Nowcasting the Russian economy macroeconomic indicators under uncertainty: Does taking into account the news sentiment help?

Author:

Makeeva N. M.1ORCID,Stankevich I. P.1ORCID,Lyubaykin N. S.2ORCID

Affiliation:

1. HSE University

2. Tinkoff Bank

Abstract

In this paper the following models are compared: restricted and unrestricted MIDAS-models (mixed data sampling models), MFBVAR-model (mixed frequency Bayesian vector autoregression), Linear model with regularization (MIDAS_L1-, MIDAS_L2and MIDAS_PC-model) and dynamic factor model. The results are compared with classical autoregression as a benchmark. Production indices for different industries and indicators characterizing Russian GDP and its components, energy prices and PMI of Russia and its main trading partners, as well as indicators derived from the analysis of sentiment of news articles published by a number of major media and blogs are used as explanatory variables. The paper also proposes a method of rapid assessment of the current state of the economy based on data for the first or first two months of the quarter in question only. The use of this approach in combination with news sentiment analysis allows to draw conclusions about current economic situation extremely rapidly. Models’ accuracy is assessed by cross-validation for periods before and after the Q2 2022, the significance of the effect of adding news variables is assessed using the Diebold—Mariano test. When testing during the crisis period (starting from the Q1 2022), the addition of news variables leads to an increase in accuracy for 45% of the models considered, and the average improvement (reduction in the average absolute error) was 1.39 points (the reduction in MAE for the science-based GDP growth rates of Russia is 0.64 p.p.). At the same time, in a calmer (pre-sanction) period, the advantage of news is less noticeable: an increase in accuracy was recorded in 30% of cases with an average decrease in error of 1.54 points (the decrease in MAE for Russia’s GDP growth rate is 0.26 p.p.), and the change accuracy of science data when adding variables reflecting the news background turns out to be statistically insignificant. Thus, the use of news sentiment is not a “silver bullet” in the task of nowcasting Russian GDP, but in times of crisis it can serve as a good and, importantly, very operative indicator of the state of the economy and can be used in conjunction with more traditional explanatory variables.

Publisher

NP Voprosy Ekonomiki

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