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Displaying results 1 to 7 of 7.

  1. Random subspace local projections
    Author: Viet Hoang Dinh; Nibbering, Didier; Wong, Benjamin
    Published: 2023
    Publisher:  Australian National University, Crawford School of Public Policy, Canberra

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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: CAMA working paper series ; 2023, 34 (July 2023)
    Subjects: Local Projections; Random Subspace; Impulse Response Functions; Large Data Sets
    Scope: 1 Online-Ressource (circa 33 Seiten), Illustrationen
  2. Mitigating climate change
    growth-friendly policies to achieve net zero emissions by 2050
    Author: Jaumotte, Florence; Liu, Weifeng; McKibbin, Warwick J.
    Published: July 2021
    Publisher:  International Monetary Fund, [Washington, D.C.]

    Background paper prepared for the October 2020 IMF World Economic Outlook. This paper provides a detailed presentation of the simulation results from the October 2020 IMF World Economic Outlook chapter 3 and an additional scenario with carbon pricing... more

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    Background paper prepared for the October 2020 IMF World Economic Outlook. This paper provides a detailed presentation of the simulation results from the October 2020 IMF World Economic Outlook chapter 3 and an additional scenario with carbon pricing only for comparison with the comprehensive policy package where green investments were also included. This paper has greatly benefitted from continuous discussions with Oya Celasun and Benjamin Carton on the design of simulations; contributions from Philip Barrett for part of the simulations; and research support from Jaden Kim. We also received helpful comments from other IMF staff. All remaining errors are ours. McKibbin and Liu acknowledge financial support from the Australian Research Council Centre of Excellence in Population Ageing Research (CE170100005)

     
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    Source: Staatsbibliothek zu Berlin
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9781513592978
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    Series: IMF working paper ; WP/21, 195
    Subjects: Climate Change; Net-Zero Emissions; Green Infrastructure; Macroeconomics; DSGE; CGE; G-Cubed; Forecasting and Other Model Applications; Large Data Sets; Model Construction and Estimation; Open Economy Macroeconomics; Quantitative Policy Modeling
    Scope: 1 Online-Ressource (circa 35 Seiten), Illustrationen
  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

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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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    Source: Staatsbibliothek zu Berlin
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9798400204425
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    Series: Working paper / International Monetary Fund ; WP/22, 52
    Subjects: Nowcasting; Factor Model; Machine Learning; Large Data Sets; Forecasting and Other Model Applications; Machine Learning Algorithm; Monetary Policy; Multiple or Simultaneous Equation Models; Nowcasting, Factor Model, Machine Learning and Large Data Sets
    Scope: 1 Online-Ressource (circa 45 Seiten), Illustrationen
  4. Tracking trade from space
    an application to Pacific Island countries
    Author: Arslanalp, Serkan; Koepke, Robin; Verschuur, Jasper
    Published: August 2021
    Publisher:  International Monetary Fund, [Washington, D.C.]

    This paper proposes an easy-to-follow approach to track merchandise trade using vessel data and applies it to Pacific island countries. Pacific islands rely heavily on imports and maritime transport for trade. They are also highly vulnerable to... more

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    This paper proposes an easy-to-follow approach to track merchandise trade using vessel data and applies it to Pacific island countries. Pacific islands rely heavily on imports and maritime transport for trade. They are also highly vulnerable to climate change and natural disasters that pose risks to ports and supply chains. Using satellite-based vessel tracking data from the UN Global Platform, we construct daily indicators of port and trade activity for Pacific island countries. The algorithm significantly advances estimation techniques of previous studies, particularly by employing ways to overcome challenges with the estimation of cargo payloads, using detailed information on shipping liner schedules to validate port calls, and applying country-specific information to define port boundaries. The approach can complement and help fill gaps in official data, provide early warning signs of turning points in economic activity, and assist policymakers and international organizations to monitor and provide timely responses to shocks (e.g., COVID-19)

     
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    Source: Staatsbibliothek zu Berlin
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9781513593531
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    Series: IMF working paper ; WP/21, 225
    Subjects: Big Data; Climate Change; Trade; Asia and Pacific; Global Supply Chains; Climate; Forecasting and Other Model Applications; Large Data Sets; Trade
    Scope: 1 Online-Ressource (circa 40 Seiten), Illustrationen
  5. 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

