Computational Codes for Optimal Ramsey Taxation with Endogenous Risk Aversion

In this data article, we provide computational codes to solve for optimal Ramsey taxation with conventional and endogenous risk aversion formulations under neoclassical growth model environments, as proposed by Ateşağaoğlu and Torul (2018). Specifically, we provide Dynare codes both for the primal and the dual approach Ramsey solutions, and we do so for two different parameter sets featuring either convex or linear disutility preferences over labor supply. Reference Ateşağaoğlu, OE., and Torul O. Optimal Ramsey taxation with endogenous risk aversion, Economics Letters, in press

本数据论文提供了可按照Ateşağaoğlu与Torul（2018）提出的方法，在新古典增长模型框架下求解常规与内生风险厌恶（endogenous risk aversion）设定下最优拉姆齐税收的计算代码。具体而言，本文针对拉姆齐问题的原问题法与对偶问题法均提供了Dynare代码，并针对两组不同的参数设定完成上述代码实现——这两组参数分别对应劳动供给负效用偏好为凸性与线性形式的场景。
参考文献：Ateşağaoğlu, OE., Torul O. 带有内生风险厌恶的最优拉姆齐税收，《经济学通讯》，即将刊出