FCVAR: A package for estimating the Fractionally Cointegrated VAR...

FCVARR Documentation

A package for estimating the Fractionally Cointegrated VAR model.


The FCVAR package estimates the Fractionally Cointegrated Vector Autoregressive (VAR) model. It includes functions for lag selection, cointegration rank selection and hypothesis testing.


Functions in the FCVAR package are divided into four categories: Estimation, Postestimation, Specification and Auxiliary functions.


Returns NULL. Object included for description only.

Estimation functions

The estimation functions include the primary estimation function FCVARestn and associated functions to set estimation options and display results. Some of these functions define, modify and test the user-specified options for estimation. FCVARoptions defines the default estimation options used in the FCVAR estimation procedure and the related programs. The user can then revise the options such as the settings for optimization and restrictions for testing hypotheses. After making these changes, an internal function FCVARoptionUpdates sets and tests estimation options for validity and compatibility.

Postestimation functions

The postestimation functions are used to display summary statistics, test hypotheses and test the goodness of fit of the estimated model. These include:


for a likelihood ratio test of a restricted vs. an unrestricted model


for generating a distribution of a likelihood ratio test statistic


for calculating recursive forecasts with the FCVAR model

Specification functions

The specification functions are used to estimate a series of models in order to make model specfication decisions. These include:


for selection of the lag order


for choosing the cointegrating rank


for generating a distribution of a likelihood ratio test statistic for the rank test

Auxiliary functions

The auxiliary functions are used to perform intermediate calculations for estimation. These functions are mainly designed for use only within the estimation function. Some exceptions include:


for fractionally differencing a multivariate series


for generating bootstrap samples from the FCVAR model


for performing a grid-search optimization with the FCVAR likelihood function


A dataset votingJNP2014 is included for examples of the model building process. Sample model builds with hypothesis tests and examples of other extensions are found in the example script FCVAR_demo_JNP2014.R. See FCVAR_README.pdf for details at


and also see https://sites.google.com/view/mortennielsen/software for more information about estimating the FCVAR model.

FCVAR documentation built on May 5, 2022, 9:06 a.m.