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Contatti:

Indirizzo postale: Dipartimento di Economia e Finanza, Università di Roma “Tor Vergata”, Via Columbia 2, 00133 Roma.
Telefono: 06 7259 5847
E-mail: gianluca.cubadda@uniroma2.it

Formazione:

Dottorato in Statistica, 1994, Università di Roma "La Sapienza".
MSc in Economics and Econometrics, 1992, University of Southampton.
Laurea magna cum laude in Scienze Statistiche e Economiche, 1990, Università di Roma "La Sapienza.

Posizioni attuali e precedenti:

Novembre 2004-presente: Professore ordinario di Statistica Economica, Università di Roma "Tor Vergata".
Settembre 2023-presente: Coordinatore del Master Data Science For Public Decision Making, in convenzione con la Banca d’Italia e l'Agenzia delle Entrate.
Maggio 2024-presente: Coordinatore del sub-gruppo di esperti valutatori di Statistica e Metodi Matematici - Area Scienze Economiche e Statistiche nell’ambito della Valutazione della Qualità della Ricerca 2020-2024.
Agosto 2017-Luglio 2022: Coordinatore del Master Big Data in Business.
Gennaio 2019-Dicembre 2021: Preside della Facoltà di Economia, Università di Roma “Tor Vergata”.
Ottobre 2018-Settembre 2021: Presidente della commissione nazionale per il conferimento dell'Abilitazione Scientifica Nazionale nel settore concorsuale 13/D2-Statistica Economica.
Maggio 2012-Ottobre 2015: Direttore del Dipartimento di Economia e Finanza, Università di Roma "Tor Vergata".
Agosto 2011-Dicembre 2014: Presidente dell'Organo Indipendente di Valutazione dell'ISTAT.
Novembre 2010-Aprile 2012: Direttore del Dipartimento di Studi Economico-Finanziari e Metodi Quantitativi dell’Università degli Studi di Roma “Tor Vergata”.
Settembre 2010-Luglio 2011: Membro dell'Organo Indipendente di Valutazione dell'ISTAT.
Novembre 2003-Ottobre 2004: Direttore del Dipartimento di Scienze Economiche Gestionali e Sociali dell’Università degli Studi del Molise.
Novembre 2001-Ottobre 2004: Professore Straordinario di Statistica Economica, Università degli Studi del Molise.
Novembre 1998-Ottobre 2001: Professore associato di Statistica Economica, Università degli Studi del Molise.
Dicembre 1995-Ottobre 1998: Ricercatore di Statistica Economica, Università degli Studi di Roma “La Sapienza”.
Dicembre 1994-Novembre 1995: Ricercatore di Economia-Econometria nel Dipartimento di Contabilità Nazionale ed Analisi Economica dell'ISTAT (Roma).

Posizioni di visiting:

1999, 2001, 2002, 2015, 2016, 2019, 2022, 2023: Visiting Professor presso il Department of Quantitative Economics of Maastricht University.
2005-2008, 2009-2012: Extramural fellow del METEOR (Maastricht research school of Economics of Technology and Organizations).
2005, 2007, 2010: Visiting Professor presso il Department of Economics of Maastricht University.

Affiliazioni e partecipazioni a comitati di società scientifiche:

1996-presente: socio della Società Italiana di Statistica (SIS).
2010-presente: socio della Società Italiana di Econometria (SIDE).
2010-presente: membro dello ERCIM working group CMStatistics.
2012-presente: membro dello International Institute of Forecasters (IIF).
2021-presente: membro della International Association of Applied Econometrics (IAAE).
1997-2014: membro della Econometric Society (ES).
2006-2010: membro del consiglio direttivo della SIS.
2008-2012: membro del comitato operativo del Gruppo di Coordinamento sull'analisi delle serie temporali ANSET-SIS.
2008-2013: membro del consiglio direttivo del Centro Interuniversitario di Econometria (CIDE).

Interessi di ricerca:

Analisi delle caratteristiche comuni,
serie storiche di grandi dimensioni,
ciclo degli affari,
stagionalità,
cointegrazione,
metodi di previsione,
modelli dinamici non-causali,
cambiamenti strutturali,
volatilità.

