Economic theory and forecasting: lessons from the literature

被引:12
|
作者
Giacomini, Raffaella [1 ,2 ]
机构
[1] UCL, Dept Econ, London WC1H 0AX, England
[2] Inst Fiscal Studies, Ctr Microdata Methods & Practice, London WC1E 7AE, England
来源
ECONOMETRICS JOURNAL | 2015年 / 18卷 / 02期
基金
英国经济与社会研究理事会;
关键词
Aggregation; DSGE models; Instability; Out-of-sample forecasting; Parameter restrictions; ESTIMATED DSGE MODEL; PERFORMANCE; AGGREGATE; INFORMATION; TESTS;
D O I
10.1111/ectj.12038
中图分类号
F [经济];
学科分类号
02 ;
摘要
Does economic theory help in forecasting key macroeconomic variables? This article aims to provide some insight into the question by drawing lessons from the literature. The definition of economic theory' includes a broad range of examples, such as accounting identities, disaggregation and spatial restrictions when forecasting aggregate variables, cointegration and forecasting with dynamic stochastic general equilibrium (DSGE) models. We group the lessons into three themes. For the first, we discuss the importance of using the correct econometric tools when answering the question. For the second, we present examples of theory-based forecasting that have not proven useful, such as theory-driven variable selection and some popular DSGE models. For the third set of lessons, we discuss types of theoretical restrictions that have shown some usefulness in forecasting, such as accounting identities, disaggregation and spatial restrictions, and cointegrating relationships. We conclude by suggesting that economic theory might help in overcoming the widespread instability that affects the forecasting performance of econometric models by guiding the search for stable relationships that could be usefully exploited for forecasting.
引用
收藏
页码:C22 / C41
页数:20
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