pvars

VAR Modeling for Heterogeneous Panels

Overview

This package implements (1) panel cointegration rank tests, (2) estimators for panels of VAR, and (3) panel-based identification methods for structural vector autoregressive (SVAR) models. The implemented functions allow to account for cross-sectional dependence in the error terms and for structural breaks in the deterministic terms of the VAR processes.

(1) The panel functions to determine the cointegration rank are:

• pcoint.JO(): panel Johansen procedures,
• pcoint.BR(): panel test with pooled two-step estimation,
• pcoint.SL(): panel SL-procedures,
• pcoint.CAIN(): correlation-augmented inverse normal test.

(2) The panel functions to estimate the VAR models are:

• pvarx.VAR(): mean-group of a panel of VAR models,
• pvarx.VEC(): pooled cointegrating vectors in a panel VECM.

(3) The panel functions to retrieve structural impact matrices are:

• pid.chol(): identification of panel SVAR models using Cholesky decomposition to impose recursive causality,
• pid.grt(): identification of panel SVEC models,
• pid.iv(): identification of panel SVAR models by means of proxy variables.
• pid.dc(): independence-based identification of panel SVAR models using distance covariance (DC) statistic,
• pid.cvm(): independence-based identification of panel SVAR models using Cramer-von Mises (CVM) distance.

Supporting tools like the panel block bootstrap procedure (sboot.pmb()) and the provided data sets allow for the replication of the implemented literature.

Installation

Install the development version

install.packages("devtools")
devtools::install_github("Lenni89/pvars")

library("pvars")