Potential of business uncertainty indicators in forecasting economic activity: The case of Russia

This study investigates the utility of business uncertainty indicators as predictive tools for forecasting economic activity in the context of Russia. In an era characterized by global economic volatility and geopolitical shifts, understanding the dynamics of economic uncertainty and its impact on o...

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Main Authors: Inna S. Lola, Dmitry G. Asoskov
Format: Article
Language:English
Published: Voprosy Ekonomiki 2024-12-01
Series:Russian Journal of Economics
Online Access:https://rujec.org/article/113578/download/pdf/
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author Inna S. Lola
Dmitry G. Asoskov
author_facet Inna S. Lola
Dmitry G. Asoskov
author_sort Inna S. Lola
collection DOAJ
description This study investigates the utility of business uncertainty indicators as predictive tools for forecasting economic activity in the context of Russia. In an era characterized by global economic volatility and geopolitical shifts, understanding the dynamics of economic uncertainty and its impact on overall economic performance is of paramount importance. The study utilizes a comprehensive dataset based on the results of business tendency surveys in Russia, spanning the period from 2009 to the first half of 2024. Given the importance of uncertainty in shaping economic outcomes, the central research question of this study is: can uncertainty indicators predict business activity in Russia or not? To address this question, we compared two alternative approaches to calculating business uncertainty: the ex‑ante approach, which uses the business community’s assessments of future business trends to measure uncertainty as the dispersion of opinions expressed, and the ex‑post approach, which applies entrepreneurial assessments of both future and current trends to determine business uncertainty as the degree of deviation of entrepreneurial expectations from the real picture. National indicators and sectoral indicators were calculated for the mining and quarrying industry, manufacturing industry, construction, retail trade, wholesale trade and services. For most of the industries under consideration (except for the construction and service sector) and at the national level, the specifications of vector autoregression models that were effective for forecasting real indicators of economic activity, characterized by lower forecast errors compared to standard autoregressive models, were built. According to the results obtained, at the national level, when forecasting GDP, clear preference should be given to the ex‑post indicator.
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spelling doaj-art-0252d17b3a444baaa75aee21ba44aecf2025-08-20T02:39:32ZengVoprosy EkonomikiRussian Journal of Economics2405-47392024-12-0110435136410.32609/j.ruje.10.113578113578Potential of business uncertainty indicators in forecasting economic activity: The case of RussiaInna S. Lola0Dmitry G. Asoskov1HSE UniversityHSE UniversityThis study investigates the utility of business uncertainty indicators as predictive tools for forecasting economic activity in the context of Russia. In an era characterized by global economic volatility and geopolitical shifts, understanding the dynamics of economic uncertainty and its impact on overall economic performance is of paramount importance. The study utilizes a comprehensive dataset based on the results of business tendency surveys in Russia, spanning the period from 2009 to the first half of 2024. Given the importance of uncertainty in shaping economic outcomes, the central research question of this study is: can uncertainty indicators predict business activity in Russia or not? To address this question, we compared two alternative approaches to calculating business uncertainty: the ex‑ante approach, which uses the business community’s assessments of future business trends to measure uncertainty as the dispersion of opinions expressed, and the ex‑post approach, which applies entrepreneurial assessments of both future and current trends to determine business uncertainty as the degree of deviation of entrepreneurial expectations from the real picture. National indicators and sectoral indicators were calculated for the mining and quarrying industry, manufacturing industry, construction, retail trade, wholesale trade and services. For most of the industries under consideration (except for the construction and service sector) and at the national level, the specifications of vector autoregression models that were effective for forecasting real indicators of economic activity, characterized by lower forecast errors compared to standard autoregressive models, were built. According to the results obtained, at the national level, when forecasting GDP, clear preference should be given to the ex‑post indicator.https://rujec.org/article/113578/download/pdf/
spellingShingle Inna S. Lola
Dmitry G. Asoskov
Potential of business uncertainty indicators in forecasting economic activity: The case of Russia
Russian Journal of Economics
title Potential of business uncertainty indicators in forecasting economic activity: The case of Russia
title_full Potential of business uncertainty indicators in forecasting economic activity: The case of Russia
title_fullStr Potential of business uncertainty indicators in forecasting economic activity: The case of Russia
title_full_unstemmed Potential of business uncertainty indicators in forecasting economic activity: The case of Russia
title_short Potential of business uncertainty indicators in forecasting economic activity: The case of Russia
title_sort potential of business uncertainty indicators in forecasting economic activity the case of russia
url https://rujec.org/article/113578/download/pdf/
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AT dmitrygasoskov potentialofbusinessuncertaintyindicatorsinforecastingeconomicactivitythecaseofrussia