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Dynamic factor models: A review of the literature

Citations

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Guest Contribution: “Nowcasting Global GDP Growth”
    by Menzie Chinn in Econbrowser on 2015-03-12 09:56:18

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
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Cited by:

  1. Carlos Trucíos & João H. G. Mazzeu & Marc Hallin & Luiz K. Hotta & Pedro L. Valls Pereira & Mauricio Zevallos, 2022. "Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: A General Dynamic Factor Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(1), pages 40-52, December.
  2. Carlos Cesar Trucios-Maza & João H. G Mazzeu & Luis K. Hotta & Pedro L. Valls Pereira & Marc Hallin, 2019. "On the robustness of the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Working Papers ECARES 2019-32, ULB -- Universite Libre de Bruxelles.
  3. Mattia Guerini & Duc Thi Luu & Mauro Napoletano, 2023. "Synchronization patterns in the European Union," Applied Economics, Taylor & Francis Journals, vol. 55(18), pages 2038-2059, April.
  4. Alejandro Steven Fonseca-Zendejas & Carmen Borrego-Salcido & María del Carmen Delgado López, 2025. "Internal migration in Spain: identifying key drivers for forecasting," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 74(2), pages 1-23, June.
  5. Hui ‘Fox’ Ling & Christian Franzen, 2017. "Online learning of time-varying stochastic factor structure by variational sequential Bayesian factor analysis," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1277-1304, August.
  6. repec:hal:spmain:info:hdl:2441/5q8fnecj1u87ka099dc571bhi2 is not listed on IDEAS
  7. David Havrlant & Peter Tóth & Julia Wörz, 2016. "On the optimal number of indicators – nowcasting GDP growth in CESEE," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 4, pages 54-72.
  8. Focardi, Sergio M. & Fabozzi, Frank J. & Mitov, Ivan K., 2016. "A new approach to statistical arbitrage: Strategies based on dynamic factor models of prices and their performance," Journal of Banking & Finance, Elsevier, vol. 65(C), pages 134-155.
  9. Amélie Charles & Olivier Darné, 2022. "Backcasting world trade growth using data reduction methods," The World Economy, Wiley Blackwell, vol. 45(10), pages 3169-3191, October.
  10. Tóth, Peter, 2014. "Malý dynamický faktorový model na krátkodobé prognózovanie slovenského HDP [A Small Dynamic Factor Model for the Short-Term Forecasting of Slovak GDP]," MPRA Paper 63713, University Library of Munich, Germany.
  11. Lütkepohl, Helmut, 2014. "Structural vector autoregressive analysis in a data rich environment: A survey," SFB 649 Discussion Papers 2014-004, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  12. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
  13. Ferrara , L. & Marsilli, C., 2016. "Nowcasting global economic growth," Rue de la Banque, Banque de France, issue 23, April..
  14. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
  15. L. Ferrara. & G. Sestieri., 2014. "US labour market and monetary policy: current debates and challenges," Quarterly selection of articles - Bulletin de la Banque de France, Banque de France, issue 36, pages 111-129, winter.
  16. Mariza Cooray & Rolando Gonzales Martinez, 2025. "Tracking the Hidden Forces Behind Laos' 2022 Exchange Rate Crisis and Balance of Payments Instability," Papers 2503.13308, arXiv.org.
  17. Karen Poghosyan & Ruben Poghosyan, 2021. "On the applicability of dynamic factor models for forecasting real GDP growth in Armenia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 61, pages 28-46.
  18. Trucíos, Carlos & Mazzeu, João H.G. & Hotta, Luiz K. & Valls Pereira, Pedro L. & Hallin, Marc, 2021. "Robustness and the general dynamic factor model with infinite-dimensional space: Identification, estimation, and forecasting," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1520-1534.
  19. Massimiliano Caporin & C. Vladimir Rodríguez-Caballero & Esther Ruiz, 2024. "The factor structure of exchange rates volatility: global and intermittent factors," Empirical Economics, Springer, vol. 67(1), pages 31-45, July.
  20. Herwartz, Helmut & Ochsner, Christian & Rohloff, Hannes, 2020. "The credit composition of global liquidity," University of Göttingen Working Papers in Economics 409, University of Goettingen, Department of Economics.
  21. repec:spo:wpmain:info:hdl:2441/5q8fnecj1u87ka099dc571bhi2 is not listed on IDEAS
  22. Amélie Charles & Olivier Darné & Fabien Tripier, 2018. "Uncertainty and the Macroeconomy: Evidence from an uncertainty composite indicator," Post-Print hal-01757042, HAL.
  23. Camacho, Maximo & Perez-Quiros, Gabriel & Poncela, Pilar, 2018. "Markov-switching dynamic factor models in real time," International Journal of Forecasting, Elsevier, vol. 34(4), pages 598-611.
  24. Marijn A. Bolhuis & Brett Rayner, 2020. "Deus ex Machina? A Framework for Macro Forecasting with Machine Learning," IMF Working Papers 2020/045, International Monetary Fund.
  25. Amélie Charles & Olivier Darné & Fabien Tripier, 2017. "Uncertainty and the Macroeconomy," Post-Print hal-01549625, HAL.
  26. repec:hum:wpaper:sfb649dp2014-004 is not listed on IDEAS
  27. Juan Laborda & Sonia Ruano & Ignacio Zamanillo, 2023. "Multi-Country and Multi-Horizon GDP Forecasting Using Temporal Fusion Transformers," Mathematics, MDPI, vol. 11(12), pages 1-26, June.
  28. Duangnate, Kannika & Mjelde, James W., 2017. "Comparison of data-rich and small-scale data time series models generating probabilistic forecasts: An application to U.S. natural gas gross withdrawals," Energy Economics, Elsevier, vol. 65(C), pages 411-423.
  29. 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.
  30. Karmous, Aida & Boubaker, Heni & Belkacem, Lotfi, 2019. "A dynamic factor model with stylized facts to forecast volatility for an optimal portfolio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
  31. Amélie Charles & Olivier Darné & Fabien Tripier, 2018. "Uncertainty and the macroeconomy: evidence from an uncertainty composite indicator," Applied Economics, Taylor & Francis Journals, vol. 50(10), pages 1093-1107, February.
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