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HERC Econometrics with Observational Data

Research Design

NOTE: A newer version of this presentation is available at

by Christine Chee, PhD
Seminar date: 10/9/2013

Description: This lecture will briefly review the challenges of inferring causality in observational studies. We will cover several quasi-experimental methods to reduce the potential for bias in treatment effects using covariate matching, differences-in-differences, and regression discontinuity. Examples will be discussed for each method.

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