rbfmvar: Residual-Based Fully Modified Vector Autoregression
Implements the Residual-Based Fully Modified Vector Autoregression
(RBFM-VAR) estimator of Chang (2000) <doi:10.1017/S0266466600166071>.
The RBFM-VAR procedure extends Phillips (1995) FM-VAR to handle any unknown
mixture of I(0), I(1), and I(2) components without prior knowledge of the
number or location of unit roots. Provides automatic lag selection via
information criteria (AIC, BIC, HQ), long-run variance estimation using
Bartlett, Parzen, or Quadratic Spectral kernels with Andrews (1991)
<doi:10.2307/2938229> automatic bandwidth selection, Granger non-causality
testing with asymptotically chi-squared Wald statistics, impulse response
functions (IRF) with bootstrap confidence intervals, forecast error variance
decomposition (FEVD), and out-of-sample forecasting.
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[aut, cre, cph],
Yoosoon Chang [ctb] (Original RBFM-VAR methodology)