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INCREASING RETURNS TO SCALE, PRICE DISPERSION, AND THE DISTRIBUTION OF RETURNS TO INNOVATION

Published online by Cambridge University Press:  31 January 2014

Michael D. Makowsky  and
David M. Levy
Michael D. Makowsky*
Affiliation:
Johns Hopkins University
David M. Levy
Affiliation:
George Mason University
*
Address correspondence to: Michael D. Makowsky, 5801 Smith Avenue, Davis Building, Suite 3220, Baltimore, MD 21209, USA; e-mail: [email protected].
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Abstract

Models of endogenous growth have not been able to account for the variety of empirically observed distributional properties of the returns to innovation, in part, because of the limitations necessarily imposed on competition to cope with increasing returns to scale. Exponential growth, fat tails, Pareto–Levy distributed upper tails, and upper value outliers, are associated with increasing returns to scale and innovation. At the same time, properties such as bifurcated research investment strategies, bimodal returns to innovation, and Laplace distributed firm growth rates are products of competition. We build an agent-based model of endogenous technical change in which heterogeneous investments in patented knowledge and increasing returns to scale emerge these distributional properties within a competitive market. The combination of heterogeneous agents, costly information, and patents allow for a competitive landscape to persist amidst increasing returns. The ability of model to foster a coexistence of competition and increasing returns underlies the observed distributional properties.

Keywords

PatentsEndogenous GrowthIncreasing Returns to ScalePrice DispersionSearchHeterogeneous Agents
Type
Articles
Information
Macroeconomic Dynamics , Volume 19 , Issue 2 , March 2015 , pp. 334 - 362
Copyright
Copyright © Cambridge University Press 2014 

