发展中国家的税收与经济增长:一种自退分配滞后方法

IF 0.5 Q4 ECONOMICS
M. H. Maganya
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引用次数: 15

摘要

坦桑尼亚与大多数其他发展中国家一样,在努力通过税收实现可持续经济增长和发展方面面临着许多经济挑战。在文献中,关于税收作为促进经济增长和经济发展的工具如何有效的争论仍然没有定论,因为各种研究报告了税收对经济增长的混合影响。本文利用最近开发的自回归分布滞后模型(ARDL)边界检验程序技术,研究了1996年至2019年期间坦桑尼亚税收对经济增长的影响。进行了各种初步检验,包括平稳检验以及成对格兰杰因果关系检验。根据所得结果,国内商品和服务(TGS)税与GDP增长呈正相关,且在1%水平上具有统计学显著性。另一方面,所得税与GDP增长呈负相关,在5%的水平上具有统计学显著性。两两格兰杰因果关系结果表明,TGS与GDP增长之间存在双向格兰杰因果关系,显著性水平为1%。政府应该以扩大、培育和维持税基为目标,进一步积极推动经济增长。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tax revenue and economic growth in developing country: an autoregressive distribution lags approach
Abstract Tanzania, like most other developing countries, faces numerous economic challenges in striving to achieve sustainable economic growth and development through taxation. In the literature, the debate on how effective taxes are as a tool for promoting economic growth and economic development remains inconclusive, as various research have reported mixed effects of tax on economic growth. This article investigates the effect of taxation on economic growth in Tanzania using the recently developed technique of autoregressive distributed lag model (ARDL) bounds testing procedure for the period from 1996 to 2019. Various preliminary tests were conducted including stationary tests as well as the pair-wise Granger causality test. According to the results obtained, domestic goods and services (TGS) taxes are positively related to GDP growth and are statistically significant at 1% level. Income taxes, on the other hand, were found to be negatively related to GDP growth and to be statistically significant at 5% level. The pair-wise Granger causality results indicated that there is bidirectional Granger causality between TGS and GDP growth at 1 % significance level. The government should aim at growing, nurturing and sustaining tax base to positively drive economic growth even further.
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来源期刊
CiteScore
0.60
自引率
0.00%
发文量
9
期刊介绍: The Central European Journal of Economic Modelling and Econometrics (CEJEME) is a quarterly international journal. It aims to publish articles focusing on mathematical or statistical models in economic sciences. Papers covering the application of existing econometric techniques to a wide variety of problems in economics, in particular in macroeconomics and finance are welcome. Advanced empirical studies devoted to modelling and forecasting of Central and Eastern European economies are of particular interest. Any rigorous methods of statistical inference can be used and articles representing Bayesian econometrics are decidedly within the range of the Journal''s interests.
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