Optimal commodity taxation – a new computational procedure with application to India

Amita Majumder, Ranjan Ray and Sattwik Santra

Indian Growth and Development Review, 2022, vol. 15, issue 1, 123-138

Abstract: Purpose - This paper aims to illustrate the usefulness of the proposed procedure to evaluate the Goods and Services Tax (GST) in India by applying it to provide evidence on optimal commodity tax rates. Design/methodology/approach - In the optimal commodity tax literature, the commonly used Ramsey–Samuelson–Diamond–Mirrlees framework assumes invariance of budget allocation between pre- and posttax regimes and uses only the first-order conditions in the two-stage optimization procedure. This paper proposes an iterative method that overcomes the above limitations in obtaining the optimal tax rates. Findings - It is found that the optimal commodity taxes are highly sensitive to the procedure used to estimate them. The resulting tax rates turn out to be close to the GST tax slabs. The results also show that on both absolute and relative measures, for all the selected states considered here and for All-India, the optimal tax systems are progressive for two chosen values of the inequality aversion parameter. Originality/value - There is a very limited literature on the computational methodology to calculate optimal commodity taxes, and consequently, the evidence is quite scarce as well. In combining contributions to the computation of optimal taxes with empirical evidence, this paper fills a significant gap in the literature. The context of India gives it added value since the GST has recently been introduced in India, and to the best of the authors’ knowledge, this is one of the first attempts at evaluating the Indian GST through the spectacles of optimal taxes.

Keywords: GST; Iterative computational procedure; Optimal commodity taxes; Ramsey–Diamond and Mirrlees framework; Tax progressivity (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eme:igdrpp:igdr-07-2021-0093

DOI: 10.1108/IGDR-07-2021-0093

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