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References

REFERENCES

Aghion, Philippe, Akcigit, Ufuk, and Howitt, Peter (2013) What Do We Learn from Schumpeterian Growth Theory? NBER Working Papers 18824.Google Scholar
Aghion, Philippe and Howitt, Peter (1992) A model of growth through creative destruction. Econometrica 60, 323–351.Google Scholar
Alfarano, Simone and Lux, Thomas (2007) A noise trader model as a generator of apparent financial power laws and long memory. Macroeconomic Dynamics 11, 80–101.CrossRefGoogle Scholar
Axtell, Robert (1999) The Emergence of Firms in a Population of Agents: Local Increasing Returns, Unstable Nash Equilibria, and Power Law Size Distributions. Center on Social and Economic Dynamics working paper, Brookings Institution.Google Scholar
Axtell, Robert (2001a) Effects of interaction topology and activation regime in several multi-agent systems. In Goos, G., Hartmanis, J., and van Leeuwen, J. (eds.), Multi-agent-based Simulation, pp. 33–48. Berlin: Springer.Google Scholar
Axtell, Robert (2001b) Zipf distribution of U.S. firm sizes. Science 293 (5536), 1818–1820.Google Scholar
Boldrin, Michele and Levine, David (2008) The case against intellectual property. American Economic Review 92, 209–212.Google Scholar
Boldrin, Michele and Levine, David K. (2013) The case against patents. Journal of Economic Perspectives 27, 3–22.Google Scholar
Bottazzi, G., Cefis, E., Dosi, G., and Secchi, A. (2007) Invariances and diversities in the patterns of industrial evolution: Some evidence from Italian manufacturing industries. Small Business Economics 29, 137–159.Google Scholar
Bottazzi, G. and Secchi, A. (2003) Why are distributions of firm growth rates tent-shaped? Economics Letters 80, 415–420.Google Scholar
Bottazzi, G. and Secchi, A. (2006) Explaining the distribution of firm growth rates. RAND Journal of Economics 37, 235–256.Google Scholar
Chu, Angus C. and Pan, Shiyuan (2013) The escape-infringement effect of blocking patents on innovation and economic growth. Macroeconomic Dynamics 17, 955–969.Google Scholar
Conlisk, John (1996) Why bounded rationality? Journal of Economic Literature 34, 669–700.Google Scholar
Dawid, H. (2006) Agent-based models of innovation and technological change. Handbook of Computational Economics 2, 1235–1272.Google Scholar
Dawid, H., Gemkow, S., Hoog, S. van der, and Neugart, M. (2011) The Eurace@Unibi Model: An Agent-Based Macroeconomic Model for Economic Policy Analysis. Working paper, Universität Bielefeld.Google Scholar
Demirel, P. and Mazzucato, M. (2007) Firm Growth Dynamics under Different Knowledge Regimes: Implications for Regional Dynamics. Open University Discussion Paper 63-2007.Google Scholar
Demirel, Pelin and Mazzucato, Mariana (2008) Does Market Selection Reward Innovators? R&D, Patents, and Growth in the US Pharmaceutical Industry. Innogen working paper 63.Google Scholar
Doornik, Jurgen A. and Hansen, Henrik (2008) An omnibus test for univariate and multivariate normality. Oxford Bulletin of Economics and Statistics 70, 927–939.Google Scholar
Dosi, G., Fagiolo, G., Napoletano, M., and Roventini, A. (2012) Income distribution, credit and fiscal policies in an agent-based Keynesian model. Journal of Economic Dynamics and Control 37 (8), 1598–1625.Google Scholar
Dosi, G., Fagiolo, G., and Roventini, A. (2010) Schumpeter meeting Keynes: A policy-friendly model of endogenous growth and business cycles. Journal of Economic Dynamics and Control 34, 1748–1767.Google Scholar
Dosi, Giovanni (2007) Statistical regularities in the evolution of industries: A guide through some evidence and challenges for the theory. In Malerba, Franco and Brusoni, Stefano (eds.), Perspectives on Innovation, pp. 1110–1121. Cambridge, MA: Cambridge University Press.Google Scholar
Dosi, Giovanni, Marengo, Luigi, and Pasquali, Corrado (2006) How much should society fuel the greed of innovators? On the relations between appropriability, opportunities and rates of innovation. Research Policy 35, 1110–1121.Google Scholar
Dosi, Giovanni and Nelson, Richard (2010) Technical change and industrial dynamics as evolutionary processes. In Hall, Bronwyn H. and Rosenberg, Nathan (eds.), Handbook of the Economics of Innovation, pp. 51–127. Amsterdam: North Holland.Google Scholar
Eicher, Theo S. and Turnovsky, Stephen J. (1999) Non-scale models of economic growth. Economic Journal 109, 394–415.Google Scholar
Ellison, Aaron M. (1987) Effect of seed dimorphism on the density-dependent dynamics of experimental populations of Atriplex triangularis (Chenopodiaceae). American Journal of Botany 74, 1280–1288.Google Scholar
Epstein, Joshua M. (2006) Generative Social Science : Studies in Agent-Based Computational Modeling. Princeton, NJ: Princeton University Press.Google Scholar
Epstein, Joshua M. and Axtell, Robert (1996) Growing Artificial Societies : Social Science from the Bottom Up. Washington, DC: Brookings Institution Press.Google Scholar
Epstein, Larry G. and Wang, Tan (1994) Asset pricing under Knightian uncertainty. Econometrica 62, 283–322.Google Scholar
Futagami, Koichi and Iwaisako, Tatsuro (2003) Patent policy in an endogenous growth model. Journal of Economics 78, 239–258.Google Scholar
Gallini, Nancy T. (2002) The economics of patents: Lessons from recent U.S. patent reform. Journal of Economic Perspectives 16, 131–154.Google Scholar
