rq.est.full: Estimating Break Sizes and Confidence Intervals Given Break...

In QR.break: Structural Breaks in Quantile Regression

Estimating Break Sizes and Confidence Intervals Given Break Dates

Description

This procedure estimates a linear quantile regression given a set of break dates. It is structured to compute break sizes between adjacent regimes and their confidence intervals.

Usage

rq.est.full(y, x, v.tau, vec.date, n.size = 1)

Arguments

y	A numeric vector of dependent variables (NT \times 1).
x	A numeric matrix of regressors (NT \times p).
v.tau	A numeric value representing the quantile of interest.
vec.date	A numeric vector of break dates, specified by the user.
n.size	An integer specifying the size of the cross-section (N).

Value

An object from the quantile regression estimates, rq(), with structural breaks.

References

Koenker, R. and G. Bassett Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33–50.

Oka, T. and Z. Qu (2011). Estimating Structural Changes in Regression Quantiles. Journal of Econometrics, 162(2), 248–267.

Examples

## data
data(gdp)
y = gdp$gdp
x = gdp[,c("lag1", "lag2")]

## quantile
v.tau = 0.8

## break date
vec.date = 146

# cross-sectional size
n.size = 1

## estimation
rq.est.full(y, x, v.tau, vec.date, n.size)

QR.break documentation built on June 8, 2025, 1:53 p.m.