Assessing Economic Policy Uncertainty Using Search Queries

D. A. Petrova ()
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D. A. Petrova: Russian Presidential Academy of National Economy and Public Administration (RANEPA), Moscow, Russian Federation

Finansovyj žhurnal — Financial Journal, 2025, issue 5, 26-39

Abstract: This study analyzes international experience in measuring fiscal policy uncertainty and provides quantitative estimates of government spending uncertainty and tax policy uncertainty for Russia from April 2011 to June 2024. The analysis of empirical studies showed that the main periods of fiscal policy uncertainty in the international context are periods of political instability and elections, fiscal and budget debates, large budget deficits, economic crises, and external shocks such as the Gulf wars and the coronavirus pandemic in early 2020. Google Trends searches on “fiscal policy” and time-varying volatility of government expenditures calculated on the basis of stochastic volatility models are used to estimate fiscal policy uncertainty on Russian data. Composite indices of fiscal, budget and tax policies uncertainty based on internet queries on Google were obtained using principal component analysis. Stochastic volatility models were estimated for the fiscal instrument on a quarterly basis. The results of the empirical analysis made identified key periods of fiscal policy uncertainty for Russia during the second quarter of 2011 to the second quarter of 2024: the coronavirus pandemic in 2020 and the geopolitical risks in 2022.

Keywords: fiscal policy uncertainty; government spending policy uncertainty; search queries; internet data; government spending; stochastic volatility model (search for similar items in EconPapers)
JEL-codes: C11 D80 E62 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:fru:finjrn:250502:p:26-39

DOI: 10.31107/2075-1990-2025-5-26-39

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