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Dr Corrado Di Guilmi


Corrado is Senior Lecturer at the Economics Discipline Group. He joined UTS in November 2008 as a Post Doctoral Research Fellow. He earned his PhD in at the Università Politecnica delle Marche (Italy). He was visiting fellow at the Department of Economics of the University of Cambridge, the Department of Applied Mathematics of the Australia National University, the New School for Social Research in New York and the Fondacao Getulio Vargas in Sao Paulo.

His early research work focussed on the empirical analysis of firms' financial heterogeneity and its impact on growth and fluctuations of aggregate output. He subsequently theoretically investigated this topic using agent based modeling techniques.
His PhD dissertation proposed an analytical solution methods for models with heterogeneous agents by introducing in macroeconomics stochastic aggregation techniques originally developed in statistical mechanics. In recent years he has applied these method to further investigate the effects of micro-financial fragility on business cycle and growth, re-elaborating the Post-Keynesian tradition and in particular the work of Hyman Minsky.
Corrado has published several papers in international refereed journals.
He is presently co-director of the program in Behavioural Macroeconomics and Complexity at the Centre of Applied Macroeconomic Analysis at ANU.

Personal website and up-to-date CV:  https://sites.google.com/site/corradodiguilmi/

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Senior Lecturer, Economics Discipline Group
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Research Interests

Business fluctuations and cycles, Agent-based and dynamic models, Complex systems

Can supervise: Yes


Di Guilmi, C., Gallegati, M. & Landini, S. 2016, Interactive Macroeconomics, Cambridge University Press.
Di Guilmi, C. 2008, The Generation of Business Fluctuations: Financial Fragility and Mean-Field Interactions, 1st, Peter Lang, USA.
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The limits imposed on economic modeling by the representative agent hypothesis have prevented dynamic analysis from fully exploring the links between the micro and macro level of the economic system. This book presents developments and applications of the innovative techniques of dynamic stochastic aggregation, first proposed by Masanao Aoki, through an implementation in a New Keynesian financial fragility framework. The introduction in macroeconomics of statistical mechanics tools, such as mean-field interaction, statistical entropy and master equation, constitutes a step toward a new definition of microfoundation and allows an integrated modeling of the relationships between micro financial variables and aggregate indicators.


