dgp_qardl

Internal function to generate data from a QARDL DGP.

internal

Implements the Quantile Autoregressive Distributed Lag (QARDL)
model of Cho, Kim and Shin (2015) <doi:10.1016/j.jeconom.2015.01.003>.
Estimates quantile-specific long-run (beta), short-run autoregressive (phi),
and impact (gamma) parameters. Features include BIC-based automatic lag
selection, Error Correction Model (ECM) parameterization, Wald tests for
parameter constancy across quantiles, rolling/recursive QARDL estimation,
Monte Carlo simulation, and publication-ready output tables.

Muhammad Alkhalaf

qardlr

Quantile Autoregressive Distributed Lag Model

Merwan Roudane

Jin Seo Cho

Tae-Hwan Kim

Yongcheol Shin

dgp_qardl function

<dl><dt>nobs</dt>
<dd>Sample size.</dd>
<dt>p</dt>
<dd>AR lag order.</dd>
<dt>q</dt>
<dd>Distributed lag order.</dd>
<dt>k</dt>
<dd>Number of covariates.</dd>
<dt>phi</dt>
<dd>AR parameters.</dd>
<dt>gamma</dt>
<dd>Impact parameters.</dd>
<dt>sigma_u</dt>
<dd>Error standard deviation.</dd>
<dt>sigma_x</dt>
<dd>Covariate innovation standard deviation.</dd></dl>

Arguments

Data Generating Process for QARDL — dgp_qardl

<dl>

<dt>nobs</dt>
<dd>Sample size.</dd>


<dt>p</dt>
<dd>AR lag order.</dd>


<dt>q</dt>
<dd>Distributed lag order.</dd>


<dt>k</dt>
<dd>Number of covariates.</dd>


<dt>phi</dt>
<dd>AR parameters.</dd>


<dt>gamma</dt>
<dd>Impact parameters.</dd>


<dt>sigma_u</dt>
<dd>Error standard deviation.</dd>


<dt>sigma_x</dt>
<dd>Covariate innovation standard deviation.</dd>

</dl>

dgp_qardl: Data Generating Process for QARDL

Description

Usage

Value

Arguments