Panel Data and Experimental Design

36 Pages Posted: 5 Jan 2017

See all articles by Fiona Burlig

Fiona Burlig

University of Chicago

Louis Preonas

University of California, Berkeley - Department of Agricultural & Resource Economics

Matt Woerman

University of Massachusetts Amherst - Department of Resource Economics

Multiple version iconThere are 3 versions of this paper

Date Written: January 2, 2017

Abstract

How should researchers design experiments to detect treatment effects with panel data? In this paper, we derive analytical expressions for the variance of panel estimators under non-i.i.d. error structures, which inform power calculations in panel data settings. Using Monte Carlo simulation, we demonstrate that, with correlated errors, traditional methods for experimental design result in experiments that are incorrectly powered with proper inference. Failing to account for serial correlation yields overpowered experiments in short panels and under-powered experiments in long panels. Using both data from a randomized experiment in China and a high-frequency data set of U.S. electricity consumption, we show that these results hold in real-world settings. Our theoretical results enable us to achieve correctly powered experiments in both simulated and real data. This paper provides researchers with the tools to design well-powered experiments in panel data settings.

Keywords: power, experimental design, panel data, sample size

JEL Classification: B4, C2, C9, O1, Q4

Suggested Citation

Burlig, Fiona and Preonas, Louis and Woerman, Matt, Panel Data and Experimental Design (January 2, 2017). Available at SSRN: https://ssrn.com/abstract=2892713 or http://dx.doi.org/10.2139/ssrn.2892713

Fiona Burlig (Contact Author)

University of Chicago ( email )

5757 S. University Ave
Chicago, IL 60637
United States

Louis Preonas

University of California, Berkeley - Department of Agricultural & Resource Economics ( email )

Berkeley, CA 94720
United States

Matt Woerman

University of Massachusetts Amherst - Department of Resource Economics ( email )

Stockbridge Hall
80 Campus Center Way
Amherst, MA 01003
United States

HOME PAGE: http://sites.google.com/site/mattwoerman

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