Landini, S., Gallegati, M., Stiglitz, J.E. & Di Guilmi, C. 2014, 'Learning and Macro-Economic Dynamics' in Dieci, R., He, X.Z. & Hommes, C. (eds), Nonlinear Economic Dynamics and Financial Modelling, Springer, Germany.
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This chapter focuses on the relevance of the learning activity in an economy populated by many heterogeneous and interacting financially constrained firms. The economy is represented as an Agent-Based Model (ABM), which constitutes the data generating process (DGP) of the aggregate observables. Following the line of a companion chapter Landini et al. 2014, agents learn and make decisions, according to the notion of 'social atom. The artificial economy is a complex system whose evolution can be predicted inferentially. The analysis of the ABM-DGP aggregate observables is analysed by means of master equations and combinatorial master equations. Inference results confirm the relevance of learning providing insights in two main directions: (a) a new perspective for the micro-foundation of macro models; (b) an interpretation of the system phase transitions.
Chiarella, C. & Di Guilmi, C. 2013, 'A reconsideration of the formal Minskyan analysis: Microfoundations, endogenous money and the public sector' in Bischi, G.I., Chiarella, C. & Sushko, I. (eds), Global analysis of dynamic models in economics and finance: Essays in honour of Laura Gardini, Springer, Germany, pp. 63-81.
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The paper presents a survey of the literature that has grown out of the work of Hyman Minsky and, in particular, of the main models which have mathematically formalised the cyclical dynamics of a capitalist economy implied by the Financial Instability Hypothesis. We identify some of the issues that the existing literature has left unsolved. We then briefly summarise the contributions by Chiarella and Di Guilmi (J Econ Dyn Control 35(8):11511171, 2011c) and (Stud Nonl Dyn Econom forthcoming, 2012), highlighting how these papers have addressed the open questions and how they could be further developed.
Di Guilmi, C., Gallegati, M. & Landini, S. 2010, 'Financial fragility, mean-field interaction and macroeconomic dynamics: A stochastic model' in Salvadori, N. (ed), Institutional and Social Dynamics of Growth and Distribution, Edward Elgar, UK, pp. 322-350.
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In recent decades, a considerable stream of research, following the complexity approach (Rosser, 2004), has developed a series of models that import concepts and tools from hard sciences to economics. They represent an attempt to identify an alternative framework to the representative agent hypothesis and to its underlying simplified solution to the aggregation problem (Kirman, 1992). Theoretical research has moved in two main directions: first, the development of agent-based models, solved by means of computer simulations (Axtell et al., 1996; Axelrod, 1997); second, formulations of stochastic frameworks for the aggregation of micro-variables (Aoki, 1996, 2002; Aoki and Yoshikawa, 2006).
Delli Gatti, D., Di Guilmi, C., Gaffeo, E., Gallegati, M., Giulioni, G. & Palestrini, A. 2005, 'Firms' size distribution and growth rates as determinants of business fluctuations' in Kirman, A. & Salzano, M. (eds), Economics: Complex Windows, Springer, US, pp. 181-186.
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Chiarella, C., Di Guilmi, C. & Zhi, T. 2014, 'Modelling the 'Animal Spirits of Bank's Lending Behaviour', Society for Nonlinear Dynamics and Econometrics 22nd Annual Symposium, New York, USA.
Chiarella, C. & Di Guilmi, C. 2012, 'A reconsideration of the formal Minskyan analysis: Microfoundations, endogenous money and the public sector', MDEF2012, Urbino, Italy.
Di Guilmi, C. 2011, 'An analytical solution for agent based models', The Paul Woolley Centre for Capital Market Dysfunctionality 2011 Conference, Sydney Australia.
Di Guilmi, C. 2010, 'Limit distribution of evolving strategies in financial markets', 11th Workshop on Optimal Control, Dynamic Games and Nonlinear Dynamics, Amsterdam, The Netherlands.
Chiarella, C. & Di Guilmi, C. 2010, 'Debt deflation dynamics in a heterogenous agent economy', 16th International Conference on Computing in Economics and Finance, London, UK.
Di Guilmi, C. 2010, 'Financial instability hypothesis: A stochastic microfoundation framework', Interacting Agents and Nonlinear Dynamics in Macroeconomics, Udine, Italy.
Di Guilmi, C. 2010, 'The financial instability hypothesis: A stochastic microfoundation', The Hyman P. Minsky Summer Seminar and Conference, New York, USA.
Di Guilmi, C. 2010, 'Debt deflation dynamics in a heterogenous agents economy', 39th Australian Conference of Economists, Sydney, Australia.
Di Guilmi, C. 2010, 'Financial instability hypothesis: A stochastic microfoundation framework', Eastern Economic Association 36th Annual Conference, Philadelphia, USA.
Chiarella, C. & Di Guilmi, C. 2009, 'Financial instability hypothesis: A stochastic microfoundation framework', Workshop on the Complexity of Financial Crisis in a Long-Period Perspective: Facts, Theory and Models, Sienna, Italy.
Di Guilmi, C. 2009, 'Financial instability hypothesis: A stochastic microfoundation framework', Paul Woolley Centre for Capital Market Dysfunctionality 2009 Annual Conference, Sydney, Australia.
Chiarella, C. & Di Guilmi, C. 2009, 'Financial instability hypothesis: A stochastic microfoundation framework', The Sixth International Workshop on Agent-based Approaches in Economic and Social Complex Systems, Taipei, Taiwan.
Chiarella, C. & Di Guilmi, C. 2009, 'Financial instability hypothesis: A stochastic microfoundation framework', 8th Annual Meeting of the European Economics and Finance Society International Conference, Warsaw, Poland.

