Pooling Multiple Case Studies Using Synthetic Controls: An Application to Minimum Wage Policies

Posted: 6 Apr 2015

See all articles by Arindrajit Dube

Arindrajit Dube

University of California, Berkeley - Institute for Research on Labor and Employment

Ben Zipperer

University of Massachusetts Amherst

Abstract

We propose a simple, distribution-free method for pooling synthetic control case studies using the mean percentile rank. We also test for heterogeneous treatment effects using the distribution of estimated ranks, which has a known form. We propose a cross-validation based procedure for model selection. Using 29 cases of state minimum wage increases between 1979 and 2013, we find a sizable, positive and statistically significant effect on the average teen wage. We do detect heterogeneity in the wage elasticities, consistent with differential bites in the policy. In contrast, the employment estimates suggest a small constant effect not distinguishable from zero.

Keywords: synthetic controls, program evaluation, heterogeneous treatment effects, minimum wage

JEL Classification: J38, J23, J88

Suggested Citation

Dube, Arindrajit and Zipperer, Ben, Pooling Multiple Case Studies Using Synthetic Controls: An Application to Minimum Wage Policies. IZA Discussion Paper No. 8944. Available at SSRN: https://ssrn.com/abstract=2589786

Arindrajit Dube (Contact Author)

University of California, Berkeley - Institute for Research on Labor and Employment ( email )

2521 Channing Way #5555
Berkeley, CA 94720
United States
510-642-9951 (Phone)

HOME PAGE: http://www.irle.berkeley.edu/cwed/dube.html

Ben Zipperer

University of Massachusetts Amherst ( email )

Department of Operations and Information Managemen
Amherst, MA 01003
United States

Register to save articles to
your library

Register

Paper statistics

Downloads
222
Abstract Views
907
rank
138,606
PlumX Metrics