Abstract
This paper presents the family of the Keynes+Schumpeter (K+S, cf. Dosi et al, J Econ Dyn Control 34 1748–1767 2010, J Econ Dyn Control 37 1598–1625 2013, J Econ Dyn Control 52 166–189 2015) evolutionary agent-based models, which study the effects of a rich ensemble of innovation, industrial dynamics and macroeconomic policies on the long-term growth and short-run fluctuations of the economy. The K+S models embed the Schumpeterian growth paradigm into a complex system of imperfect coordination among heterogeneous interacting firms and banks, where Keynesian (demand-related) and Minskian (credit cycle) elements feed back into the meso and macro dynamics. The model is able to endogenously generate long-run growth together with business cycles and major crises. Moreover, it reproduces a long list of macroeconomic and microeconomic stylized facts. Here, we discuss a series of experiments on the role of policies affecting i) innovation, ii) industry dynamics, iii) demand and iv) income distribution. Our results suggest the presence of strong complementarities between Schumpeterian (technological) and Keynesian (demand-related) policies in ensuring that the economic system follows a path of sustained stable growth and employment.
Similar content being viewed by others
Notes
According to such a paradigm, losses are inherent to the growth process, and also, normatively, technology policy measures should be expected to fail a good deal of the time, hoping for a few large successes (Scherer and Harhoff 2000).
Such coordination is not to be mistaken for strategic interactions among a few forward-looking firms. The latter is indeed incompatible with a Knightian uncertainty (Knight 1921) concerning the future path of technology advances as well as of demand in complex evolving systems.
The stock of capital of a new consumption-goods firm is obtained by multiplying the average stock of capital of the incumbents by a random draw from a Uniform distribution with support [ϕ 1, ϕ 2], 0 < ϕ 1, < ϕ 2 ≤ 1.
Here, as well as in Aghion and Howitt (2007), firms’ distance to the frontier affects the impact of different sets of policies, as well as the overall performance of the economic system.
The non-linearities present in agents’ decision rules and their interaction patterns require extensive Monte-carlo simulations to analyze the properties of the stochastic processes governing the coevolution of micro- and macro- variables, washing away across-simulation variability. Consequently, all results below refer to across-run averages over 100 replications. Admittedly, this whole exercise involves a major puzzle: should one wash out the inherent path-dependency of evolutionary processes? Should one account for within-path long-run dependency? But these questions are well beyond the scope of this work.
Interestingly, most statistical regularities concerning the structure of the economy appear to hold across an ample parameter range, under positive technological progress, even when policies undergo the changes we study in the following.
The results of the experiments concerning technology and industry policies are drawn from Dosi et al. (2010).
By replacing their leapfrogging assumption (the entrant innovator instantaneously takes over the entire market) with a “step-by-step” innovation process (the entrant has to catch-up with the technology - and tacit knowledge - of the incumbent before potentially becoming a leader), Aghion et al. (2013) explain that the effect of patent protection on innovation becomes more complex. In particular, the traditional incentive to innovate to escape competition is much attenuated in unleveled sectors, where laggards will prefer to catch-up with the leader by imitating than costly investing in R&D to innovate, given the remote probability that they may overtake the market.
