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Analysis of the Decisive Factors of the VAT Gap

Author

Listed:
  • Radu CIOBANU

    (Bucharest University of Economic Studies)

  • Adriana Florina POPA

    (Bucharest University of Economic Studies)

  • Daniela-Nicoleta SAHLIAN

    (Bucharest University of Economic Studies)

Abstract

This paper aims to identify the possible factors that influence the value added tax gap – the VAT gap. The VAT gap is an estimate of the unpaid VAT in the economy, calculated as the difference between the theoretical obligation for the value added tax that can be collected in respect with all the transactions in the economy and the actual VAT paid to the state budget. A high value of this indicator may highlight issues related to tax evasion and the inefficiency of the tax system. The article summarizes existing studies that quantify the VAT gap and aims to identify the relationship between the VAT gap or the VAT revenues and various economic, fiscal and social factors present in EU member countries. The panel regression and clustered regression models have been used in this paper in order to determine the statistically significant variables that have an impact on the VAT gap.

Suggested Citation

  • Radu CIOBANU & Adriana Florina POPA & Daniela-Nicoleta SAHLIAN, 2022. "Analysis of the Decisive Factors of the VAT Gap," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), vol. 3(10), pages 34-41, October.
    • Handle: RePEc:ahd:journl:v:3:y:2022:i:10:p:34-41
    DOI: 10.37945/cbr.2022.10.05
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    More about this item

    Keywords

    VAT; VAT gap; collection deficits; tax fraud; tax evasion;
    All these keywords.

    JEL classification:

    • F15 - International Economics - - Trade - - - Economic Integration
    • H21 - Public Economics - - Taxation, Subsidies, and Revenue - - - Efficiency; Optimal Taxation
    • H22 - Public Economics - - Taxation, Subsidies, and Revenue - - - Incidence
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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