On the Informativeness of Descriptive Statistics for Structural Estimates

Bravo Working Paper # 2020-006

54 Pages Posted: 24 Feb 2020

See all articles by Isaiah Andrews

Isaiah Andrews

Harvard Society of Fellows

Matthew Gentzkow

Stanford University

Jesse M. Shapiro

Harvard University - Department of Economics; National Bureau of Economic Research (NBER)

Multiple version iconThere are 2 versions of this paper

Date Written: October 1, 2019

Abstract

We propose a way to formalize the relationship between descriptive analysis and structural estimation. A researcher reports an estimate ĉ of a structural quantity of interest c that is valid under some model. The researcher also reports descriptive statistics ˆγ that estimate features γ of the distribution of the data, and highlights the economic relationship between γ and c under the model. We compare the bound on the absolute bias of ĉ across all models in a local neighborhood of the assumed model with the bound across a subset of these models under which the assumed relationship between γ and c is correct. Our main result shows that the ratio of these tight bounds depends only on a quantity we call the informativeness of ˆγ for ĉ. 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.

Suggested Citation

Andrews, Isaiah and Gentzkow, Matthew and Shapiro, Jesse M., On the Informativeness of Descriptive Statistics for Structural Estimates (October 1, 2019). Bravo Working Paper # 2020-006 , Available at SSRN: https://ssrn.com/abstract=3527041 or http://dx.doi.org/10.2139/ssrn.3527041

Isaiah Andrews

Harvard Society of Fellows ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

Matthew Gentzkow

Stanford University ( email )

Jesse M. Shapiro (Contact Author)

Harvard University - Department of Economics ( email )

Littauer Center
Cambridge, MA 02138
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
31
Abstract Views
456
PlumX Metrics