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BVAR mapping

Author

Listed:
  • Demeshev, Boris

    (National Research University Higher School of Economics, Moscow, Russian Federation;)

  • Malakhovskaya, Oxana

    (National Research University Higher School of Economics, Moscow, Russian Federation;)

Abstract

This paper reviews estimation and forecasting with Bayesian vector autoregressions (BVARs). In the first part of the paper, we propose a clear classification of the most frequently used prior distributions and we show how the parameters of posterior distributions can be computed for the priors we consider in the paper. A separate section describes the endogenous choice of prior hyperparameters that is currently a key step to estimate a BVAR in a data-rich environment. The second part of this paper is devoted to forecasting with BVARs. We review both point and density forecasting.

Suggested Citation

  • Demeshev, Boris & Malakhovskaya, Oxana, 2016. "BVAR mapping," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 43, pages 118-141.
    • Handle: RePEc:ris:apltrx:0300
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    References listed on IDEAS

    as
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    4. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
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    Cited by:

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    2. M. Tiunova G. & М. Тиунова Г., 2018. "Влияние Внешних Шоков На Российскую Экономику // The Impact Of External Shocks On The Russian Economy," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 22(4), pages 146-170.
    3. Shevelev A.A., 2017. "Bayesian approach to evaluate the impact of external shocks on Russian macroeconomics indicators," World of economics and management / Vestnik NSU. Series: Social and Economics Sciences, Socionet, vol. 17(1), pages 26-40.
    4. M. Tiunova G. & М. Тиунова Г., 2018. "Моделирование Эффекта Переноса Валютного Курса На Цены В России // Modeling The Transfer Effect Of Exchange Rate On Prices In Russia," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 22(3), pages 136-154.
    5. Anton I. Votinov & Ivan P. Stankevich, 2017. "VAR Approach to Efficiency Evaluation of Fiscal Economy Encouragement Measures," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 127006, Russia, issue 6, pages 64-74, December.
    6. И Управления Мир Экономики, 2017. "Байесовский подход к анализу влияния монетарной политики на макроэкономические показатели России. Bayesian approach to the analysis of monetary policy impact on Russian macroeconomics indicators," Мир экономики и управления // Вестник НГУ. Cерия: Cоциально-экономические науки, Socionet;Новосибирский государственный университет, vol. 17(4), pages 53-70.

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    More about this item

    Keywords

    BVAR; prior distributions; point forecasting; density forecasting;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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