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Modeling and Policy Analysis for the U.S. Science Sector

  • Jacques Kibambe Ngoie


    (Department of Economics, University of Pretoria)

  • Arnold Zellner


    (Booth School of Business, University of Chicago)

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This paper analyzes the production process of scientific outputs and its implications on the U.S. economy using variants of a disaggregated Marshallian Macroeconomic Model (MMM). Federal spending on scientific activities produces innovation which we measure using the number of patents awarded. Additionally, this study makes use of the Bass diffusion model to investigate how innovative patents generate new products that attract new firms in existing sectors of the U.S. economy. Firms are assumed to be Bayesian learners while forming expectations about product prices. Using a set of policy simulations, this research provides measured information on how selected science policies may affect sectoral growth of the U.S. economy. Moreover, issues such as bifurcation pertaining to dynamic models are thoroughly addressed in this paper. Among others, our findings suggest that federal spending on applied research has larger shortrun growth enhancement effects than spending on development or basic research. The return of current federal spending on applied research depends largely on past spending on basic research, something that is well captured through the lag structure imposed in our model. Recipients of federal grants for basic research often lay foundation for outstanding applied research.

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Paper provided by University of Pretoria, Department of Economics in its series Working Papers with number 201207.

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Length: 20 pages
Date of creation: Feb 2012
Date of revision:
Handle: RePEc:pre:wpaper:201207
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  1. Zellner, Arnold & Tobias, Justin, 2004. "A Note on Aggregation, Disaggregation and Forecasting Performance," Staff General Research Papers Archive 12371, Iowa State University, Department of Economics.
  2. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
  3. Robert J. Barro, 1988. "Government Spending in a Simple Model of Endogenous Growth," NBER Working Papers 2588, National Bureau of Economic Research, Inc.
  4. Griliches, Zvi, 1990. "Patent Statistics as Economic Indicators: A Survey," Journal of Economic Literature, American Economic Association, vol. 28(4), pages 1661-1707, December.
  5. Taylor, John B, 1979. "Estimation and Control of a Macroeconomic Model with Rational Expectations," Econometrica, Econometric Society, vol. 47(5), pages 1267-86, September.
  6. Marianne Baxter & Robert G. King, 1995. "Measuring Business Cycles Approximate Band-Pass Filters for Economic Time Series," NBER Working Papers 5022, National Bureau of Economic Research, Inc.
  7. Zellner, Arnold & Chen, Bin, 2001. "Bayesian Modeling Of Economies And Data Requirements," Macroeconomic Dynamics, Cambridge University Press, vol. 5(05), pages 673-700, November.
  8. Veloce, William & Zellner, Arnold, 1985. "Entry and empirical demand and supply analysis for competitive industries," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 459-471.
  9. Zellner, Arnold & Israilevich, Guillermo, 2005. "The Marshallian macroeconomic model: A progress report," International Journal of Forecasting, Elsevier, vol. 21(4), pages 627-645.
  10. repec:fth:harver:1473 is not listed on IDEAS
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