Pubblicazioni principali:

Cubadda G. (1994), Testing for Cointegration at any Frequency Using Spectral Methods, Journal of the Italian Statistical Society, 3, 37–50.
Cubadda G. (1995), A Note on Testing for Seasonal Cointegration using Principal Components in the Frequency Domain, Journal of Time Series Analysis, 16, 499–508
Cubadda G., Fachin S., and F. Nucci (1999), Disaggregated Import Demand Functions for the Italian Economy, in Kriesler P., and C. Sardoni (eds.), Keynes, Post-Keynesianism and Political Economy. Essays in honour of G. Harcourt, volume three, Routledge Frontiers of Political Economy, 22, 510–526.
Cubadda G. (1999), Common Cycles in Seasonal Non-Stationary Time Series, Journal of Applied Econometrics, 14, 273–291.
Cubadda G. (1999), Common Serial Correlation and Common Business Cycles: A Cautious Note, Empirical Economics, 24, 529–535.
Cubadda G. (2001), Common Features in Time Series with both Deterministic and Stochastic Seasonality, Econometric Reviews, 20, 201–216.
Cubadda G. (2001), Complex Reduced Rank Models for Seasonally Cointegrated Time Series, Oxford Bulletin of Economics and Statistics, 63, 497–511.
Cubadda G., and A. Hecq (2001), On Non-Contemporaneous Short-Run Comovements, Economics Letters, 73, 389–397.
Cubadda G., and P. Daddi (2001), Dynamics and Comovements of Regional Exports in Italy, in Borra S., Rocci R., Vichi M., and M. Schader (eds.), Advances in Classification and Data Analysis, Springer-Verlag, 275–282.
Bruno G., Cubadda G., Lupi C., and E. Giovannini (2002), The Flash Estimate of the Italian Real Gross Domestic Product, in Barcellan R., and G.L. Mazzi (eds.), Workshop on Quarterly National Accounts, Eurostat Working Papers and Studies, Cat. No. KS-AN-03-014, 225–235.
Cubadda G., Savio G., and R. Zelli (2002), Seasonality, Productivity Shocks, and Sectoral Comovements in a Real Business Cycle Model for Italy, Macroeconomic Dynamics, 6, 1–20.
Centoni M., and G. Cubadda (2003), Measuring the Business Cycle Effects of Permanent and Transitory Shocks in Cointegrated Time Series, Economics Letters, 80, 45–51.
Cubadda G., and P. Omtzigt (2005), Small-Sample Improvements in the Statistical Analysis of Seasonally Cointegrated Systems, Computational Statistics & Data Analysis, 49, 333–348.
Centoni M., Cubadda G., and A. Hecq (2006), Measuring the Sources of Cyclical Fluctuations in the G7 Economies, in Mazzi G.L., and G. Savio (Eds.), Growth and Cycle in the Euro-zone, 152–159, Palgrave Macmillan.
Candelon B, and G. Cubadda (2006), Testing for Parameter Stability in Dynamic Models Across Frequencies, Oxford Bulletin of Economics and Statistics, 68, 741–760.
Centoni M., Cubadda G., and A. Hecq (2007), Common Shocks, Common Dynamics, and the International Business Cycle, Economic Modelling, 24, 149–166.
Cubadda G. (2007), A Reduced Rank Regression Approach to Coincident and Leading Indexes Building, Oxford Bulletin of Economics and Statistics, 69, 271–292.
Cubadda G. (2007), A Unifying Framework for Analysing Common Cyclical Features in Cointegrated Time Series, Computational Statistics & Data Analysis, 52, 896–906.
Cubadda G., Hecq A., and F. C. Palm (2008), Macro-Panels and Reality, Economics Letters, 99, 537–540.
Atella V., Centoni M., and G. Cubadda (2008), Technology Shocks, Structural Breaks and the Effects on the Business Cycle, Economics Letters, 100, 392–395.
Cubadda G., Hecq A., and F. C. Palm (2009), Studying Co-movements in Large Multivariate Models Prior to Multivariate Modelling, Journal of Econometrics, 148, 25–35.
Cubadda G., and A. Hecq (2011), Testing for Common Autocorrelation in Data Rich Environments, Journal of Forecasting, 30, 325–335.
Cubadda G., and U. Triacca (2011), An Alternative Solution to the Autoregressivity Paradox in Time Series Analysis, Economic Modelling, 28, 1451–1454.
Centoni M., and G. Cubadda (2011), Modelling Comovements of Economic Time Series: A Selective Survey, Statistica, 71, 267–294.
Cubadda G., and B. Guardabascio (2012), On the Use of Partial Least Squares Regression for Forecasting Large Sets of Cointegrated Time Series, in Di Ciaccio et al. (Eds.), Advanced Statistical Methods for the Analysis of Large Data-Sets, Studies in Theoretical and Applied Statistics, Springer-Verlag, 171–180.
Cubadda G., and B. Guardabascio (2012), A medium-N Approach to Macroeconomic Forecasting, Economic Modelling, 29, 1099–1105.
Cubadda G., Guardabascio B. and A. Hecq (2013), A General to Specific Approach for Selecting the Best Business Cycle Indicators, Economic Modelling, 33, 367–374.
Cubadda G., Guardabascio B., and A. Hecq (2013), Building a Synchronous Common-Cycle Index for the European Union, in Cheung Y.W., and F. Westermann (Eds.), Global Interdependence, Decoupling, and Recoupling, The MIT Press, 37–52.
Bernardini E. and G. Cubadda (2015), Macroeconomic Forecasting and Structural Analysis through Regularized Reduced-rank Regression, International Journal of Forecasting, 31, 682–691.
Centoni M., and G. Cubadda (2015), Common Feature Analysis of Economic Time Series: An Overview and Recent Developments, Communications for Statistical Applications and Methods, 22, 1–20
Cubadda G., Guardabascio B. and A. Hecq (2017), A Vector Heterogeneous Autoregressive Index Model for Realized Volatility Measures, International Journal of Forecasting, 33, 337–344.
Cubadda G., and B. Guardabascio (2019), Representation, Estimation and Forecasting of the Multivariate Index-Augmented Autoregressive Model, International Journal of Forecasting, 35, 67–79.
Cubadda G., Hecq A., and S. Telg (2019), Detecting Co-Movements in Noncausal Time Series, Oxford Bulletin of Economics and Statistics, 81, 697–715.
Cubadda G., Hecq A., and A. Riccardo (2019), Forecasting Realized Volatility Measures with Multivariate and Univariate Models: The Case of The US Banking Sector, in Chevallier J., Goutte S., Guerreiro D., Saglio S., and B. Sanhaji (Eds.), Financial Mathematics, Volatility and Covariance Modelling. Vol. 2, Part 3: Financial Volatility and Covariance Modelling, Routledge, UK, 286–307.
del Barrio Castro T., Cubadda G., and D. R. Osborn (2022), On Cointegration for Processes Integrated at Different Frequencies, Journal of Time Series Analysis, 43, 412–435.
Cubadda, G., and A. Hecq (2022), Reduced Rank Regression Models in Economics and Finance, in Oxford Research Encyclopedia of Economics and Finance, Oxford University Press, doi: 10.1093/acrefore/9780190625979.013.677.
Cubadda, G., and A. Hecq (2022), Dimension Reduction for High Dimensional Vector Autoregressive Models, Oxford Bulletin of Economics and Statistics, 84, 1123–1152.
Cubadda G., Hecq A., and E. Voisin (2023), Detecting Common Bubbles in Multivariate Mixed Causal-Noncausal Models, Econometrics, 11, 1–16.
Cubadda G., and M. Mazzali (2024), The Vector Error Correction Index Model: Representation, Estimation and Identification, Econometrics Journal, 27, 126–150.
Cubadda G., Giancaterini F., Hecq A., and J. Jasiak (2024), Optimization of the Generalized Covariance Estimator in Noncausal Processes, Statistics and Computing, 34, n. 127.
Cubadda G., Grassi S., and B. Guardabascio (2025), The Time Varying Multivariate Autoregressive Index Model, International Journal of Forecasting, 41, 175-190.

