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Productive Capabilities: An Empirical Investigation of their Determinants [electronic resource] / Christian Daude, Arne Nagengast and José Ramón Perea

By: Contributor(s): Material type: ArticleArticleSeries: OECD Development Centre Working Papers ; no.321.Publication details: Paris : OECD Publishing, 2014.Description: 35 p. ; 21 x 29.7cmSubject(s): Other classification:
  • C11
  • O33
  • F43
  • O14
  • O11
Online resources: Abstract: Recent contributions to the growth literature have argued that the structure of an economy, as measured by its productive capabilities, is a key determinant for inter-country differences in development. Productive capabilities have been shown to be highly predictive of future economic growth, yet their country-level determinants have remained unknown. In this paper, we empirically explore their determinants using a model averaging framework that can handle a very large number of explanatory variables without the need for model selection. In order to estimate our dynamic panel specification, we propose a novel Bayesian Averaging of Classical Estimates procedure based on the simple and efficient bias-corrected LSDV estimator. Our baseline and robustness analysis consider a large number of variables, sample periods and model priors. We find that the existing stock of capabilities (as measured by the lagged dependent variable), commodity terms of trade, energy availability, government consumption, capital per worker, arable land and capital inflows show a strong and robust association with capabilities.
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Item type Home library Collection Call number Status Date due Barcode Item holds
Working Paper Biblioteca Digital Colección OECD OECD 5k3tt0dh36zv-en (Browse shelf(Opens below)) Not For Loan
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Recent contributions to the growth literature have argued that the structure of an economy, as measured by its productive capabilities, is a key determinant for inter-country differences in development. Productive capabilities have been shown to be highly predictive of future economic growth, yet their country-level determinants have remained unknown. In this paper, we empirically explore their determinants using a model averaging framework that can handle a very large number of explanatory variables without the need for model selection. In order to estimate our dynamic panel specification, we propose a novel Bayesian Averaging of Classical Estimates procedure based on the simple and efficient bias-corrected LSDV estimator. Our baseline and robustness analysis consider a large number of variables, sample periods and model priors. We find that the existing stock of capabilities (as measured by the lagged dependent variable), commodity terms of trade, energy availability, government consumption, capital per worker, arable land and capital inflows show a strong and robust association with capabilities.

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