The growing emphasis on nation-states and their pivotal role in economic development has emerged as a central theme in contemporary economic discourse. This review examines the concept of state capacity as discussed in the economic literature, focusing on its practical implications. While the definition of state capacity remains multifaceted, this analysis delves into its economic implications. We focus primarily on the literature surrounding fiscal capacity, exploring how a state’s ability to raise and manage revenue impacts economic development and other critical economic outcomes. This review aims to shed light on the crucial role of fiscal capacity in shaping economic performance, inspiring further research and policy development in this area. (JEL codes: D72, D73, D74, E62, H11, H20, H77, and H83)
Most tax administrations have struggled with tax under-reporting, which has cost them greatly financially and hampered economic growth overall. For most countries, value-added tax (VAT) is the main source of domestic revenue. VAT is the major contributor to total tax revenue in Rwanda, so even a small increase in its collection can raise overall significant revenue. Researchers have attempted to address the issue of under-reporting using various techniques. The purpose of this paper is to use machine learning models to detect and predict the VAT under-reporting in Rwanda. Several evaluation criteria are used to compare different supervised machine learning models. A number of factors are shown to be more influential on VAT under-reporting than others, including cross-border businesses, taxpayers with fewer years of experience, and taxpayers in sectors such as wholesale and retail trade as well as construction. Leveraging such approaches can increase revenue mobilization as tax administrations will have a quick and innovative method of predicting VAT under-reporting in advance and identify high-risk cases for audit.
This study is significant as it explores whether firm heterogeneity with non-tradable goods and financial integration contributes to better international risk-sharing. We construct a dynamic stochastic general equilibrium framework to examine the impact of wealth effects on international risk-sharing. Our findings reveal that the wealth effect is another crucial factor for the limited risk-sharing observed in response to a positive idiosyncratic shock affecting heterogeneous firms, despite the non-tradable goods sector and incomplete financial market being the primary reasons for limited risk-sharing between the two countries. We further investigate the implication of wealth effects for international risk-sharing and demonstrate that financial frictions across borders impede the spillover of wealth effects from the home country to the foreign country, resulting in decreased risk-sharing (the consumption co-movement across countries is low). The impact of wealth effects will be weakened if domestic households prefer to consume more non-tradable or home-produced goods, leading to lower risk-sharing.
The collection of value added tax (VAT) is essential for achieving domestic revenue objectives, yet VAT gap estimation is rarely performed in developing countries. This study utilizes innovative tax declaration and audit data to estimate VAT misreporting in Tanzania, applying a machine learning approach to predict evasion in unaudited firms and periods. We measure the underreporting component of the compliance gap, quantifying potential revenue losses due to inaccurate reporting. Our findings indicate that firms often avoid excessive audits, leading to increased evasion, with those firms showing the largest VAT gaps. We estimate a 62% VAT gap among small and medium-sized enterprises in Tanzania. Finally, we present a cost-benefit ratio, suggesting that while auditing sectors with large VAT gaps is cost-effective, those contributing significantly to the overall VAT gap should also be prioritized for revenue generation. (JEL codes: H25, H26, and H32)
