Quantile Autoregressive Distributed Lag Unit Root Test

Implements the Quantile Autoregressive Distributed Lag (QADF) unit root test proposed by Koenker and Xiao (2004) . The test examines unit root behaviour across the conditional distribution of a time series using quantile regression, providing a richer characterisation of persistence than standard ADF tests. Critical values follow Hansen (1995) . Lag order selection is supported via AIC, BIC, or the t-statistic sequential testing approach.

qadf

Quantile ADF Unit Root Test for R

Overview

qadf implements the Quantile Autoregressive Distributed Lag (QADF) unit root test proposed by Koenker and Xiao (2004, JASA). The test uses quantile regression to examine unit root behaviour across the conditional distribution of a time series, providing a richer characterisation of persistence than classical ADF tests.

Installation

# From CRAN (once published):
install.packages("qadf")

Usage

library(qadf)

set.seed(42)
y <- cumsum(rnorm(120))

# Test at median (tau = 0.5) with constant model
result <- qadf(y, tau = 0.5, model = "c", max_lags = 8, ic = "aic")
print(result)

# Test at lower tail (tau = 0.25) with trend model
result_q25 <- qadf(y, tau = 0.25, model = "ct", ic = "bic")
print(result_q25)

References

Koenker, R. and Xiao, Z. (2004). Unit Root Quantile Autoregression Inference. Journal of the American Statistical Association, 99(465), 775–787. https://doi.org/10.1198/016214504000001114

Hansen, B. E. (1995). Rethinking the Univariate Approach to Unit Root Tests. Econometric Theory, 11(5), 1148–1171. https://doi.org/10.1017/S0266466600009993

License

GPL-3