Corps professoral

Laurent FERRARA

Professeur

Economie internationale, Macroéconomie, Prévision, Cycles, Modélisation économétrique

Télécharger le CV
Laurent FERRARA

Académie

Globalisation

Centre de recherche

SKEMA Centre for Global Risks

Localisation

Paris

Discipline

Finance
Formation
2007
HDR en Economie, Université Paris 1 Panthéon-Sorbonne, France
2000
Doctorat en Econométrie, Université Sorbonne Paris Nord, France
Expérience professionnelle
Positions académiques principales
Depuis 2019
Professor of Economics, SKEMA Business School, France
Autres affiliations académiques
2005 - 2007
Adjunct Professor, École normale supérieure de Cachan, France
Autres expériences professionnelles
2020 - 2024
Membre du comité directeur de l'AFSE, Association Française de Science Economique, France
2014 - 2019
Head of International Macro Division, Banque de France, France
2012 - 2020
Member of the Board of Directors, International Institute of Forecasters, Etats-Unis d'Amérique
2010 - 2013
Deputy Head of International Macro Division, Banque de France, France
2007 - 2010
Economist-Researcher, Banque de France, France
Contrats de recherche, prix et distinctions
Contrats de recherche
2021
Prise de Décision sous Incertitude
Activités professionnelles
Autres activités professionnelles
Depuis 2024
Membre du jury des posts de blog étudiant, Banque de France
Autres activités de recherche
Editeur associé d'une revue
Depuis 2021
International Economics
Depuis 2014
International Journal of Forecasting
Relecteur pour :
Journal of International Economics, Journal of Applied Econometrics, Journal of Business and Economic Statistics
Organisation d’une conférence ou d’un séminaire
Depuis 2022
International Macro workshop, Banque de France, France
2022
DEMUR Conference, Aix-Marseille Université, France
2021
Workshop on inflation forecasting, SKEMA Business School, France
2020
Macroeconometrics workshop, Paris School of Economics, France
2020
Economic Forecasting at times of Covid-19, International Institute of Forecasters, Etats-Unis d'Amérique
2019
1st Macroeconometrics workshop, Paris School of Economics, France
Affiliations
Depuis 2020
Member of the board of directors, Association Française de Science Economique
2012 - 2020
Member of the board of directors, International Institute of Forecasting
Autres activités académiques
Depuis 2023
Président du Jury du Prix Malinvaud, Association Française de Science Economique
2022
International Symposium on Forecasting, International Institute of Forecasters, Etats-Unis d'Amérique
2022
AFSE Annual Conference, Association Française de Science Economique

