Fast, "Robust", and Approximately Correct: Estimating Mixed Demand Systems

B. Salanié, F. Wolak
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引用次数: 10

Abstract

Many econometric models used in applied work integrate over unobserved heterogeneity. We show that a class of these models that includes many random coefficients demand systems can be approximated by a "small-sigma" expansion that yields a straightforward 2SLS estimator. We study in detail the models of market shares popular in empirical IO ("macro BLP"). Our estimator is only approximately correct, but it performs very well in practice. It is extremely fast and easy to implement, and it accommodates to misspecifications in the higher moments of the distribution of the random coefficients. At the very least, it provides excellent starting values for more commonly used estimators of these models.
快速、“稳健”和近似正确:估计混合需求系统
在实际工作中使用的许多计量经济模型都包含了未观察到的异质性。我们证明了一类包含许多随机系数需求系统的模型可以通过“小西格玛”展开来近似,从而产生一个直接的2SLS估计量。我们详细研究了实证IO中流行的市场份额模型(“宏观BLP”)。我们的估计只是近似正确的,但在实践中表现得很好。它是非常快速和容易实现的,并且它适应在随机系数分布的高矩处的错误规范。至少,它为这些模型的更常用的估计器提供了很好的起始值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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