PREDICTION IN THE ONE-WAY ERROR COMPONENT MODEL WITH SERIAL-CORRELATION

被引：22

作者：

BALTAGI, BH ^{[1
]}

QI, L ^{[1
]}

机构：

[1] UNIV GUELPH,DEPT ECON,GUELPH N1G 2W1,ONTARIO,CANADA

来源：

JOURNAL OF FORECASTING | 1992年 / 11卷 / 06期

关键词：

ERROR COMPONENTS; PANEL DATA; AUTOREGRESSIVE; MOVING AVERAGE; PREDICTION;

D O I：

10.1002/for.3980110605

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper derives the best linear unbiased predictor for a one-way error component model with serial correlation. A transformation derived by Baltagi and Li (1991) is used to show how the forecast can be easily computed from the GLS estimates and residuals. This result is useful for panel data applications which utilize the error component specification and exhibit serial correlation in the remainder disturbance term. Analytical expressions for this predictor are given when the remainder disturbances follow (1) an AR(1) process, (2) an AR(2) process, (3) a special AR(4) process for quarterly data, and (4) an MA(1) process.

引用

页码：561 / 567

页数：7

共 19 条

[1] POOLING CROSS SECTION AND TIME SERIES DATA IN ESTIMATION OF A DYNAMIC MODEL - DEMAND FOR NATURAL GAS [J].