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We build a simple dynamic model to study the effects of technological learning, market selection and international competition in the determination of export flows and market shares. The model features two countries populated by firms with heterogeneous productivity levels and sales. Market selection in each country is driven by a finite pairwise Pólya urn process. We show that market selection leads either to a national or to an international monopoly in presence of a static distribution of firm productivity levels. We then incorporate firm learning and entry-exit in the model and we show that the market structure does not converge to a monopoly. In addition, we show that the extended model is able to jointly reproduce a wide ensemble of stylized facts concerning intra-industry trade, industry and firm dynamics.

We investigate upon the shape and the determinants of the age distribution of business firms. By employing a novel dataset covering the population of French businesses, we highlight that a geometric law provides a reasonable approximation for the age distribution. However, relevant systematic deviations and sectoral heterogeneity appear. We develop a stochastic model of firm dynamics to explain the mechanisms behind this evidence and relate them to business dynamism. Results reveal a long-term decline in entry rates and lower survival probabilities of young firms. Our findings bear important implications for aggregate outcomes, notably employment growth.

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 functions (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, coordination failures emerge and the economy persistently deviates from full-employment. Moreover, agents display persistent heterogeneity. Our results suggest that macroeconomic models should explicitly account for agents' heterogeneity and direct interactions. Moreover, our results point to the role of quantity adjustments in determining the ability of the economy to return or not to full-employment.

In this paper, we investigate the causal effects of public and private debts on US output dynamics. We estimate a battery of Cointegrated Structural Vector Autoregressive models, and we identify structural shocks by employing Independent Component Analysis, a data-driven technique which avoids ad-hoc identification choices. The econometric results suggest that the impact of debt on economic activity isJanus-faced. Public debt shocks have positive and persistent influence on economic activity. In contrast, rising private debt has a milder positive impact on gross domestic product, but it fades out over time. The analysis of the possible transmission mechanisms reveals that public debtcrowds inprivate consumption and investment. In contrast, mortgage debt fuels consumption and output in the short-run, but shrinks them in the medium-run.

Since the survey by Windrum et al. (Journal of Artificial Societies and Social Simulation 10:8, 2007), research on empirical validation of agent-based models in economics has made substantial advances, thanks to a constant flow of high-quality contributions. This Chapter attempts to take stock of such recent literature to offer an updated critical review of the existing validation techniques. We sketch a simple theoretical framework that conceptualizes existing validation approaches, which we examine along three different dimensions: (i) comparison between artificial and real-world data; (ii) calibration and estimation of model parameters; and (iii) parameter space exploration. Finally, we discuss open issues in the field of ABM validation and estimation. In particular, we argue that more research efforts should be devoted toward advancing hypothesis testing in ABM, with specific emphasis on model stationarity and ergodicity.

In this paper we discuss some of the monetary policy issues that have involved major central banks worldwide since the 2008 financial crisis, and which remain open. We provide an ex-cursus of the unconventional monetary policies adopted by central banks in the last decade, focusing on the European Central Bank and the Federal Reserve, and we discuss the rationale and efficacy of some unconventional monetary instruments, of inflation targeting and of central bank independence. We also provide a perspective on possible future developments of monetary policy. We argue that while unconventional monetary policy was useful, there is still ample space for improvement: in the recessions to come, unconventional monetary policy will need to be better coordinated with fiscal, micro- and macro-prudential policies to provide more inclusive results that might positively affect the real economy beyond the financial system.

We develop a new method to estimate the parameters of threshold distributions for market participation based on an agent-specific attribute and its decision outcome. This method requires few behavioral assumptions, is not data demanding, and can adapt to various parametric distributions. An application to export decisions by French firms shows that threshold distributions are generally right-skewed. We then reveal the asymmetric effects of past policies over different quantiles of the threshold distributions.

This paper proposes a new method to empirically validate simulation models that generate artificial time series data comparable with real-world data. The approach is based on comparing structures of vector autoregression models which are estimated from both artificial and real-world data by means of causal search algorithms. This relatively simple procedure is able to tackle both the problem of confronting theoretical simulation models with the data and the problem of comparing different models in terms of their empirical reliability. Moreover the paper provides an application of the validation procedure to the agent-based macroeconomic model proposed by Dosi et al. (2015).

We develop a model to study the impact of corporate governance on firm investment decisions and industry competition. In the model, governance structure affects the distribution of shares among short- and long-term oriented investors, the robustness of the management regarding possible stockholder interference, and the managerial remuneration scheme. A bargaining process between firm’s stakeholders determines the optimal allocation of financial resources between real investments in R&D and financial investments in shares buybacks. We characterize the relation between corporate governance and firm’s optimal investment strategy and we study how different governance structures shape technical progress and the degree of competition over the industrial life cycle. Numerical simulations of a calibrated set-up of the model show that pooling together industries characterized by heterogeneous governance structures generate the well-documented inverted-U shaped relation between competition and innovation.