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Abstract

Numerous experimental studies use a panel approach to analyze repeated experiments involving a large number of periods. They use “static” panel techniques and do not incorporate any temporal dependency (lags) of the dependent variable. This paper introduces dynamic panel data techniques to experimental economists. This is a standard tool in many other fields of economics and might also be useful in our discipline. It uses the lags of the dependent variable as explanatory variables. Although the coefficients on lagged dependent variables might be far from our interest, the introduction of these lags becomes crucial to control for the dynamics of the process. To show the advantages of this technique, we have compared two datasets using static and dynamic panel data. We conclude that the use of dynamic panel data models in the context of experiments allows to unravel new relationships between experimental variables and highlighting new paths in behaviors

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File URL: http://www.ugr.es/~teoriahe/RePEc/gra/wpaper/thepapers10_22.pdf
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Paper provided by Department of Economic Theory and Economic History of the University of Granada. in its series ThE Papers with number 10/22.

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Length: 13 pages
Date of creation: 01 Sep 2011
Date of revision:
Handle: RePEc:gra:wpaper:10/22

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1. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
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   • M Arellano & O Bover, 1990. "Another Look at the Instrumental Variable Estimation of Error-Components Models," CEP Discussion Papers dp0007, Centre for Economic Performance, LSE.
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   • Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
   • Blundell, R. & Bond, S., 1995. "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models," Economics Papers 104, Economics Group, Nuffield College, University of Oxford.
   • R Blundell & Steven Bond, . "Initial conditions and moment restrictions in dynamic panel data model," Economics Papers W14&104., Economics Group, Nuffield College, University of Oxford.
6. John List & Todd Cherry, 2000. "Learning to Accept in Ultimatum Games: Evidence from an Experimental Design that Generates Low Offers," Experimental Economics, Springer, vol. 3(1), pages 11-29, June.
7. Glenn Harrison, 2007. "House money effects in public good experiments: Comment," Experimental Economics, Springer, vol. 10(4), pages 429-437, December.
8. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-95, November.
9. Pablo Brañas-Garza & Enrique Fatas & Pablo Guillen, 2006. "Inducing a Self-Fulfilling Prophecy in Public Goods Games," ThE Papers 06/01, Department of Economic Theory and Economic History of the University of Granada..
   
   • Guillen, Pablo & Fatas, Enrique & Brañas-Garza, Pablo, 2010. "Inducing efficient conditional cooperation patterns in public goods games, an experimental investigation," Journal of Economic Psychology, Elsevier, vol. 31(6), pages 872-883, December.
10. Anabela Botelho & Glenn W. Harrison & Marc A. Hirsch & Elisabet E. Rutstrom, 2001. "Bargaining behavior, demographics and nationality: a reconsideration of the experimental evidence," NIMA Working Papers 16, Núcleo de Investigação em Microeconomia Aplicada (NIMA), Universidade do Minho.
11. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
12. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.

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