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摘要翻译：
准蒙特卡罗(qMC)方法是经典蒙特卡罗(MC)积分的有力替代方法。在一定条件下，它们可以以比通常的中心极限定理更快的速度逼近所需的积分，从而得到更精确的估计。本文以Owen(1995)的scramble为重点，在一个基于仿真的估计环境中探索了这些方法。对于横截面和短板，得到的矩量置乱方法简单地用置乱代替随机数发生器（大多数软件都有），以降低仿真噪声。还考虑了置乱间接推理估计。对于时间序列，由于时间维度上的维数诅咒，qMC可能不能直接应用。文中给出了一个简单的算法和一类矩，从而避免了这一问题。给出了每种算法的渐近结果。蒙特卡罗的例子在有限的样本中说明了这些结果，包括一个具有“大量异质性”的收入过程。
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英文标题：
《A Scrambled Method of Moments》
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作者：
Jean-Jacques Forneron
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最新提交年份：
2019
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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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一级分类：Statistics 统计学
二级分类：Methodology 方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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英文摘要：
Quasi-Monte Carlo (qMC) methods are a powerful alternative to classical Monte-Carlo (MC) integration. Under certain conditions, they can approximate the desired integral at a faster rate than the usual Central Limit Theorem, resulting in more accurate estimates. This paper explores these methods in a simulation-based estimation setting with an emphasis on the scramble of Owen (1995). For cross-sections and short-panels, the resulting Scrambled Method of Moments simply replaces the random number generator with the scramble (available in most softwares) to reduce simulation noise. Scrambled Indirect Inference estimation is also considered. For time series, qMC may not apply directly because of a curse of dimensionality on the time dimension. A simple algorithm and a class of moments which circumvent this issue are described. Asymptotic results are given for each algorithm. Monte-Carlo examples illustrate these results in finite samples, including an income process with "lots of heterogeneity."
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PDF链接：
https://arxiv.org/pdf/1911.09128
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