Книги
A real-time historical database of macroeconomic indicators for Russia
A real-time historical database of macroeconomic indicators for Russia / D. Gornostaev, A. Ponomarenko, S. Seleznev, A. Sterkhova; The Central Bank of the Russian Federation, Research and Forecasting Department. — Moscow : Bank of Russia, july 2021. — 15 p.: il.. — (Working paper series; # 76). — References: p. 13.
Gornostaev, D., Ponomarenko, A., Seleznev, S. and Sterkhova, A., (july 2021), A real-time historical database of macroeconomic indicators for Russia, The Central Bank of the Russian Federation, Research and Forecasting Department, Moscow: Bank of Russia, july 2021, 15 p., RU.
Gornostaev D, Ponomarenko A, Seleznev S, Sterkhova A. A real-time historical database of macroeconomic indicators for Russia. Moscow: Bank of Russia; july 2021. 15 p. DOI:DOI.
Аннотация
We compile a database that contains data vintages of a large collection of short-term economic indicators. The main result of the work is a database which is available as an electronic annex to this working paper. The Research and Forecasting Department of the Bank of Russia plans to update this database in the future. We also perform an illustrative analysis of the properties of the revisions for a number of indicators. The preliminary results indicate that the magnitude of the revisions is in many cases substantial.
-
УДК:330.4
-
DOI: DOI — Digital Object Identifier — цифровой идентификатор объекта. Современный стандарт обозначения объектов информационной деятельности в сети Интернет, позволяющий идентифицировать и искать научные данные, размещённые в сети Интернет и привязывать к объекту дополнительные метаданные. Номер DOI всегда остаётся неизменным, который позволяет найти объект, даже если сведения о нем не полные или не точные.
Рекомендовано к ознакомлению
- 1. Grishchenko, V. A feasible aproach to projecting household demand for the digital ruble in Russia / V. Grishchenko, A. Ponomarenko, S. Seleznev. — Moscow : Bank of Russia, february 2023. — 41 p.. — (Working Paper Series. # 108).
- 2. Seleznev, S.M. Solving DSGE models with stochastic trends / S. M. Seleznev. — Moscow : Bank of Russia, 2016. — 27 p.. — (Working Paper Series. № 15 / september).
- 3. Koshelev, D. Amortized neural networks for agent-based model forecasting / D. Koshelev, A. Ponomarenko, S. Seleznev. — Moscow : Bank of Russia, july 2023. — 36 p.. — (Working paper series. # 115).
- 4. Popova, S. Idiosyncratic shocks: estimation and the impact on aggregate fluctuations / S. Popova. — Moscow : Bank of Russia, 2019. — 32 p.. — (Working paper series. 46, september).
- 5. Грищенко, В. Возможные подходы к прогнозированию спроса российских домохозяйств на цифровой рубль / В. Грищенко, А. Пономаренко, С. Селезнев. — Москва : Банк России, февраль 2023. — 45 с.. — (Серия докладов об экономических исследованиях. № 108).
- 6. Deryugina, E.B. A large Bayesian vector autoregression model for Russia / E. B. Deryugina, A. A. Ponomarenko. — Moscow : Bank of Russia, 2015. — 23 p.. — (Working Paper Series. № 1/March).
- 7. Khabibullin, R. Stochastic gradient variational Bayes and normalizing flows for estimating macroeconomic models / R. Khabibullin, S. Seleznev. — Moscow : Bank of Russia, 2020. — 49 p.. — (Working paper series. 61, september).
- 8. Khabibullin, R. Fast estimation of bayesian state space models using amortized simulation-based inference / R. Khabibullin, S. Seleznev. — Moscow : Bank of Russia, december 2022. — 38 p.. — (Working Paper Series. # 104).
- 9. Khabibullin, R. Forecasting the implications of foreign exchange reserve accumulation with an agent-based model / R. Khabibullin, A. Ponomarenko, S. Seleznev. — Moscow : Bank of Russia, 2018. — 30 p.. — (Working paper series. 37, november).
- 10. Disentangling loan demand and supply shocks in Russia / E. Deryugina [et al.]. — Moscow : Bank of Russia, 2015. — 32 p.. — (Working Paper Series. № 3/March).
Отзывы читателей
0