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Micro and macro policies in the Keynes+Schumpeter evolutionary models

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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.

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Notes

  1. 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).

  2. 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.

  3. For germane ABMs, see Ciarli et al. (2010), Mandel et al. (2010), Delli Gatti et al. (2005), Delli Gatti et al. (2010), Ashraf et al. (2011), Dawid et al. (2014a), Dawid et al. (2014b), Raberto et al. (2014), and Riccetti et al. (2013).

  4. 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.

  5. 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.

  6. 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.

  7. Details of the validation exercise are not included here due to space limitations. See Dosi et al. (2006), Dosi et al. (2008), Dosi et al. (2010), Dosi et al. (2013), and Dosi et al. (2015) and (Napoletano et al. 2012) for more discussions.

  8. 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.

  9. In Napoletano et al. (2012) and Dosi et al. (2013) and Dosi et al. (2015) we also consider statistics related to the probability of large crises.

  10. The results of the experiments concerning technology and industry policies are drawn from Dosi et al. (2010).

  11. 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.

  12. This is in line with the intuitions of Stiglitz (2012) and Piketty (2014) about the existence of a vicious downward spiral of excessive inequality and economic instability.

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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”.

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Authors and Affiliations

  1. Institute of Economics (LEM), Scuola Superiore Sant’Anna, Piazza Martiri della Libertá 33, I-56127, Pisa, Italy

    Giovanni Dosi, Mauro Napoletano, Andrea Roventini & Tania Treibich

  2. Skema Business School, Sophia-Antipolis, France

    Mauro Napoletano

  3. OFCE, Sophia-Antipolis, France

    Mauro Napoletano, Andrea Roventini & Tania Treibich

  4. Maastricht University, Maastricht, the Netherlands

    Tania Treibich

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  1. Giovanni Dosi
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  2. Mauro Napoletano
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  4. Tania Treibich
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Correspondence to Giovanni Dosi.

Appendix

Appendix

Table 6 Benchmark Parameters
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Table 7 Parameters of interest in the policy experiments
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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

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