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Clément Marsilli
(Clement Marsilli)

Personal Details

First Name:Clement
Middle Name:
Last Name:Marsilli
Suffix:
RePEc Short-ID:pma1639
[This author has chosen not to make the email address public]
Banque de France International Macroeconomics Division 31 rue Croix des Petits-Champs F-75001 PARIS
33 1 42 97 77 11
Twitter: @clementmarsilli

Affiliation

Banque de France

Paris, France
http://www.banque-france.fr/
RePEc:edi:bdfgvfr (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Chapters

Working papers

  1. Denisa Georgiana Banulescu & Ferrara Laurent & Marsilli Clément, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," Working Papers hal-03563168, HAL.
  2. Cabrillac, Bruno & Al-Haschimi, Alexander & Babecká Kucharčuková, Oxana & Borin, Alessandro & Bussière, Matthieu & Cezar, Raphael & Derviz, Alexis & Dimitropoulou, Dimitra & Ferrara, Laurent & Gächter, 2016. "Understanding the weakness in global trade - What is the new normal?," Occasional Paper Series 178, European Central Bank.
  3. C. Marsilli, 2014. "Variable Selection in Predictive MIDAS Models," Working papers 520, Banque de France.
  4. L. Ferrara & C. Marsilli, 2014. "Nowcasting global economic growth: A factor-augmented mixed-frequency approach," Working papers 515, Banque de France.
  5. Ferrara, L. & Marsilli, C. & Ortega, J-P., 2013. "Forecasting growth during the Great Recession: is financial volatility the missing ingredient?," Working papers 454, Banque de France.
  6. Laurent Ferrara & Clément Marsilli, 2012. "Financial variables as leading indicators of GDP growth: Evidence from a MIDAS approach during the Great Recession," EconomiX Working Papers 2012-19, University of Paris Nanterre, EconomiX.

Articles

  1. Rafaël Cezar & Rémy Lecat & Clément Marsilli & Floriane Van Den Hove, 2022. "Covid 19 crisis and capital outflows from emerging economies: global safety nets are effective, but need to be strengthened [Crise Covid 19 et sorties de capitaux dans les économies émergentes : de," Bulletin de la Banque de France, Banque de France, issue 239.
  2. Camille Fabre & Clément Marsilli, 2021. "Dette des pays émergents et en développement : panorama des années 1970 à la crise actuelle," Revue d'économie financière, Association d'économie financière, vol. 0(1), pages 23-44.
  3. Genre Véronique & Lecat Rémy & Marsilli Clément, 2020. "The euro in the history of the international monetary system [L’euro dans l’histoire du système monétaire international]," Bulletin de la Banque de France, Banque de France, issue 229.
  4. Bruno Cabrillac & Clément Marsilli & Sophie Rivaud, 2020. "De la libéralisation à la gestion des flux de capitaux internationaux," Revue d'économie financière, Association d'économie financière, vol. 0(1), pages 269-298.
  5. Laurent Ferrara & Clément Marsilli, 2019. "Nowcasting global economic growth: A factor‐augmented mixed‐frequency approach," The World Economy, Wiley Blackwell, vol. 42(3), pages 846-875, March.
  6. Clément Marsilli, 2017. "Nowcasting US inflation using a MIDAS augmented Phillips curve," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 7(1/2), pages 64-77.
  7. Ferrara , L. & Marsilli, C., 2016. "Nowcasting global economic growth," Rue de la Banque, Banque de France, issue 23, April..
  8. Ferrara, Laurent & Marsilli, Clément & Ortega, Juan-Pablo, 2014. "Forecasting growth during the Great Recession: is financial volatility the missing ingredient?," Economic Modelling, Elsevier, vol. 36(C), pages 44-50.
  9. Laurent Ferrara & Cl�ment Marsilli, 2013. "Financial variables as leading indicators of GDP growth: Evidence from a MIDAS approach during the Great Recession," Applied Economics Letters, Taylor & Francis Journals, vol. 20(3), pages 233-237, February.

