How important is innovation?: A Bayesian factor-augmented productivity model on panel data

Georges Bresson, J-M. Etienne () and Pierre Mohnen
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J-M. Etienne: Université Paris-Sud 11

No 2014-052, MERIT Working Papers from United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT)

Abstract: This paper proposes a Bayesian approach to estimate a factor augmented productivity equation. We exploit the panel dimension of our data and distinguish individual-specific and time-specific factors. On the basis of 21 technology, infrastructure and institution indicators from 82 countries over a 19-year period 1990 to 2008, we construct summary indicators of these three components and estimate their effect on the growth and the international differences in GDP per capita.

Keywords: Productivity; Technology; Innovation; Economic growth; GDP per capita; Panel data; Bayesian models (search for similar items in EconPapers)
JEL-codes: C23 C38 O47 (search for similar items in EconPapers)
Date: 2014-06-30
New Economics Papers: this item is included in nep-ecm, nep-eff, nep-gro and nep-sbm
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Citations: View citations in EconPapers (1)

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Related works:
Working Paper: How important is innovation? A Bayesian factor-augmented productivity model on panel data (2011)
Working Paper: How important is innovation? A Bayesian factor-augmented productivity model on panel data (2011)
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Persistent link: https://EconPapers.repec.org/RePEc:unm:unumer:2014052

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