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文章基本信息

  • 标题:Optimal Dynamic Nonlinear Income Taxation under Loose Commitment
  • 作者:Jang-Ting Guo ; Alan Krause
  • 期刊名称:Discussion Papers in Economics / Department of Economics, University of York
  • 出版年度:2010
  • 卷号:2010
  • 出版社:University of York
  • 摘要:This paper examines an infinite-horizon model of dynamic nonlinear income taxation in which there exists a small probability that the government cannot commit to its future tax policy. In this "loose commitment" environment, we find that even a little uncertainty over whether the government can commit yields substantial effects on the optimal dynamic nonlinear income tax system. Under an empirically plausible parameterization, numerical simulations show that high-skill individuals must be subsidized in the short run, despite the government's redistributive objective, unless the probability of commitment is higher than 98%. Loose commitment also reverses the short-run welfare effects of changes in most model parameters. In particular, all individuals are worse-off, rather than better-off, in the short run when the proportion of high-skill individuals in the economy increases. Finally, our main findings remain qualitatively robust to a setting in which loose commitment is modelled as a Markov switching process.
  • 关键词:Dynamic Income Taxation; Loose Commitment
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