Forecasting Using Heterogeneous Panels with Cross-Sectional Dependence
Urga, G., Akgun, O. & Pirotte, A. (2020). Forecasting Using Heterogeneous Panels with Cross-Sectional Dependence. International Journal of Forecasting, 36(4), pp. 1211-1227. doi: 10.1016/j.ijforecast.2019.11.007
Abstract
In this paper, we focus on forecasting heterogeneous panels in presence of cross-sectional depen-dence in terms of both spatial error dependence and common factors. We propose two mainapproaches 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 throughMonte Carlo simulation exercises and used in an application to predict house price inflation inOECD countries.
| Publication Type: | Article |
|---|---|
| Additional Information: | © Elsevier 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| Publisher Keywords: | Cross-Sectional dependence, Common factors, Spatial dependence, House priceinflation, Inflation forecasting, Macroeconomic forecasting |
| Subjects: | H Social Sciences > HG Finance |
| Departments: | Bayes Business School > Finance |
| SWORD Depositor: |
Available under License Creative Commons Attribution Non-commercial No Derivatives.
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