USING MIMIC MODELS TO EXAMINE DETERMINANTS OF VAT GAP IN LITHUANIA Cover Image

USING MIMIC MODELS TO EXAMINE DETERMINANTS OF VAT GAP IN LITHUANIA
USING MIMIC MODELS TO EXAMINE DETERMINANTS OF VAT GAP IN LITHUANIA

Author(s): Gindra Kasnauskienė, Jolita Krimisieraitė
Subject(s): Economy, National Economy, Business Economy / Management, EU-Accession / EU-DEvelopment
Published by: Vilniaus Universiteto Leidykla
Keywords: VAT gap; VAT revenue; tax evasion; MIMIC;

Summary/Abstract: In recent years analysis of economic loss attributed to different aspects of shadow economy has attracted much attention of both academics and policy makers. Recent statistical data shows that new member states have on average a 9 percent higher VAT gap than the older members of the European Union. Knowing that economies of emerging markets rely on the VAT for a substantially higher percentage of their government revenues, it is very important to understand the determinants limiting revenue mobilization in those countries. In Lithuania, the VAT gap increased dramatically after the crisis of 2008 , and now is one of the largest in the EU. However, few studies have empirically tested some hypotheses about the VAT as a revenue-raising instrument in the country. The purpose of this study is to identify the determinants significantly influencing the size of the VAT gap in Lithuania using the MIMIC method for quarterly data of the period 2000-2013. The applied MIMIC model indicated that two factors (General government consumption expenditure and inflation) have a statistically significant impact on the VAT gap in the long-run. The results of the eMIMIC model show that two determinants (inflation and household deposits) have a statistically significant influence on the gap in the short-run. The authors believe that the key findings of the study can be used as one of the supporting tools in adjusting Lithuanian pro-growth tax policy and improving administration of VAT taxes.

  • Issue Year: 6/2015
  • Issue No: 11
  • Page Range: 107-126
  • Page Count: 20
  • Language: English