interval

<code>interval()</code> computes confidence intervals for the break dates based on
approximating the limiting distribution of the break date following
the "shrinking shifts" asymptotic framework

Functions provide comprehensive treatments for estimating, inferring, testing and model selecting in linear regression models with structural breaks. The tests, estimation methods, inference and information criteria implemented are discussed in Bai and Perron (1998) "Estimating and Testing Linear Models with Multiple Structural Changes" <doi:10.2307/2998540>.

Linh Nguyen

mbreaks

Estimation and Inference for Structural Breaks in Linear
Regression Models

Yohei Yamamoto

Pierre Perron

interval function

<dl><dt>y</dt>
<dd>matrix of dependent variable</dd>
<dt>z</dt>
<dd>matrix of independent variables with coefficients allowed to change
across regimes</dd>
<dt>zbar</dt>
<dd>partitioned matrix of independent variables with coefficients allowed
to change across regimes according to break date vector <code>b</code></dd>
<dt>b</dt>
<dd>vector of break breaks</dd>
<dt>q</dt>
<dd>number of <code>z</code> regressors</dd>
<dt>m</dt>
<dd>maximum number of breaks</dd>
<dt>robust</dt>
<dd>set to <code>1</code> to allow for heterogeneity
and autocorrelation in the residuals, <code>0</code> otherwise.
The method used is Andrews(1991) automatic bandwidth with AR(1) approximation with quadratic
kernel. Note: Do not set to <code>1</code> if lagged dependent variables are
included as regressors.</dd>
<dt>prewhit</dt>
<dd>Option of using prewhitening process. If <code>1</code>, an AR(1)
process will be used to filter. If <code>0</code>, skipped the filtering process</dd>
<dt>hetomega, hetq</dt>
<dd>options for assumptions of error terms
structure. For more details, refers to <code>mdl()</code></dd>
<dt>x</dt>
<dd>matrix of independent variables with coefficients constant
across regimes</dd>
<dt>p</dt>
<dd>number of <code>x</code> regressors</dd></dl>

Arguments

Estimatd break confidence interval — interval

<dl>

<dt>y</dt>
<dd>matrix of dependent variable</dd>


<dt>z</dt>
<dd>matrix of independent variables with coefficients allowed to change
across regimes</dd>


<dt>zbar</dt>
<dd>partitioned matrix of independent variables with coefficients allowed
to change across regimes according to break date vector <code>b</code></dd>


<dt>b</dt>
<dd>vector of break breaks</dd>


<dt>q</dt>
<dd>number of <code>z</code> regressors</dd>


<dt>m</dt>
<dd>maximum number of breaks</dd>


<dt>robust</dt>
<dd>set to <code>1</code> to allow for heterogeneity
and autocorrelation in the residuals, <code>0</code> otherwise.
The method used is Andrews(1991) automatic bandwidth with AR(1) approximation with quadratic
kernel. Note: Do not set to <code>1</code> if lagged dependent variables are
included as regressors.</dd>


<dt>prewhit</dt>
<dd>Option of using prewhitening process. If <code>1</code>, an AR(1)
process will be used to filter. If <code>0</code>, skipped the filtering process</dd>


<dt>hetomega, hetq</dt>
<dd>options for assumptions of error terms
structure. For more details, refers to <code>mdl()</code></dd>


<dt>x</dt>
<dd>matrix of independent variables with coefficients constant
across regimes</dd>


<dt>p</dt>
<dd>number of <code>x</code> regressors</dd>

</dl>

interval: Estimatd break confidence interval

Description

Usage

Value

Arguments