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Макроэкономическое Прогнозирование С Помощью Bvar Литтермана

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  • ДЕМЕШЕВ БОРИС БОРИСОВИЧ

    (Национальный исследовательский университет «Высшая школа экономики»)

  • МАЛАХОВСКАЯ ОКСАНА АНАТОЛЬЕВНА

    (Национальный исследовательский университет «Высшая школа экономики»)

Abstract

В работе проводится сравнение прогнозных способностей моделей случайного блуждания, частотной (VAR) и байесовской векторных авторегрессий с априорным распределением Миннесоты (BVAR) по российским квартальным данным 1995-2014 гг. Максимальное количество переменных, включаемых в модель, равно 14, что требует эндогенного подбора оптимального гиперпараметра регуляризации. Для его определения используется механизм, описанный в работах [Bańbura et al., 2010; Bloor, Matheson, 2011]. В соответствии с этим механизмом гиперпараметр регуляризации подбирается так, чтобы качество прогнозов BVAR и частотной VAR моделей совпадало при минимальной рассматриваемой размерности модели (три переменных). Для любой размерности BVAR-модели оптимальная величина гиперпараметра регуляризации является робастной к рассматриваемым функциям относительной прогнозной точности. В результате показано, что на исследуемой выборке BVAR позволяет получить более точный прогноз, чем частотная VAR. Для ключевых макроиндикаторов (индекса промышленного производства, индекса потребительских цен и процентной ставки) на всех рассматриваемых прогнозных горизонтах и независимо от числа переменных в модели среднеквадратичная ошибка прогноза модели BVAR оказывается ниже, чем для частотной VAR. Кроме того, BVAR позволяет получить прогноз с большей точностью, чем модель случайного блуждания для ИПЦ и белого шума для процентной ставки. Однако предсказать индекс промышленного производства с помощью BVAR более точно, чем с помощью модели случайного блуждания, не удается.

Suggested Citation

  • Демешев Борис Борисович & Малаховская Оксана Анатольевна, 2016. "Макроэкономическое Прогнозирование С Помощью Bvar Литтермана," Higher School of Economics Economic Journal Экономический журнал Высшей школы экономики, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 20(4), pages 691-710.
  • Handle: RePEc:scn:025886:16949947
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