Forecasting with spatial panel data

被引：48

作者：

Baltagi, Badi H. ^{[1
,2
]}

Bresson, Georges ^{[3
,4
]}

Pirotte, Alain ^{[3
,4
,5
]}

机构：

[1] Syracuse Univ, Dept Econ, Syracuse, NY 13244 USA

[2] Syracuse Univ, Ctr Policy Res, Syracuse, NY 13244 USA

[3] Univ Paris 02, CNRS, ERMES, F-75231 Paris 05, France

[4] Univ Paris 02, CNRS, TEPP, F-75231 Paris 05, France

[5] Natl Inst Res Transports & Safety, INRETS DEST, Paris, France

来源：

COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2012年 / 56卷 / 11期

关键词：

Forecasting; BLUP; Panel data; Spatial dependence; Heterogeneity; MOVING AVERAGE ERRORS; MOMENTS ESTIMATOR; DATA MODELS; GENERALIZED-METHOD; PREDICTION;

D O I：

10.1016/j.csda.2010.08.006

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Various forecasts using panel data with spatial error correlation are compared using Monte Carlo experiments. The true data generating process is assumed to be a simple error component regression model with spatial remainder disturbances of the autoregressive or moving average type. The best linear unbiased predictor is compared with other forecasts ignoring spatial correlation, or ignoring heterogeneity due to the individual effects. In addition, the root mean squared error performance of these forecasts is examined under misspecification of the spatial error process, various spatial weight matrices, and heterogeneous rather than homogeneous panel data models. (C) 2010 Elsevier B.V. All rights reserved.

引用

页码：3381 / 3397

页数：17

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