Mixed-Frequency Bayesian VAR Models in R: The mfbvar Package

• Time series are often sampled at different frequencies, which leads to mixed-frequency data. Mixed frequencies are often neglected in applications as high-frequency series are aggregated to lower frequencies. In the mfbvar package, we introduce the possibility to estimate Bayesian vector autoregressive (VAR) models when the set of included time series consists of monthly and quarterly variables. The package implements several common prior distributions as well as stochastic volatility methods. The mixed-frequency nature of the data is handled by assuming that quarterly variables are weighted averages of unobserved monthly observations. We provide a user-friendly interface for model estimation and forecasting. The capabilities of the package are illustrated in an application.

Ämnesord

NATURVETENSKAP  -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)

NATURAL SCIENCES  -- Mathematics -- Probability Theory and Statistics (hsv//eng)

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