compute_gaps

Computes the gap of each observable, i.e., it sums up the
respective cycle and all cycles the observable additionally loads on.

internal

Determining potential output and the output gap - two inherently unobservable variables - is a major challenge for macroeconomists. 'sectorgap' features a flexible modeling and estimation framework for a multivariate Bayesian state space model identifying economic output fluctuations consistent with subsectors of the economy. The proposed model is able to capture various correlations between output and a set of aggregate as well as subsector indicators. Estimation of the latent states and parameters is achieved using a simple Gibbs sampling procedure and various plotting options facilitate the assessment of the results. For details on the methodology and an illustrative example, see Streicher (2024) <https://www.research-collection.ethz.ch/handle/20.500.11850/653682>.

Sina Streicher

sectorgap

Consistent Economic Trend Cycle Decomposition

compute_gaps function

<dl><dt>model</dt>
<dd>state space model object, returned by the function
<code>define_ssmodel</code></dd>
<dt>state</dt>
<dd>state vector</dd>
<dt>idx_state</dt>
<dd>names of all cycle states</dd>
<dt>idx_obs</dt>
<dd>names of all observations (excluding constraints)</dd></dl>

Arguments

Gaps of observation equations — compute_gaps

<dl>

<dt>model</dt>
<dd>state space model object, returned by the function
<code>define_ssmodel</code></dd>


<dt>state</dt>
<dd>state vector</dd>


<dt>idx_state</dt>
<dd>names of all cycle states</dd>


<dt>idx_obs</dt>
<dd>names of all observations (excluding constraints)</dd>

</dl>

compute_gaps: Gaps of observation equations

Description

Usage

Value

Arguments