wow-inequalities/02-data/intermediate/wos_sample/85b589e8e24c35a8bebcb66a9f9904ed-monteduro-maria-ter/info.yaml

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