rotation_null_test

Tests whether the observed correlation structure between X and Y factor spaces
is significantly stronger than would be expected under random orthogonal rotations.

Tests convergence in macro-financial panels combining
Dynamic Factor Models (DFM) and mean-reverting Ornstein-Uhlenbeck (OU)
processes. Provides: (i) static/approximate DFMs for large panels with
VAR/VECM stability checks, Portmanteau tests and rolling out-of-sample R^2,
following Stock and Watson (2002) <doi:10.1198/073500102317351921> and the
Generalized Dynamic Factor Model of Forni, Hallin, Lippi and Reichlin (2000)
<doi:10.1162/003465300559037>; (ii) cointegration analysis à la Johansen
(1988) <doi:10.1016/0165-1889(88)90041-3>; (iii) OU-based convergence and
half-life summaries grounded in Uhlenbeck and Ornstein (1930)
<doi:10.1103/PhysRev.36.823> and Vasicek (1977) <doi:10.1016/0304-405X(77)90016-2>;
(iv) robust inference via 'sandwich' HC/HAC estimators (Zeileis (2004)
<doi:10.18637/jss.v011.i10>) and regression diagnostics ('lmtest'); and
(v) optional PLS-based factor preselection (Mevik and Wehrens (2007)
<doi:10.18637/jss.v018.i02>). Functions emphasize reproducibility and clear,
publication-ready summaries.

José Mauricio Gómez Julián

convergenceDFM

Convergence and Dynamic Factor Models

rotation_null_test function

<dl><dt>scores_X</dt>
<dd>Factor scores from first dataset</dd>
<dt>scores_Y</dt>
<dd>Factor scores from second dataset</dd>
<dt>lag</dt>
<dd>Number of lags for the model (default: 1)</dd>
<dt>B</dt>
<dd>Number of bootstrap iterations (default: 1000)</dd>
<dt>seed</dt>
<dd>Random seed for reproducibility (default: 123)</dd>
<dt>compute</dt>
<dd>Vector of methods to compute: 'procrustes', 'cca', 'principal', 'dynbeta'</dd>
<dt>progress</dt>
<dd>Logical, show progress bar (default: TRUE)</dd>
<dt>rotate</dt>
<dd>Which dataset to rotate: 'X' or 'Y' (default: 'Y')</dd></dl>

Arguments

Rotation null hypothesis test for factor coupling — rotation_null_test

<dl>

<dt>scores_X</dt>
<dd>Factor scores from first dataset</dd>


<dt>scores_Y</dt>
<dd>Factor scores from second dataset</dd>


<dt>lag</dt>
<dd>Number of lags for the model (default: 1)</dd>


<dt>B</dt>
<dd>Number of bootstrap iterations (default: 1000)</dd>


<dt>seed</dt>
<dd>Random seed for reproducibility (default: 123)</dd>


<dt>compute</dt>
<dd>Vector of methods to compute: 'procrustes', 'cca', 'principal', 'dynbeta'</dd>


<dt>progress</dt>
<dd>Logical, show progress bar (default: TRUE)</dd>


<dt>rotate</dt>
<dd>Which dataset to rotate: 'X' or 'Y' (default: 'Y')</dd>

</dl>

rotation_null_test: Rotation null hypothesis test for factor coupling

Description

Usage

Value

Arguments

Details