References
Aghion P, Howitt P (1992) A model of growth through creative destruction. Econometrica 60:323–351
Aghion P, Howitt P (2007) Appropriate growth policy: a unifying framework. J Eur Econ Assoc 4:269–314
Aghion P, Askenazy P, Berman N, Cette G, Eymard L (2008) Credit constraints and the cyclicality of R&D investment: Evidence from France. J Eur Econ Assoc 10:1001–1024
Aghion P, Blundell R, Griffith R, Howitt P, Prantl S (2009) The effects of entry on incumbent innovation and productivity. Rev Econ Stat 91(1):20–32
Aghion P, Angeletos GM, Banerjee A, Manova K (2010) Volatility and growth: Credit constraints and the composition of investment. J Monet Econ 57 (3):246–265
Aghion P, Akcigit U, Howitt P (2013) What do we learn from Schumpeterian growth theory? Working Paper 18824, National Bureau of Economic Research
Aghion P, Hemous D, Kharroubi E (2014) Cyclical fiscal policy, credit constraints, and industry growth. J Monet Econ 62:41–58
Ashraf Q, Gershman B, Howitt P (2011) Banks, market organization, and macroeconomic performance: An agent-based computational analysis. Working Paper 17102, National Bureau of Economic Research
Ausloos M, Miskiewicz J, Sanglier M (2004) The durations of recession and prosperity: Does their distribution follow a power or an exponential law? Physica A 339:548–558
Bartelsman E, Doms M (2000) Understanding productivity: Lessons from longitudinal microdata. J Econ Lit 38:569–94
Bartelsman EJ, Scarpetta S, Schivardi F (2005) Comparative analysis of firm demographics and survival: Micro-level evidence for the oecd countries. Ind Corp Chang 14:365–391
Bellone F, Musso P, Nesta L, Quéré M (2008) Market selection along the firm life cycle. Ind Corp Chang 17(4):753–777
BIS (1999) Capital requirements and bank behaviour: The impact of the Basle accord. Working Papers 1, Bank for International Settlements
Bottazzi G, Secchi A (2003) Common properties and sectoral specificities in the dynamics of U.S. manufacturing firms. Rev Ind Organ 23:217–32
Bottazzi G, Secchi A (2006) Explaining the distribution of firm growth rates. RAND J Econ 37:235–256
Burns AF, Mitchell WC (1946) Measuring business cycles. NBER, New York
Castaldi C, Dosi G (2009) The patterns of output growth of firms and countries: Scale invariances and scale specificities. Empir Econ 37:475–495
Caves R (1998) Industrial organization and new findings on the turnover and mobility of firms. J Econ Lit 36:1947–1982
Ciarli T, Lorentz A, Savona M, Valente M (2010) The effect of consumption and production structure on growth and distribution. a micro to macro model. Metroeconomica 61(1):180–218
Cimoli M, Dosi G, Maskus K E, Okediji R L, Reichman J H (eds.) (2014) Intellectual property rights. Legal and Economic Challenges for Development, Oxford University Press
Dawid H, Gemkow S, Harting P, van der Hoog S, Neugart M (2014a) Agent-based macroeconomic modeling and policy analysis: The eurace@unibi model. In: Chen SH, Kaboudan M (eds) Handbook on Computational Economics and Finance. Oxford University Press, Oxford
Dawid H, Harting P, Neugart M (2014b) Economic convergence: Policy implications from a heterogeneous agent model. J Econ Dyn Control 44:54–80
Delli Gatti D, Di Guilmi C, Gaffeo E, Giulioni G, Gallegati M, Palestrini A (2005) A new approach to business fluctuations: Heterogeneous interacting agents, scaling laws and financial fragility. J Econ Behav Organ 56:489–512
Delli Gatti D, Gallegati M, Greenwald B, Russo A, Stiglitz J (2010) The financial accelerator in an evolving credit network. J Econ Dyn Control 34:1627–1650
Di Guilmi C, Gallegati M, Ormerod P (2004) Scaling invariant distributions of firms’ exit in OECD countries. Phys A 334:267–273
Doms M, Dunne T (1998) Capital adjustment patterns in manufacturing plants. Rev Econ Dyn 1:409–29
Dosi G (2007) Statistical regularities in the evolution of industries. a guide through some evidence and challenges for the theory. In: Malerba F, Brusoni S (eds) Perspectives on innovation. Cambridge University Press, Cambridge MA
