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

Georges Bresson, Jean-Michel Etienne and Pierre Mohnen

Macroeconomic Dynamics, 2016, vol. 20, issue 8, 1987-2009

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.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:cup:macdyn:v:20:y:2016:i:08:p:1987-2009_00

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