print.qardl_wald

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

print.qardl_wald function

<dl><dt>x</dt>
<dd>Object of class <code>"qardl_wald"</code>.</dd>
<dt>digits</dt>
<dd>Number of decimal places. Default is 4.</dd>
<dt>...</dt>
<dd>Additional arguments (unused).</dd></dl>

Arguments

Print QARDL Wald Test Results — print.qardl_wald

<dl>

<dt>x</dt>
<dd>Object of class <code>"qardl_wald"</code>.</dd>


<dt>digits</dt>
<dd>Number of decimal places. Default is 4.</dd>


<dt>...</dt>
<dd>Additional arguments (unused).</dd>

</dl>

Print QARDL Wald Test Results

print.qardl_wald: Print QARDL Wald Test Results

Description

Usage

Value

Arguments