Short-term real-time forecasting model for spanish GDP (Spain-STING): new specification and reassessment of its predictive power

Author:

Gómez Loscos Ana1,González Simón Miguel Ángel1,Pacce Matías José1

Affiliation:

1. Banco de España

Abstract

The predictive power of short-term forecasting models was impaired by the increased volatility observed in most economic indicators following the outbreak of COVID-19. This paper sets out a revision of the Spain-STING model (one of the tools used by the Banco de España for short-term forecasts of quarter-on-quarter GDP growth) with a view to improving its predictive power in the wake of the pandemic. In particular, the revision entails three main changes: (i) the correlation between the indicators included in the model and the estimated common component is now coincident for all of the indicators, rather than leading in the case of some of them; (ii) by using a stochastic process to model the variance in the estimated common component, such variance may now vary over time; (iii) the set of indicators has been revised in order to include only those that provide the most relevant information when it comes to predicting post-pandemic GDP growth. These modifications yield a substantial improvement in the predictive power of Spain-STING in the post-pandemic period, and maintain such predictive power for the pre-pandemic period.

Publisher

Banco de España

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3