Automatic leading indicators versus macroeconometric structural models: A comparison of inflation and GDP growth forecasting

被引：8

作者：

Qin, Duo ^{[1
]}

Cagas, Marie Anne ^{[3
]}

Ducanes, Geoffrey ^{[3
]}

Magtibay-Ramos, Nedelyn ^{[2
]}

Quising, Pilipinas ^{[2
]}

机构：

[1] Univ London, Dept Econ, London E1 4NS, England

[2] ADB, Manila, Philippines

[3] Univ Philippines, Quezon City 1101, Philippines

来源：

INTERNATIONAL JOURNAL OF FORECASTING | 2008年 / 24卷 / 03期

关键词：

dynamic factor models; equilibrium/error corrections; model reduction; VAR;

D O I：

10.1016/j.ijforecast.2008.04.002

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper compares the forecast performance of automatic leading indicators (ALIs) and macroeconometric structural models (MESMs) commonly used by non-academic macroeconomists. Inflation and GDP growth form the forecast objects for comparison, using data from China, Indonesia and Philippines. ALIs are found to outperform MESMs for one-period-ahead forecasts, but this superiority disappears as the forecast horizon increases. It is also found that ALIs involve greater uncertainty in choosing indicators, mixing data frequencies and utilizing unrestricted VARs. Two ways of reducing the uncertainty are explored; (i) give theory priority in choosing indicators, and include theory-based disequilibrium shocks in the indicator sets; and (ii) reduce the VARs by means of the general-to-specific modeling procedure. (C) 2008 International of Forecasters. Published by Elsevier B.V. All rights reserved.

引用

页码：399 / 413

页数：15

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