80 lines
2.5 KiB
YAML
80 lines
2.5 KiB
YAML
abstract: 'This paper addresses how to nowcast household income changes in a
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context of generalized but asymmetric economic shocks like the COVID-19
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pandemic by integrating real-time data into microsimulation models. The
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analysis provides an accurate assessment of distributional impacts of
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COVID-19 and Italian policy responses during 2020, thanks to quarterly
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data on the turnover of firms and professionals and on costs (goods,
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services and personnel). Thanks to these data, we can nowcast both the
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income dynamics of the self-employed and entrepreneurs and the
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wage-supplementation scheme for working time reduction, as well as all
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the other interventions based on turnover variations. The nowcasting
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procedure applies the firm-level data to the TAXBEN-DF microsimulation
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model (Italian Department of Finance) already relying on a particularly
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rich and update database of survey and administrative data at individual
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level that makes it an almost unique model of its kind. Results suggest
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that policy measures in response to the first pandemic year have been
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effective in keeping overall income inequality under control, while not
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yet being able to avoid a concerning polarization of incomes and large
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heterogeneous effects in terms of both income losses and measures''
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compensation.'
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affiliation: 'De Rosa, D (Corresponding Author), Minist Econ \& Finance, Dept Finance,
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Rome, Italy.
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Monteduro, Maria Teresa; De Rosa, Dalila; Subrizi, Chiara, Minist Econ \& Finance,
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Dept Finance, Rome, Italy.'
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author: Monteduro, Maria Teresa and De Rosa, Dalila and Subrizi, Chiara
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author-email: 'mariateresa.monteduro@mef.gov.it
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dalila.derosa@mef.gov.it
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chiara.subrizi@mef.gov.it'
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author_list:
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- family: Monteduro
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given: Maria Teresa
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- family: De Rosa
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given: Dalila
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- family: Subrizi
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given: Chiara
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da: '2023-09-28'
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doi: 10.1007/s40797-023-00232-8
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earlyaccessdate: JUN 2023
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eissn: 2199-3238
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files: []
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issn: 2199-322X
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journal: ITALIAN ECONOMIC JOURNAL
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keywords: 'COVID-19; Nowcasting; Administrative and survey data; Microsimulation;
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Inequalities'
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keywords-plus: POVERTY; INDICATORS; INEQUALITY
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language: English
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month: 2023 JUN 27
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number-of-cited-references: '43'
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papis_id: ab8520f06fa2c5eb3ff487d2df6294d7
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ref: Monteduro2023hownowcast
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times-cited: '0'
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title: How to Nowcast Uncertain Income Shocks in Microsimulation Models? Evidence
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from COVID-19 Effects on Italian Households
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type: article
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unique-id: WOS:001017553800001
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usage-count-last-180-days: '0'
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usage-count-since-2013: '0'
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web-of-science-categories: Economics
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year: '2023'
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