Powered by OpenAIRE graph
Found an issue? Give us feedback
addClaim

Predicting Tax Reform

Authors: Hassett, Kevin A.; Mathur, Aparna;

Predicting Tax Reform

Abstract

Despite the frequency of tax changes and their potential importance to investors, there has been relatively little modeling of anticipated tax changes. Yet whether future tax reforms are predictable or not will have an enormous effect on estimates of the impact of current tax policies. This paper develops a probit model for predicting tax reforms. We find that the likelihood that a country will lower its corporate tax rate in the future is significantly affected by what we describe as “learning” and “strategic” factors. The learning comes from a country’s own experience with tax rate reductions. Hence a country is more likely to lower rates if it has lowered rates in the past and seen an economic benefit from such actions. At the same time, countries respond strategically to tax rates in competing countries. They are more likely to lower rates if their rates are higher than the average for their neighbor countries. Hence countries do appear to engage in tax competition. Our model performs well, with an in-sample and out-of-sample accuracy of close to 85 percent. We conclude that empirical investment research should account for the fact that future tax changes are highly predictable.

Related Organizations
Keywords

H, ddc:330, tax reform

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    1
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!