Measuring the impact of R&D on Productivity from a Econometric Time Series Perspective
In this paper we argue that the standard sequential reduction approach to modelling dynamic relationships may be sub-optimal when long lag lengths are required and especially when the intermediate lags may be less important. A flexible model search approach is adopted using the insights of Bayesian Model probabilities, and new information criteria based on forecasting performance. This approach is facilitated by exploiting Genetic Algorithms. Using data on U.K. and U.S. agriculture the bivariate time series relationship between R&D expenditure and productivity is analysed. Long lags are found in the relationship between R&D expenditures and productivity in the U.K. and in the U.S. which remain undiscovered when using the orthodox approach. This finding is of particular importance in the debate on the optimal level of public R&D funding. Copyright Springer Science+Business Media, Inc. 2005
If 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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
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.:
- Huffman, Wallace E. & Evenson, Robert E., 2006.
"Science for Agriculture: A Long Term Perspective,"
Staff General Research Papers
12362, Iowa State University, Department of Economics.
- Phillips, Peter C. B., 1995.
"Bayesian model selection and prediction with empirical applications,"
Journal of Econometrics,
Elsevier, vol. 69(1), pages 289-331, September.
- Peter C.B. Phillips, 1992. "Bayesian Model Selection and Prediction with Empirical Applications," Cowles Foundation Discussion Papers 1023, Cowles Foundation for Research in Economics, Yale University.
- Carmen Fernandez & Eduardo Ley & Mark F J Steel, 1998.
"Benchmark priors for Bayesian model averaging,"
ESE Discussion Papers
66, Edinburgh School of Economics, University of Edinburgh.
- Carmen Fernandez & Eduardo Ley & Mark F J Steel, 1998. "Benchmark priors for Bayesian model averaging," ESE Discussion Papers 26, Edinburgh School of Economics, University of Edinburgh.
- Carmen Fernandez & Eduardo Ley & Mark F.J. Steel, 1998. "Benchmark Priors for Bayesian Model Averaging," Econometrics 9804001, EconWPA, revised 31 Jul 1999.
- Shenggen Fan, 2000. "Research Investment and the Economic Returns To Chinese Agricultural Research," Journal of Productivity Analysis, Springer, vol. 14(2), pages 163-182, September.
- G. Duggal, Vijaya & Saltzman, Cynthia & Klein, Lawrence R., 1999. "Infrastructure and productivity: a nonlinear approach," Journal of Econometrics, Elsevier, vol. 92(1), pages 47-74, September.
- Thirtle, C. & Bottomley, P. & Palladino, P. & Schimmelpfennig, D. & Townsend, R., 1998.
"The rise and fall of public sector plant breeding in the United Kingdom: a causal chain model of basic and applied research and diffusion,"
Agricultural Economics of Agricultural Economists,
International Association of Agricultural Economists, vol. 19(1-2), September.
- Thirtle, C. & Bottomley, P. & Palladino, P. & Schimmelpfennig, D. & Townsend, R., 1998. "The rise and fall of public sector plant breeding in the United Kingdom: a causal chain model of basic and applied research and diffusion," Agricultural Economics, Blackwell, vol. 19(1-2), pages 127-143, September.
- Chao, John C. & Phillips, Peter C. B., 1999.
"Model selection in partially nonstationary vector autoregressive processes with reduced rank structure,"
Journal of Econometrics,
Elsevier, vol. 91(2), pages 227-271, August.
- John C. Chao & Peter C.B. Phillips, 1997. "Model Selection in Partially Nonstationary Vector Autoregressive Processes with Reduced Rank Structure," Cowles Foundation Discussion Papers 1155, Cowles Foundation for Research in Economics, Yale University.
When requesting a correction, please mention this item's handle: RePEc:kap:jproda:v:24:y:2005:i:1:p:49-72. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla)or (Christopher F. Baum)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.