Working papers:

http://econpapers.repec.org/ras/pcu1.htm
http://ssrn.com/author=180354

Attività editoriale e di revisione scientifica:

Associate editor: Forecasting (2020-), Statistical Methods and Applications (2005-07).
Referee: Communications in Statistics - Theory and Methods, Computational Statistics & Data Analysis, Econometric Theory, Econometrics and Statistics, Economic Modelling, Empirical Economics, International Journal of Forecasting, Journal of Applied Econometrics, Journal of Business Cycle Analysis and Measurement, Journal of Business and Economic Statistics, Journal of Econometrics, Journal of Forecasting, Journal of Multivariate Analysis, Journal of Nonparametric Statistics, Journal of Statistical Computation and Simulation, Journal of the Italian Statistical Society, Journal of the Korean Statistical Society, Journal of Time Series Analysis, Labour, Metron, Oxford Bulletin of Economics and Statistics, Quantitative Finance, Quarterly Review, Statistical Methods and Applications, and Studies in Nonlinear Dynamics & Econometrics.

Partecipazioni a gruppi di ricerca:

- Vice-coordinatore della ricerca Nazionale: Prin 2022 Methodological and computational issues in large-scale time series models for economics and finance.

- Responsabile di unità locali nell’ambito delle seguenti ricerche nazionali:

Cofin 2000 Modelli stocastici e metodi di simulazione per l'analisi di dati dipendenti.
CNR 2000 Modelli statistici di serie temporali per la previsione.
Cofin 2003 Metodi e modelli statistici per la previsione di serie temporali non stazionarie e non lineari. Aspetti teorici e applicazioni.
Prin 2020 Towards an Anticipatory Governance System (TAGS)

- Partecipante ai seguenti progetti di ricerca nazionali:

Cofin 2000 Modelli statistici per l'analisi delle serie temporali.
Prin 2010 La previsione economica e finanziaria: il ruolo dell'informazione e la capacità di modellare il cambiamento.

