qardlr (version 1.0.1)

qardl_sim: Simulated QARDL Dataset

Description

A simulated dataset for demonstrating QARDL estimation. The data is generated from a QARDL(2,2) process with two covariates.

Usage

qardl_sim

Format

A data frame with 200 observations and 3 variables:

y

Dependent variable generated from QARDL process

x1

First covariate (I(1) random walk)

x2

Second covariate (I(1) random walk)

Details

The data generating process follows: $$y_t = 0.4 y_{t-1} + 0.2 y_{t-2} + 0.5 x_{1t} + 0.3 x_{2t} + u_t$$

where \(u_t \sim N(0, 1)\) and \(x_{it}\) are independent random walks.

True parameters:

• \(\phi_1 = 0.4\), \(\phi_2 = 0.2\)

• \(\gamma_1 = 0.5\), \(\gamma_2 = 0.3\)

• \(\beta_1 = 0.5/(1-0.6) = 1.25\), \(\beta_2 = 0.3/(1-0.6) = 0.75\)

References

Cho, J.S., Kim, T.-H., & Shin, Y. (2015). Quantile cointegration in the autoregressive distributed-lag modeling framework. Journal of Econometrics, 188(1), 281-300. tools:::Rd_expr_doi("10.1016/j.jeconom.2015.01.003")

Examples

data(qardl_sim)
head(qardl_sim)
summary(qardl_sim)

# Estimate QARDL model
fit <- qardl(y ~ x1 + x2, data = qardl_sim, tau = c(0.25, 0.50, 0.75), p = 2, q = 2)
summary(fit)