Journal articles

Di Guilmi, C. & Chiarella, C. 2016, 'Monetary Policy and Debt Deflation: Some Computational Experiments,', Macroeconomic Dynamics.
Chiarella, C. & Di Guilmi, C. 2015, 'The limit distribution of evolving strategies in financial markets', Studies in Nonlinear Dynamics and Econometrics, vol. 19, no. 2, pp. 137-159.
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This paper reconsiders the popular Brock and Hommes [Brock, W. A., and C. H. Hommes. 1997. 'A Rational Route to Randomness.' Econometrica 65: 1059-1096.] framework for the study of the evolution of agents' choices when different behavioural strategies are available. In particular, we model the intensity of choice as an endogenous variable and not a parameter as it is commonly treated in the literature. We make use of the maximum entropy inference to obtain an analogous exponential type probability function for strategies, with the intensity of choice varying over time according to the performance of each strategy. We test this approach on an existing asset pricing model, highlighting the effects on the system of the different switching pattern that originate in the endogenous switching intensity.
Chiarella, C. & Di Guilmi, C. 2014, 'Financial instability and debt deflation dynamics in a bottom-up approach', Economics Bulletin, vol. 34, no. 1, pp. 125-132.
Di Guilmi, C., He, X. & Li, K. 2014, 'Herding, trend chasing and market volatility', Journal of Economic Dynamics and Control, vol. 48, pp. 349-373.
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Chiarella, C. & Di Guilmi, C. 2012, 'The fiscal cost of financial instalbility', Studies in NonLinear Dynamics and Econometrics, vol. 16, no. 4, pp. 1-27.
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This paper presents an agent based model that investigates the possible outcomes of different fiscal and regulatory policies in a financially fragile economy. We analyse the consequences of the attempt by the government to counteract a downturn when it ignores the debt dynamics as modelled by Fisher and Minsky. In particular, we formulate an educated guess about the burden that the government and the taxpayer must bear when a bubble bursts, and its relationship with the extent of government intervention and the taxation system. We also evaluate the outcomes of possible alternatives or complementary regulatory policies. We model four different scenarios treating separately a tax on profits and a tax on private wealth and, for both of them, we specify two cases depending on whether the financial system is able to autonomously generate liquidity. Therefore, we can assess the effect of endogenous money and endogenous credit on the different stabilization policies.
Gaffeo, E., Di Guilmi, C., Gallegati, M. & Russo, A. 2012, 'On The Mean/variance Relationship Of The Firm Size Distribution: Evidence And Some Theory', Ecological Complexity, vol. 11, no. NA, pp. 109-117.
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Firm-level data fora small sample of European countries are used to provide evidence of a positive linear relationship between the mean and the variance of firms' size at a sectoral level, an empirical regularity known in mathematical biology and ecology
Delli Gatti, D., Di Guilmi, C., Gallegati, M. & Landini, S. 2012, 'Reconstructing Aggregate Dynamics in Heterogeneous Agents Models', Revue de l'OFCE, vol. 124, no. 5, pp. 117-117.
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Chiarella, C. & Di Guilmi, C. 2011, 'The financial instability hypothesis: A stochastic microfoundation framework', Journal of Economic Dynamics and Control, vol. 35, no. 8, pp. 1151-1171.
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This paperexaminesthedynamicsoffinancialdistressandinparticularthemechanism of transmissionofshocksfromthefinancialsectortotherealeconomy.Theanalysisis performedbyrepresentingthelinkagesbetweenmicroeconomicfinancialvariablesand the aggregateperformanceoftheeconomybymeansofamicrofoundedmodelwith firms thathaveheterogeneouscapitalstructures.Themodelissolvedbothnumerically and analytically,bymeansofastochasticapproximationthatisabletoreplicatequite well thenumericalsolution.Thesemethodologies,byovercomingtherestrictions imposedbythetraditionalmicrofoundedapproach,enableustoprovidesomeinsights into thestabilizationpolicieswhichmaybeeffectiveinafinanciallyfragilesystem.
Delli Gatti, D., Di Guilmi, C., Gallegati, M., Gaffeo, E., Giulioni, G. & Palestrini, A. 2008, 'Scaling laws in the macroeconomy', Advances in Complex Systems, vol. 11, no. 1, pp. 131-138.
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The practice of detecting power laws and scaling behaviors in economics and finance has gained momentum in the last few years, due to the increased use of concepts and methods first developed in statistical physics. Some disappointment has emerged in the economic profession, however, as regards the models proposed so far to theoretically explain these phenomena. In this paper we aim to address this criticism, showing that scaling behaviors can naturally emerge in a multiagent system with optimizing interacting units characterized by financial fragility
Di Guilmi, C., Clementi, F., Di Matteo, T. & Gallegati, M. 2008, 'Social networks and labor productivity in Europe: An empirical investigation', Journal of Economic Interaction and Coordination, vol. 3, no. 1, pp. 43-57.
