Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-25T16:58:57.262Z Has data issue: false hasContentIssue false

R&D POLICY IN THE ECONOMY WITH STRUCTURAL CHANGE AND HETEROGENEOUS SPILLOVERS

Published online by Cambridge University Press:  12 July 2019

Anton Bondarev*
Affiliation:
Xi’an Jiaotong-Liverpool University
*
Address correspondence to: Anton Bondarev, International Business School Suzhou, Xi’an Jiaotong-Liverpool University, 8, Chongwen Road, 215123 Suzhou, People’s Republic of China, e-mail: [email protected]

Abstract

This paper develops an endogenous growth model with doubly differentiated R&D being the growth engine. The model incorporates dynamic structural change and heterogeneous knowledge spillovers. As a result, decentralized economy may exhibit non-monotonic growth paths and declining R&D productivity. Conditions on the knowledge spillover operator granting the existence of balanced growth for first-best and market economies are obtained. Different regulation tools helpful in achieving the sustainable path and their limits are studied.

Type
Articles
Copyright
© Cambridge University Press 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

This research is part of the activities of SCCER CREST (Swiss Competence Center for Energy Research), which is financially supported by the Swiss Commission for Technology and Innovation (CTI) under contract KTI.2014.0114. Preliminary version of this paper has been presented at the conference “Finance and Growth in the Aftermath of the Crisis” in Milan. Author thanks the participants of the conference and H. Dawid in particular for their helpful comments.

References

REFERENCES

Acemoglu, D., Akcigit, U. and Kerr, W. R. (2016) Innovation Network. Proceedings of the National Academy of Sciences 113(41), 1148311488.CrossRefGoogle ScholarPubMed
Acemoglu, D. and Cao, D. (2015) Innovation by entrants and incumbents. Journal of Economic Theory 157(C), 255294.CrossRefGoogle Scholar
Acemoglu, D., Gancia, G., and Zilibotti, F. (2012) Competing engines of growth: Innovation and standardization Journal of Economic Theory 147(2), 570601, e3. Issue in honor of David Cass.CrossRefGoogle Scholar
Akcigit, U. and Kerr, W. R. (2018) Growth through heterogeneous innovations. Journal of Political Economy 126(4), 13741443.CrossRefGoogle Scholar
Barbier, E. (1999) Endogenous growth and natural resource scarcity. Environmental and Resource Economics 14(1), 5174.CrossRefGoogle Scholar
Bondarev, A. and Greiner, A. (2019) Endogenous growth and structural change through vertical and horizontal innovations. Macroeconomic Dynamics 23(1), 5279.CrossRefGoogle Scholar
Bondarev, A. and Krysiak, F. (2017) Dynamic heterogeneous r&d with cross-technologies interactions. WWZ Working paper 2017/13, University of Basel.Google Scholar
Bresnahan, T. (2010) General purpose technologies. In Hall, B. H. and Rosenberg, N. (eds.), Handbook of the Economics of Innovation, Volume 2, pp. 761791. North-Holland.CrossRefGoogle Scholar
Chu, A. C., Cozzi, G., Furukawa, Y. and Liao, C.-H. (2017) Inflation and economic growth in a schumpeterian model with endogenous entry of heterogeneous firms. European Economic Review 98, 392409.CrossRefGoogle Scholar
Chu, A. C., Cozzi, G. and Galli, S. (2012) Does intellectual monopoly stimulate or stifle innovation? European Economic Review 56(4), 727746.CrossRefGoogle Scholar
Fernald, J. G. and Jones, C. I. (2014) The future of US economic growth. American Economic Review 104(5), 4449.CrossRefGoogle Scholar
Gordon, R. (2016) The Rise and Fall of American Growth: The U.S. Standard of Living since the Civil War. Princeton: Princeton University Press.CrossRefGoogle Scholar
Hamano, M. and Zanetti, F. (2017) Endogenous product turnover and macroeconomic dynamics. Review of Economic Dynamics 26, 263279.CrossRefGoogle Scholar
Kolmogorov, A. and Fomin, S. (1999) Elements of the Theory of Functions and Functional Analysis. Dover: Dover Publications; Dover Books on Mathematics edition.Google Scholar
Mumtaz, H. and Zanetti, F. (2016) The effect of labor and financial frictions on aggregate fluctuations. Macroeconomic Dynamics 20(1), 313341.CrossRefGoogle Scholar
Peretto, P. and Connolly, M. (2007) The manhattan metaphor. Journal of Economic Growth 12(4), 329350.CrossRefGoogle Scholar
Peretto, P. and Smulders, S. (2002) Technological distance, growth and scale effects. The Economic Journal 112(481), 603624.CrossRefGoogle Scholar
Peretto, P. and Valente, S. (2015) Growth on a finite planet: Resources, technology and population in the long run. Journal of Economic Growth 20(3), 305331.CrossRefGoogle Scholar
Storper, M. (2011) Justice, efficiency and economic geography: Should places help one another to develop? European Urban and Regional Studies 18(1), 321.CrossRefGoogle Scholar
Stromberg, K. (1981) Introduction to Classical Real Analysis. Wadsworth: Wadsworth International Group.Google Scholar
Van der Hoog, S. and Dawid, H. (2019) Bubbles, crashes, and the financial cycle: the impact of banking regulation on deep recessions. Macroeconomic Dynamics 23(3), 12051246.CrossRefGoogle Scholar
Weintraub, S. (2008) Jordan Canonical Form: Application to Differential Equations. San Rafael: Morgan & Claypool Publishers.Google Scholar
Zanetti, F. (2019) Financial shocks, job destruction shocks and labor market fluctuations. Macroeconomic Dynamics 23(3), 11371165. doi:10.1017/S1365100517000190 CrossRefGoogle Scholar
Supplementary material: PDF

Bondarev supplementary material

Bondarev supplementary material 1

Download Bondarev supplementary material(PDF)
PDF 422.1 KB