DOI: 10.32609/j.ruje.12.158069

Authors: Karen A. Tumanyants, Fyodor B. Kuleshov, Henry I. Penikas, Vasily E. Zuev

Abstract: Many studies have found that inflation expectations vary systematically across population groups. This heterogeneity is driven among other factors by the level of financial literacy — a pattern documented for Russia as well. Earlier Russian evidence, however, rested on a single survey wave; we confirm the finding using data spanning three years: respondents with higher financial literacy tend to have lower inflation expectations. For this study, we rely on the pseudo-panel method to combine the results of two regular household surveys focused on inflation expectations and consumer finance. Our findings are based on responses to both quantitative and qualitative questions, controlling for key socio-demographic characteristics. We show that inflation expectations are linked to the level of financial literacy, but this relationship is nonlinear. Our conclusion holds for short- (one month ahead), medium- (one year ahead) and long-term (three years ahead) expectations. The nonlinearity of the relationship is evident: despite similar differences in the level of financial literacy, the gap in inflation expectations is larger in the least competent group of respondents in comparison with financially literate participants. We find that estimates of future inflation are linked to financial literacy through the perception of observed inflation, as more financially literate respondents cite lower rates of price growth, and their opinions about future inflation are tied to their estimates of observed price movements. Financially literate respondents’ estimates of current inflation are closer to the Rosstat-calculated measure of price growth than are the estimates of other respondents.

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DOI: 10.32609/j.ruje.10.113578

Authors: Inna S. Lola, Dmitry G. Asoskov

Abstract: 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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