Raw XBRL Provides Greater Insights Than Commercial Data Set in Tax Case Study

Raw XBRL Provides Greater Insights Than Commercial Data Set in Tax Case Study

By Devlekar 27 June, 2022

XBRL US has published an interesting case study, presenting student research on whether big companies are paying their “fair share” of tax. “Controversial questions require the right dataset,” it argues, with access to high quality, timely data enabling students (and others!) to carry out more meaningful analyses.

Students at the University of Mississippi’s Patterson School of Accountancy investigated 55 large companies that paid no tax in 2020, comparing their Effective Tax Rates (ETRs) with those of peers. Initially, they used a commercially available data set. As the case study explains, such data sets are usually ‘normalised’, or structured in accordance with a set of norms set by the data provider. Normalised data often aggregates companies’ reported facts, making it easier to compare multiple companies across a single line item, but reducing specificity and detail – and indeed, the students were unable to determine statistically significant associations between the companies and various economic factors, including ETRs.

To find out more details please visit : https://xbrl.org/