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Determinants of Regional Economic Growth by Quantile

Listed author(s):
  • Jesus regstdpo-Cuaresma
  • Neil Foster
  • Robert Stehrer

regstdpo-Cuaresma J., Foster N. and Stehrer R. Determinants of regional economic growth by quantile, Regional Studies. The robustness of growth determinants across European Union regions is analysed using quantile regression. Using Bayesian model averaging (BMA) on the class of quantile regression models, it is proposed that the set of relevant covariates is assessed, allowing for different effects across growth quantiles. The results indicate that the robust growth determinants differ across quantiles. The set of robust variables includes physical investment when taking country fixed-effects into account, and skill endowment and initial gross domestic product per capita when not. Even when a variable is found to be robust across quantiles, its estimated impact on growth is often found to vary across quantiles. [image omitted] regstdpo-Cuaresma J., Foster N. et Stehrer R. Les determinants de la croissance economique par quantile, Regional Studies. A partir d'une regression par quantile, on analyse la solidite des determinants de la croissance a travers les regions de l'Union europeenne. Employant un Bayesian Averaging Model (BMA) sur la categorie de modeles de regression par quantile, on propose une evaluation de la covariance, compte tenu des effets differents suivant les quantiles de croissance. L'ensemble de variables solides comprend l'investissement materiel quand on tient compte des effets specifiques a un pays, sinon la dotation en connaissance et le produit interieur brut initial par tete. Meme quand une variable s'avere solide a travers les quantiles, l'impact prevu sur la croissance varie souvent a travers les quantiles. Croissance regionale Bayesian model averaging Regression par quantiles regstdpo-Cuaresma J., Foster N. und Stehrer R. Determinanten regionalen Wachstums nach Quantilen, Regional Studies. In diesem Beitrag wird die Robustheit von Wachstumsdeterminanten in EU-Regionen mittels Quantilsregressionen analysiert. Dabei wird ein Bayesian Model Averaging (BMA) fur Quantilsregressionen verwendet, um die relevanten Kovariaten, die unterschiedliche Effekte in den jeweiligen Wachstumsquantilen aufweisen konnen, zu ermitteln. Die Resultate zeigen, dass die robusten Wachstumsdeterminanten in den jeweiligen Quantilen tatsachlich unterschiedlich sind. Unter Berucksichtigung von landerspezifischen Effekten ist insbesondere die Variable Anlageinvestitionen ein robuster Erklarungsfaktor regionalen Wachstums; ohne Berucksichtigen dieser Effekte sind Humankapitalausstattung und das Pro-Kopf-Einkommen robuste Determinanten. Auch wenn eine bestimmte Variable robust in mehreren oder allen Quantilen ist, sind die ermittelten Effekte auf das Wachstum der Regionen in den jeweiligen Quantilen oftmals unterschiedlich. Regionales Wachstum Bayesian Model Averaging Quantilsregressionen regstdpo-Cuaresma J., Foster N. y Stehrer R. Determinantes del crecimiento economico regional por cuantiles, Regional Studies. Analizamos la solidez de los determinantes de crecimiento en las regiones de la Union Europea usando una regresion cuantilica. Mediante el uso de promedios de modelo bayesiano sobre la clase de los modelos de regresion cuantilica, proponemos que se evalue el conjunto de las covariantes correspondientes teniendo en cuenta los diferentes efectos en los cuantiles de crecimiento. Los resultados indican que los determinantes de un crecimiento solido son diferentes entre los cuantiles. Si se tienen en cuenta los efectos fijos de cada pais, la inversion fisica es una variable fuerte, de no ser asi son variables fuertes la dotacion de habilidades y el producto interno bruto per capita inicial. Incluso cuando se halla una variable que es solida en varios cuantiles, se observa con frecuencia que el impacto estimado en el crecimiento varia entre los cuantiles. Crecimiento regional Promedios de modelo bayesiano Regresion cuantilica

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Article provided by Taylor & Francis Journals in its journal Regional Studies.

Volume (Year): 45 (2011)
Issue (Month): 6 ()
Pages: 809-826

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Handle: RePEc:taf:regstd:v:45:y:2011:i:6:p:809-826
DOI: 10.1080/00343401003713456
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