Dosi G (2012) Economic coordination and dynamics: Some elements of an alternative “evolutionary” paradigm. Working Paper 2012/08, LEM Working Paper Series
Dosi G, Nelson RR (2010) Technological change and industrial dynamics as evolutionary processes. In: Hall B H, Rosenberg N (eds) Handbook of the economics of innovation. Elsevier, Amsterdam, chap, p 4
Dosi G, Freeman C, Nelson R, Silverberg G, Soete L (1988) Technical change and economic theory, vol 988. Pinter London
Dosi G, Malerba F, Marsili O, Orsenigo L (1997) Industrial structures and dynamics: evidence, interpretations and puzzles. Ind Corp Chang 6:3–24
Dosi G, Fagiolo G, Roventini A (2006) An evolutionary model of endogenous business cycles. Comput Econ 27:3–34
Dosi G, Fagiolo G, Roventini A (2008) The microfoundations of business cycles: an evolutionary, multi-agent model. J Evol Econ 18:413–432
Dosi G, Fagiolo G, Roventini A (2010) Schumpeter meeting Keynes, a policy-friendly model of endogenous growth and business cycles. J Econ Dyn Control 34:1748–1767
Dosi G, Fagiolo G, Napoletano M, Roventini A (2013) Income distribution, credit and fiscal policies in an agent-based keynesian model. J Econ Dyn Control 37:1598–1625
Dosi G, Fagiolo G, Napoletano M, Roventini A, Treibich T (2015) Fiscal and monetary policies in complex evolving economies. J Econ Dyn Control 52:166–189
Dosi G, Napoletano M, Roventini S, Stiglitz J, Treibich T (2016a) Expectation formation, fiscal policies and macroeconomic performance when agents are heterogeneous and the world is changing. LEM Working Paper forthcoming, Scuola Superiore Sant’Anna
Dosi G, Pereira M, Roventini A, Virgillito M (2016b) When more flexibility yields more fragility: The microfoundations of keynesian aggregate unemployment. LEM Working Paper 2016/06, Scuola Superiore Sant’Anna
Fagiolo G, Roventini A (2012) On the scientific status of economic policy: a tale of alternative paradigms. Knowl Eng Rev 27:163–185
Fagiolo G, Napoletano M, Roventini A (2008) Are output growth-rate distributions fat-tailed? Some evidence from OECD countries. J Appl Econom 23:639–669
Foos D, Norden L, Weber M (2010) Loan growth and riskiness of banks. J Bank Financ 34:2929–2940
G. Fagiolo AM, Windrum P (2007) A critical guide to empirical validation of agent-based models in economics: methodologies, procedures, and open problems. Comput Econ 30:195–226
Greenwald B, Stiglitz J (1993) Financial market imperfections and business cycles. Q J Econ 108:77–114
Hubbard GR (1998) Capital-market imperfections and investment. J Econ Lit 36:193–225
Jaimovich N, Floetotto M (2008) Firm dynamics, markup variations, and the business cycle. J Monet Econ 55:1238–1252
Knight F (1921) Risk, uncertainty and profits. Chicago University Press, Chicago
Kuznets S, Murphy JT (1966) Modern Economic Growth: Rate, Structure, and Spread. Yale University Press, New Haven
Laeven L, Valencia F (2008) Systemic banking crises: A new database. Working Paper WP/08/224, International Monetary Fund
Lamperti F, Dosi G, Napoletano M, Roventini A, Sapio S (2016) Faraway, so close: an agent-based model for climate energy and macroeconomic policy. LEM Working Paper forthcoming, Scuola Superiore Sant’Anna
Leary M (2009) Bank loan supply, lender choice, and corporate capital structure. J Financ 64:1143–1185
Leijonhufvud A (1973) Effective demand failures. Swed J Econ:27–48
Levine R (1997) Financial development and economic growth: Views and agenda. J Econ Lit:688–726
Lown C, Morgan D (2006) The credit cycle and the business cycle: New findings using the loan officer opinion survey. J Money, Credit, Bank 38:1575–1597
Mandel A, Jaeger C, Fuerst S, Lass W, Lincke D, Meissner F, Pablo-Marti F, Wolf S, etal (2010) Agent-based dynamics in disaggregated growth models. CES Working Paper 2010.77, Université Paris 1 Panthéon Sorbonne
Mendoza E, Terrones M (2012) An anatomy of credit booms and their demise. Working Paper 18379, National Bureau of Economic Research
Metcalfe JS (1994) Competition, Fisher’s principle and increasing returns to selection. J Evol Econ 4:327–346