Articles académiques revus

FERRARA, L., KARADIMITROPOULOU, A. et TRIANTAFYLLOU, A. (2024). Oil jump tail risk as a driver of inflation dynamics. Journal of Commodity Markets, 36, pp. 100434.
BERMPEI, T., FERRARA, L., KARADIMITROPOULOU, A. et TRIANTAFYLLOU, A. (2024). Commodity currencies revisited: The role of global commodity price uncertainty. Journal of International Money and Finance, 145, pp. 103096.
FERRARA, L. et SIMONI, A. (2023). When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage. Journal of Business and Economic Statistics, 41(4), pp. 1188-1202.
AVIAT, A., BEC, F., DIEBOLT, C., DOZ, C., FERRAND, D., FERRARA, L. ... PIONNIER, P.A. (2023). Les cycles économiques de la France: une datation de référence. Revue Economique, 74(2023/2), pp. 5-52.
BUSSIÈRE, M., CHINN, M., FERRARA, L. et HEIPERTZ, J. (2022). The new Fama puzzle. IMF Economic Review, 70(3), pp. 451-486.
FERRARA, L. et YAPI, J. (2022). Measuring exchange rate risks during periods of uncertainty. International Economics, 170, pp. 202-212.
DELLE CHIAIE, S., FERRARA, L. et GIANNONE, D. (2022). Common factors of commodity prices. Journal of Applied Econometrics, 37(3), pp. 461-476.
FERRARA, L., MOGLIANI, M. et SAHUC, J.G. (2022). High-frequency monitoring of Growth-at-Risk. International Journal of Forecasting, 38(2), pp. 582-595.
FERRARA, L., METELLI, L., NATOLI, F. et DANIELE, S. (2021). Questioning the puzzle: Fiscal policy, real exchange rate and inflation. Journal of International Economics, 133, pp. 103524.
CANDELON, B., FERRARA, L. et JOETS, M. (2021). Global financial interconnectedness: a non-linear assessment of the uncertainty channel. Applied Economics, 53(25), pp. 2865-2887.
FERRARA, L. et MARSILLI, C. (2019). Nowcasting global economic growth: A factor-augmented mixed-frequency approach. World Economy, 42(3), pp. 846-875.
CHINN, M., FERRARA, L. et GIACOMINI, R. (2018). Impact of uncertainty shocks on the global economy. Journal of International Money and Finance, 88, pp. 209-211.
FERRARA, L. et GUERIN, P. (2018). What are the macroeconomic effects of high-frequency uncertainty shocks? Journal of Applied Econometrics, 33(5), pp. 662-679.
CHARLES, A., DARNÉ, O. et FERRARA, L. (2018). Does the Great Recession imply the end of the Great Moderation? International evidence. Economic Inquiry, 56(2), pp. 745-760.
FERRARA, L. et BELLEGO, C. (2017). Forecasting euro area recessions by combining financial information. International Journal of Computational Economics and Econometrics, 7(1-2), pp. 78-94.
BARHOUMI, K., DARNÉ, O. et FERRARA, L. (2016). A World Trade Leading Index (WTLI). Economics Letters, 146, pp. 111-115.
FERRARA, L., MARCELLINO, M. et MOGLIANI, M. (2015). Macroeconomic forecasting during the Great Recession: The return of non-linearity? International Journal of Forecasting, 31(3), pp. 664-679.
AMÉLIE, C., DARNÉ, O., DIEBOLT, C. et FERRARA, L. (2015). A new monthly chronology of the US industrial cycles in the prewar economy. Journal of Financial Stability, 17, pp. 3-9.
BEC, F., BOUADALLAH, O. et FERRARA, L. (2015). Comparing the shapes of recoveries: France, the UK and the US. Economic Modelling, 44, pp. 327-334.
FERRARA, L., CHINN, M. et MIGNON, V. (2014). Explaining US Employment Growth after the Great Recession: The role of Output-Employment Non-linearities. Journal of Macroeconomics, 42, pp. 118-129.
BEC, F., BOUADALLAH, O. et FERRARA, L. (2014). The way out of recessions: Evidence from a bounce-back augmented threshold regression. International Journal of Forecasting, 30(3), pp. 539-549.
FERRARA, L., MARSILLI, C. et ORTEGA, J.P. (2014). Forecasting growth during the Great Recession: is financial volatility the missing ingredient? Economic Modelling, 36, pp. 44-50.
FERRARA, L. et VAN DIJK, D. (2014). Forecasting the business cycle. International Journal of Forecasting, 30, pp. 517-519.
FERRARA, L., BILLIO, M., GUEGAN, D. et MAZZI, G.L. (2013). Evaluation of regime-switching models for real-time business cycle analysis of the euro area. Journal of Forecasting, 32(7), pp. 577-586.
FERRARA, L. (2013). Comments on: “Examining the quality of early GDP component estimates”. International Journal of Forecasting, 29(4), pp. 751-753.
FERRARA, L. et MARSILLI, C. (2013). Financial variables as leading indicators of GDP growth: Evidence from a MIDAS approach during the Great Recession. Applied Economics Letters, 20(3), pp. 233-237.
BARHOUMI, K., DARNÉ, O. et FERRARA, L. (2013). Testing the number of factors: An empirical assessment for forecasting purposes. Oxford Bulletin of Economics and Statistics, 75(1), pp. 64-79.
BARHOUMI, K., DARNÉ, O. et FERRARA, L. (2012). Une revue de la littérature des modèles à facteurs dynamiques. Economie et Prévision, 199, pp. 51-77.
BARHOUMI, K., DARNÉ, O., FERRARA, L. et PLUYAUD, B. (2012). Monthly GDP forecasting using bridge models: Application for the french economy. Bulletin of Economic Research, 64(s1), pp. 53-70.
BELLEGO, C. et FERRARA, L. (2012). Macro-financial linkages and business cycles: A factor-augmented probit approach. Economic Modelling, 29(5), pp. 1793-1797.
DARNÉ, O. et FERRARA, L. (2011). Identification of slowdowns and accelerations for the euro area economy;. Oxford Bulletin of Economics and Statistics, 73(3), pp. 335-364.
BARHOUMI, K. et FERRARA, L. (2010). Are disaggregate data useful for forecasting French GDP with dynamic factor models ? Journal of Forecasting, 29(1-2), pp. 132-144.
FERRARA, L. (2010). Les variables financières sont-elles utiles pour anticiper la croissance économique ? Quelques évidences économétriques. Revue Economique, 61(3), pp. 645-655.
FERRARA, L., GUEGAN, D. et RAKOTOMAROLAHY, P. (2010). GDP nowcasting with ragged-edge data: a semi-parametric modeling. Journal of Forecasting, 29(1-2), pp. 186-199.
ADANERO-DONDERIS, M., DARNÉ, O. et FERRARA, L. (2009). Un indicateur probabiliste du cycle d'accélération pour l'économie française. Economie et Prévision, 189, pp. 95-114.
FERRARA, L. (2009). Caractérisation et datation des cycles économiques en zone Euro. Revue Economique, 60(3), pp. 703-712.
FERRARA, L. et GUEGAN, D. (2008). Business surveys modelling with Seasonal-Cyclical Long Memory models. Economics Bulletin, 3, pp. 1-10.
FERRARA, L. (2003). A three-regime real-time indicator for the US economy. Economics Letters, 81(3), pp. 373-378.
FERRARA, L. et GUEGAN, D. (2001). Forecasting with k-factor Gegenbauer processes: Theory and applications. Journal of Forecasting, 20(8), pp. 581-601.