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This paper uses firm-level data recorded in the Amadeus database to investigate the distribution of labour productivity in different European countries. We find that the upper tail of the empirical productivity distributions follows a decaying power-law, whose exponent ? is obtained by a semi-parametric estimation technique recently developed by Clementi et al. [Physica A 370(1):4953, 2006]. The emergence of fat tails in productivity distribution has already been detected in Di Matteo et al. [Eur Phys J B 47(3):459466, 2005] and explained by means of a model of social network. Here we show that this model is tested on a broader sample of countries having different patterns of social network structure. These different social attitudes, measured using a social capital indicator, reflect in the power-law exponent estimates, verifying in this way the existence of linkages among firms productivity performance and social network.
LANDINI, S.I.M.O.N.E., DI GUILMI, C.O.R.R.A.D.O. & GALLEGATI, M.A.U.R.O. 2008, 'A MAXENT MODEL FOR MACROSCENARIO ANALYSIS', Advances in Complex Systems, vol. 11, no. 05, pp. 719-744.
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Di Guilmi, C., Gallegati, M. & Landini, S. 2008, 'Economic dynamics with financial fragility and mean-field interaction: A model', Physica A: Statistical Mechanics and its Applications, vol. 387, no. 15, pp. 3852-3861.
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Delli Gatti, D., Di Guilmi, C., Gallegati, M. & Giulioni, G. 2007, 'Financial Fragility, Industrial Dynamics and Business Fluctuations in an Agent Based Model', Macroeconomic Dynamics, vol. 11, no. S1, pp. 62-79.
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n the 1990s a large body of literature--sometimes referred to as the financial accelerator hypothesis, broad credit view, or balance sheet channel--focused on the role of financial factors in business fluctuations and in the transmission of monetary shocks [Bernanke and Gertler (1989, 1990, 1995), Bernanke et al. (1996, 1999), Greenwald and Stiglitz (1988, 1990, 1993), Stiglitz and Greenwald (2003)]. Insightful new additions to the literature, albeit along different lines, have been provided by Kiyotaki and Moore (1997, 2002) and Cooley and Quadrini (2001). In these models, in principle, agents are heterogeneous, and sometimes it is also recognized that heterogeneity is a necessary ingredient of important business cycle features (such as composition effects), but the nature and consequences of heterogeneity are not thoroughly explored. At a certain point of the analysis, the representative agent pops up and heterogeneity gets lost or is simply neglected. The temptation to keep the analysis simple by resorting to the representative agent is understandable. After all, the representative agent framework has been one of the most successful tools in economics [Hartley (1997); Stoker (1993)] and is still the cornerstone of standard macroeconomics. This modeling strategy, however, is justified if heterogeneity is temporary, that is, if the population of different households/firms converges over time to a stationary distribution in which agents are identical. This condition is generally not fulfilled empirically. In real economies heterogeneity is not bound to disappear and the evolution over time of the distribution of heterogeneous agents affects the dynamics of the macrovariables. If macroeconomic modeling relies on the representative agent, therefore, the analysis of business fluctuations and of the transmission mechanism of monetary policy will be too simple and sometimes even simplistic.
Di Guilmi, C., Gaffeo, E., Gallegati, M. & Palestrini, A. 2005, 'International evidence on business cycle magnitude dependence', International Journal of Applied Econometrics and Quantitative Studies, vol. 2, no. 1, pp. 5-16.
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Are expansions and recessions more likely to end as their magnitude increases? In this paper we apply parametric hazard models to investigate this issue in a sample of 16 countries from 1881 to 2000. For the total sample we find evidence of positive magnitude dependence for recessions, while for expansions we are not able to reject the null of magnitude independence. This last result is likely due to a structural change in the mechanism guiding expansions before and after the second World War. In particular, upturns show negative magnitude dependence in the post-World War II sub-sample, meaning that in this period expansions become less likely to end as their magnitude increases.
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', Journal of Economic Behavior and Organization, vol. 56, no. 4, pp. 489-512.
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In this paper, we discuss a scaling approach to business fluctuations. Our starting point consists in recognizing that concepts and methods derived from physics have allowed economists to (re)discover a set of stylized facts which have to be satisfactorily accounted for in their models. Standard macroeconomics, based on a reductionist approach centered on the representative agent, is definitely badly equipped for this task. On the contrary, we show that a simple financial fragility agent-based model, based on complex interactions of heterogeneous agents, is able to replicate a large number of scaling type stylized facts with a remarkable high degree of statistical precision.
Delli Gatti, D., Di Guilmi, C., Gaffeo, E. & Gallegati, M. 2004, 'Bankruptcy as an Exit Mechanism for Systems with a Variable Number of Components', Physica A: Statistical Mechanics and its Applications, vol. 344, no. 1-2, pp. 8-13.
