On the Informativeness of Descriptive Statistics for Structural Estimates
Isaiah Andrews, Matthew Gentzkow, Jesse M. Shapiro
Econometrica · 2020 · Volume 88 · Issue 6
Abstract
We propose a way to formalize the relationship between descriptive analysis and structural estimation. A researcher reports an estimateĉof a structural quantity of interestcthat is exactly or asymptotically unbiased under some base model. The researcher also reports descriptive statisticsthat estimate featuresγof the distribution of the data that are related tocunder the base model. A reader entertains a less restrictive model that is local to the base model, under which the estimateĉmay be biased. We study the reduction in worst-case bias from a restriction that requires the reader's model to respect the relationship betweencandγspecified by the base model. Our main result shows that the proportional reduction in worst-case bias depends only on a quantity we call theinformativenessofforĉ. Informativeness can be easily estimated even for complex models. We recommend that researchers report estimated informativeness alongside their descriptive analyses, and we illustrate with applications to three recent papers.
Keywords
Local misspecification, transparency
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