Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations

This study aims to refine unemployment forecasts by incorporating the degree of consensus in consumers' expectations. With this objective, we first model the unemployment rate in eight European countries using the step-wise algorithm proposed by Hyndman and Khandakar (J Stat Softw 27(3):1-22, 2...

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Author: Clavería González, Óscar
Format: article
Status:Published version
Publication Date:2019
Country:España
Institution:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repository:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/129623
Online Access:https://hdl.handle.net/2445/129623
Access Level:Open access
Keyword:Atur
Conducta dels consumidors
Enquestes de consum
Anàlisi de regressió
Indicadors econòmics
Unemployment
Consumer behavior
Consumer surveys
Regression analysis
Economic indicators
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oai_identifier_str oai:recercat.cat:2445/129623
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repository_id_str
spelling Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectationsClavería González, ÓscarAturConducta dels consumidorsEnquestes de consumAnàlisi de regressióIndicadors econòmicsUnemploymentConsumer behaviorConsumer surveysRegression analysisEconomic indicatorsThis study aims to refine unemployment forecasts by incorporating the degree of consensus in consumers' expectations. With this objective, we first model the unemployment rate in eight European countries using the step-wise algorithm proposed by Hyndman and Khandakar (J Stat Softw 27(3):1-22, 2008). The selected optimal autoregressive integrated moving average (ARIMA) models are then used to generate out-of-sample recursive forecasts of the unemployment rates, which are used as benchmark. Finally, we replicate the forecasting experiment including as predictors both an indicator of unemployment, based on the degree of agreement in consumer unemployment expectations, and a measure of disagreement based on the dispersion of expectations. In both cases, we obtain an improvement in forecast accuracy in most countries. These results reveal that the degree of agreement in consumers' expectations contains useful information to predict unemployment rates, especially for the detection of turning points.Springer2019201920192019info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion10 p.application/pdfapplication/pdfhttps://hdl.handle.net/2445/129623Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésReproducció del document publicat a: https://doi.org/10.1186/s12651-019-0253-4Journal for Labour Market Research, 2019, vol. 53, num. 3, p. 1-10https://doi.org/10.1186/s12651-019-0253-4cc-by (c) Clavería González, Óscar , 2019http://creativecommons.org/licenses/by/3.0/esinfo:eu-repo/semantics/openAccessoai:recercat.cat:2445/1296232026-05-29T05:05:01Z
dc.title.none.fl_str_mv Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations
title Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations
spellingShingle Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations
Clavería González, Óscar
Atur
Conducta dels consumidors
Enquestes de consum
Anàlisi de regressió
Indicadors econòmics
Unemployment
Consumer behavior
Consumer surveys
Regression analysis
Economic indicators
title_short Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations
title_full Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations
title_fullStr Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations
title_full_unstemmed Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations
title_sort Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations
dc.creator.none.fl_str_mv Clavería González, Óscar
author Clavería González, Óscar
author_facet Clavería González, Óscar
author_role author
dc.subject.none.fl_str_mv Atur
Conducta dels consumidors
Enquestes de consum
Anàlisi de regressió
Indicadors econòmics
Unemployment
Consumer behavior
Consumer surveys
Regression analysis
Economic indicators
topic Atur
Conducta dels consumidors
Enquestes de consum
Anàlisi de regressió
Indicadors econòmics
Unemployment
Consumer behavior
Consumer surveys
Regression analysis
Economic indicators
description This study aims to refine unemployment forecasts by incorporating the degree of consensus in consumers' expectations. With this objective, we first model the unemployment rate in eight European countries using the step-wise algorithm proposed by Hyndman and Khandakar (J Stat Softw 27(3):1-22, 2008). The selected optimal autoregressive integrated moving average (ARIMA) models are then used to generate out-of-sample recursive forecasts of the unemployment rates, which are used as benchmark. Finally, we replicate the forecasting experiment including as predictors both an indicator of unemployment, based on the degree of agreement in consumer unemployment expectations, and a measure of disagreement based on the dispersion of expectations. In both cases, we obtain an improvement in forecast accuracy in most countries. These results reveal that the degree of agreement in consumers' expectations contains useful information to predict unemployment rates, especially for the detection of turning points.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019
2019
2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/129623
url https://hdl.handle.net/2445/129623
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.1186/s12651-019-0253-4
Journal for Labour Market Research, 2019, vol. 53, num. 3, p. 1-10
https://doi.org/10.1186/s12651-019-0253-4
dc.rights.none.fl_str_mv cc-by (c) Clavería González, Óscar , 2019
http://creativecommons.org/licenses/by/3.0/es
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by (c) Clavería González, Óscar , 2019
http://creativecommons.org/licenses/by/3.0/es
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 10 p.
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.812429

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