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; Early Access
unique-id: WOS:001017553800001
usage-count-last-180-days: '0'
usage-count-since-2013: '0'
web-of-science-categories: Economics
year: '2023'