Structural Breaks in a System of Equations

Methods for detecting, estimating, and conducting inference on multiple structural breaks in a linear system of equations, such as multivariate linear regressions, seemingly unrelated regressions, vector autoregressions, and network vector autoregressions. Breaks can occur in the regression coefficients, the covariance matrix of the errors, or both, and can be restricted to a subset of the coefficients. The main function, sysbreak(), returns the number of breaks detected and confidence intervals for the break dates and for the regression coefficients. A separate function ordbreak() estimates ordered breaks, in which a break in one subset of equations occurs before a break in another. Specialized functions for vector autoregressions varbreak() and network vector autoregressions netbreak() are also provided. Reference: Qu, Z., and Perron, P. (2007). 'Estimating and Testing Structural Changes in Multivariate Regressions.' Econometrica, 75(2), 459-502.

sysbreak

Structural Breaks in a System of Equations

Overview

Methods for estimating and testing multivariate linear structural break models with coefficient breaks, covariance breaks, or both. The package also includes VAR, Network VAR and ordered-break routines, tests of what changes at each break, and generalized Diebold-Yilmaz spillover measures.

Example

library(sysbreak)

set.seed(1)
bigt <- 60
x <- rnorm(bigt)
beta <- rbind(c(1, 0.5), c(2, -0.2), c(0.5, 0.8))
y <- numeric(bigt)
y[1:20] <- beta[1, 1] + beta[1, 2] * x[1:20] + rnorm(20, sd = 0.4)
y[21:40] <- beta[2, 1] + beta[2, 2] * x[21:40] + rnorm(20, sd = 0.4)
y[41:60] <- beta[3, 1] + beta[3, 2] * x[41:60] + rnorm(20, sd = 0.4)
dat <- data.frame(y = y, x = x)

fit <- sysbreak(y ~ x, data = dat, m = 2, trim = 0.15)
fit$estimation$breaks
fit$testing$statistic

References

Qu, Z., and Perron, P. (2007). "Estimating and Testing Structural Changes in Multivariate Regressions". Econometrica, 75(2), 459-502.

Bai, J., and Perron, P. (2003). "Critical Values for Multiple Structural Change Tests". The Econometrics Journal, 6(1), 72-78.

Diebold, F. X., and Yilmaz, K. (2012). "Better to Give than to Receive: Predictive Directional Measurement of Volatility Spillovers". International Journal of Forecasting, 28(1), 57-66.