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Dynamical systems with components whose sizes evolve according to multiplicative stochastic rules have been recently combined with entry and exit processes. We show that the assumptions usually made in modeling exits are at odds with the available evidence. We discuss a recently proposed macroeconomic model with random multiplicative shocks and a mechanism for exit based on bankruptcy, which displays several observed stylized facts for firms' dynamics, like power law distributions for firms' sizes and Laplace distributions for firms' growth rates
Fujiwara, Y., Di Guilmi, C., Aoyama, H., Gallegati, M. & Souma, W. 2004, 'Do Pareto-Zipf and Gibrat Law Hold True? An Analysis with European Firms', Physica A: Statistical Mechanics and its Applications, vol. 335, no. 1-2, pp. 197-216.
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By employing exhaustive lists of large firms in European countries, we show that the upper-tail of the distribution of firm size can be fitted with a power-law (ParetoZipf law), and that in this region the growth rate of each firm is independent of the firm's size (Gibrat's law of proportionate effect). We also find that detailed balance holds in the large-size region for periods we investigated; the empirical probability for a firm to change its size from a value to another is statistically the same as that for its reverse process. We prove several relationships among ParetoZipf's law, Gibrat's law and the condition of detailed balance. As a consequence, we show that the distribution of growth rate possesses a non-trivial relation between the positive side of the distribution and the negative side, through the value of Pareto index, as is confirmed empirically.
Di Guilmi, C., Gallegati, M. & Ormerod, P. 2004, 'Scaling Invariant Distributions of Firms' Exits in OECD Countries', Physica A: Statistical Mechanics and its Applications, vol. 334, no. 1-2, pp. 267-273.
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Self-similar models are largely used to describe the extinction rate of biological species. In this paper we analyse the extinction rate of firms in eight OECD countries. Firms are classified by industrial sectors and sizes. We find that while a power-law distribution with exponent close to 2 fits the extinction rate very well by sector, a Weibull distribution is more appropriate if one analyses the firms size.
Di Guilmi, C., Gaffeo, E. & Gallegati, M. 2004, 'Empirical Results on the Size Distribution of Business Cycle Phases', Physica A: Statistical Mechanics and its Applications, vol. 333, pp. 325-334.
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We study the size distribution of business cycles phases, that is expansions and contractions, for a sample of 16 industrialized countries over 120 years. We find that the best-fitting distribution for both expansions and contractions is Weibull, meaning that business cycles possess a characteristic scale. Furthermore, we discuss how parameters estimates can be used to make inference on the probability a typical episode ends, that is on what economists call turning points.
Delli Gatti, D., Di Guilmi, C., Gaffeo, E., Gallegati, M., Giulioni, G. & Palestrini, A. 2004, 'Business Cycle Fluctuations and Firms - Size Distribution Dynamics', Advances in Complex Systems, vol. 7, no. 2, pp. 223-240.
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Power law behavior is an emerging property of many economic models. In this paper we emphasize the fact that power law distributions are persistent but not time invariant. In fact, the scale and shape of the firms' size distribution fluctuate over time. In particular, on a loglog space, both the intercept and the slope of the power law distribution of firms' size change over the cycle: during expansions (recessions) the straight line representing the distribution shifts up and becomes less steep (steeper). We show that the empirical distributions generated by simulations of the model presented in Ref. 11 mimic real empirical distributions remarkably well.
Fujiwara, Y., Aoyama, H., Di Guilmi, C., Souma, W. & Gallegati, M. 2004, 'Gibrat and Pareto-Zipf revisited with European firms', Physica A: Statistical Mechanics and its Applications, vol. 344, no. 1-2, pp. 112-116.
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A firms growth and failure are the two sides of the same coin. This paper reports new phenomenological findings for firm size distribution and growth, and bankruptcy. This paper is based on [Y. Fujiwara et al., Physica A 335 (2004) 197] and on [Y. Fujiwara, Physica A 337 (2004) 219]. See also these proceedings for kinematical relationship between Pareto½Zipf and Gibrat's laws.
Di Guilmi, C., Gaffeo, E. & Gallegati, M. 2003, 'Power Law Scaling in World Income Distribution', Economics Bulletin, vol. 15, no. 6, pp. 1-7.
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We show that over the period 1960-1997, the range comprised between the 30th and the 85th percentiles of the world income distribution expressed in terms of GDP per capita invariably scales down as a Pareto distribution. Furthermore, the time path of the power law exponent displays a negatively sloped trend. Our findings suggest that the cross-country average growth process appears to be scale invariant but for countries in the tails of the world income distribution, and that the relative volatility of smaller countries' growth processes have increased over time.


