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Estimating the Optimal Taxation Rate on Consumer Goods Harmful to Health by Microstimulating in Iran
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Ali asghar Salem *   , Elham Gholami |
| , salem207@yahoo.com |
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Abstract: (1468 Views) |
| Reducing the consumption of goods harmful to human health is one of the government’s policies goals all around the world. One of the control tools in order to reduce the consumption of these goods is to increase their consumption tax rate in order to increase prices resulting less consumption and provide the required financial resources for culturalization, education and consumption control in the society. The purpose of this article is to estimate the optimal taxation rate on the consumption of goods harmful to health in a way that despite increased tax revenues, it would have the least disruptive effects on the household’s welfare. For this purpose, using the almost ideal quadratic demand system based on non-linear seemingly unrelated regressions and the household’s data for 1390 to 1398, the demand for health-damaging goods, has been estimated and relevant price elasticities are calculated. Then, based on the compensating variation as a welfare measure by micro-data (for each sample household) and in various income scenarios, the optimal tax rates have been estimated and analyzed for year 1398, using nonlinear optimization methods. Based on the results and considering that implementing a same tax rate for all good groups are easier and more practical, a tax rate of 31% (including VAT and duties of article 48 of the Law on Accession Some Articles to the Regulatory for Part of Government Financial Regulations Act, 1393) is suggested to apply for all good groups. In this situation, the average welfare reduction for each household is close to 2310 thousand Rials and the amount of tax revenues would be 68,595 billion Rials, based on the information of year 1398. This tax revenue is more than 4 times of the budget law performance in this year. |
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| Keywords: Goods Harmful to Health, Optimal Tax Rate, Quadratic Almost Ideal Demand System, Nonlinear Seemingly Unrelated Regression Method. |
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Full-Text [PDF 754 kb]
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Type of Study: Research |
Subject:
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