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Estimating and Evaluating Proxies for the Marginal Tax Rate
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Kerry Pattenden
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Abstract
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Graham (1996b) tested proxies for the marginal tax rate and derived a number of
important results. This paper re-examines two factors raised by Graham's work: the
impact of tax regulations on proxy performance, and the presence of bias in proxy
construction. Simulation methods create a simple tax world where the 'true'
marginal tax rate is known. Tax proxies are ranked against this rate using
regression diagnostics. Manzon's proxy is the best performing of the simple tax
proxies tested and is an unbiased estimate of the underlying tax process. The impact
on proxies of tax loss treatments is assessed. Evidence is found that proxies differ
in performance across different loss treatments. Evidence is found of an inbuilt
preference between some variants of a simulated tax proxy and the tax benchmark.
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Download this article.
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Keywords
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TAX RATES; TALOSS TREATMENTS; SIMULATION MODEL.
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Contact Details
Kerry Pattenden
School of Business and Economics
Sydney University
Sydney NSW 2006
E-mail: kpattenden@econ.usyd.edu.au
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This paper is drawn from my PhD dissertation at the University of New
South Wales. I am grateful to Greg Clinch of MBS, Doug Foster, Baljit
Sidhu, Tom Smith and Garry Twite of AGSM, John Graham of Duke University,
and Kim Sawyer of University of Melbourne for comments and suggestions. All
errors and omissions are my own.
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