Research & Development and Long-Term Economic Growth: A Bayesian Model Averaging Analysis
We examine the effect of research and development (R&D) on long-term economic growth using the Bayesian model averaging (BMA) to deal rigorously with model uncertainty. Previous empirical studies investigated the effect of dozens of regressors on long-term growth, but they did not examine the effect of R&D due to data unavailability. We extend these studies by proposing to capture the R&D intensity by the number of Nobel prizes in science. Using our indicator, our estimates show that R&D exerts a positive effect on long-term growth with posterior inclusion probability of 0.25 using our preferred parameter and model priors.
|Date of creation:||Jun 2011|
|Date of revision:||Jun 2011|
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- Xavier Sala-I-Martin & Gernot Doppelhofer & Ronald I. Miller, 2004.
"Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach,"
American Economic Review,
American Economic Association, vol. 94(4), pages 813-835, September.
- Gernot Doppelhofer & Ronald I. Miller & Xavier Sala-i-Martin, 2000. "Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (Bace) Approach," OECD Economics Department Working Papers 266, OECD Publishing.
- Gernot Doppelhofer & Ronald I. Miller & Xavier Sala-i-Martin, 2000. "Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach," NBER Working Papers 7750, National Bureau of Economic Research, Inc.