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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

Listed author(s):
  • Diana Weinhold

[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. [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.

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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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  1. 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.
  2. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1989. "The Revenues-Expenditures Nexus: Evidence from Local Government Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(2), pages 415-429, May.
  3. Carroll, Christopher D. & Weil, David N., 1994. "Saving and growth: a reinterpretation," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 40(1), pages 133-192, June.
  4. Sen, Amartya, 1983. "Development: Which Way Now?," Economic Journal, Royal Economic Society, vol. 93(372), pages 742-762, December.
  5. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
  6. 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.
  7. J. Bradford De Long & Lawrence H. Summers, 1991. "Equipment Investment and Economic Growth," The Quarterly Journal of Economics, Oxford University Press, vol. 106(2), pages 445-502.
  8. Hsiao, Cheng & Mountain, Dean C. & Chan, M. W. Luke & Tsui, Kai Y., 1989. "Modeling Ontario regional electricity system demand using a mixed fixed and random coefficients approach," Regional Science and Urban Economics, Elsevier, vol. 19(4), pages 565-587, December.
  9. 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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