Matteo BARIGOZZI - Research

Post-Doctoral Researcher
European Center for Advanced Research in Economics and Statistics (ECARES) - Université Libre de Bruxelles

         

Contacts Vita Research Topics Published Papers Selected Working Papers Statistics and Econometrics - Economics

Current Projects Notes Matlab Codes Talks & Slides Links

	Contacts	Top
	Office Address
	Room S 12.127 ECARES - Université Libre de Bruxelles 44 Avenue Jeanne B-1050 Brussels Belgium
	Postal Address
	ECARES - Université Libre de Bruxelles 50 Avenue F.D. Roosevelt CP 114 B-1050 Brussels Belgium
	Phone
	+32 (0)2 650 33 75 mattebar
	Email
	matteo.barigozzi gmail.com  -  matteo.barigozziulb.ac.be
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	Vita	Top
	Full CV
	Past Research Positions
	Researcher - Evolutionary Economics Group - Max Planck Institut für Ökonomik, Jena - 2008.
	Researcher - Laboratory of Economics and Management - Scuola Superiore Sant'Anna, Pisa - 2006 - 2008.
	Education
	PhD Economics and Management - Scuola Superiore Sant'Anna, Pisa - 2008.
	Dynamic Factor Models - New Developments in Forecasting and Structural Identification Techinques - Supervisor: Marco Lippi - Introduction.
	MSc Modeling and Simulation of Complex Realities - International Centre for Theoretical Physics, Trieste - 2003.
	BSc and MSc "Laurea" degree in Physics - Astrophysics - Universitá  degli Studi di Milano - 2002.
	Visiting
	Department of Quantitative Economics - Universiteit Maastricht - Maastricht -Feb 2010.
	Columbia Business School - Columbia University - New York - Oct 2006 - Apr 2007.
	Departamento de Estadí­stica - Universidad Carlos III - Madrid - Oct 2005 - Dec 2005.
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		Research Topics		Top
	Statistics and Econometrics		Economics
	Dynamic factor models and spectral analysis. Nonfundamental representations of time series models. Evolutionary dynamic factor models.		Phenomenology of consumption behaviour. International trade networks ( http://www.tradenet-it.tk/).
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	Published Papers	Top
	The Multi-Network of International Trade: A Commodity-Specific Analysis, (with G. Fagiolo and D. Garlaschelli), Physical Review E, forthcoming 2010.
	Abstract:  We study the topological properties of the multi-network of commodity-specific trade relations among world countries over the 1992-2003 period, comparing them with those of the aggregate-trade network, known in the literature as the international trade network (ITN). We show that link-weight distributions of commodity-specific networks are extremely heterogeneous and (quasi) log-normality of aggregate linkweight distribution is generated as a sheer outcome of aggregation. Commodity-specific networks also display average connectivity, clustering and centrality levels very different from their aggregate counterpart. We also find that ITN complete connectivity is mainly achieved through the presence of many weak links that keep commodity-specific networks together, and that the correlation structure existing between topological statistics within each single network is fairly robust and mimics that of the aggregate network. Finally, we employ cross-commodity correlations between link weights to build taxonomies of commodities. Our results suggest that on the top of a relatively time-invariant “intrinsic” taxonomy (based on inherent between-commodity similarities), the roles played by different commodities in the ITN have become more and more dissimilar, possibly as the result of an increased trade specialization.
	On the distributional properties of household consumption expenditures. The case of Italy (with L. Alessi, M. Capasso, G. Fagiolo), Empirical Economics, forthcoming 2010 and online 2009.
	Abstract: In this paper we explore the statistical properties of the distributions of consumption expenditures for a large sample of Italian households in the period 1989-2004. Goodness-of-fit tests show that household aggregate (and age-conditioned) consumption distributions are not log-normal. Rather, their logs can be invariably characterized by asymmetric exponential-power densities. Departures from log-normality are mainly due to the presence of thick lower tails coexisting with upper tails thinner than Gaussian ones. The emergence of this irreducible heterogeneity in statistical patterns casts some doubts on the attempts to explain log-normality of household consumption patterns by means of simple models based on Gibrat's Law applied to permanent income and marginal utility.
	On approximating the distributions of goodness-of-fit test statistics based on the empirical distribution function: The case of unknown parameters (with L. Alessi, M. Capasso and G. Fagiolo),  Advances in Complex Systems, 2009, 12(2), pp1-11.
	Abstract: This paper discusses some problems possibly arising when approximating via Monte-Carlo simulations the distributions of goodness-of-fit test statistics based on the empirical distribution function. We argue that failing to re-estimate unknown parameters on each simulated Monte-Carlo sample -- and thus avoiding to employ this information to build the test statistic -- may lead to wrong, overly-conservative testing. Furthermore, we present a simple example suggesting that the impact of this possible mistake may turn out to be dramatic and does not vanish as the sample size increases.
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	Selected Working Papers Statistics and Econometrics	Top
	(View my research also on my RePEc or SSRN Author pages)
	Time Varying Money Demand for the Euro Area, (with A. Conti), coming soon!
	Abstract: Classical specifications of Euro Area money demand equation fail in achieving stability after 2002, consequently raising issues for price stability and the linkage between money and inflation. We argue that the time varying cointegration approach developed in Bierens and Martins (2010) represents the proper way to test for stability of the long run money demand equation. Results show that a time invariant relation between real balances and income is strongly rejected by data, even when accounting for financial, housing wealth and labour markets variables. We also find monotonically increasing long run income elasticity, which calls for a deeper analysis in terms of dynamic changes in the underlying deep parameters as risk aversion and elasticity of substitution between consumption and real balances.
	Estimation and Forecasting in Large Datasets with Conditionally Heteroskedastic Dynamic Common Factors, (with L. Alessi and M. Capasso), European Central Bank Working Paper .
