How important is innovation? A Bayesian factor-augmented productivity model on panel data
This paper proposes a Bayesian approach to estimate a factor augmented productivity equation. We exploit the panel dimension of our data and distinguish individual-speci c and time-speci c factors. On the basis of 14 technology and infrastructure indicators from 37 countries over a 10-year period (1998 to 2007), we construct summary indicators of these two components and estimate their e ect on the growth and the international diff erences in GDP per capita.
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