Publications

07 Oct 19

Inference for treatment effects of job training on wages: using bounds to compute Fisher’s exact p-value.

Authors: BLANCO German, BIA Michela.

Online First: 07/01/2019

DOI: http://doi.org/10.1080/13504851.2018.1564113

Abstract:

In the context of a training program’s randomized evaluation, where estimating wage effects is of interest, we propose employing bounds that control for sample selection as a model-based statistic to conduct randomization-based inference à la Fisher. Inference is based on a sharp null hypothesis of no treatment effect for anyone. In contrast to conventional inference, Fisher p-values are nonparametric and do not employ large sample approximations.

Reference: BLANCO German, BIA Michela. Inference for treatment effects of job training on wages: using bounds to compute Fisher’s exact p-value. Applied Economics Letters, 2019, vol. 26, n°17, pp. 1424-1428.

Keywords:
Nonparametric bounds,
randomization inference,
sample selection,
training effects