Forecasting using heterogeneous panels with cross-sectional dependence

被引：1
|
作者：
Akgun, Oguzhan [1 ]
Pirotte, Alain [1 ]
Urga, Giovanni [2 ,3 ]
机构：
[1] Univ Paris 2 Pantheon Assas, CRED, Paris, France
[2] City Univ London, Fac Finance, Ctr Econometr Anal, Cass Business Sch, 106 Bunhil Row EC1Y Londo, London, England
[3] Bergamo Univ, Dept Management Econ & Quantitat Methods, Via Caniana 2, I-24127 Bergamo, Italy
来源：
INTERNATIONAL JOURNAL OF FORECASTING | 2020年 / 36卷 / 04期
关键词：
Cross-sectional dependence; Common factors; Spatial dependence; House price inflation; Inflation forecasting; Macroeconomic forecasting; FACTOR MODELS; ESTIMATORS; INFERENCE; NUMBER; WEAK; GDP;
D O I：
10.1016/j.ijforecast.2019.11.007
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
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. (C) 2020 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
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页码：1211 / 1227
页数：17
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