extracted forms part of a Research Masters project and comments from the audience are welcomed.
Challenges have occurred during the data collection and collation component of the research. First, we are unable to include companies with net operating losses in the analysis because econometric analyses do not permit negative logs i.e. positive size and negative income. Second, existing data is focused on financial analysis of individual companies for commercial use which limits the details captured and requires considerable manipulation of publically available data to meet research requirements. This presentation will describe the logic and steps taken to address these aforementioned challenges Data extracted forms part of a Research Masters project and comments from the audience are welcomed.