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In this work we study the granular origins of business cycles and their possible underlying drivers. As shown by Gabaix (2011), the skewed nature of firm size distributions implies that idiosyncratic (and independent) firm-level shocks may account for a significant portion of aggregate volatility. Yet, we question the original view grounded on “supply granularity”, as proxied by productivity growth shocks – in line with the Real Business Cycle framework–, and we provide empirical evidence of a “demand granularity”, based on investment growth shocks instead. The role of demand in explaining aggregate fluctuations is further corroborated by means of a macroeconomic Agent-Based Model of the “Schumpeter meeting Keynes” family (Dosi et al., 2015). Indeed, the investigation of the possible microfoundation of RBC has led us to the identification of a sort of microfounded Keynesian multiplier.

We analyze the individual and macroeconomic impacts of heterogeneous expectations and action rules within an agent-based model populated by heterogeneous, interacting firms. Agents have to cope with a complex evolving economy characterized by deep uncertainty resulting from technical change, imperfect information and coordination hurdles. In these circumstances, we find that neither individual nor macroeconomic dynamics improve when agents replace myopic expectations with less näive learning rules. In fact, more sophisticated, e.g. recursive least squares (RLS) expectations produce less accurate individual forecasts and also considerably worsen the performance of the economy. Finally, we experiment with agents that adjust simply to technological shocks, and we show that individual and aggregate performances dramatically degrade. Our results suggest that fast and frugal robust heuristics are not a second-best option: rather they are "rational" in macroeconomic environments with heterogeneous, interacting agents and changing "fundamentals".

We develop an agent-based model in which heterogeneous firms and households interact in labor and good markets according to centralized or decentralized search and matching protocols. As the model has a deterministic backbone and a full-employment equilibrium, it can be directly compared to Dynamic Stochastic General Equilibrium (DSGE) models. We study the effects of negative productivity shocks by way of impulse-response func- tions (IRF). Simulation results show that when search and matching are centralized, the economy is always able to return to the full employment equilibrium and IRFs are similar to those generated by DSGE models. However, when search and matching are local, co- ordination failures emerge and the economy persistently deviates from full employment. Moreover, agents display persistent heterogeneity. Our results suggest that macroeco- nomic models should explicitly account for agents’ heterogeneity and direct interactions

In this work we analyze the short- and long-run effects of fiscal austerity policies, employing an agent-based model populated by heterogeneous, boundedly-rational firms and banks. The model, in line with the family of "Keynes+Schumpeter" formalism, is able to account for a wide array of macro and micro empirical regularities. In particular, it endogenously generates self-sustained growth patterns together with persistent economic fluctuations punctuated by deep downturns. On the policy side, we find that austerity policies considerably harm the economy, by increasing output volatility, unemployment, and the incidence of crises. In addition, they depress innovation and the diffusion of new technologies, thus reducing long-run productivity and GDP growth. Finally, we show that "discipline-guided" fiscal rules are self-defeating, as they do not stabilize public finances, but, on the contrary, they disrupt them.

In this work we analyze the short- and long-run effects of fiscal austerity policies, employing an agent-based model populated by heterogeneous, boundedly-rational firms and banks. The model, in line with the family of "Keynes+Schumpeter" formalism, is able to account for a wide array of macro and micro empirical regularities. In particular, it endogenously generates self-sustained growth patterns together with persistent economic fluctuations punctuated by deep downturns. On the policy side, we find that austerity policies considerably harm the economy, by increasing output volatility, unemployment, and the incidence of crises. In addition, they depress innovation and the diffusion of new technologies, thus reducing long-run productivity and GDP growth. Finally, we show that "discipline-guided" fiscal rules are self-defeating, as they do not stabilize public finances, but, on the contrary, they disrupt them.

In this work we analyze the short- and long-run effects of fiscal austerity policies, employing an agent-based model populated by heterogeneous, boundedly-rational firms and banks. The model, in line with the family of “Keynes+Schumpeter” formalism, is able to account for a wide array of macro and micro empirical regularities. In particular, it endogenously generates self-sustained growth patterns together with persistent economic fluctuations punctuated by deep downturns. On the policy side, we find that austerity policies considerably harm the economy, by increasing output volatility, unemployment, and the incidence of crises. In addition, they depress innovation and the diffusion of new technologies, thus reducing long-run productivity and GDP growth. Finally, we show that “discipline-guided” fiscal rules are self-defeating, as they do not stabilize public finances, but, on the contrary, they disrupt them.

This paper presents the family of the Keynes+Schumpeter (K+S, cf. Dosi et al, 2010, 2013, 2014) 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

This paper presents the family of the Keynes+Schumpeter (K+S, cf. Dosi et al, 2010, 2013, 2014) 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.