obs2Optim

Finds the most suitable model for the second observation equation according 
to the BIC.

internal

The output gap indicates the percentage difference between the actual output of an economy and its potential. Since potential output is a latent process, the estimation of the output gap poses a challenge and numerous filtering techniques have been proposed. 'RGAP' facilitates the estimation of a Cobb-Douglas production function type output gap, as suggested by the European Commission (Havik et al. 2014) <https://ideas.repec.org/p/euf/ecopap/0535.html>. To that end, the non-accelerating wage rate of unemployment (NAWRU) and the trend of total factor productivity (TFP) can be estimated in two bivariate unobserved component models by means of Kalman filtering and smoothing. 'RGAP' features a flexible modeling framework for the appropriate state-space models and offers frequentist as well as Bayesian estimation techniques. Additional functionalities include direct access to the 'AMECO' <https://economy-finance.ec.europa.eu/economic-research-and-databases/economic-databases/ameco-database_en> database and automated model selection procedures. See the paper by Streicher (2022) <http://hdl.handle.net/20.500.11850/552089> for details.

Sina Streicher

RGAP

Production Function Output Gap Estimation

obs2Optim function

<dl><dt>x1</dt>
<dd>A time series, the second observation equation.</dd>
<dt>xexo</dt>
<dd>(Optional) A (multiple) time series with exogenous variables.</dd>
<dt>errorARmax</dt>
<dd>Integer, maximal AR order of the error process of the 2nd observation 
equation.</dd>
<dt>errorMAmax</dt>
<dd>Integer, maximal MA order of the error process of the 2nd observation 
equation.</dd>
<dt>maxCycleLag</dt>
<dd>Integer, maximal cycle lag included in the 2nd observation 
equation.</dd>
<dt>maxAR</dt>
<dd>Integer, maximal AR order of the time series <code>x2</code> in the 2nd observation 
equation. <code>0</code> means that no lag is included.</dd>
<dt>nModels</dt>
<dd>Integer, maximum number of models chosen to be fitted.</dd></dl>

Arguments

Find suitable 2nd observation specification — obs2Optim

<dl>

<dt>x1</dt>
<dd>A time series, the second observation equation.</dd>


<dt>xexo</dt>
<dd>(Optional) A (multiple) time series with exogenous variables.</dd>


<dt>errorARmax</dt>
<dd>Integer, maximal AR order of the error process of the 2nd observation 
equation.</dd>


<dt>errorMAmax</dt>
<dd>Integer, maximal MA order of the error process of the 2nd observation 
equation.</dd>


<dt>maxCycleLag</dt>
<dd>Integer, maximal cycle lag included in the 2nd observation 
equation.</dd>


<dt>maxAR</dt>
<dd>Integer, maximal AR order of the time series <code>x2</code> in the 2nd observation 
equation. <code>0</code> means that no lag is included.</dd>


<dt>nModels</dt>
<dd>Integer, maximum number of models chosen to be fitted.</dd>

</dl>

obs2Optim: Find suitable 2nd observation specification

Description

Usage

Value

Arguments