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  1. Nowcasting GDP
    a scalable approach using DFM, machine learning and novel data, applied to European economies
    Author: Dauphin, Jean-François; Dybczak, Kamil; Maneely, Morgan; Taheri Sanjani, Marzie; Suphaphiphat, Nujin; Wang, Yifei; Zhang, Hanqi
    Published: 2022 MAR
    Publisher:  International Monetary Fund, [Washington, D.C.]

    This paper describes recent work to strengthen nowcasting capacity at the IMF's European department. It motivates and compiles datasets of standard and nontraditional variables, such as Google search and air quality. It applies standard dynamic... more

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    This paper describes recent work to strengthen nowcasting capacity at the IMF's European department. It motivates and compiles datasets of standard and nontraditional variables, such as Google search and air quality. It applies standard dynamic factor models (DFMs) and several machine learning (ML) algorithms to nowcast GDP growth across a heterogenous group of European economies during normal and crisis times. Most of our methods significantly outperform the AR(1) benchmark model. Our DFMs tend to perform better during normal times while many of the ML methods we used performed strongly at identifying turning points. Our approach is easily applicable to other countries, subject to data availability

     
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  2. Global economic prospects
    Published: 2022; ©2022
    Publisher:  World Bank Publications, Washington, D. C.

    Cover -- Half Title -- Title Page -- Copyright Page -- Summary of Contents -- Contents -- Acknowledgments -- Foreword -- Executive Summary -- Abbreviations -- Chapter 1 Global Outlook -- Summary -- Global Context -- Global Trade -- Commodity Markets... more

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    Cover -- Half Title -- Title Page -- Copyright Page -- Summary of Contents -- Contents -- Acknowledgments -- Foreword -- Executive Summary -- Abbreviations -- Chapter 1 Global Outlook -- Summary -- Global Context -- Global Trade -- Commodity Markets -- Global Inflation -- Financial Developments -- Major Economies: Recent Developments and Outlook -- Advanced Economies -- China -- Emerging Market and Developing Economies -- Recent Developments -- Outlook -- Global outlook and risks -- Global Outlook -- Risks to The Outlook -- Growth Under Alternative Downside Scenarios -- Policy Challenges -- Key Global Challenges -- Challenges in Advanced Economies -- Challenges in Emerging Market and Developing Economies -- References -- Special Focus 1 Global Stagflation -- Introduction -- Evolution of Inflation -- Evolution of Growth -- Echoes of The Stagflation of The 1970s? -- Similarities to The 1970s -- Differences from The 1970s -- End of Stagflation of The 1970s and Lessons for today -- Aftermath of High Inflation in The 1970s -- Implications for The 2020s -- Structural Forces of Disinflation -- Challenges for EMDEs -- Policy Options for EMDEs -- Annex SF1.1 Methodology: Decomposing Inflation -- Annex SF1.2 Methodology: Estimating Potential Growth -- References -- Special Focus 2 Russia's Invasion of Ukraine: Implications for Energy Markets and Activity -- Introduction -- Comparison With Previous Energy Shocks -- Lessons from Previous Energy Shocks -- Implications for The Global Economy -- Channels -- Impact on Global Activity -- Policy Implications -- References -- Chapter 2 Regional Outlooks -- East Asia and Pacific -- Recent Developments -- Outlook -- Risks -- Europe and Central Asia -- Recent Developments -- Outlook -- Risks -- Latin America and The Caribbean -- Recent Developments -- Outlook -- Risks -- Middle East and North Africa.

     
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    Source: Union catalogues
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9781464818448
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    Edition: 1st ed.
    Series: Global economic prospects ; June 2022
    World Bank Group flagship report ; June 2022
    Subjects: Developing countries; Economic forecasting; Economic history; Electronic books
    Scope: 1 Online-Ressource (150 Seiten)
  3. Nowcasting GDP
    a scalable approach using DFM, machine learning and novel data, applied to European economies
    Author: Dauphin, Jean-François; Dybczak, Kamil; Maneely, Morgan; Taheri Sanjani, Marzie; Suphaphiphat, Nujin; Wang, Yifei; Zhang, Hanqi
    Published: 2022 MAR
    Publisher:  International Monetary Fund, [Washington, D.C.]

    This paper describes recent work to strengthen nowcasting capacity at the IMF's European department. It motivates and compiles datasets of standard and nontraditional variables, such as Google search and air quality. It applies standard dynamic... more

    Access:
    Verlag (kostenfrei)
    Verlag (kostenfrei)
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    Verlag (kostenfrei)

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    Staatsbibliothek zu Berlin - Preußischer Kulturbesitz, Haus Unter den Linden
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    This paper describes recent work to strengthen nowcasting capacity at the IMF's European department. It motivates and compiles datasets of standard and nontraditional variables, such as Google search and air quality. It applies standard dynamic factor models (DFMs) and several machine learning (ML) algorithms to nowcast GDP growth across a heterogenous group of European economies during normal and crisis times. Most of our methods significantly outperform the AR(1) benchmark model. Our DFMs tend to perform better during normal times while many of the ML methods we used performed strongly at identifying turning points. Our approach is easily applicable to other countries, subject to data availability

     
    Export to reference management software   RIS file
      BibTeX file