A study of profit shifting using the Hines and Rice approach

TTPI Working Paper 12/2021

Authors: Alfred Tran & Wanmeng Xu (ANU Research School of Accounting)

Adopting and modifying the approach used by Hines and Rice (1994), we investigate the extent of cross border profit shifting activities by foreign-owned Australian companies (FOACs) and evaluate the effectiveness of the measures implemented by the Australian government to combat base erosion and profit shifting (BEPS) by multinational enterprises (MNEs). Specifically, we measure the sensitivity of profit before tax reported in Australia by FOACs to the tax rate differentials between Australia and other countries where the related foreign-based MNE groups operate and examine whether such sensitivity decreases after the implementation of BEPS countermeasures. Overall, we find that profit shifting from Australia to low-tax countries took place throughout the 14-year study period, 2007 to 2020. The higher the Australian corporate tax rate relative to the tax rates of immediate parent entity, ultimate parent entity, and the higher the ranking of Australian tax rate relative to those of other countries where the foreign MNEs operate, the lower is the profit reported in Australia. In general, cross border profit shifting from Australia to low-tax countries has not reduced in the post-BEPS period from 2013 to 2020 after the launch of the BEPS Project by the OECD and the implementation of BEPS countermeasures in Australia, although there is some evidence from breaking down the post-BEPS period by years which shows that profit shifting might have reduced in the year 2019. Such reduction, however, does not sustain in 2020.

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The ATO Longitudinal Information Files (ALife): Individuals – A new dataset for public policy research

TTPI Working Paper 13/2021

Authors: Thomas Abhayaratna, Andrew Carter and Shane Johnson

The Australian Taxation Office Longitudinal Information Files: Individuals (ALife: Individuals), is one of the most comprehensive tax administrative datasets in the world. The ALife: Individuals dataset, which currently covers the period 1990-91 to 2017-18, is based on a 10 per cent longitudinal sample of administrative unit-record personal income tax data. This new, high quality, longitudinal, de-identified, research-ready dataset is available to approved researchers through secure environments that safeguard taxpayers’ information. The availability of ALife: Individuals opens exciting new possibilities for public policy research and evaluation that will improve understanding of taxpayer behavior and support policy development and its administration.

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