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Copyright © Cambridge University Press 2016 The paper presents an agent-based model to study the possible effects of different fiscal and monetary policies in the context of debt deflation. We introduce a modified Taylor rule that includes the financial position of firms as a target. Monte Carlo simulations provide a representation of the complex feedback effects generated by the interaction among the different transmission channels of monetary policy. The model also reproduces the evidence of low inflation during stock market booms and shows how it can lead to overinvestment and destabilize the system. The paper also investigates the possible reasons behind this stylized fact by testing different behavioral rules for the central bank. We find that, in a context of sticky prices and volatile expectations, endogenous credit creation can be identified as the main source of the divergent dynamics of prices in the real and financial sectors.
Di Guilmi, C. & Catalano, M. 2016, 'Uncertainty, rationality and complexity in a multi-sectoral dynamic model: the Dynamic Stochastic Generalized Aggregation approach', CAMA working paper series 16/2016.
Di Guilmi, C. & Carvalho, L. 2015, 'The Dynamics of Leverage in a Minskyan Model with Heterogeneous Firms'.
Di Guilmi, C. & Carvalho, L. 2014, 'Income inequality and macroeconomic instability: a stock-flow consistent approach with heterogeneous agents'.
Di Guilmi, C., Gallegati, M., Landini, S. & Stiglitz, J.E. 2013, 'Dynamic Aggregation of Heterogeneous Interacting Agents and Network: An Analytical Solution for Agent Based Models'.
Di Guilmi, C. 2008, 'Financial determinants of firms profitability: A hazard function investigation', Working Paper Series, Department of Economics, Università Politecnica delle Marche.
Working Paper Number: 318 Abstract: In this paper a hazard function analysis is performed on a set of European firms in order to identify a stochastic relationship among financial structure and profits. The relative proportions of debt and equity financing appear to influence expected profitability with a different degree for each nation. Within each country, relevant differences are recorded among listed and non listed firms. These results highlight the role of institutional factors, in particular related to credit and stock markets, in reducing informational asymmetries between investors and managers. The cross-sectional study is performed by means of degradation analysis, an engineering tool new in economics.
Gaffeo, E., Di Guilmi, C., Gallegati, M. & Russo, A. 2008, 'On the mean/variance relationship of the firm size distribution: Evidence and some theory', Discussion Paper, Department of Economics, University of Trento.
Di Guilmi, C., Gallegati, M. & Landini, S. 2008, 'Modeling Maximum Entropy and Mean-Field Interaction in Macroeconomics', Economics Discussion Paper No. 2008-36..