- Partecipante al 2002-04 European Science Foundation Network Econometric Methods for the Modelling of Nonstationary Data, Policy Analysis, and Forecasting.

Relazioni invitate:

XLI Riunione Scientifica della Società Italiana di Statistica, 5-7 Giugno 2002, Milano.
4th Eurostat and DG ECFIN Colloquium on Modern Tools for Business Cycle Analysis, 20-22 Ottobre 2003, Luxembourg.
Joint Statistical Meetings, Luglio 29-Agosto 2 2007, Salt Lake City, Utah, USA.
Methods in International Finance Network 1st Workshop, 24-25 September 2007, Maastricht, The Netherlands.
5th Eurostat-EUI Colloquium on Modern Tools for Business Cycle Analysis, 29 September-1 Ottobre 2008, Luxembourg.
1st IMS Asia Pacific Rim Meetings, 28 Giugno–1 Luglio 2009, Seoul, Korea.
31st Annual International Symposium on Forecasting, 26-29 Giugno 2011, Prague, Czech Republic.
CESifo Workshop on Global Interdependence, Decoupling And Recoupling, 22-23 Luglio 2011, Island of San Servolo (Venezia).
CIRET/KOF/HSE Workshop on National Business Cycles in the Global World, 15-17 September 2011, Moscow, Russia.
32nd Annual International Symposium on Forecasting, 24-27 Giugno 2012, Boston, USA.
6th CSDA International Conference on Computational and Financial Econometrics,1-3 Dicembre 2012, Oviedo, Spain.
International Statistical Conference SIS 2013 Advances in Latent Variables - Methods, Models and Applications, 19-21 Giugno 2013, Brescia.
7th CSDA International Conference on Computational and Financial Econometrics, 14-16 Dicembre 2013, London, UK.
8th CSDA International Conference on Computational and Financial Econometrics, 6-8 Dicembre 2014, Pisa.
9th CSDA International Conference on Computational and Financial Econometrics, 12-14 Dicembre 2015, London, UK.
36th Annual International Symposium on Forecasting, 19-22 Giugno 2016, Santander, Spagna.
10th CSDA International Conference on Computational and Financial Econometrics, 9-11 Dicembre 2016, Siviglia, Spagna.
1st International Conference on Econometrics and Statistics, 15-17 Giugno 2017, Hong Kong, Cina.
49th Scientific meeting of the Italian Statistical Society, 20-22 Giugno 2018, Palermo.
15th International Conference on Computational and Financial Econometrics, 18-20 Dicembre 2021, London, UK.
2nd Workshop on Time Series Methods for Official Statistics, 22-23 Settembre 2022, OECD, Paris.
16th International Conference on Computational and Financial Econometrics, December 17-19, 2022, London, UK.
Workshop on Advanced Time Series Methods, 19-20 Giugno 2023, Perugia.
Intermediate Workshop of the PRIN2022 project Methodological and computational issues in large-scale time series models for economics and finance, 11 Settembre, Messina.
The Villa Mondragone Time Series Symposium in honour of Marco Lippi, Villa Mondragone, 2-4 Ottobre 2024, Monte Porzio Catone, Roma.

Partecipazioni a comitati scientifici di conferenze:

Common Features in Maastricht, 15-16 Dicembre 2003, Maastricht, Olanda
XLII Riunione Scientifica della Società Italiana di Statistica, 9-11 Giugno 2004, Bari.
Frontiers in Time Series Analysis, 29-31 Maggio 2005, Olbia.
Eurostat conference on Seasonality, Seasonal Adjustment and Their Implications for Short-term Analysis and Forecasting, 10-12 Maggio 2006, Luxembourg.
4th Italian Congress of Econometrics and Empirical Economics, 18-21 Gennaio 2011, Pisa.
23rd (EC)2 Conference on Hypothesis Testing, 14-15 Dicembre 2012, Maastricht, Olanda.
9th CSDA International Conference on Computational and Financial Econometrics, 12-14 Dicembre 2015, Londra, Regno Unito.
9th Italian Congress of Econometrics and Empirical Economics, 21-23 Gennaio 2021, Cagliari.
Workshop on Dimensionality Reduction and Inference in High-Dimensional Time Series, 5-6 Luglio, 2021, Maastricht, Olanda
7th International conference on Time Series and Forecasting, 19-21 Luglio, 2021, Gran Canaria, Spagna.
Workshop on Dimensionality Reduction and Inference in High-Dimensional Time Series, 13-14 Giugno 2022, Maastricht, Olanda.
8th International conference on Time Series and Forecasting, 27-30 Giugno 2022, Gran Canaria, Spagna.
16th International Conference on Computational and Financial Econometrics, 17-19 Dicembre 2022, Londra, Regno Unito.
10th Italian Congress of Econometrics and Empirical Economics, 26-28 Maggio 2023, Cagliari.
9th International conference on Time Series and Forecasting, 12-24 Luglio 2023, Gran Canaria, Spagna.
17th International Conference on Computational and Financial Econometrics, 16-18 Dicembre 2023, Berlino, Germania.
10th International conference on Time Series and Forecasting, 15-17 Luglio 2024, Gran Canaria, Spagna.

