Can Panel Data Designs and Estimators Substitute for Randomized Controlled Trials in the Evaluation of Environmental Policy
RFF Academic Seminar
PresentersPaul J. Ferraro
Professor, Department of Economics, Andrew Young School of Policy Studies,
Georgia State University Abstract
In environmental policy, as in other areas of social policy, randomized evaluation designs are difficult to implement and thus researchers must rely on non-experimental empirical designs to evaluate program impacts. Yet there is considerable debate about whether non-experimental designs can generate accurate estimates of program impact. Design-replication studies assess the ability of non-experimental designs to replicate unbiased (experimental) estimators of program impact. Our design-replication study uses, as a benchmark, a large-scale randomized field experiment that tested the effectiveness of messages designed to induce voluntary reductions in water consumption during a drought. We find that, in general, traditional panel data estimators are unable to replicate the estimates from the experimental design except in one case: when caliper-matching methods are used to pre-process the data before applying a fixed-effects panel data estimator. Understanding how the caliper matching changes the sample, however, will be critical for interpreting the estimates from such an estimator in other contexts. Insights for best-practice econometric analysis are offered.
Thursday, October 18, 2012
12:00 - 1:30 p.m.
Lunch will be provided.
1st Floor Conference Room
1616 P St. NW
Washington, D.C. 20036
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