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oapen-20.500.12657-563842022-06-02T03:26:27Z 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. 2022-06-01T12:21:19Z 2022-06-01T12:21:19Z 2021 chapter ONIX_20220601_9788855184618_569 2704-5846 9788855184618 https://library.oapen.org/handle/20.500.12657/56384 eng Proceedings e report application/pdf Attribution 4.0 International 26308.pdf https://books.fupress.com/doi/capitoli/978-88-5518-461-8_40 Firenze University Press 10.36253/978-88-5518-461-8.40 10.36253/978-88-5518-461-8.40 bf65d21a-78e5-4ba2-983a-dbfa90962870 9788855184618 132 6 Florence open access
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OAPEN
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English
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| 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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26308.pdf
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26308.pdf
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| title_short |
26308.pdf
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| title_full |
26308.pdf
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| title_fullStr |
26308.pdf
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26308.pdf
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26308.pdf
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| publisher |
Firenze University Press
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2022
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| url |
https://books.fupress.com/doi/capitoli/978-88-5518-461-8_40
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1771297598151327744
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