Didattica:

Time Series and Econometrics
Advanced Topics in Time Series
Supervised Learning
High-Dimensional Econometrics

Personal:

Citizenship: Italian.
Office address: Dipartimento di Economia e Finanza, Università di Roma “Tor Vergata”, Via Columbia 2, 00133 Roma – Italy.
Telephone: +39 06 7259 5847
E-mail: gianluca.cubadda@uniroma2.it

Education:

PhD in Statistics, 1994, Sapienza University of Rome "La Sapienza".
MSc in Economics and Econometrics, 1992, University of Southampton.
Laurea magna cum laude in Statistics and Economics, 1990, Sapienza University of Rome.

Current and previous positions:

November 2004-present: Full Professor of Economic Statistics, Tor Vergata University of Rome.
September 2023-present: Coordinator of the Master Data Science for Public Decision Making, affiliated with the Bank of Italy and the Italian Revenue Agency.
May 2025-present : Chairperson of the sub-panel of experts in Statistics and Mathematics - Economics and Statistics for the 2020-2024 Evaluation of Italian Research.
August 2017-July 2022: Coordinator of the Master Big Data in Business.
January 2019-December 2021: Dean of the School of Economics, Tor Vergata University of Rome.
October 2018-September 2021: Chairperson of the Italian University National Recruitment Committee in Economic Statistics.
May 2012-October 2015: Chairperson of the Department of Economics and Finance, Tor Vergata University of Rome.
August 2011-December 2014: Chairperson of the Independent Assessment Body of the Italian National Statistical Office.
November 2010-April 2012: Chairperson of the Department of Financial Economics and Quantitative Methods, Tor Vergata University of Rome.
September 2010-July 2011: Member of the Independent Assessment Body of the Italian National Statistical Office.
November 2003-October 2004: Chairperson of the Department of Economics, Management & Social Sciences, University of Molise.
November 2001-October 2004: Professor of Economic Statistics, University of Molise.
November 1998-October 2001: Associate Professor of Economic Statistics, University of Molise.
December 1995-October 1998: Lecturer of Economic Statistics, Sapienza University of Rome.
December 1994-November 1995: Researcher of Economics-Econometrics, Italian National Statistical Office (ISTAT), Rome.

Visiting positions:

1999, 2001, 2002, 2015, 2016, 2019, 2022, 2023: Visiting Professor at the Department of Quantitative Economics, Maastricht University.
2005-2008, 2009-2012: Extramural fellow of METEOR (Maastricht research school of Economics of Technology and Organizations).
2005, 2007, 2010: Visiting Professor at the Department of Economics, Maastricht University.

Scientific societies affiliations and committees:

- Member of the following scientific societies:

Italian Statistical Society (since 1999).
Italian Econometric Association (since 2010).
ERCIM working group CMStatistics (since 2010).
International Institute of Forecasters (IIF) (since 2012).
Econometric Society (1997-2014).

- Member of the steering committee of the following scientific societies:

Italian Statistical Society (2006-2010).
Italian Statistical Society Workgroup for Time Series Analysis (2008-2012).
Centro Interuniversitario di Econometria (CIDE) (2008-2013)

Scientific interests:

Common features,
high dimensional time series,
business cycle analysis,
seasonality,
cointegration,
forecasting,
non-causal autoregressive models,
structural breaks,
volatility.

Selected publications:

