Stochastic semi-nonparametric frontier approach for tax administration efficiency measure: Evidence from a cross-country study

Trang T.T. Nguyen, Diego Prior and Stefan Van Hemmen

Economic Analysis and Policy, 2020, vol. 66, issue C, 137-153

Abstract: Under globalisation, countries all over the world have been impacted differently by both their macroeconomic conditions and other random factors particular to them. As such, governments and policymakers require a comparison of tax systems across different countries and, consequently, a study on the performance of Tax administration (TA) at a cross-country level would be a necessary reference for governments when designing tax policy. This paper seeks to measure the performance of TA across 44 countries, while considering the presence of contextual variables, using the recently developed and advanced frontier estimators, such as the semi-nonparametric StoNED (Stochastic Nonparametric Envelopment of Data) approach by Johnson and Kuosmanen (2011, 2012) and the conditional order-m (Daraio and Simar, 2005, 2007) approach, for two periods between 2008–2011 and 2012–2015. The results show that Tax agencies in these countries could have increased tax revenue, on average, by about 58.7% and 34.2% for the two periods, respectively. Equivalently, $7,737 and $4,667 PPP (purchasing power parity) per capita of tax revenue could have been increased for the two periods, respectively. It is also suggested, in general, the latter period (2012–2015) shows a higher level of efficiency than the former period (2008–2011), justified by both estimators.

Keywords: Tax administration; Efficiency analysis; Contextual variable; StoNED; Conditional order-m (search for similar items in EconPapers)
JEL-codes: H21 H83 M21 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0313592619305223
Full text for ScienceDirect subscribers only

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:eee:ecanpo:v:66:y:2020:i:c:p:137-153

DOI: 10.1016/j.eap.2020.03.002

Access Statistics for this article

Economic Analysis and Policy is currently edited by Clevo Wilson

More articles in Economic Analysis and Policy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().