Evaluating the Chile Solidario program: results using the Chile Solidario panel and the administrative databases

This paper presents the results of a three-year evaluation performed on the first cohorts of Chile Solidario, the most important anti-poverty program in Chile. The paper presents a description of the program, emphasizing the mechanism by which people were admitted into the program. We then propose evaluation strategies and discuss their validity. The final evaluation is conducted using a Matching estimator, and we discuss the principles surrounding the potential for this to be a valid evaluation method. The initial results using the Chile Solidario Panel suggest that the program had positive effects on psychosocial welfare and on take-up of subsidies and social programs. However, it is not possible to obtain reliable results due to data shortcomings, particularly the lack of baseline data. In order to solve the problem, we generated a database using six years of administrative data, including around 1,000,000 family records per year. A method for overcoming the treatment substitution problem is discussed and implemented. Results are much more robust than those of the Chile Solidario Panel and show small, but clearly positive effects for several variables, especially the number of workers in the family, the percentage of workers in the famly and the employment of the head of the family.Matching, Extreme poverty, Impact evaluation, Treatment substitution, Administrative data.

A Framework for Open Policy Analysis

The evidence-based policy movement promotes the use of empirical evidence to inform policy decision-making. While several social science disciplines are undergoing a “credibility revolution” focused on openness and replication, policy analysis has yet to systematically embrace transparency and reproducibility. We argue that policy analysis should adopt the open research practices increasingly espoused in related disciplines to advance the credibility of evidence-based policymaking. We first discuss the importance of evidence-based policy in an era of increasing disagreement about facts, analysis, and expertise. We present a novel framework for “open” policy analysis (OPA) and how to achieve it, focusing on examples of recent policy analyses that have incorporated open research practices such as transparent reporting, open data, and code sharing. We conclude with recommendations on how key stakeholders in evidence-based policy can make OPA the norm and thus safeguard trust in using empirical evidence to inform important public policy decisions

Author Correction: A consensus-based transparency checklist.

An amendment to this paper has been published and can be accessed via a link at the top of the paper

A consensus-based transparency checklist

We present a consensus-based checklist to improve and document the transparency of research reports in social and behavioural research. An accompanying online application allows users to complete the form and generate a report that they can submit with their manuscript or post to a public repository

Template for mass data upload to the Social Science Reproduction Platform

This is a template form to upload reproductions meta-data onto the Social Science Reproduction Platform

How Transparency and Reproducibility Can Increase Credibility in Policy Analysis: A Case Study of the Minimum Wage Policy Estimate

The analysis of public policies, even when performed by the best non-partisan agencies, often lacks credibility (Manski, 2013). This allows policy makers to cherrypick between reports, or within a specific report, to select estimates that better match their beliefs. For example, in 2014 the Congressional Budget Office (CBO) produced a report on the effects of raising the minimum wage that was cited both by opponents and supporters of the policy, with each side accepting as credible only partial elements of the report. Lack of transparency and reproducibility (TR) in a policy report implies that its credibility relies on the reputation of the authors, and their organizations, instead of on a critical appraisal of the analysis. This dissertation translates to policy analysis solutions developed to address the lack of credibility in a different setting: the reproducibility crisis in science. I adapt the Transparency and Openness Promotion (TOP) guidelines (Nosek et al, 2015) to the policy analysis setting. The highest standards from the adapted guidelines involve the use of two key tools: dynamic documents that combine all elements of an analysis in one place, and open source version control (git). I then implement these high standards in a case study of the CBO report mentioned above, and present the complete analysis in the form of an open-source dynamic document. In addition to increasing the credibility of the case study analysis, this methodology brings attention to several components of the policy analysis that have been traditionally overlooked in academic research, for example the distribution of the losses used to pay for the increase in wages. Increasing our knowledge in these overlooked areas may prove most valuable to an evidence-based policy debate

Evaluating the Chile Solidario program: results using the Chile Solidario panel and the administrative databases

This paper presents the results of a three-year evaluation performed on the first cohorts of Chile Solidario, the most important anti-poverty program in Chile. The paper presents a description of the program, emphasizing the mechanism by which people were admitted into the program. We then propose evaluation strategies and discuss their validity. The final evaluation is conducted using a Matching estimator, and we discuss the principles surrounding the potential for this to be a valid evaluation method. The initial results using the Chile Solidario Panel suggest that the program had positive effects on psychosocial welfare and on take-up of subsidies and social programs. However, it is not possible to obtain reliable results due to data shortcomings, particularly the lack of baseline data. In order to solve the problem, we generated a database using six years of administrative data, including around 1,000,000 family records per year. A method for overcoming the treatment substitution problem is discussed and implemented. Results are much more robust than those of the Chile Solidario Panel and show small, but clearly positive effects for several variables, especially the number of workers in the family, the percentage of workers in the family and the employment of the head of the family