Do SMEs Face a Higher Tax Burden? Evidence from Belgian Tax Return Data

Pieter Buyl and Annelies Roggeman

Prague Economic Papers, 2019, vol. 2019, issue 6, 729-747

Abstract: The public debate on taxation of domestic small and medium enterprises (SMEs) versus large and multinational enterprises (MNEs) is highly relevant nowadays. Using confidential tax return data instead of financial statement data, the results indicate that domestic SMEs face on average a 1.6 and 4.8 percentage-point higher effective tax burden compared to large domestic and large MNEs respectively. This suggests that tax incentives for SMEs are inadequate to compensate for the tax advantages of large and internationally operating companies. Furthermore, we show that the use of information built exclusively upon accounting data could bias the results.

Keywords: corporate tax return data; SMEs; effective tax burden; reduced tax rates (search for similar items in EconPapers)
JEL-codes: F23 H25 H26 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://pep.vse.cz/doi/10.18267/j.pep.719.html (text/html)
http://pep.vse.cz/doi/10.18267/j.pep.719.pdf (application/pdf)
free of charge

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:prg:jnlpep:v:2019:y:2019:i:6:id:719:p:729-747

Ordering information: This journal article can be ordered from
Editorial office Prague Economic Papers, University of Economics, nám. W. Churchilla 4, 130 67 Praha 3, Czech Republic
http://pep.vse.cz

DOI: 10.18267/j.pep.719

Access Statistics for this article

Prague Economic Papers is currently edited by Klára Pavlová

More articles in Prague Economic Papers from Prague University of Economics and Business Contact information at EDIRC.
Bibliographic data for series maintained by Stanislav Vojir ().