Andrew Chamberlain heads up a research program that provides surprising perspective on everything from the best-paid jobs in America to how millennials think about the gender gap at work.
— The Ladders

Research

My research focuses on the intersection of technology, data science, and economics. I use tools from econometrics and machine learning to develop behavioral insights from online data.

Below are a few examples of my recent projects.


 
 
 

Incentives Can Reduce Bias in Online Reviews

This NBER working paper using online data from a major tech platform presents experimental and observational evidence about how offering simple economic incentives to users can help correct well-known “polarization bias” in online reviews. 


 

Why Do Workers Quit? The Factors That Predict Employee Turnover

This private-sector study uses data on more than 5,000 real-world job transitions from online resumes to study the factors that statistically predict whether an employee will stay or leave their current employer when moving to the next role in their career path.


 

Metro Movers: Where Are Americans Moving for Jobs, And Is It Worth It?

This private-sector study uses big data on more than 668,000 online job applications from a major tech platform to illustrate recent trends in work-related geographic migration among the 40 biggest metro areas in the U.S. 


 

How to Analyze Your Gender Pay Gap: An Employer’s Guide

This guide and sample code provides a technical step-by-step guide in R for how to analyze company gender and other pay gaps. Provided to encourage human resources practitioners to apply rigorous econometric methods to detect pay anomalies company payroll data.


 

Are State Workers Overpaid? Survey Evidence from Liquor Privatization in Washington State

This academic study presents econometric evidence on the causal effect of a 2012 privatization of liquor retailing in Washington State on the wages and benefits of workers who were displaced by the policy. It’s based on an original field survey of impacted workers I administered in cooperation with a local labor union.