Chapter Unemployment dynamics in Italy: a counterfactual analysis at Covid time

This work performs a counterfactual analysis on unemployment dynamics in Italy during the year 2020. In doing so, ARIMA models are estimated and used to make projections for the 2020 quarters. This exercise is performed at population level and for each gender, age and educational groups. Data are fr...

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Váldodahkkit: Bakurov, Illya, Culotta, Fabrizio
Materiálatiipa: Online
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Almmustuhtton: Firenze University Press 2022
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Liŋkkat:ONIX_20220601_9788855184618_569
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author Bakurov, Illya
Culotta, Fabrizio
author_browse Bakurov, Illya
Culotta, Fabrizio
author_facet Bakurov, Illya
Culotta, Fabrizio
author_sort Bakurov, Illya
collection Directory of Open Access Books
description This work performs a counterfactual analysis on unemployment dynamics in Italy during the year 2020. In doing so, ARIMA models are estimated and used to make projections for the 2020 quarters. This exercise is performed at population level and for each gender, age and educational groups. Data are from the Italian Labor Force Survey covering the years 2015-2019 at quarterly frequency. Over the quarters of the year 2020, i.e. a time period covered by the Covid-19 pandemic and related restrictions, actual and counterfactual unemployment dynamics are compared. Overall, this work tries to answer to the following question: what would have happened to unemployment dynamics if Covid-19 pandemic and related restrictions would not arise as they did? Results can be informative to policymakers if the ARIMA projections can represent a reference for the aftermath of the pandemic.
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spelling doab-20.500.12854ir-835812022-06-02T04:34:05Z Chapter Unemployment dynamics in Italy: a counterfactual analysis at Covid time Bakurov, Illya Culotta, Fabrizio Covid-19 Italy Unemployment Dynamics Counterfactual Analysis ARIMA This work performs a counterfactual analysis on unemployment dynamics in Italy during the year 2020. In doing so, ARIMA models are estimated and used to make projections for the 2020 quarters. This exercise is performed at population level and for each gender, age and educational groups. Data are from the Italian Labor Force Survey covering the years 2015-2019 at quarterly frequency. Over the quarters of the year 2020, i.e. a time period covered by the Covid-19 pandemic and related restrictions, actual and counterfactual unemployment dynamics are compared. Overall, this work tries to answer to the following question: what would have happened to unemployment dynamics if Covid-19 pandemic and related restrictions would not arise as they did? Results can be informative to policymakers if the ARIMA projections can represent a reference for the aftermath of the pandemic. 2022-06-02T04:34:04Z 2022-06-02T04:34:04Z 2022-06-01T12:21:19Z 2021 chapter ONIX_20220601_9788855184618_569 2704-5846 https://library.oapen.org/handle/20.500.12657/56384 9788855184618 https://directory.doabooks.org/handle/20.500.12854/83581 eng Proceedings e report open access image/jpeg Attribution 4.0 International https://library.oapen.org/bitstream/20.500.12657/56384/1/26308.pdf Firenze University Press 10.36253/978-88-5518-461-8.40 10.36253/978-88-5518-461-8.40 2ec4474d-93b1-4cfa-b313-9c6019b51b1a 9788855184618 6 Florence open access
spellingShingle Covid-19
Italy
Unemployment Dynamics
Counterfactual Analysis
ARIMA
Bakurov, Illya
Culotta, Fabrizio
Chapter Unemployment dynamics in Italy: a counterfactual analysis at Covid time
title Chapter Unemployment dynamics in Italy: a counterfactual analysis at Covid time
title_full Chapter Unemployment dynamics in Italy: a counterfactual analysis at Covid time
title_fullStr Chapter Unemployment dynamics in Italy: a counterfactual analysis at Covid time
title_full_unstemmed Chapter Unemployment dynamics in Italy: a counterfactual analysis at Covid time
title_short Chapter Unemployment dynamics in Italy: a counterfactual analysis at Covid time
title_sort chapter unemployment dynamics in italy a counterfactual analysis at covid time
topic Covid-19
Italy
Unemployment Dynamics
Counterfactual Analysis
ARIMA
topic_facet Covid-19
Italy
Unemployment Dynamics
Counterfactual Analysis
ARIMA
url ONIX_20220601_9788855184618_569
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