In this talk, we propose a way to broker the evaluation of public policies. Educational researchers, psychometricians or statisticians become honest brokers when they clarify all policy options and their associated uncertainties. In the context of public policy evaluation, we argue that a partial identification analysis is a way to make explicit different non-testable assumptions. Each of these assumptions combined with observational evidence will provide different policy recommendations. These recommendations imply different volitional attitudes of the policy maker, which can be considered as the final position of scientific research in the sense of Neyman, that is, the inductive behavior. In this context covariates are no longer viewed as controls, but as contexts in which the policy eventually works. In passing, it is shown that the ignorability conditions typically used in the evaluation of public policies are logically strong but incredible. (This is joint work with Trinidad González-Larrondo.)
about the speaker
Ernesto San Martín is Full Professor at the Faculty of Mathematics, Pontificia Universidad Católica de Chile and Invited Professor at the Economics School of Louvain, Université Catholique de Louvain, Belgium. His research interests focus on the statistical modeling of social phenomena, particularly in education. Examples of his research are the following: identification problems in psychometric model construction; school effectiveness and value-added models; credible evaluations of educational public policies; learning spaces and classroom diversity. This research, mainly developed at the Interdisciplinary Laboratory of Social Statistics (LIES), is pursuit through scientific collaborations with psychologists, educational scientists and mathematicians.