Doctoral Dissertation Research in Economics: The Economic and Behavioral Effects of a Value Added Tax: Evidence from Firm-level Data

Tulane University, New Orleans LA

Investigators

Abstract

The Value-Added Tax (VAT) is a tax on consumption. It is one of the youngest yet among the most important sources of government revenue. The VAT was first introduced in 1967 in Brazil and Denmark and by 2013 more than 160 countries had adopted it. One of the key reasons for the rapid adoption of the VAT is that it is believed to be an efficient tax instrument. That is, a VAT does not create distortions in firms' production decisions, implying that government can raise revenue with minimum cost and without impeding economic growth. A key weakness of this prediction is that it is based on an environment with perfect tax compliance and perfect tax enforcement, which is often violated in practice. Thus, whether the VAT is an efficient tax system is ultimately an empirical question. There is, however, surprisingly little evidence evaluating these efficiency properties of a VAT. This proposed research uses a commercial database that contains information on millions of firms for up to 10 years, to estimate the causal impact of a VAT on firm' growth (e.g, output, employment, investment spending, and productivity) and firms' behavioral responses (e.g, under-reporting of the revenue or over-reporting of the cost to claim undue tax credit). Randomized experiments are considered the gold standard in studying the effect of a treatment. However, due to ethical or economic reasons, most of the social and economic policies (including a VAT) are not implemented randomly. The PI uses Regression Discontinuity Designs (RDD) to create the conditions for a local random experiment by exploiting behavior around a registration threshold imposed by law. This research makes several contributions. It analyzes the effects of a VAT by exploiting a VAT rule that creates the conditions for a local random experiment. Second, most of the previous studies on the effects of a VAT use aggregate data that often mask great deal of variability. Isolating causality using aggregate data is difficult due to many omitted variables that can affect growth. The PI uses rich micro data that allow establishment of a tighter link between a VAT and relevant outcomes. Third, there is a voluminous literature on firms? behavioral responses to direct taxation such as the corporate income tax. However, the literature on firms? behavioral responses to the indirect taxation such as a VAT is small. This study contributes to this small but important literature. Finally, at present, the full impact of a VAT is poorly understood. The results from this study will provide insights on how to improve the administration, enforcement, and ultimately the effectiveness of a VAT system.