Cubadda G. (1994), Testing for Cointegration at any Frequency Using Spectral Methods, Journal of the Italian Statistical Society, 3, 37–50.
Cubadda G. (1995), A Note on Testing for Seasonal Cointegration using Principal Components in the Frequency Domain, Journal of Time Series Analysis, 16, 499–508
Cubadda G., Fachin S., and F. Nucci (1999), Disaggregated Import Demand Functions for the Italian Economy, in Kriesler P., and C. Sardoni (eds.), Keynes, Post-Keynesianism and Political Economy. Essays in honour of G. Harcourt, volume three, Routledge Frontiers of Political Economy, 22, 510–526.
Cubadda G. (1999), Common Cycles in Seasonal Non-Stationary Time Series, Journal of Applied Econometrics, 14, 273–291.
Cubadda G. (1999), Common Serial Correlation and Common Business Cycles: A Cautious Note, Empirical Economics, 24, 529–535.
Cubadda G. (2001), Common Features in Time Series with both Deterministic and Stochastic Seasonality, Econometric Reviews, 20, 201–216.
Cubadda G. (2001), Complex Reduced Rank Models for Seasonally Cointegrated Time Series, Oxford Bulletin of Economics and Statistics, 63, 497–511.
Cubadda G., and A. Hecq (2001), On Non-Contemporaneous Short-Run Comovements, Economics Letters, 73, 389–397.
Cubadda G., and P. Daddi (2001), Dynamics and Comovements of Regional Exports in Italy, in Borra S., Rocci R., Vichi M., and M. Schader (eds.), Advances in Classification and Data Analysis, Springer-Verlag, 275–282.
Bruno G., Cubadda G., Lupi C., and E. Giovannini (2002), The Flash Estimate of the Italian Real Gross Domestic Product, in Barcellan R., and G.L. Mazzi (eds.), Workshop on Quarterly National Accounts, Eurostat Working Papers and Studies, Cat. No. KS-AN-03-014, 225–235.
Cubadda G., Savio G., and R. Zelli (2002), Seasonality, Productivity Shocks, and Sectoral Comovements in a Real Business Cycle Model for Italy, Macroeconomic Dynamics, 6, 1–20.
Centoni M., and G. Cubadda (2003), Measuring the Business Cycle Effects of Permanent and Transitory Shocks in Cointegrated Time Series, Economics Letters, 80, 45–51.
Cubadda G., and P. Omtzigt (2005), Small-Sample Improvements in the Statistical Analysis of Seasonally Cointegrated Systems, Computational Statistics & Data Analysis, 49, 333–348.
Centoni M., Cubadda G., and A. Hecq (2006), Measuring the Sources of Cyclical Fluctuations in the G7 Economies, in Mazzi G.L., and G. Savio (Eds.), Growth and Cycle in the Euro-zone, 152–159, Palgrave Macmillan.
Candelon B, and G. Cubadda (2006), Testing for Parameter Stability in Dynamic Models Across Frequencies, Oxford Bulletin of Economics and Statistics, 68, 741–760.
Centoni M., Cubadda G., and A. Hecq (2007), Common Shocks, Common Dynamics, and the International Business Cycle, Economic Modelling, 24, 149–166.
Cubadda G. (2007), A Reduced Rank Regression Approach to Coincident and Leading Indexes Building, Oxford Bulletin of Economics and Statistics, 69, 271–292.
Cubadda G. (2007), A Unifying Framework for Analysing Common Cyclical Features in Cointegrated Time Series, Computational Statistics & Data Analysis, 52, 896–906.
Cubadda G., Hecq A., and F. C. Palm (2008), Macro-Panels and Reality, Economics Letters, 99, 537–540.
Atella V., Centoni M., and G. Cubadda (2008), Technology Shocks, Structural Breaks and the Effects on the Business Cycle, Economics Letters, 100, 392–395.
Cubadda G., Hecq A., and F. C. Palm (2009), Studying Co-movements in Large Multivariate Models Prior to Multivariate Modelling, Journal of Econometrics, 148, 25–35.
Cubadda G., and A. Hecq (2011), Testing for Common Autocorrelation in Data Rich Environments, Journal of Forecasting, 30, 325–335.
Cubadda G., and U. Triacca (2011), An Alternative Solution to the Autoregressivity Paradox in Time Series Analysis, Economic Modelling, 28, 1451–1454.
Centoni M., and G. Cubadda (2011), Modelling Comovements of Economic Time Series: A Selective Survey, Statistica, 71, 267–294.
Cubadda G., and B. Guardabascio (2012), On the Use of Partial Least Squares Regression for Forecasting Large Sets of Cointegrated Time Series, in Di Ciaccio et al. (Eds.), Advanced Statistical Methods for the Analysis of Large Data-Sets, Studies in Theoretical and Applied Statistics, Springer-Verlag, 171–180.
Cubadda G., and B. Guardabascio (2012), A medium-N Approach to Macroeconomic Forecasting, Economic Modelling, 29, 1099–1105.
Cubadda G., Guardabascio B. and A. Hecq (2013), A General to Specific Approach for Selecting the Best Business Cycle Indicators, Economic Modelling, 33, 367–374.
Cubadda G., Guardabascio B., and A. Hecq (2013), Building a Synchronous Common-Cycle Index for the European Union, in Cheung Y.W., and F. Westermann (Eds.), Global Interdependence, Decoupling, and Recoupling, The MIT Press, 37–52.
Bernardini E. and G. Cubadda (2015), Macroeconomic Forecasting and Structural Analysis through Regularized Reduced-rank Regression, International Journal of Forecasting, 31, 682–691.
Centoni M., and G. Cubadda (2015), Common Feature Analysis of Economic Time Series: An Overview and Recent Developments, Communications for Statistical Applications and Methods, 22, 1–20
Cubadda G., Guardabascio B. and A. Hecq (2017), A Vector Heterogeneous Autoregressive Index Model for Realized Volatility Measures, International Journal of Forecasting, 33, 337–344.
Cubadda G., and B. Guardabascio (2019), Representation, Estimation and Forecasting of the Multivariate Index-Augmented Autoregressive Model, International Journal of Forecasting, 35, 67–79.
Cubadda G., Hecq A., and S. Telg (2019), Detecting Co-Movements in Noncausal Time Series, Oxford Bulletin of Economics and Statistics, 81, 697–715.
Cubadda G., Hecq A., and A. Riccardo (2019), Forecasting Realized Volatility Measures with Multivariate and Univariate Models: The Case of The US Banking Sector, in Chevallier J., Goutte S., Guerreiro D., Saglio S., and B. Sanhaji (Eds.), Financial Mathematics, Volatility and Covariance Modelling. Vol. 2, Part 3: Financial Volatility and Covariance Modelling, Routledge, UK, 286–307.
del Barrio Castro T., Cubadda G., and D. R. Osborn (2022), On Cointegration for Processes Integrated at Different Frequencies, Journal of Time Series Analysis, 43, 412–435.
Cubadda, G., and A. Hecq (2022), Reduced Rank Regression Models in Economics and Finance, in Oxford Research Encyclopedia of Economics and Finance, Oxford University Press, doi: 10.1093/acrefore/9780190625979.013.677.
Cubadda, G., and A. Hecq (2022), Dimension Reduction for High Dimensional Vector Autoregressive Models, Oxford Bulletin of Economics and Statistics, 84, 1123–1152.
Cubadda G., Hecq A., and E. Voisin (2023), Detecting Common Bubbles in Multivariate Mixed Causal-Noncausal Models, Econometrics, 11, 1–16.
Cubadda G., and M. Mazzali (2024), The Vector Error Correction Index Model: Representation, Estimation and Identification, Econometrics Journal, 27, 126–150.
Cubadda G., Giancaterini F., Hecq A., and J. Jasiak (2024), Optimization of the Generalized Covariance Estimator in Noncausal Processes, Statistics and Computing, 34, #127.
Cubadda G., Grassi S., and B. Guardabascio (2025), The Time Varying Multivariate Autoregressive Index Model, International Journal of Forecasting, 41, 175-190.

