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Forecasting using heterogeneous panels with cross-sectional dependence

Author

Listed:
  • Oguzhan Akgun

    (UP1 UFR02 - Université Paris 1 Panthéon-Sorbonne - École d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne)

  • Alain Pirotte

    (CRED - Centre de Recherche en Economie et Droit - UP2 - Université Panthéon-Assas)

  • Giovanni Urga

    (UniBg - Università degli Studi di Bergamo = University of Bergamo)

Abstract

In this paper, we focus on forecasting methods that use heterogeneous panels in the presence of cross-sectional dependence in terms of both spatial error dependence and common factors. We propose two main approaches to estimating the factor structure: a residuals-based approach, and an approach that uses a panel of auxiliary variables to extract the factors. Small sample properties of the proposed methods are investigated through Monte Carlo simulations and applied to predict house price inflation in OECD countries.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Oguzhan Akgun & Alain Pirotte & Giovanni Urga, 2020. "Forecasting using heterogeneous panels with cross-sectional dependence," Post-Print hal-04120413, HAL.
    • Handle: RePEc:hal:journl:hal-04120413
    DOI: 10.1016/j.ijforecast.2019.11.007
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