data_ch

A dataset containing quarterly Swiss economic data, sourced on November 20, 2023.

datasets

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

data_ch function

A list object with two lists. The first list cotains all untransformed endogenous variables:<dl>
<dt>output</dt>
<dd>Gross domestic product at 2020 prices, in million</dd><dt>vaA</dt>
<dd>value added in sector A: Goods-producing industries, at 2020 prices in million</dd><dt>vaB</dt>
<dd>value added in sector B: Service industries, at 2020 prices in million</dd><dt>vaC</dt>
<dd>value added in sector C: Government and adjustments,at 2020 prices in million</dd><dt>exp1</dt>
<dd>expenditure side sector i: Total consumption, at 2020 prices in million</dd><dt>exp2</dt>
<dd>expenditure side sector ii: Investment, at 2020 prices in million</dd><dt>exp3</dt>
<dd>expenditure side sector iii: Exports, at 2020 prices in million</dd><dt>exp4</dt>
<dd>expenditure side sector iv: Imports, at 2020 prices in million</dd><dt>fteA</dt>
<dd>full-time equivalent empoyment in sector A: Goods-producing industries, in thousand</dd><dt>fteB</dt>
<dd>full-time equivalent empoyment in sector B: Service industries, in thousand</dd><dt>fteC</dt>
<dd>full-time equivalent empoyment in government sector, in thousand</dd><dt>employment</dt>
<dd>full-time equivalent empoyment, in thousand</dd><dt>urate</dt>
<dd>ILO unemployment rate, in percent</dd><dt>inflation</dt>
<dd>consumer price inflation, year on year in percent</dd>
</dl>

Format

Swiss data set — data_ch

A list object with two lists. The first list cotains all untransformed endogenous variables:<dl>
<dt>output</dt>
<dd>Gross domestic product at 2020 prices, in million</dd>

<dt>vaA</dt>
<dd>value added in sector A: Goods-producing industries, at 2020 prices in million</dd>

<dt>vaB</dt>
<dd>value added in sector B: Service industries, at 2020 prices in million</dd>

<dt>vaC</dt>
<dd>value added in sector C: Government and adjustments,at 2020 prices in million</dd>

<dt>exp1</dt>
<dd>expenditure side sector i: Total consumption, at 2020 prices in million</dd>

<dt>exp2</dt>
<dd>expenditure side sector ii: Investment, at 2020 prices in million</dd>

<dt>exp3</dt>
<dd>expenditure side sector iii: Exports, at 2020 prices in million</dd>

<dt>exp4</dt>
<dd>expenditure side sector iv: Imports, at 2020 prices in million</dd>

<dt>fteA</dt>
<dd>full-time equivalent empoyment in sector A: Goods-producing industries, in thousand</dd>

<dt>fteB</dt>
<dd>full-time equivalent empoyment in sector B: Service industries, in thousand</dd>

<dt>fteC</dt>
<dd>full-time equivalent empoyment in government sector, in thousand</dd>

<dt>employment</dt>
<dd>full-time equivalent empoyment, in thousand</dd>

<dt>urate</dt>
<dd>ILO unemployment rate, in percent</dd>

<dt>inflation</dt>
<dd>consumer price inflation, year on year in percent</dd>


</dl>

data_ch: Swiss data set

Description

Usage

Arguments

Format