Chapters

  1. Vincent Grossmann-Wirth & Clément Marsilli, 2018. "The Role of Debt Dynamics in US Household Consumption," Financial and Monetary Policy Studies, in: Laurent Ferrara & Ignacio Hernando & Daniela Marconi (ed.), International Macroeconomics in the Wake of the Global Financial Crisis, pages 115-128, Springer.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Ferrara, L. & Marsilli, C. & Ortega, J-P., 2013. "Forecasting growth during the Great Recession: is financial volatility the missing ingredient?," Working papers 454, Banque de France.

    Mentioned in:

    1. Guest Contribution: “Nowcasting Global GDP Growth”
      by Menzie Chinn in Econbrowser on 2015-03-12 09:56:18
  2. L. Ferrara & C. Marsilli, 2014. "Nowcasting global economic growth: A factor-augmented mixed-frequency approach," Working papers 515, Banque de France.

    Mentioned in:

    1. Guest Contribution: “Nowcasting Global GDP Growth”
      by Menzie Chinn in Econbrowser on 2015-03-12 09:56:18

Working papers

  1. Cabrillac, Bruno & Al-Haschimi, Alexander & Babecká Kucharčuková, Oxana & Borin, Alessandro & Bussière, Matthieu & Cezar, Raphael & Derviz, Alexis & Dimitropoulou, Dimitra & Ferrara, Laurent & Gächter, 2016. "Understanding the weakness in global trade - What is the new normal?," Occasional Paper Series 178, European Central Bank.

    Cited by:

    1. Kilian, Lutz & Zhou, Xiaoqing, 2018. "Modeling fluctuations in the global demand for commodities," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 54-78.
    2. Guillaume Gaulier & Aude Sztulman & Deniz Ünal, 2019. "Are global value chains receding? The jury is still out. Key findings from the analysis of deflated world trade in parts and components," Working papers 715, Banque de France.
    3. C. Mazet-Sonilhac & J.-S. Mésonnier, 2016. "The cost of equity for large non-financial companies in the euro area: an estimation over the last decade," Quarterly selection of articles - Bulletin de la Banque de France, Banque de France, issue 44, pages 28-39, Winter.
    4. Gächter, Martin & Gkrintzalis, Ioannis, 2017. "The finance–trade nexus revisited: Is the global trade slowdown also a financial story?," Economics Letters, Elsevier, vol. 158(C), pages 21-25.
    5. A. Boileau & L. Carlino & A. S. Lafon, 2016. "In the first half of 2016, the main French groups increased their profitability," Quarterly selection of articles - Bulletin de la Banque de France, Banque de France, issue 44, pages 40-51, Winter.
    6. R. Cezar, 2016. "France’s pharmaceutical industry in global value chains," Quarterly selection of articles - Bulletin de la Banque de France, Banque de France, issue 44, pages 52-63, Winter.
    7. E. Buttin, 2016. "Green bonds: a solution for financing the energy transition or a simple buzzword?," Quarterly selection of articles - Bulletin de la Banque de France, Banque de France, issue 44, pages 20-27, Winter.
    8. William F. Lincoln & Andrew H. McCallum & Michael Siemer, 2019. "The Great Recession and a Missing Generation of Exporters," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 67(4), pages 703-745, December.
    9. B. Cabrillac & L. Gauvin & J.-L. Gossé, 2016. "GDP-indexed bonds: what are the benefits for issuing countries, investors and international financial stability?," Quarterly selection of articles - Bulletin de la Banque de France, Banque de France, issue 44, pages 6-19, Winter.
    10. Rougès, D. & Strauss-Kahn, M.-O., 2017. "Sondage 2016 sur les Français et l’économie : comportements, préoccupations et attentes," Bulletin de la Banque de France, Banque de France, issue 209, pages 15-23.
    11. Xuefeng Qian & Zhao Liu & Ying Pan, 2017. "China's Trade Slowdown: Cyclical or Structural?," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 25(6), pages 65-83, November.
    12. Humbertclaude, S. & Monteil, F., 2017. "Le patrimoine économique national en 2015 : un modeste rebond," Bulletin de la Banque de France, Banque de France, issue 209, pages 5-14.
    13. Cezar, R., 2017. "L’industrie pharmaceutique française dans les chaînes de valeur mondiales," Bulletin de la Banque de France, Banque de France, issue 209, pages 57-69.
    14. Gunnella, Vanessa & Al-Haschimi, Alexander & Benkovskis, Konstantins & Chiacchio, Francesco & de Soyres, François & Di Lupidio, Benedetta & Fidora, Michael & Franco-Bedoya, Sebastian & Frohm, Erik & G, 2019. "The impact of global value chains on the euro area economy," Occasional Paper Series 221, European Central Bank.
    15. Bureau, B. & Bürker, M. & Libert, T., 2017. "La situation des entreprises en France en 2015," Bulletin de la Banque de France, Banque de France, issue 209, pages 39-55.
    16. Sondermann, David & Consolo, Agostino & Gunnella, Vanessa & Koester, Gerrit & Lambrias, Kyriacos & Lopez-Garcia, Paloma & Nerlich, Carolin & Petroulakis, Filippos & Saiz, Lorena & Serafini, Roberta, 2019. "Economic structures 20 years into the euro," Occasional Paper Series 224, European Central Bank.
    17. Hagemejer, Jan & Hałka, Aleksandra & Kotłowski, Jacek, 2022. "Global value chains and exchange rate pass-through—The role of non-linearities," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 461-478.
    18. Boileau, A. & Chavy-Martin, A.-C., 2017. "Les délais de paiement sont stables en 2015," Bulletin de la Banque de France, Banque de France, issue 209, pages 25-38.