Gans, Joshua S. and Quiggin, John (2003) A technological and organisational explanation for the size distribution of firms. Small Business Economics 21, 243–256.Google Scholar
Gatti, DDelli, Corrado Di Guilmi, Gallegati, Mauro, and Giulioni, Gianfranco (2007) Financial fragility, industrial dynamics, and business fluctuations in an agent-based model. Macroeconomic Dynamics 11, 62–79.Google Scholar
Grossman, Gene M. and Helpman, Elhanan (1991) Quality ladders in the theory of growth. Review of Economic Studies 58, 43–61.Google Scholar
Grossman, Gene M. and Helpman, Elhanan (1994) Endogenous innovation in the theory of growth. Journal of Economic Perspectives 8, 23–44.Google Scholar
Harhoff, Dietmar, Narin, Francis, Scherer, F.M., and Vopel, Katrin (1999) Citation frequency and the value of patented inventions. Review of Economics and Statistics 81, 511–515.Google Scholar
Harhoff, Dietmar, Scherer, F.M., and Vopel, Katrin (1998) Exploring the Tail of Patent Value Distributions. Working paper, Center for European Economic Research.Google Scholar
Hellwig, Martin and Irme, Andreas (2001) Endogenous technical change in a competitive economy. Journal of Economic Theory 101, 1–39.Google Scholar
Hill, Bruce M. (1975) A simple general approach to inference about the tail of a distribution. Annals of Statistics 3, 1163–1174.Google Scholar
Horowitz, Andrew W. and Lai, Edwin L. C. (1996) Patent length and the rate of innovation. International Economic Review 37, 785–801.Google Scholar
Hoskisson, Robert O. and Johnson, Richard A. (1992) Research notes and communications corporate restructuring and strategic change: The effect on diversification strategy and R & D intensity. Strategic Management Journal 13, 625–634.Google Scholar
Imbert, Eric, Escarre, Jose, and Lepart, Jacques (1996) Achene dimorphism and among-population variation in Crepis sancta (Asteraceae). International Journal of Plant Sciences 157, 309–315.Google Scholar
Iwaisako, Tatsuro and Futagami, Koichi (2007) Dynamic analysis of patent policy in an endogenous growth model. Journal of Economic Theory 132, 306–334.Google Scholar
Judd, Kenneth L. (1985) On the performance of patents. Econometrica 53, 567–586.Google Scholar
Klein, Judy L. (1997) Statistical Visions in Time: A History of Time Series Analysis 1662–1938. Cambridge, UK: Cambridge University Press.Google Scholar
Kortum, Samuel (1993) Equilibrium R&D and the patent–R&D ratio: U.S. evidence. American Economic Review 83, 450–457.Google Scholar
Kwan, Y.K. and Lai, E.L.C. (2003) Intellectual property rights protection and endogenous economic growth. Journal of Economic Dynamics and Control 27, 853–873.Google Scholar
Lee, Jeho and Harrison, J. Richard (2011) Innovation and industry bifurcation: The evolution of R&D strategy. Industrial and Corporate Change 20, 115–149.Google Scholar
Levy, David and Makowsky, Michael D. (2010) Price dispersion and increasing returns to scale. Journal of Economic Behavior and Organization 73, 406–417.Google Scholar
Levy, David M. and Peart, Sandra J. (2008) Thinking about analytical egalitarianism. American Journal of Economics and Sociology 67, 473–479.Google Scholar
Luke, Sean, Cioffi-Revilla, Claudio, Panait, Liviu, Sullivan, Keith, and Balan, Gabriel (2005) MASON: A multiagent simulation environment. SIMULATION 81, 517–527.Google Scholar
Luttmer, Erzo G.J. (2007) Selection, growth, and the size distribution of firms. Quarterly Journal of Economics 122, 1103–1144.Google Scholar
Lux, Thomas (2006) Financial Power Laws: Empirical Evidence, Models, and Mechanisms. Economics Working Papers 2006.12, Department of Economics, Christian-Albrechts-University of Kiel.Google Scholar
Nelson, Richard R. and Sidney, G. Winter (2002) Evolutionary theorizing in economics. Journal of Economic Perspectives 16, 23–46.Google Scholar
Nordhaus, W.D. (2007) Two centuries of productivity growth in computing. Journal of Economic History 67, 128–159.Google Scholar
O'Donoghue, Ted and Zweimüller, Josef (2004) Patents in a model of endogenous growth. Journal of Economic Growth 9, 81–123.Google Scholar
Pearson, Karl (1894) Contributions to the mathematical theory of evolution. Philosophical Transactions of the Royal Society of London A 185, 71–110.Google Scholar
Romer, Paul M. (1990) Endogenous technological change. Journal of Political Economy 98, S71–S102.Google Scholar
Romer, Paul M. (1994) The origins of endogenous growth. Journal of Economic Perspectives 8, 3–22.Google Scholar
SAS Institute (1989) SAS/STAT User's Guide. Cary, NC: SAS Institute.Google Scholar
Scherer, F.M., Harhoff, Dietmar, and Kukies, Jorg (2000) Uncertainty and the size distribution of rewards from innovation. Journal of Evolutionary Economics 10, 175–200.Google Scholar
Scotto, Manuel G. (2001) Hill estimator for the index of regular variation. Stata Technical Bulletin 10, 1–52.Google Scholar
Silverberg, Gerald and Verspagen, Bart (2007) The size distribution of innovations revisited: An application of extreme value statistics to citation and value measures of patent significance. Journal of Econometrics 139, 318–339Google Scholar
Tukey, John W. (1972) Some graphic and semigraphic displays. In Bancroft, T.A. and Brown, S.A. (eds.), Statistical Papers in Honor of George W. Snedecor, pp. 293–316. Ames: Iowa State University Press.Google Scholar
Tukey, John W. (1977) Exploratory Data Analysis. Reading, MA: Addison-Wesley.Google Scholar
Warsh, David (2006) Knowledge and the Wealth of Nations : A Story of Economic Discovery. New York: W.W. Norton.Google Scholar