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HOW IMPORTANT IS INNOVATION? A BAYESIAN FACTOR-AUGMENTED PRODUCTIVITY MODEL BASED ON PANEL DATA

  • Georges Bresson (a1), Jean-Michel Etienne (a2) and Pierre Mohnen (a3)

Abstract

This paper proposes a Bayesian approach to estimating a factor-augmented GDP per capita equation. We exploit the panel dimension of our data and distinguish between individual-specific and time-specific factors. On the basis of 21 technology, infrastructure, and institutional indicators from 82 countries over a 19-year period (1990 to 2008), we construct summary indicators of each of these three components in the cross-sectional dimension and an overall indicator of all 21 indicators in the time-series dimension and estimate their effects on growth and international differences in GDP per capita. For most countries, more than 50% of GDP per capita is explained by the four common factors we have introduced. Infrastructure is the greatest contributor to total factor productivity, followed by technology and institutions.

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Copyright

Corresponding author

Address correspondence to: Pierre Mohnen, UNU-MERIT Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands; e-mail : mohnen@merit.unu.edu.

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Supplementary materials

Bresson supplementary material
Figures S1-S5 and Tables S1-S3

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