compute_weights

This function computes weights for linear growth or non-linear
level constraints.

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_weights function

<dl><dt>tsl_r</dt>
<dd>time series list with real level series</dd>
<dt>tsl_n</dt>
<dd>time series list with nominal level series</dd>
<dt>idx</dt>
<dd>index for aggregate</dd>
<dt>pos</dt>
<dd>sectors to be added</dd>
<dt>neg</dt>
<dd>sectors to be substracted</dd>
<dt>weight_type</dt>
<dd>type of weights, either <code>growth</code> or <code>level</code>,
default is <code>growth</code></dd></dl>

Arguments

Computes weights from sub sector data — compute_weights

<dl>

<dt>tsl_r</dt>
<dd>time series list with real level series</dd>


<dt>tsl_n</dt>
<dd>time series list with nominal level series</dd>


<dt>idx</dt>
<dd>index for aggregate</dd>


<dt>pos</dt>
<dd>sectors to be added</dd>


<dt>neg</dt>
<dd>sectors to be substracted</dd>


<dt>weight_type</dt>
<dd>type of weights, either <code>growth</code> or <code>level</code>,
default is <code>growth</code></dd>

</dl>

compute_weights: Computes weights from sub sector data

Description

Usage

Value

Arguments