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Regular version of the site

Working paper

Сравнение случайного блуждания, VAR, BVAR Литтермана при прогнозировании выпуска, индекса цен и процентной ставки

This paper compares the forecasting performance of random walk, frequentist vector autoregression  (VAR), and Bayesian vector autoregression with Minnesota prior (BVAR) models while forecasting the industrial production index, consumer price index and the interbank interest rate. We show that the BVAR provides a more accurate forecast than the standard VAR. For all three macroindicators of interest, all forecasting horizons, and all model sizes, the mean squared error of the BVAR is lower than for the VAR.   Moreover, the results show that the forecast made using the BVAR is more precise than the forecast made with a reference model (random walk – white noise)  for the CPI and the interbank rate. But the BVAR cannot beat the random walk when forecasting the industrial production index.