Research & Development and Long-Term Economic Growth: A Bayesian Model Averaging Analysis
AbstractWe 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies in its series Working Papers IES with number 2011/19.
Date of creation: Jun 2011
Date of revision: Jun 2011
research and development; economic growth; Bayesian model averaging.;
Find related papers by JEL classification:
- O30 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - General
- O32 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Management of Technological Innovation and R&D
- O10 - Economic Development, Technological Change, and Growth - - Economic Development - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-06-25 (All new papers)
- NEP-FDG-2011-06-25 (Financial Development & Growth)
- NEP-INO-2011-06-25 (Innovation)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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," NBER Working Papers 7750, National Bureau of Economic Research, Inc.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Lenka Herrmannova).
If references are entirely missing, you can add them using this form.