     
    Export to reference management software   RIS file
      BibTeX file
    Source: Staatsbibliothek zu Berlin
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9798400204425
    Other identifier:
    Series: Working paper / International Monetary Fund ; WP/22, 52
    Subjects: Nowcasting; Factor Model; Machine Learning; Large Data Sets; Forecasting and Other Model Applications; Machine Learning Algorithm; Monetary Policy; Multiple or Simultaneous Equation Models; Nowcasting, Factor Model, Machine Learning and Large Data Sets
    Scope: 1 Online-Ressource (circa 45 Seiten), Illustrationen
  6. Tracking trade from space
    an application to Pacific Island countries
    Author: Arslanalp, Serkan; Koepke, Robin; Verschuur, Jasper
    Published: August 2021
    Publisher:  International Monetary Fund, [Washington, D.C.]

    This paper proposes an easy-to-follow approach to track merchandise trade using vessel data and applies it to Pacific island countries. Pacific islands rely heavily on imports and maritime transport for trade. They are also highly vulnerable to... more

    Access:
    Verlag (kostenfrei)
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    This paper proposes an easy-to-follow approach to track merchandise trade using vessel data and applies it to Pacific island countries. Pacific islands rely heavily on imports and maritime transport for trade. They are also highly vulnerable to climate change and natural disasters that pose risks to ports and supply chains. Using satellite-based vessel tracking data from the UN Global Platform, we construct daily indicators of port and trade activity for Pacific island countries. The algorithm significantly advances estimation techniques of previous studies, particularly by employing ways to overcome challenges with the estimation of cargo payloads, using detailed information on shipping liner schedules to validate port calls, and applying country-specific information to define port boundaries. The approach can complement and help fill gaps in official data, provide early warning signs of turning points in economic activity, and assist policymakers and international organizations to monitor and provide timely responses to shocks (e.g., COVID-19)

     
    Export to reference management software   RIS file
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    Source: Staatsbibliothek zu Berlin
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9781513593531
    Other identifier:
    Series: IMF working paper ; WP/21, 225
    Subjects: Big Data; Climate Change; Trade; Asia and Pacific; Global Supply Chains; Climate; Forecasting and Other Model Applications; Large Data Sets; Trade
    Scope: 1 Online-Ressource (circa 40 Seiten), Illustrationen
  7. Mitigating climate change
    growth-friendly policies to achieve net zero emissions by 2050
    Author: Jaumotte, Florence; Liu, Weifeng; McKibbin, Warwick J.
    Published: July 2021
    Publisher:  International Monetary Fund, [Washington, D.C.]

    Background paper prepared for the October 2020 IMF World Economic Outlook. This paper provides a detailed presentation of the simulation results from the October 2020 IMF World Economic Outlook chapter 3 and an additional scenario with carbon pricing... more

    Access:
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    e-Book International Monetary Fund eLibrary
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    Background paper prepared for the October 2020 IMF World Economic Outlook. This paper provides a detailed presentation of the simulation results from the October 2020 IMF World Economic Outlook chapter 3 and an additional scenario with carbon pricing only for comparison with the comprehensive policy package where green investments were also included. This paper has greatly benefitted from continuous discussions with Oya Celasun and Benjamin Carton on the design of simulations; contributions from Philip Barrett for part of the simulations; and research support from Jaden Kim. We also received helpful comments from other IMF staff. All remaining errors are ours. McKibbin and Liu acknowledge financial support from the Australian Research Council Centre of Excellence in Population Ageing Research (CE170100005)

     
    Export to reference management software   RIS file
      BibTeX file
    Source: Staatsbibliothek zu Berlin
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9781513592978
    Other identifier:
    Series: IMF working paper ; WP/21, 195
    Subjects: Climate Change; Net-Zero Emissions; Green Infrastructure; Macroeconomics; DSGE; CGE; G-Cubed; Forecasting and Other Model Applications; Large Data Sets; Model Construction and Estimation; Open Economy Macroeconomics; Quantitative Policy Modeling
    Scope: 1 Online-Ressource (circa 35 Seiten), Illustrationen