	Abstract: We propose a new method for multivariate forecasting which combines Dynamic Factor and multivariate GARCH models. The information contained in large datasets is captured by few dynamic common factors, which we assume being conditionally heteroskedastic. After presenting the model, we propose a multi-step estimation technique which combines asymptotic principal components and multivariate GARCH. We also prove consistency of the estimated conditional covariances. We present simulation results in order to assess the finite sample properties of the estimation technique. Finally, we carry out two empirical applications respectively on macroeconomic series, with a particular focus on different measures of inflation, and on financial asset returns. Our model outperforms the benchmarks in forecasting the inflation level, its conditional variance and the volatility of returns. Moreover, we are able to predict all the conditional covariances among the observable series.
	A Review of Nonfundamentalness and Identification in Structural VAR Models, (with L. Alessi and M. Capasso), European Central Bank Working Paper and Last Version here .
	Abstract: We review, under a historical perspective, the development of the problem of nonfundamentalness of Moving Average (MA) representations of economic models. Nonfundamentalness typically arises when agents' information space is larger than the econometrician's one. Therefore it is impossible for the latter to use standard econometric techniques, as Vector AutoRegression (VAR), to estimate economic models. We restate the conditions under which it is possible to invert an MA representation in order to get an ordinary VAR and identify the shocks, which in a VAR are fundamental by construction. By reviewing the work by Lippi and Reichlin [1993] we show that nonfundamental shocks may be very different from fundamental shocks. Therefore, nonfundamental representations should not be ruled out by assumption and indeed methods to detect nonfundamentalness have been recently proposed in the literature. Moreover, Structural VAR (SVAR) can be legitimately used for assessing the validity of Dynamic Stochastic General Equilibrium models only if the representation associated with the economic model is fundamental. Factor models can be an alternative to SVAR for validation purposes as they do not have to deal with the problem of nonfundamentalness.
	A Robust Criterion for Determining the Number of Factors in Approximate Factor Models, (with L. Alessi and M. Capasso), European Central Bank Working Paper and Last Version ECARES working paper (Matlab code here)
	Abstract: We modify the criterion by Bai and Ng (2002) for determining the number of factors in approximate factor models. As in the original criterion, for any given number of factors we estimate the common and idiosyncratic components of the model by applying principal component analysis. We select the true number of factors as the number that minimizes the variance explained by the idiosyncratic component. In order to avoid overparametrization, minimization is subject to penalization. At this step, we modify the original procedure by multiplying the penalty function by a positive real number, which allows us to tune its penalizing power, by analogy with the method used by Hallin and Liška (2007) in the frequency domain. The contribution of this paper is twofold. First, our criterion retains the asymptotic properties of the original criterion, but corrects its tendency to overestimate the true number of factors. Second, we provide a computationally easy way to implement the new method by iteratively applying the original criterion. Monte Carlo simulations show that our criterion is in general more robust than the original one. A better performance is achieved in particular in the case of large idiosyncratic disturbances. These conditions are the most difficult for detecting a factor structure but are not unusual in the empirical context. Two applications on a macroeconomic and a financial dataset are also presented.
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	Selected Working Papers Economics	Top
	(View my research also on my RePEc or SSRN Author pages)
	The Consumption Polarization of Documented and Undocumented Immigrants, (with B. Speciale), available upon request.
	Abstract: In this paper we study immigrants’ consumption behavior as an important dimension in their integration in the host country. We use a large sample of documented and undocumented immigrants living in Italy. Representativeness of this sample is ensured through the “center sampling technique”. Our regression analysis shows that - conditional on individual and household characteristics – there is a large heterogeneity in the consumption behavior of immigrants due to differences in region of origin. This heterogeneity already exists at the time of arrival in the destination country and is affected by immigrants’ legal status as well. Moreover, differences in consumption behavior at arrival tend to persist over time and are not affected by the years of permanence in the host country. Our results show a high level of polarization in Italy, which may imply a high likelihood of racial tensions.
	Immigrant's Legal Status, Permanence in the Destination Country and the Distribution of Consumption Expenditure, (with B. Speciale). ECARES Working Paper .
	Abstract: This paper considers the distribution of consumption expenditures for a large sample of documented and undocumented immigrants in Italy. Using the one-sided and two-sided Kolmogorov-Smirnov tests, we show that the distribution of consumption of immigrants with higher permanence in the host country first-order stochastically dominates the one of immigrants with lower permanence. These distributions are first-order stochastically dominated by the ones of natives with similar characteristics. Apart from differences in the first years since migration, undocumented immigrants show similar consumption distributions to the ones of documented immigrants. All results also hold when correcting for possible immigrants’ misreporting on their legal status.
	The Distribution of Consumption-Expenditure Budget Shares. Evidence from Italian Households, (with L. Alessi, M. Capasso and G. Fagiolo), European Central Bank Working Paper .
	Abstract: This paper explores the statistical properties of household consumption-expenditure budget shares distributions (HBSDs) defined as the share of household total expenditure spent for purchasing a specific category of commodities for a large sample of Italian households in the period 1989-2004. We find that HBSDs are fairly stable over time for each specific category, but profoundly heterogeneous across commodity categories. We then derive a parametric density that is able to satisfactorily characterize HBSDs and: (i) is consistent with the observed statistical properties of the underlying levels of household consumption-expenditure distributions; (ii) can accommodate the observed acrosscategory heterogeneity in HBSDs. Finally, we taxonomize commodity categories according to the estimated parameters of the proposed density. We show that the resulting classification is consistent with the traditional economic scheme that labels commodities as necessary, luxury or inferior.
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