  2. C. Marsilli, 2014. "Variable Selection in Predictive MIDAS Models," Working papers 520, Banque de France.

    Cited by:

    1. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2022. "Machine Learning Time Series Regressions With an Application to Nowcasting," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1094-1106, June.
    2. Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Post-Print hal-03647097, HAL.
    3. Götz, T.B. & Hecq, A.W., 2014. "Testing for Granger causality in large mixed-frequency VARs," Research Memorandum 028, Maastricht University, Graduate School of Business and Economics (GSBE).
    4. Matteo Mogliani & Anna Simoni, 2020. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Post-Print hal-03089878, HAL.
    5. Boriss Siliverstovs, 2017. "Short-term forecasting with mixed-frequency data: a MIDASSO approach," Applied Economics, Taylor & Francis Journals, vol. 49(13), pages 1326-1343, March.
    6. O-Chia Chuang & Chenxu Yang, 2022. "Identifying the Determinants of Crude Oil Market Volatility by the Multivariate GARCH-MIDAS Model," Energies, MDPI, vol. 15(8), pages 1-14, April.
    7. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
    8. Xu, Qifa & Zhuo, Xingxuan & Jiang, Cuixia & Liu, Xi & Liu, Yezheng, 2018. "Group penalized unrestricted mixed data sampling model with application to forecasting US GDP growth," Economic Modelling, Elsevier, vol. 75(C), pages 221-236.
    9. Yoshiki Nakajima & Naoya Sueishi, 2022. "Forecasting the Japanese macroeconomy using high-dimensional data," The Japanese Economic Review, Springer, vol. 73(2), pages 299-324, April.
    10. Li, Xiafei & Liang, Chao & Chen, Zhonglu & Umar, Muhammad, 2022. "Forecasting crude oil volatility with uncertainty indicators: New evidence," Energy Economics, Elsevier, vol. 108(C).
    11. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2019. "High-Dimensional Granger Causality Tests with an Application to VIX and News," Papers 1912.06307, arXiv.org, revised Feb 2021.
    12. Ghysels, Eric & Qian, Hang, 2019. "Estimating MIDAS regressions via OLS with polynomial parameter profiling," Econometrics and Statistics, Elsevier, vol. 9(C), pages 1-16.
    13. Jiang, Cuixia & Xiong, Wei & Xu, Qifa & Liu, Yezheng, 2021. "Predicting default of listed companies in mainland China via U-MIDAS Logit model with group lasso penalty," Finance Research Letters, Elsevier, vol. 38(C).

  3. L. Ferrara & C. Marsilli, 2014. "Nowcasting global economic growth: A factor-augmented mixed-frequency approach," Working papers 515, Banque de France.

