Forensic Econometrics: Demand Estimation When Data are Missing

IF 1.5 4区经济学 Q2 ECONOMICS

Japanese Economic Review Pub Date : 2019-08-16 DOI:10.1111/jere.12242

Julian Hidalgo, Michelle Sovinsky

引用次数: 0

Abstract

Often empirical researchers face many data constraints when estimating models of demand. These constraints can sometimes prevent adequate evaluation of policies. In this article, we discuss two such missing data problems that arise frequently: missing data on prices and missing information on the size of the potential market. We present some ways to overcome these limitations in the context of two recent research projects. Jacobi and Sovinsky (2018), which addresses how to incorporate unobserved price heterogeneity, and Hidalgo and Sovinsky (2018), which focuses on how to use modelling techniques to estimate missing market size. Our aim is to provide a starting point for thinking about ways to overcome common data issues.

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司法计量经济学:数据缺失时的需求估计

经验研究人员在估计需求模型时往往面临许多数据约束。这些限制有时会妨碍对政策进行充分的评估。在本文中，我们将讨论两个经常出现的数据缺失问题:价格数据缺失和潜在市场规模信息缺失。在最近的两个研究项目中，我们提出了一些克服这些限制的方法。Jacobi和Sovinsky(2018)解决了如何纳入未观察到的价格异质性，Hidalgo和Sovinsky(2018)关注的是如何使用建模技术来估计缺失的市场规模。我们的目标是为思考克服常见数据问题的方法提供一个起点。

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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来源期刊

Japanese Economic Review ECONOMICS-

CiteScore

2.70

自引率

0.00%

发文量

期刊介绍： Started in 1950 by a group of leading Japanese economists under the title The Economic Studies Quarterly, the journal became the official publication of the Japanese Economic Association in 1959. As its successor, The Japanese Economic Review has become the Japanese counterpart of The American Economic Review, publishing substantial economic analysis of the highest quality across the whole field of economics from researchers both within and outside Japan. It also welcomes innovative and thought-provoking contributions with strong relevance to real economic issues, whether political, theoretical or policy-oriented.