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Simulating power of economic experiments: the powerBBK package

Published online by Cambridge University Press:  01 January 2025

Charles Bellemare Open the ORCID record for Charles Bellemare [Opens in a new window] ,
Luc Bissonnette  and
Sabine Kröger
Charles Bellemare*
Affiliation:
Department of Economics, Laval University, Pavillon J.A.DeSève, Québec, Québec G1V 0A6, Canada
Luc Bissonnette*
Affiliation:
Department of Economics, Laval University, Pavillon J.A.DeSève, Québec, Québec G1V 0A6, Canada
Sabine Kröger*
Affiliation:
Department of Economics, Laval University, Pavillon J.A.DeSève, Québec, Québec G1V 0A6, Canada
*
e-mail: [email protected]
[email protected]
[email protected]
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Abstract

In this article, we highlight how simulation methods can be used to analyze power of economic experiments. We provide the powerBBK package programmed for experimental economists, that can be used to perform simulations in STATA. Power can be simulated using a single command line for various statistical tests (nonparametric and parametric), estimation methods (linear, binary, and censored regression models), treatment variables (binary, continuous, time-invariant or time varying), sample sizes, experimental periods, and other design features (within or between-subjects design). The package can be used to predict minimum sample sizes required to reach a user-specific level of power, to maximize power of a design given the researcher supplied a budget constraint, or to compute power to detect a user-specified treatment order effect in within-subjects designs. The package can also be used to compute the probability of sign errors—the probability of rejecting the null hypothesis in the wrong direction as well as the share of rejections pointing in the wrong direction. The powerBBK package is provided as an .ado file along with a help file, both of which can be downloaded here (http://www.bbktools.org).

Keywords

Statistical powerSimulation methodsEconomic experimentsC8C9D03
Type
Experimental Tools
Information
Journal of the Economic Science Association , Volume 2 , Issue 2 , November 2016 , pp. 157 - 168
Copyright
Copyright © Economic Science Association 2016

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Footnotes

Part of the paper was written at the Institute of Finance at the School of Business and Economics at Humboldt Universität zu Berlin and at the Department of Economics at Zurich University. We thank both institutions for their hospitality. We thank Nicolas Couët for his valuable research assistance. We are grateful to participants at the ASFEE conference in Montpellier (2012), ESA meeting in New York (2012), the IMEBE in Madrid (2013), and seminar participants at the Department of Economics at Zurich University (2013) and at Technische Universität Berlin (2013). Finally, we thank reviewers and co-editors for extremely helpful comments and suggestions.

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