摘要翻译：
可计算一般均衡模型的不确定性和鲁棒性可以通过进行系统的灵敏度分析来评估。文献中对CGE模型的SSA采用了不同的方法，如高斯求积法和蒙特卡罗法。本文利用基于Halton和Sobol'序列的拟随机蒙特卡罗方法，提高了常规蒙特卡罗SSA的效率，从而减少了SSA的计算量。结果表明，通过使用低差异序列，可以显著减少常规MC SSA方法所需的模拟次数，从而降低CGE模型SSA所需的计算时间。
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英文标题：
《Quasi-random Monte Carlo application in CGE systematic sensitivity
  analysis》
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作者：
Theodoros Chatzivasileiadis
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最新提交年份：
2017
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分类信息：

一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
  The uncertainty and robustness of Computable General Equilibrium models can be assessed by conducting a Systematic Sensitivity Analysis. Different methods have been used in the literature for SSA of CGE models such as Gaussian Quadrature and Monte Carlo methods. This paper explores the use of Quasi-random Monte Carlo methods based on the Halton and Sobol' sequences as means to improve the efficiency over regular Monte Carlo SSA, thus reducing the computational requirements of the SSA. The findings suggest that by using low-discrepancy sequences, the number of simulations required by the regular MC SSA methods can be notably reduced, hence lowering the computational time required for SSA of CGE models.
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PDF链接：
https://arxiv.org/pdf/1709.09755