Siddhartha Chib
;
Liana Jacobi

bayesian fuzzy regression discontinuity analysis and returns to compulsory schooling (replication data)

This paper is concerned with the use of a Bayesian approach to fuzzy regression discontinuity (RD) designs for understanding the returns to education. The discussion is motivated by the change in government policy in the UK in April of 1947, when the minimum school leaving age was raised from 14 to 15?a change that had a discontinuous impact on the probability of leaving school at age 14 for cohorts who turned 14 around the time of the policy change. We develop a Bayesian fuzzy RD framework that allows us to take advantage of this discontinuity to calculate the effect of an additional year of education on subsequent log earnings for the (latent) class of subjects that complied with the policy change. We illustrate this approach with a new dataset composed from the UK General Household Surveys.

Data and Resources

Suggested Citation

Chib, Siddhartha; Jacobi, Liana (2016): Bayesian Fuzzy Regression Discontinuity Analysis and Returns to Compulsory Schooling (replication data). Version: 1. Journal of Applied Econometrics. Dataset. http://dx.doi.org/10.15456/jae.2022326.0659211091