Working papers:

http://econpapers.repec.org/ras/pcu1.htm
http://ssrn.com/author=180354

Editorial and referee services:

Associate editor: Forecasting(2020-), Statistical Methods and Applications(2005-07).
Referee for: Communications in Statistics - Theory and Methods, Computational Statistics & Data Analysis, Econometric Theory, Econometrics and Statistics, Economic Modelling, Empirical Economics, International Journal of Forecasting, Journal of Applied Econometrics, Journal of Business Cycle Analysis and Measurement, Journal of Business and Economic Statistics, Journal of Econometrics, Journal of Forecasting, Journal of Multivariate Analysis, Journal of Nonparametric Statistics, Journal of Statistical Computation and Simulation, Journal of the Italian Statistical Society, Journal of the Korean Statistical Society, Journal of Time Series Analysis, Labour, Metron, Oxford Bulletin of Economics and Statistics, Quantitative Finance, Quarterly Review, Statistical Methods and Applications, and Studies in Nonlinear Dynamics & Econometrics.

Research grants:

- Vice Principal Investigator of the national research project: Prin 2022 Methodological and computational issues in large-scale time series models for economics and finance.

- Coordinator of research unities within the following national research projects:

Cofin2000 Stochastic models and simulation methods for dependent data.
CNR2000 Statistical modeling and forecasting of time series.
Cofin2003 Statistical methods and models for non-stationary and non-linear time series forecasting, theory and applications.
Prin 2020 Towards an Anticipatory Governance System (TAGS)

- Participant in the following national research projects:

Cofin 2000 Statistical models for time series analysis.
Prin 2010 Forecasting economic and financial time series: understanding the complexity and modelling structural change.

- Participant in the 2002-04 European Science Foundation Network Econometric Methods for the Modelling of Nonstationary Data, Policy Analysis, and Forecasting.