    Cited by:

    1. Christiane Baumeister & Pierre Guérin, 2020. "A Comparison of Monthly Global Indicators for Forecasting Growth," CESifo Working Paper Series 8656, CESifo.
    2. Kose, M. Ayhan & Sugawara, Naotaka & E. Terrones, Marco, 2020. "Global Recessions," CEPR Discussion Papers 14397, C.E.P.R. Discussion Papers.
    3. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2020. "Nowcasting Norwegian household consumption with debit card transaction data," Working Paper 2020/17, Norges Bank.
    4. Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
    5. Zhemkov, Michael, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, Elsevier, vol. 168(C), pages 10-24.
    6. Francesco Ravazzolo & Joaquin Vespignani, 2017. "World steel production: A new monthly indicator of global real economic activity," CAMA Working Papers 2017-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Maximo Camacho & Jaime Martinez-Martin, 2015. "Monitoring the world business cycle," Working Papers 1509, Banco de España.
    8. Stankevich, Ivan, 2020. "Comparison of macroeconomic indicators nowcasting methods: Russian GDP case," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 113-127.
    9. Luciano Campos & Danilo Leiva-León & Steven Zapata- Álvarez, 2022. "Latin American Falls, Rebounds and Tail Risks," Borradores de Economia 1201, Banco de la Republica de Colombia.
    10. Baumann, Ursel & Gomez-Salvador, Ramon & Seitz, Franz, 2019. "Detecting turning points in global economic activity," Working Paper Series 2310, European Central Bank.
    11. Ferrara , L. & Marsilli, C., 2016. "Nowcasting global economic growth," Rue de la Banque, Banque de France, issue 23, April..
    12. Katja Heinisch & Axel Lindner, 2019. "For how long do IMF forecasts of world economic growth stay up-to-date?," Applied Economics Letters, Taylor & Francis Journals, vol. 26(3), pages 255-260, February.
    13. Chatelais, Nicolas & Stalla-Bourdillon, Arthur & Chinn, Menzie D., 2023. "Forecasting real activity using cross-sectoral stock market information," Journal of International Money and Finance, Elsevier, vol. 131(C).
    14. Johanna Garnitz & Robert Lehmann & Klaus Wohlrabe, 2019. "Forecasting GDP all over the world using leading indicators based on comprehensive survey data," CESifo Working Paper Series 7691, CESifo.
    15. Mahmut Gunay, 2018. "Nowcasting Annual Turkish GDP Growth with MIDAS," CBT Research Notes in Economics 1810, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    16. Nicolas Chatelais & Arthur Stalla-Bourdillon & Menzie D. Chinn, 2022. "Macroeconomic Forecasting using Filtered Signals from a Stock Market Cross Section," NBER Working Papers 30305, National Bureau of Economic Research, Inc.
    17. Jack Fosten & Shaoni Nandi, 2023. "Nowcasting from cross‐sectionally dependent panels," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 898-919, September.
    18. Denisa BANULESCU-RADU & Laurent FERRARA & Clément MARSILLI, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," LEO Working Papers / DR LEO 2710, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    19. Garnitz, Johanna & Lehmann, Robert & Wohlrabe, Klaus, 2017. "Forecasting GDP all over the World: Evidence from Comprehensive Survey Data," MPRA Paper 81772, University Library of Munich, Germany.
    20. C. Marsilli, 2014. "Variable Selection in Predictive MIDAS Models," Working papers 520, Banque de France.

  4. Ferrara, L. & Marsilli, C. & Ortega, J-P., 2013. "Forecasting growth during the Great Recession: is financial volatility the missing ingredient?," Working papers 454, Banque de France.

    Cited by:

