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Timely Indicators for Inequality and Poverty Using the Italian Labour Force Survey

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  • Francesca Carta

    (Bank of Italy
    Dondena)

Abstract

Income distribution measures obtained from standard household income surveys are usually published with a significant delay, of about 2 years. In this paper we propose a methodology for obtaining timelier indicators using the Italian Labour Force Survey (ILFS), a database which collects detailed information not only on individuals’ labour market status, but also on their households and wages. We develop a framework to estimate household labour income and we use it to construct distributional indicators that are available 1 year and half before the standard measures. After discussing the limitations of our approach, we show that the ILFS-based indicators closely track those calculated on standard household income surveys. The suggested indicators are not meant to substitute standard income measures but can offer up-to-date information, with the aim of better monitoring the distributional impact of changing macroeconomic conditions.

Suggested Citation

  • Francesca Carta, 2020. "Timely Indicators for Inequality and Poverty Using the Italian Labour Force Survey," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 149(1), pages 41-65, May.
    • Handle: RePEc:spr:soinre:v:149:y:2020:i:1:d:10.1007_s11205-019-02238-1
    DOI: 10.1007/s11205-019-02238-1
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    Cited by:

    1. Cathal O’Donoghue & Denisa M Sologon & Iryna Kyzyma & John McHale, 2021. "A Microsimulation Analysis of the Distributional Impact over the Three Waves of the COVID-19 Crisis in Ireland," International Journal of Microsimulation, International Microsimulation Association, vol. 14(2), pages 81-105.
    2. Astarita, Caterina & Alcidi, Cinzia, 2022. "Did the COVID-19 pandemic impact income distribution?," MPRA Paper 113851, University Library of Munich, Germany.
    3. Barbieri, Teresa, 2021. "Changes in the Italian wage distribution: the role of routine and social tasks," MPRA Paper 113407, University Library of Munich, Germany.
    4. Francesca Carta & Marta De Philippis, 2021. "The impact of the COVID-19 shock on labour income inequality: evidence from Italy," Questioni di Economia e Finanza (Occasional Papers) 606, Bank of Italy, Economic Research and International Relations Area.
    5. O'Donoghue, Cathal & Sologon, Denisa Maria, 2023. "The Transformation of Public Policy Analysis in Times of Crisis – A Microsimulation-Nowcasting Method Using Big Data," IZA Discussion Papers 15937, Institute of Labor Economics (IZA).

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    More about this item

    Keywords

    Inequality; Poverty; Employment; Nowcasting;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure

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