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American Economic Review Vol. 114 No. 5 2024

On Binscatter

Matias D. Cattaneo1; Richard K. Crump2; Max H. Farrell3; Yingjie Feng4

1 Department of Operations Research and Financial Engineering, Princeton University (email: ) · 2 Macrofinance Studies, Federal Reserve Bank of New York (email: ) · 3 Department of Economics, UC Santa Barbara (email: ) · 4 School of Economics and Management, Tsinghua University (email: )

Abstract

Binscatter is a popular method for visualizing bivariate relationships and conducting informal specification testing. We study the properties of this method formally and develop enhanced visualization and econometric binscatter tools. These include estimating conditional means with optimal binning and quantifying uncertainty. We also highlight a methodological problem related to covariate adjustment that can yield incorrect conclusions. We revisit two applications using our methodology and find substantially different results relative to those obtained using prior informal binscatter methods. General purpose software in Python, R, and Stata is provided. Our technical work is of independent interest for the nonparametric partition-based estimation literature.

DOI
10.1257/aer.20221576
Volume
114
Issue
5
Pages
1488-1514
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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