Articles académiques non revus

ANAS, J., BILLIO, M., FERRARA, L. et MAZZI, G.L. (2008). A system for dating and detecting turning points in the euro area. Manchester School, 76(5), pp. 549-577.

Chapitres d’ouvrage

FERRARA, L., MARSILLI, C. et BANULESCU-RADU, D. (2020). Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences. Dans: Amélie Charles, Olivier Darné et Laurent Ferrara eds. Méthodes de Prévision en Finance. 1st ed. Economica.
FERRARA, L. et MAZZI, G.L. (2018). Parametric models for cyclical composite indicators. Dans: G.L. Mazzi (ed.). Handbook on cyclical composite indicators for business cycle analysis. 1st ed. European Union and United Nations, pp. 327-356.
FERRARA, L., ANAS, J., BILLIO, M., CARATI, L. et MAZZI, G.L. (2017). Cyclical composite indicators detecting turning points. Dans: Handbook on cyclical composite indicators for business cycle analysis. 1st ed. European Union and United Nations, pp. 357-398.
FERRARA, L. et VIGNA, O. (2010). Cyclical relationships between GDP and housing market in France: Facts and factors at play. Dans: O. De Bandt, T. Knetsch, J. Peñalosa and F. Zollino eds. Housing Markets in Europe: A Macroeconomic Perspective. 1st ed. Berlin: Springer, pp. 39-60.
FERRARA, L. et KOOPMAN, S.J. (2010). Common business and housing markets cycles in the euro area from a multivariate decomposition. Dans: O. De Bandt, T. Knetsch, J. Peñalosa and F. Zollino eds. Housing Markets in Europe: A Macroeconomic Perspective. 1st ed. Berlin: Springer, pp. 105-128.
FERRARA, L., ALVARES, L., CABRERO, A., BULLIGAN, G. et STAHL, H. (2010). Housing cycles in the major euro area countries. Dans: O. De Bandt, T. Knetsch, J. Peñalosa and F. Zollino eds. Housing Markets in Europe: A Macroeconomic Perspective. 1st ed. Springer, pp. 85-103.

