印度特殊类别邦税收工作的效率分析:来自随机前沿模型的证据

Mohd Yousuf Malik, Kulsoom Raza, Samia Ansari
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摘要

本文探讨了被国家发展委员会授予特殊类别地位的印度主要山区邦的税收工作。这些邦一直面临预算压力,部分依赖于 "援助 "赠款和其他中央转移支付形式的中央资金。本文采用随机前沿分析(SFA)模型来评估特殊类州的 "税收努力"。模型结果表明,"税收努力 "随着第二产业比重、收入支出和道路基础设施的增加而上升。此外,债务水平降低了 "税收努力",而引入 FRBM 和商品及服务税制度(GST)则提高了自身税收动员的效率。根据约翰-德鲁(JLMS)方法计算的税收努力指数,本研究还表明,阿萨姆邦、北阿坎德邦、查谟和克什米尔邦的税收努力得分远高于东北部特殊类别邦。JEL Codes:H2, H21, H22, H71
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Inefficiency Analysis of Tax Efforts in Special Category States of India: Evidence from a Stochastic Frontier Model
The current article examines the tax efforts of India’s main mountainous states that have been accorded special category status by the National Development Council. These states have been under persistent budgetary pressure and are partially reliant on central funds in the form of grants in ‘aid’ and other central transfers. The present article employs the Stochastic Frontier Analysis (SFA) model to assess ‘tax effort’ of special category states. The model results implied that ‘tax effort’ rises with increase in the share of secondary sector, revenue expenditure and road infrastructure. Further, the level of debt lowers ‘tax effort’, whereas the introduction of FRBM and Goods and Service Tax Regime (GST) has raised the inefficiency in own tax mobilization. On the basis of tax effort index, computed through John Drew (JLMS) methodology, this study also indicates that Assam, Uttarakhand, and Jammu and Kashmir are in a far better position in tax efforts score compared to the north eastern special category states. JEL Codes: H2, H21, H22, H71
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