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Dr Corrado Di Guilmi

Biography

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/

RePEc page

Google Scholar citation page

Personal web page

Senior Lecturer, Economics Discipline Group
Ph.D.
Download CV  (PDF 299 Kb, 7 pages)
Phone
+61 2 9514 4746

Research Interests

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

Can supervise: Yes

Books

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.

Chapters

Landini, S., Gallegati, M., Stiglitz, J.E., Li, X. & Di Guilmi, C. 2014, 'Learning and macro-economic dynamics' in Nonlinear Economic Dynamics and Financial Modelling: Essays in Honour of Carl Chiarella, pp. 109-134.
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© 2014 Springer International Publishing Switzerland. All rights are reserved. 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 Institutional and Social Dynamics of Growth and Distribution, pp. 322-350.
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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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Conferences

Chiarella, C. & Di Guilmi, C. 2015, 'The limit distribution of evolving strategies in financial markets', Studies in Nonlinear Dynamics and Econometrics, pp. 137-159.
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© 2015 by De Gruyter. 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. & 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.
Chiarella, C. & Di Guilmi, C. 2011, 'The financial instability hypothesis: A stochastic microfoundation framework', JOURNAL OF ECONOMIC DYNAMICS & CONTROL, pp. 1151-1171.
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Di Guilmi, C. 2011, 'An analytical solution for agent based models', The Paul Woolley Centre for Capital Market Dysfunctionality 2011 Conference, Sydney Australia.
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.
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

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.
Di Guilmi, C. & Chiarella, C. 2015, 'Monetary Policy and Debt Deflation: Some Computational Experiments,', Macroeconomic Dynamics.
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.
In this paper we expand the agent based model introduced by Chiarella and Di Guilmi (Chiarella, C. and Di Guilmi, C., The financial instability hypothesis: A stochastic microfoundation framework. Journal of Economic Dynamics and Control, 35(8):1151 – 1171, 2011) in which the business cycle originates by the modifications in firms' balance sheets induced by their investment decisions. During periods of market euphoria, firms increase their capital stock and their level of debt. At the same time the increasing availability of liquidity for investors causes inflation in asset price. When firms' debt reaches an unsustainable level the virtuous cycle is reversed in a depression. We modify the original model in order to study the impact of the dependence of firms' expectations on the stock market performance and of the rise in the proportion of Ponzi firms. We also run a further computational experiment to assess the effect of the buy-back of firms' shares.
Di Guilmi, C., He, X.Z. & Li, K. 2014, 'Herding, trend chasing and market volatility', Journal of Economic Dynamics and Control, vol. 48, pp. 349-373.
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© 2014 Elsevier B.V. We introduce a heterogeneous agent asset pricing model in continuous-time to show that, although trend chasing, switching and herding all contribute to market volatility in price and return and to volatility clustering, their impacts are different. The fluctuations of the market price and return and the level of the significant autocorrelations (ACs) of the absolute and squared returns increase with the intensities of herding and trend chasing based on long time horizon. However an increase in switching intensity reduces the return volatility and in particular a low switching intensity reduces the price volatility and increases the level of the significant ACs, but the effect becomes opposite when the switching intensity is high. We also show that market noise plays a more important role than fundamental noise on the power-law behavior of returns.
Chiarella, C. & Di Guilmi, C. 2012, 'The Fiscal Cost of Financial Instability', STUDIES IN NONLINEAR DYNAMICS AND ECONOMETRICS, vol. 16, no. 4.
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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
Gatti, D.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.
GATTI, D.D.E.L.L.I., DI GUILMI, C., GALLEGATI, M., GAFFEO, E., GIULIONI, G. & PALESTRINI, A. 2008, 'SCALING LAWS IN THE MACROECONOMY', Advances in Complex Systems, vol. 11, no. 01, pp. 131-138.
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Di Guilmi, C., Clementi, F., Di Matteo, T. & Gallegati, M. 2008, 'Social networks and labour productivity in Europe: an empirical investigation', Journal of Economic Interaction and Coordination, vol. 3, no. 1, pp. 43-57.
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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.
Gatti, D.D., Guilmi, C.D., 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 & Organization, vol. 56, no. 4, pp. 489-512.
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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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Fujiwara, Y., Di Guilmi, C., Aoyama, H., Gallegati, M. & Souma, W. 2004, 'Do Pareto–Zipf and Gibrat laws 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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Guilmi, C.D., Gallegati, M. & Ormerod, P. 2004, 'Scaling invariant distributions of firms' exit in OECD countries', Physica A: Statistical Mechanics and its Applications, vol. 334, no. 1-2, pp. 267-273.
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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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DELLI GATTI, D.O.M.E.N.I.C.O., DI GUILMI, C.O.R.R.A.D.O., GAFFEO, E.D.O.A.R.D.O., GIULIONI, G.I.A.N.F.R.A.N.C.O., GALLEGATI, M.A.U.R.O. & PALESTRINI, A.N.T.O.N.I.O. 2004, 'BUSINESS CYCLE FLUCTUATIONS AND FIRMS' SIZE DISTRIBUTION DYNAMICS', Advances in Complex Systems, vol. 07, no. 02, pp. 223-240.
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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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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.

Other

Di Guilmi, C. & Carvalho, L. 2014, 'Income inequality and macroeconomic instability: a stock-flow con- sistent 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'.
Gaffeo, E., Di Guilmi, C., Gallegati, M. & Russo, A. 2012, 'On the mean/variance relationship of the firm size distribution: Evidence and some theory'.
Firm-level data for a 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 as Taylor power law. We recur to computational experiments to show how this empirical fact can be fruitfully employed to discriminate amongst alternative theoretical explanations of firms' growth. © 2012 Elsevier B.V.
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.
Di Guilmi, C., Gallegati, M. & Landini, S. 2008, 'Modeling Maximum Entropy and Mean-Field Interaction in Macroeconomics', Economics Discussion Paper No. 2008-36..