Потенциал использования текстовых данных для оценки инфляционных ожиданий в России
DOI:
https://doi.org/10.22394/1993-7601-2026-81-26-45Ключевые слова:
инфляционные ожидания, обработка естественного языка, денежно-кредитная политика, средства массовой информации, инфляционное таргетированиеАннотация
В статье предлагается методология измерения инфляционных ожиданий фирм в России на основе анализа текстовых данных крупнейших СМИ. Из социальной сети ВКонтакте выгружены более 2.3 млн новостных публикаций 13 российских изданий за период с января 2015 по октябрь 2024 г. Для выделения публикаций, посвященных именно инфляции, а не просто содержащих соответствующие ключевые слова, применяется модель латентного размещения Дирихле (LDA)—метод вероятностного тематического моделирования. Построенный индикатор интенсивности инфляционных ожиданий демонстрирует корреляцию 78% с ценовыми ожиданиями предприятий Банка России, что существенно выше корреляции с ожиданиями населения (48%). С помощью LASSO-регрессии установлено, что наибольший вклад в объяснение динамики ожиданий фирм обеспечивают три издания экономической направленности—«Коммерсантъ», «Ведомости» и «Эксперт», которые совместно объясняют 75% дисперсии ценовых ожиданий предприятий. Результаты подтверждают, что текстовые данные СМИ могут служить эффективным дополнением к опросным методам оценки инфляционных ожиданий.Скачивания
Библиографические ссылки
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Aromí J. D., Llada M. (2020). Forecasting inflation with Twitter. Economica, 69, 64–85.
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Haubrich J., Pennacchi G., Ritchken P. (2012). Inflation expectations, real rates, and risk premia: Evidence from inflation swaps. Review of Financial Studies, 25 (5), 1588–1629. DOI: 10.1093/rfs/hhs003.
Huber S., Minina D., Schmidt T. (2023). The pass-through from inflation perceptions to inflation expectations. Deutsche Bundesbank Discussion Paper, No. 17/2023.
Lei C., Lu Z., Zhang C. (2015). News on inflation and the epidemiology of inflation expectations in China. Economic Systems, 39 (4), 644–653. DOI: 10.1016/j.ecosys.2015.04.006.
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Malmendier U., Nagel S. (2016). Learning from inflation experiences. The Quarterly Journal of Economics, 131 (1), 53–87. DOI: 10.1093/qje/qjv037.
Mankiw N. G., Reis R. (2002). Sticky information versus sticky prices: A proposal to replace the New Keynesian Phillips curve. The Quarterly Journal of Economics, 117 (4), 1295–1328. DOI: 10.1162/003355302320935034.
Phillips A. W. (1958). The relation between unemployment and the rate of change of money wage rates in the United Kingdom, 1861–1957. Economica, 25 (100), 283–299.
Saakshi, Sahu S., Chattopadhyay S. (2020). Epidemiology of inflation expectations and internet search: An analysis for India. Journal of Economic Interaction and Coordination, 15, 649–671. DOI: 10.1007/s11403‑019‑00255‑4.
Svensson L. E. O. (2010). Inflation targeting. In: Handbook of Monetary Economics, 1237–1302. Elsevier.
Tversky A., Kahneman D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185 (4157), 1124–1131. DOI: 10.1126/science.185.4157.1124.