Exploring determinants of VAT gaps using structural equation models: a MIMIC approach
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Abstract
This study explores the estimation of the VAT gap using the Multiple Indicators and Multiple Causes (MIMIC) model, a specific type of structural equation model. The VAT gap, a significant indicator of tax revenue loss and inefficiency in VAT collection, is treated as a latent variable driven by various causes and reflected through specific indicators. Drawing on data from European countries, the model incorporates variables such as economic openness, government spending, corruption perceptions, and the e-government development index, each serving as proxies for underlying VAT collection challenges. This study presents a first-time application of the MIMIC model to the Czech Republic, estimating the VAT gap of 2003 – 2020 and revealing fluctuations between 27 % and 35 % of total tax liability, with stabilization at 31 % since 2016. The findings underscore policy areas for potential improvements in VAT compliance and collection efficiency, particularly through enhanced digitalization efforts and governance quality in tax administration by highlighting key factors contributing to the VAT gap.
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