Estimating the Elasticity of Taxable Income When Earnings Responses Are Sluggish
Trine Engh Vattø
FinanzArchiv: Public Finance Analysis, 2020, vol. 76, issue 4, 329-369
Abstract:
Estimates of the elasticity of taxable income (ETI) are conventionally obtained by stacking three-year overlapping differences in the estimation. This means that the ETI estimate is an average of first-, second-, and third-year effects. The present paper suggests that if gradual adjustment can be expected, the analyst should consider estimating the ETI by a dynamic panel data model. When Norwegian income tax return data for wage earners over a 14-year period (1995-2008) are used in the estimation, an ETI estimate of 0.15 is obtained from the dynamic specification, compared to 0.11 by the conventional approach. Importantly, the conventional approach fails to produce a long-term elasticity estimate by increasing the time span of each difference.
Keywords: elasticity of taxable income; time frame; tax reform; earnings dynamics (search for similar items in EconPapers)
JEL-codes: H24 H31 J22 (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.mohrsiebeck.com/en/article/estimating- ... h-101628fa-2020-0012
Fulltext access is included for subscribers to the printed version.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:mhr:finarc:urn:doi:10.1628/fa-2020-0012
Ordering information: This journal article can be ordered from
Mohr Siebeck GmbH & Co. KG, P.O.Box 2040, 72010 Tübingen, Germany
DOI: 10.1628/fa-2020-0012
Access Statistics for this article
FinanzArchiv: Public Finance Analysis is currently edited by Alfons Weichenrieder, Ronnie Schöb and Jean-François Tremblay
More articles in FinanzArchiv: Public Finance Analysis from Mohr Siebeck, Tübingen
Bibliographic data for series maintained by Thomas Wolpert ().