Editeur invité d’un numéro spécial

FERRARA, L. et SHENG, S.X. (2022). Economic forecasting in times of Covid-19. International Journal of Forecasting, 38(2), pp. 527-528.

Ouvrages et édition d’ouvrages

FERRARA, L., CHARLES, A. et DARNÉ, O. [Eds] (2020). Méthodes de Prévision en Finance. Economica, 216 pages.
FERRARA, L., HERNANDO, I. et MARCONI, D. (2018). International Macroeconomics in the Wake of the Global Financial Crisis. Springer, 312 pages.
FERRARA, L. et GUEGAN, D. (2002). Analyser les séries chronologiques avec S-Plus : Une approche paramétrique. Presses Universitaires de Rennes, 147 pages.

Présentations dans des conférences

FERRARA, L. (2021). High frequency monitoring of Growth-at-Risk. Dans: AFSE (Annual conference French Economic Association). Lille.
FERRARA, L. (2021). High frequency monitoring of Growth-at-Risk. Dans: Computational Economics and Finance. Tokyo (Virtual).
FERRARA, L. (2021). High frequency monitoring of Growth-at-Risk. Dans: OFCE seminar. Paris.
FERRARA, L. (2021). High frequency monitoring of Growth-at-Risk. Dans: European Commission Conference on Big Data. Milan.
FERRARA, L. (2021). High frequency monitoring of Growth-at-Risk. Dans: European Central Bank, Forecasting Conference. Frankfurt.
FERRARA, L., SAHUC, J.G. et MOGLIANI, M. (2020). Real-time high frequency monitoring of Growth-at-Risk. Dans: Workshop on Economic Forecasting at times of Covid-19. Washington.
FERRARA, L. (2020). Business cycle dynamics after the Great Recession: An extended Markov-Switching Dynamic Factor Model. Dans: International Symposium on Forecasting. Rio.
FERRARA, L. (2019). Business Cycle Dynamics after the Great Recession: An Extended Markov-Switching Dynamic Factor Model. Dans: Real-time data Workshop. Brussels.
FERRARA, L. et SIMONI, A. (2019). When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage. Dans: International Symposium on Forecasting. Thessaloniki.
FERRARA, L. et SIMONI, A. (2019). When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage. Dans: OECD Workshop on Time Series Methods. Paris.
FERRARA, L. (2019). Business cycle dynamics after the Great Recession: An extended Markov-Switching Dynamic Factor Model. Dans: Conference on Forecasting at Central Banks, Bank of Canada. Ottawa.

Présentations dans des séminaires de recherche

FERRARA, L. (2021). Business cycle dynamics after the Great Recession: An extended Markov-Switching Dynamic Factor Model. Dans: University of Piraeus seminar. Piraeus.
FERRARA, L. (2020). Business cycle dynamics after the Great Recession: An extended Markov-Switching Dynamic Factor Model. Dans: University Paris Nanterre Seminar. Nanterre.
FERRARA, L. (2020). Business cycle dynamics after the Great Recession: An extended Markov-Switching Dynamic Factor Model. Dans: Essex Business School Seminar. London.

Presse et réseaux sociaux

FERRARA, L. (2022). The Surprising Drop in French Economic Activity. Econbrowser.
FERRARA, L., SAHUC, J.G. et MOGLIANI, M. (2022). High-frequency macroeconomic risk measures in the wake of the war in Ukraine. VoxEU.
FERRARA, L. (2021). The Covid-19 recession in France: The trough is behind us, but let’s stay vigilant. VoxEU, France.
FERRARA, L. (2021). Dating business cycles in France: A reference chronology. VoxEU.
FERRARA, L., BUSSIÈRE, M., CHINN, M. et HEIPERTZ, J. (2018). The new Fama puzzle. VoxEU.