Invited lectures:

XLI Italian Statistical Society Scientific Meeting, 5-7 June 2002, Milano, Italy.
4th Eurostat and DG ECFIN Colloquium on Modern Tools for Business Cycle Analysis, 20-22 October 2003, Luxembourg.
Joint Statistical Meetings, 29 July-2 August 2007, Salt Lake City, Utah, USA.
Methods in International Finance Network 1st Workshop, 24-25 September 2007, Maastricht, The Netherlands.
5th Eurostat-EUI Colloquium on Modern Tools for Business Cycle Analysis, 29 September-1 October 2008, Luxembourg.
1st IMS Asia Pacific Rim Meetings, 28 June–1 July 2009, Seoul, Korea.
31st Annual International Symposium on Forecasting, 26-29 June 2011, Prague, Czech Republic.
CESifo Workshop on Global Interdependence, Decoupling And Recoupling, 22-23 July 2011, Island of San Servolo (Venice), Italy.
CIRET/KOF/HSE Workshop on National Business Cycles in the Global World, 15-17 September 2011, Moscow, Russia.
32nd Annual International Symposium on Forecasting, 24-27 June 2012, Boston, USA.
6th CSDA International Conference on Computational and Financial Econometrics, 1-3 December 2012, Oviedo, Spain.
International Statistical Conference SIS 2013 Advances in Latent Variables - Methods, Models and Applications, 19-21 June 2013, Brescia, Italy.
7th CSDA International Conference on Computational and Financial Econometrics, 14-16 December 2013, London, UK.
8th CSDA International Conference on Computational and Financial Econometrics, 6-8 December 2014, Pisa, Italy.
9th CSDA International Conference on Computational and Financial Econometrics, 12-14 December 2015, London, UK.
36th Annual International Symposium on Forecasting, 19-22 June 2016, Santander, Spain.
10th CSDA International Conference on Computational and Financial Econometrics, 9-11 December 2016, Seville, Spain.
1st International Conference on Econometrics and Statistics, 15-17 June 2017, Hong Kong, China.
49th Scientific meeting of the Italian Statistical Society, 20-22,June 2018, Palermo, Italy.
15th International Conference on Computational and Financial Econometrics, 18-20 December 2021, London, UK.
2nd Workshop on Time Series Methods for Official Statistics, 22-23 Settembre 2022, OECD, Paris, France.
16th International Conference on Computational and Financial Econometrics, 17-19 December 2022, London, UK.
Workshop on Advanced Time Series Methods, 19-20 June 2023, Perugia, Italy.
Intermediate Workshop of the PRIN2022 project Methodological and computational issues in large-scale time series models for economics and finance, 11 September, Messina.
The Villa Mondragone Time Series Symposium in honour of Marco Lippi, Villa Mondragone, 2-4 October 2024, Monte Porzio Catone, Rome.

Conference scientific committees:

Common Features in Maastricht, 15-16 December 2003, Maastricht, The Netherlands.
XLII Italian Statistical Society Scientific Meeting, 9-11 June 2004, Bari, Italy.
Frontiers in Time Series Analysis, 29-31 May 2005, Olbia, Italy.
Eurostat conference on Seasonality, Seasonal Adjustment and Their Implications for Short-term Analysis and Forecasting, 10-12 May 2006, Luxembourg.
4th Italian Congress of Econometrics and Empirical Economics, 18-21 January 2011, Pisa, Italy.
23rd (EC)2 Conference on Hypothesis Testing, 14-15 December 2012, Maastricht, The Netherlands.
9th CSDA International Conference on Computational and Financial Econometrics, 12-14 December 2015, London, UK.
9th Italian Congress of Econometrics and Empirical Economics, 21-23 January 2021, Cagliari, Italy.
Workshop on Dimensionality Reduction and Inference in High-Dimensional Time Series, 5-6 July 2021, Maastricht, The Netherlands
7th International conference on Time Series and Forecasting, 19-21 July 2021, Gran Canaria, Spain.
Workshop on Dimensionality Reduction and Inference in High-Dimensional Time Series, 13-14 June 2022, Maastricht, The Netherlands.
8th International conference on Time Series and Forecasting, 27-30 June 2022, Gran Canaria, Spain.
16th International Conference on Computational and Financial Econometrics, 17-19 December 2022, London, UK.
10th Italian Congress of Econometrics and Empirical Economics, 26-28 May 2023, Cagliari, Italy.
9th International conference on Time Series and Forecasting, 12-14 July 2023, Gran Canaria, Spain.
17th International Conference on Computational and Financial Econometrics, 16-18 December 2023, Berlin, Germany.
10th International conference on Time Series and Forecasting, 15-17 July 2024, Gran Canaria, Spain.

Teaching:

Time Series and Econometrics
Advanced Topics in Time Series
Supervised Learning
High-Dimensional Econometrics

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