    1. Laurent Ferrara & Stéphane Lhuissier & Fabien Tripier, 2017. "Uncertainty Fluctuations: Measures, Effects and Macroeconomic Policy Challenges," CEPII Policy Brief 2017-20, CEPII research center.
    2. Marcelle Chauvet & Zeynep Senyuz & Emre Yoldas, 2013. "What does financial volatility tell us about macroeconomic fluctuations?," Finance and Economics Discussion Series 2013-61, Board of Governors of the Federal Reserve System (U.S.).
    3. Mikosch, Heiner & Solanko, Laura, 2017. "Should one follow movements in the oil price or in money supply? Forecasting quarterly GDP growth in Russia with higher-frequency indicators," BOFIT Discussion Papers 19/2017, Bank of Finland Institute for Emerging Economies (BOFIT).
    4. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
    5. Vortelinos, Dimitrios I., 2017. "Forecasting realized volatility: HAR against Principal Components Combining, neural networks and GARCH," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 824-839.
    6. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
    7. Marie Bessec, 2019. "Revisiting the transitional dynamics of business-cycle phases with mixed-frequency data," Post-Print hal-02181552, HAL.
    8. Grégory Levieuge, 2017. "Explaining and forecasting bank loans. Good times and crisis," Post-Print hal-03529226, HAL.
    9. Heiner Mikosch & Laura Solanko, 2019. "Forecasting Quarterly Russian GDP Growth with Mixed-Frequency Data," Russian Journal of Money and Finance, Bank of Russia, vol. 78(1), pages 19-35, March.
    10. Cremers, Martijn & Fleckenstein, Matthias & Gandhi, Priyank, 2021. "Treasury yield implied volatility and real activity," Journal of Financial Economics, Elsevier, vol. 140(2), pages 412-435.
    11. Laurent Ferrara & Clément Marsilli, 2019. "Nowcasting global economic growth: A factor‐augmented mixed‐frequency approach," The World Economy, Wiley Blackwell, vol. 42(3), pages 846-875, March.
    12. Junttila, Juha & Vataja, Juuso, 2018. "Economic policy uncertainty effects for forecasting future real economic activity," Economic Systems, Elsevier, vol. 42(4), pages 569-583.
    13. Giovanni Ballarin & Petros Dellaportas & Lyudmila Grigoryeva & Marcel Hirt & Sophie van Huellen & Juan-Pablo Ortega, 2022. "Reservoir Computing for Macroeconomic Forecasting with Mixed Frequency Data," Papers 2211.00363, arXiv.org, revised Jan 2024.
    14. an de Meulen, Philipp, 2015. "Das RWI-Kurzfristprognosemodell," RWI Konjunkturberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, vol. 66(2), pages 25-46.
    15. Fatemeh Salimi, 2020. "Exchange Rates, Stock Prices, and Stock Market Uncertainty," Working Papers halshs-03007904, HAL.
    16. Gani Ramadani & Magdalena Petrovska & Vesna Bucevska, 2021. "Evaluation of mixed frequency approaches for tracking near-term economic developments in North Macedonia," Working Papers 2021-03, National Bank of the Republic of North Macedonia.
    17. Marie Bessec, 2015. "Revisiting the transitional dynamics of business-cycle phases with mixed frequency data," Post-Print hal-01276824, HAL.
    18. Kitlinski, Tobias & an de Meulen, Philipp, 2015. "The role of targeted predictors for nowcasting GDP with bridge models: Application to the Euro area," Ruhr Economic Papers 559, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    19. Fatemeh Salimi Namin, 2020. "Exchange Rates, Stock Prices, and Stock Market Uncertainty," AMSE Working Papers 2037, Aix-Marseille School of Economics, France.
    20. Laine, Olli-Matti & Lindblad, Annika, 2020. "Nowcasting Finnish GDP growth using financial variables: a MIDAS approach," BoF Economics Review 4/2020, Bank of Finland.
    21. Stefan Gebauer, 2017. "The Use of Financial Market Variables in Forecasting," DIW Roundup: Politik im Fokus 115, DIW Berlin, German Institute for Economic Research.
    22. Ramadani Gani & Petrovska Magdalena & Bucevska Vesna, 2021. "Evaluation of Mixed Frequency Approaches for Tracking Near-Term Economic Developments in North Macedonia," South East European Journal of Economics and Business, Sciendo, vol. 16(2), pages 43-52, December.
    23. C. Marsilli, 2014. "Variable Selection in Predictive MIDAS Models," Working papers 520, Banque de France.
    24. Schumacher, Christian, 2016. "A comparison of MIDAS and bridge equations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 257-270.

  5. Laurent Ferrara & Clément Marsilli, 2012. "Financial variables as leading indicators of GDP growth: Evidence from a MIDAS approach during the Great Recession," EconomiX Working Papers 2012-19, University of Paris Nanterre, EconomiX.

