Measuring Intersectoral Knowledge Spillovers: an Application of Sensitivity Analysis to Italy
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- Giovanni Cerulli & Bianca Poti`, 2009. "Measuring Intersectoral Knowledge Spillovers: An Application Of Sensitivity Analysis To Italy," Economic Systems Research, Taylor & Francis Journals, vol. 21(4), pages 409-436.
References listed on IDEAS
- Roland-Holst, David W & Sancho, Ferran, 1992.
"Relative Income Determination in the United States: A Social Accounting Perspective,"
Review of Income and Wealth,
International Association for Research in Income and Wealth, vol. 38(3), pages 311-327, September.
- Roland-Holst, D.W. & Sancho, F., 1991. "Ralative Income Determination in the United States: A Social Accounting Perspective," UFAE and IAE Working Papers 188.92, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
- Ina Drejer, 2000. "Comparing Patterns of Industrial Interdependence in National Systems of Innovation - A Study of Germany, the United Kingdom, Japan and the United States," Economic Systems Research, Taylor & Francis Journals, vol. 12(3), pages 377-399.
- Zvi Griliches, 1998.
"Interindustry Technology Flows and Productivity Growth: A Reexamination,"
NBER Chapters,in: R&D and Productivity: The Econometric Evidence, pages 241-250
National Bureau of Economic Research, Inc.
- Griliches, Zvi & Lichtenberg, Frank, 1984. "Interindustry Technology Flows and Productivity Growth: A Re-examination," The Review of Economics and Statistics, MIT Press, vol. 66(2), pages 324-329, May.
- Scherer, F M, 1982. "Inter-Industry Technology Flows and Productivity Growth," The Review of Economics and Statistics, MIT Press, vol. 64(4), pages 627-634, November.
- Adams, James D, 1990. "Fundamental Stocks of Knowledge and Productivity Growth," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 673-702, August.
- Goto, Akira & Suzuki, Kazuyuki, 1989. "R&D Capital, Rate of Return on R&D Investment and Spillover of R&D in Japanese Manufacturing Industries," The Review of Economics and Statistics, MIT Press, vol. 71(4), pages 555-564, November.
- Frederic Scherer, 2003. "Technology Flows Matrix Estimation Revisited," Economic Systems Research, Taylor & Francis Journals, vol. 15(3), pages 327-358.
- Bart Los & Bart Verspagen, 2000. "R&D spillovers and productivity: Evidence from U.S. manufacturing microdata," Empirical Economics, Springer, vol. 25(1), pages 127-148.
- Erik Dietzenbacher & Bart Los, 2002. "Externalities of R&D Expenditures," Economic Systems Research, Taylor & Francis Journals, vol. 14(4), pages 407-425.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Kristkova, Z. Smeets & Gardebroek, K. & van Dijk, M. & van Meijl, H., 2015. "The impact of R&D on factor-augmenting technical change- an empirical assessment at the sector level," 2015 Conference, August 9-14, 2015, Milan, Italy 230229, International Association of Agricultural Economists.
- Cerina, Fabio & Mureddu, Francesco, 2014.
"Is agglomeration really good for growth? Global efficiency, interregional equity and uneven growth,"
Journal of Urban Economics,
Elsevier, vol. 84(C), pages 9-22.
- F. Cerina & F. Mureddu, 2009. "Is Agglomeration really good for Growth? Global Efficiency, Interregional Equity and Uneven Growth," Working Paper CRENoS 200913, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
- Fabio Cerina & Francesco Mureddu, 2010. "Is Agglomeration really Good for Growth? Global Efficiency, Interregional Equity and Uneven Growth," DEGIT Conference Papers c015_022, DEGIT, Dynamics, Economic Growth, and International Trade.
- repec:kap:jtecht:v:42:y:2017:i:6:d:10.1007_s10961-016-9528-x is not listed on IDEAS
More about this item
KeywordsR&D spillovers; Input-output models; Sensitivity analysis; Monte Carlo simulations;
- O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
- C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-ALL-2008-03-15 (All new papers)
- NEP-INO-2008-03-15 (Innovation)
- NEP-KNM-2008-03-15 (Knowledge Management & Knowledge Economy)
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