rbfmvar-package: rbfmvar: Residual-Based Fully Modified Vector Autoregression

In rbfmvar: Residual-Based Fully Modified Vector Autoregression

rbfmvar: Residual-Based Fully Modified Vector Autoregression

Description

Implements the Residual-Based Fully Modified Vector Autoregression (RBFM-VAR) estimator following Chang (2000). 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.

Main Functions

rbfmvar

Estimate an RBFM-VAR model.

granger_test

Test for Granger non-causality.

irf

Compute impulse response functions.

fevd

Compute forecast error variance decomposition.

forecast.rbfmvar

Generate out-of-sample forecasts.

Key Features

• Handles unknown mixtures of I(0), I(1), and I(2) variables

• Automatic lag selection via AIC, BIC, or HQ

• Multiple kernels for LRV estimation (Bartlett, Parzen, QS)

• Andrews (1991) automatic bandwidth selection

• Granger non-causality testing with asymptotic chi-squared inference

• Impulse response functions with bootstrap confidence intervals

• Forecast error variance decomposition

• Out-of-sample forecasting

Methodology

The RBFM-VAR model is based on Chang (2000), which develops a fully modified VAR estimation procedure that is robust to unknown integration orders. The key innovation is using second differences to eliminate I(2) trends while applying FM corrections to handle endogeneity from I(1) regressors.

The estimator achieves:

• Zero mean mixed normal limiting distribution

• Chi-square Wald statistics for hypothesis testing

• Consistent estimation regardless of integration orders

Author(s)

Maintainer: Muhammad Alkhalaf [e-mail] (ORCID) [copyright holder]

Other contributors:

• Yoosoon Chang (Original RBFM-VAR methodology) [contributor]

References

Chang, Y. (2000). Vector Autoregressions with Unknown Mixtures of I(0), I(1), and I(2) Components. Econometric Theory, 16(6), 905-926. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1017/S0266466600166071")}

Phillips, P. C. B. (1995). Fully Modified Least Squares and Vector Autoregression. Econometrica, 63(5), 1023-1078. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2307/2171721")}

Andrews, D. W. K. (1991). Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation. Econometrica, 59(3), 817-858. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2307/2938229")}

See Also

Useful links:

• https://github.com/muhammedalkhalaf/rbfmvar

• Report bugs at https://github.com/muhammedalkhalaf/rbfmvar/issues

rbfmvar documentation built on April 9, 2026, 9:08 a.m.