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Forecasting growth during the Great Recession: is financial volatility the missing ingredient?

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. 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.
  2. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
  3. 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.
  4. Marie Bessec, 2019. "Revisiting the transitional dynamics of business cycle phases with mixed-frequency data," Econometric Reviews, Taylor & Francis Journals, vol. 38(7), pages 711-732, August.
  5. Laurent Ferrara & Stéphane Lhuissier & Fabien Tripier, 2018. "Uncertainty Fluctuations: Measures, Effects and Macroeconomic Policy Challenges," Financial and Monetary Policy Studies, in: Laurent Ferrara & Ignacio Hernando & Daniela Marconi (ed.), International Macroeconomics in the Wake of the Global Financial Crisis, pages 159-181, Springer.
  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. Laine, Olli-Matti & Lindblad, Annika, 2020. "Nowcasting Finnish GDP growth using financial variables: a MIDAS approach," BoF Economics Review 4/2020, Bank of Finland.
  8. 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.
  9. repec:zbw:bofitp:2017_019 is not listed on IDEAS
  10. Junttila, Juha & Vataja, Juuso, 2018. "Economic policy uncertainty effects for forecasting future real economic activity," Economic Systems, Elsevier, vol. 42(4), pages 569-583.
  11. C. Marsilli, 2014. "Variable Selection in Predictive MIDAS Models," Working papers 520, Banque de France.
  12. Marie Bessec, 2015. "Revisiting the transitional dynamics of business-cycle phases with mixed frequency data," Post-Print hal-01276824, HAL.
  13. Grégory Levieuge, 2017. "Explaining and forecasting bank loans. Good times and crisis," Applied Economics, Taylor & Francis Journals, vol. 49(8), pages 823-843, February.
  14. Schumacher, Christian, 2016. "A comparison of MIDAS and bridge equations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 257-270.
  15. 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.
  16. 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 Economies in Transition.
  17. repec:dau:papers:123456789/15246 is not listed on IDEAS
  18. Chauvet, Marcelle & Senyuz, Zeynep & Yoldas, Emre, 2015. "What does financial volatility tell us about macroeconomic fluctuations?," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 340-360.
  19. 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.
  20. an de Meulen, Philipp, 2015. "Das RWI-Kurzfristprognosemodell," RWI Konjunkturberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, vol. 66(2), pages 25-46.
  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. 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).
  24. 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.
  25. Fatemeh Salimi, 2020. "Exchange Rates, Stock Prices, and Stock Market Uncertainty," Working Papers halshs-03007904, HAL.
  26. 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.
  27. Fatemeh Salimi Namin, 2020. "Exchange Rates, Stock Prices, and Stock Market Uncertainty," AMSE Working Papers 2037, Aix-Marseille School of Economics, France.
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