Binscatter Regressions

Event Date: 

Wednesday, May 15, 2024 - 3:30pm to 4:30pm

Event Date Details: 

Wednesday May 15, 2024

Event Location: 

  • HSSB 1174

Event Price: 


Event Contact: 

Max Farrell 


Associate Professor of Economics 

Mellichamp Chair of Mind and Machine Intelligence

  • Department Seminar

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.


Paper Link: