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Tests de causalité sur données de panel : une application à l'étude de la causalité entre l'investissement et la croissance

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  • Diana Weinhold

Abstract

[fre] Tests de causalité sur données de panel : une application à l'étude de la causalité entre l'investissement et . la croissance par Diana Weinhold . Cet article développe une approche de l'analyse de la causalité sur données de panel, permettant une plus grande souplesse dans la modélisation de la relation causale selon les individus, en estimant la distribution de la causalité dans un panel éventuellement hétérogène. Deux méthodes possibles d'estimation pour un modèle mixte à coefficients fixes et aléatoires sont étudiées. Ces deux méthodes permettent aux coefficients d'une variable causale orthogonalisée de varier aléatoirement et d'éviter une grande part des problèmes que pose l'estimation, sur données de panel, de modèles dynamiques à coefficients aléatoires. À l'aide de simulations, permettant de développer une méthode d'interprétation des distributions estimées, il est alors possible de prévoir les probabilités de causalité associées au panel. Cette approche est alors appliquée à l'étude de la causalité entre l'investissement et la croissance pour un panel de pays. Dans cet article, nous montrons que cette relation se caractérise par une grande instabilité et des effets de rétroaction entre les pays. Par conséquent, il est clair que les hypothèses restrictives des modèles usuels sur données empilées peuvent s' avérer inappropriées, particulièrement pour les modèles élémentaires. Ce problème se posant dans cette étude, les résultats de cet article montrent d'autant plus la nécessité d'une souplesse d'interprétation ; ce que le test de causalité que nous proposons permet. [eng] Causaliy Testing in Panel Data with an Application to the Question of Investment and Growth . by Diana Weinhold . This paper develops an approach for panel causality analysis which allows for flexibility in the causal relationship from unity to unity, allowing estimation of distribution of causality in a possibly heterogeneous panel. Two possible estimation techniques for "mixed fixed and random" coefficients model are explored. These methods both allow the coefficients of an orthogonalized causal variable to vary randomly while avoiding many of the problems associated with random coefficients and dynamics in panels. Using simulations to develop a method for interpreting the estimated distributions, it is then possible to predict the probabilities of causality associated with the panel. . This approach is then applied to the question of causality between investment and growth in a panel of countries. The paper find that there is great instability and feedback among countries in this relationship. Therefore, it is clear that the restricting assumptions of traditional pooling models can be inappropriate, especially in simple models. Because the analysis signals this problem, the paper's results further underline the need for the interpretive flexibility that this proposed causality test imparts.

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File URL: http://dx.doi.org/doi:10.3406/ecop.1996.5829
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File URL: http://www.persee.fr/articleAsPDF/ecop_0249-4744_1996_num_126_5_5829/ecop_0249-4744_1996_num_126_5_5829.pdf?mode=light
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Bibliographic Info

Article provided by Programme National Persée in its journal Économie & prévision.

Volume (Year): 126 (1996)
Issue (Month): 5 ()
Pages: 163-175

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Handle: RePEc:prs:ecoprv:ecop_0249-4744_1996_num_126_5_5829

Note: DOI:10.3406/ecop.1996.5829
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Web page: http://www.persee.fr/web/revues/home/prescript/revue/ecop

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References

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  1. Christopher D. Carroll & David N. Weil, 1993. "Saving and growth: a reinterpretation," Working Paper Series / Economic Activity Section 140, Board of Governors of the Federal Reserve System (U.S.).
  2. Hsiao, C. & Mountain, D.C. & Tsui, K.Y. & Chan, M.W.L., 1989. "Modeling Ontario Regional Electricity System Demand Using A Mixed Fixed And Random Coefficients Approach," Papers m8906, Southern California - Department of Economics.
  3. Modigliani, Franco, 1986. "Life Cycle, Individual Thrift, and the Wealth of Nations," American Economic Review, American Economic Association, vol. 76(3), pages 297-313, June.
  4. 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.
  5. J. Bradford De Long & Lawrence H. Summers, . "Equipment Investment and Economic Growth," J. Bradford De Long's Working Papers _122, University of California at Berkeley, Economics Department.
  6. Sen, Amartya, 1983. "Development: Which Way Now?," Economic Journal, Royal Economic Society, vol. 93(372), pages 742-62, December.
  7. Lach, Saul & Schankerman, Mark, 1989. "Dynamics of R&D and Investment in the Scientific Sector," Journal of Political Economy, University of Chicago Press, vol. 97(4), pages 880-904, August.
  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.
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Citations

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Cited by:
  1. Christophe Hurlin & Elena Dumitrescu, 2012. "Testing for Granger Non-causality in Heterogeneous Panels," Working Papers halshs-00224434, HAL.
  2. Cândida Ferreira, 2013. "Bank performance and economic growth: evidence from Granger panel causality estimations," Working Papers Department of Economics 2013/21, ISEG - School of Economics and Management, Department of Economics, University of Lisbon.
  3. Christophe Hurlin & Baptiste Venet, 2008. "Financial Development and Growth: A Re-Examination using a Panel Granger Causality Test," Working Papers halshs-00319995, HAL.
  4. Marie-Estelle Binet, 2000. "Dynamique périurbaine et dépenses publiques locales : une analyse en termes de causalité," Économie et Prévision, Programme National Persée, vol. 146(5), pages 95-111.
  5. Venet, Baptiste & Hurlin, Christophe, 2001. "Granger Causality Tests in Panel Data Models with Fixed Coefficients," Economics Papers from University Paris Dauphine 123456789/6159, Paris Dauphine University.

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