On Binscatter
This addresses methodological flaws in a popular econometric visualization tool, improving reliability for researchers in economics and related fields.
The authors formally analyzed the binscatter method for visualizing bivariate relationships, developed enhanced tools with optimal binning and uncertainty quantification, and identified a methodological issue in covariate adjustment that can lead to incorrect conclusions. They applied this to two cases, finding substantially different results compared to prior informal methods.
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.