    Cited by:

    1. Deimante Teresiene & Greta Keliuotyte-Staniuleniene & Yiyi Liao & Rasa Kanapickiene & Ruihui Pu & Siyan Hu & Xiao-Guang Yue, 2021. "The Impact of the COVID-19 Pandemic on Consumer and Business Confidence Indicators," JRFM, MDPI, vol. 14(4), pages 1-23, April.
    2. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
    3. Özgür Ömer Ersin & Melike Bildirici, 2023. "Financial Volatility Modeling with the GARCH-MIDAS-LSTM Approach: The Effects of Economic Expectations, Geopolitical Risks and Industrial Production during COVID-19," Mathematics, MDPI, vol. 11(8), pages 1-26, April.
    4. Mittal, Amit & Garg, Ajay Kumar, 2021. "Bank stocks inform higher growth—A System GMM analysis of ten emerging markets in Asia," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 210-220.
    5. Laurent Ferrara & Clément Marsilli & Juan-Pablo Ortega, 2013. "Forecasting US growth during the Great Recession: Is the financial volatility the missing ingredient?," Working Papers hal-04141198, HAL.
    6. Laurent Ferrara & Clément Marsilli, 2019. "Nowcasting global economic growth: A factor‐augmented mixed‐frequency approach," The World Economy, Wiley Blackwell, vol. 42(3), pages 846-875, March.
    7. Mittal, Amit & Garg, Ajay Kumar, 2018. "Bank stocks inform higher growth – A System GMM analysis of ten emerging markets in Asia," MPRA Paper 98253, University Library of Munich, Germany.
    8. Morita, Hiroshi, 2022. "Forecasting GDP growth using stock returns in Japan: A factor-augmented MIDAS approach," Discussion paper series HIAS-E-118, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    9. Gong, Yuting & Chen, Qiang & Liang, Jufang, 2018. "A mixed data sampling copula model for the return-liquidity dependence in stock index futures markets," Economic Modelling, Elsevier, vol. 68(C), pages 586-598.
    10. Petralias, Athanassios & Petros, Sotirios & Prodromídis, Pródromos, 2013. "Greece in recession: economic predictions, mispredictions and policy implications," LSE Research Online Documents on Economics 52626, London School of Economics and Political Science, LSE Library.
    11. C. Marsilli, 2014. "Variable Selection in Predictive MIDAS Models," Working papers 520, Banque de France.
    12. Barhoumi, K. & Darné, O. & Ferrara, L., 2013. "Dynamic Factor Models: A review of the Literature ," Working papers 430, Banque de France.

Articles

  1. Laurent Ferrara & Clément Marsilli, 2019. "Nowcasting global economic growth: A factor‐augmented mixed‐frequency approach," The World Economy, Wiley Blackwell, vol. 42(3), pages 846-875, March.
    See citations under working paper version above.
  2. Clément Marsilli, 2017. "Nowcasting US inflation using a MIDAS augmented Phillips curve," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 7(1/2), pages 64-77.

    Cited by:

    1. Xindi Wang & Zeshui Xu & Xinxin Wang & Marinko Skare, 2022. "A review of inflation from 1906 to 2022: a comprehensive analysis of inflation studies from a global perspective," Oeconomia Copernicana, Institute of Economic Research, vol. 13(3), pages 595-631, September.
    2. Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 20-31, Federal Reserve Bank of Cleveland.
    3. Barış Soybilgen & M. Ege Yazgan & Hüseyin Kaya, 2023. "Nowcasting Turkish Food Inflation Using Daily Online Prices," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(2), pages 171-190, September.

  3. Ferrara, Laurent & Marsilli, Clément & Ortega, Juan-Pablo, 2014. "Forecasting growth during the Great Recession: is financial volatility the missing ingredient?," Economic Modelling, Elsevier, vol. 36(C), pages 44-50.
    See citations under working paper version above.
  4. Laurent Ferrara & Cl�ment Marsilli, 2013. "Financial variables as leading indicators of GDP growth: Evidence from a MIDAS approach during the Great Recession," Applied Economics Letters, Taylor & Francis Journals, vol. 20(3), pages 233-237, February.
    See citations under working paper version above.

Chapters

    Sorry, no citations of chapters recorded.

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 6 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-FOR: Forecasting (4) 2012-04-17 2013-07-15 2013-10-25 2014-12-19
  2. NEP-MAC: Macroeconomics (3) 2013-10-25 2014-11-22 2014-12-19
  3. NEP-ECM: Econometrics (1) 2014-12-19
  4. NEP-ETS: Econometric Time Series (1) 2014-12-19
  5. NEP-INT: International Trade (1) 2016-10-02

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