In this paper, we focus on forecasting heterogeneous panels in presence of cross-sectional dependence in terms of both spatial error dependence and common factors. We propose two main approaches to estimate the factor structure, one using the residuals (Residuals Based Approach", RBA) while the second using a panel of some variables (Auxiliary Variables Approach", AVA) to extract the factors. Small sample properties of the methods proposed is investigated through Monte Carlo simulation exercises and used in an application to predict house price inflation in OECD countries.
(2020). Forecasting Using Heterogeneous Panels with Cross-Sectional Dependence [journal article - articolo]. In INTERNATIONAL JOURNAL OF FORECASTING. Retrieved from http://hdl.handle.net/10446/152810
Forecasting Using Heterogeneous Panels with Cross-Sectional Dependence
Urga, Giovanni
2020-01-01
Abstract
In this paper, we focus on forecasting heterogeneous panels in presence of cross-sectional dependence in terms of both spatial error dependence and common factors. We propose two main approaches to estimate the factor structure, one using the residuals (Residuals Based Approach", RBA) while the second using a panel of some variables (Auxiliary Variables Approach", AVA) to extract the factors. Small sample properties of the methods proposed is investigated through Monte Carlo simulation exercises and used in an application to predict house price inflation in OECD countries.File | Dimensione del file | Formato | |
---|---|---|---|
APU_Manuscript (Final).pdf
Solo gestori di archivio
Versione:
publisher's version - versione editoriale
Licenza:
Licenza default Aisberg
Dimensione del file
367.1 kB
Formato
Adobe PDF
|
367.1 kB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
Aisberg ©2008 Servizi bibliotecari, Università degli studi di Bergamo | Terms of use/Condizioni di utilizzo