A Primer for Applying Propensity-Score Matching

By Carolyn J. Heinrich, A. Maffioli, Gonzalo Vázquez. 2010

393 citations recorded by the source corpus.

This document provides a guide to the key aspects of implementing Propensity-Score Matching (PSM) methodology. It summarizes the basic conditions under which PSM can be used to estimate the impact of a program and the data required, presenting examples of PSM applications. It explains how the Conditional Independence Assumption, combined with the Overlap Condition, reduces selection bias when participation in a program is determined by observable characteristics. It also describes different matching algorithms and some tests to assess the quality of the matching.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/dfbcc996f6c18ed47e194432f284343c57f41e69

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Citations in the corpus

• Does the Use of Mobile Phones by Smallholder Maize Farmers Affect Productivity in Ghana? (2018, background): “Heinrich, Maffioli, and Vazquez (2010) argue that there is no strong advantage in using a logit or probit model.”
• Cooperative membership and dairy performance among smallholders in Ethiopia (2016, background): “Propensity Score Matching is one of the available econometric techniques to deal with these biases (Heinrich et al., 2010).”
• From protection to production: productive impacts of the Malawi Social Cash Transfer scheme (2012, background): “Some papers indicate that this loss of observations prevents the average treatment effect from being accurately estimated (Diaz and Handa 2006, Heinrich et al. 2010, Khandker et al. 2010, Gertler et al. 2011).”
• Switching to self-employment can be good for your health (2019, methodology): “Under this assumption, the matched DID design in principle allows eliminating selection bias in observational data (Card et al., 2011; Heinrich et al., 2010).”
• Capital Flow Management Measures: What Are They Good For? (2014, background): “31 See Forbes et al. (2012) for information on coverage in the EPFR database on equity and bond flows. able to capture the magnitude or intensity of different types of CFMs, this extension can also be loosely interpreted as an assessment if larger changes in CFMs had different effects than in the fu”