Minsky H (1983) Money and crisis in schumpeter and keynes. Working Paper 58 Washington University St. Louis, Missouri
Minsky H (1986) Stabilizing an unstable economy. Yale University Press, New Haven
Myers S, Majluf N (1984) Corporate financing and investment decisions when firms have information that investors do not have. J Financ Econ 13:187–221
Napoletano M, Roventini A, Sapio S (2006) Are business cycles all alike? a bandpass filter analysis of the italian and us cycles. Rivista Italiana degli Economisti 1:87–118
Napoletano M, Dosi G, Fagiolo G, Roventini A (2012) Wage formation, investment behavior and growth regimes: an agent-based analysis. Revue de l’OFCE 124:235–261
Nelson RR, Winter SG (1982) An evolutionary theory of economic change. The Belknap Press of Harvard University Press, Cambridge
Piketty T (2014) Capital in the Twenty-First Century. Belknap Press
Raberto M, Cincotti S, Teglio A (2014) Fiscal consolidation and sovereign debt risk in balance-sheet recessions: an agent-based approach. In: Mamica L, Tridico P (eds) Economic Policy and the Financial Crisis, Routledge
Reinhart C, Rogoff K (2009) The aftermath of financial crises. Working Paper 14656, National Bureau of Economic Research
Riccetti L, Russo A, Gallegati M (2013) Leveraged network-based financial accelerator. J Econ Dyn Control 37:1626–1640
Scherer FM, Harhoff D (2000) Technology policy for a world of skew-distributed outcomes. Res Policy 29:559–566
Stiglitz J (1994) Endogenous growth and cycles. In: Shionoya Y, Perlman M (eds) Innovation in technology, industries, and institutions. Studies in schumpeterian perspectives. The University of Michigan Press, Ann Arbor
Stiglitz J (2012) The Price of Inequality: How Today’s Divided Society Endangers Our Future. W. W. Norton and Company
Stiglitz J (2014) Reconstructing macroeconomic theory to manage economic policy. Working Paper 20517, National Bureau of Economic Research
Stiglitz J, Weiss A (1981) Credit rationing in markets with imperfect information. Am Econ Rev 71:393–410
Stock J, Watson M (1999) Business cycle fluctuations in U.S. macroeconomic time series. In: Taylor J, Woodford M (eds) Handbook of Macroeconomics. Elsevier, Amsterdam, The Netherlands, pp 3–64
Tesfatsion L (2006) ACE: A constructive approach to economic theory. In: Tesfatsion L, Judd K (eds) Handbook of Computational Economics II: Agent-Based Computational Economics, Amsterdam, North Holland
Walde K, Woitek U (2004) R&d Expenditure in G7 countries and the implications for endogenous fluctuations and growth. Econ Lett 82:91–97
Woodford M (2003) Interest and prices: Foundations of a theory of monetary policy princeton. Princeton University Press, NJ
Wright I (2005) The duration of recessions follows an exponential not a power law. Physica A 345(3):608–610
Zarnowitz V (1985) Recent works on business cycles in historical perspectives: a review of theories and evidence. J Econ Lit 23:523–80
Acknowledgments
Thanks, with all usual disclaimers, to Giorgio Fagiolo, as well to participants to the workshop “Schumpeter and the Schumpeterians on economic policy issues” organized in Amiens, May 2014— in particular, Agnès Festré. The authors gratefully acknowledge the financial support of the Institute for New Economic Thinking (INET) grants #220, “The Evolutionary Paths Toward the Financial Abyss and the Endogenous Spread of Financial Shocks into the Real Economy” and INO12-00039, “INET Task force in Macroeconomic Efficiency and Stability”.
Author information
Authors and Affiliations
Corresponding author
Appendix
Appendix
Rights and permissions
About this article
Cite this article
Dosi, G., Napoletano, M., Roventini, A. et al. Micro and macro policies in the Keynes+Schumpeter evolutionary models. J Evol Econ 27, 63–90 (2017). https://doi.org/10.1007/s00191-016-0466-4
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00191-016-0466-4
Keywords
- Agent-based model
- Innovation
- Evolution
- Innovation policies
- Macroeconomic policies
- Income inequality
- Disequilibrium dynamics