Labor Economics Analysis
Econometric analysis of 69K+ Census records quantifying the marginal return to work hours using log-linear regression.
The Problem
Earnings & Work Hours
Policymakers need reliable estimates of how work hours affect earnings to inform labor regulations. The challenge was isolating this relationship from confounding factors in large-scale survey data.
The Approach
Econometric Regression
Analyzed 69K+ employed workers from 2023 CPS ASEC Census data. Compared linear, log-linear, and polynomial regression specifications with robust standard errors (HC1). Applied log transformation to address income skewness and improve model fit.
Technologies & Methods
The Results
5.6% Marginal Return
Log-linear model (R²=0.307) showed each additional hour increases earnings by 5.6%, outperforming linear and polynomial specifications. Residual diagnostics confirmed model validity for policy-relevant interpretation using nationally representative Census data.