The economic crisis engendered by the social distancing and lockdown measures implemented to limit the spread of COVID-19 contagions is expected to have strong consequences on income levels, in general, and on poverty diffusion, in particular. In absence of data on household income and living conditions at the times of pandemic, the application of microsimulation models on pre-pandemic survey data represents a valuable alternative to provide some insights on the impact of the COVID-19 outbreak and emergency benefits introduced on incomes of Italian households. In this research project, we aim to fill the gap existing in the literature on this topic by means of nowcasting procedures in order to improve hypotheses adopted in the microsimulation model and to make trends observed in pre-pandemic data in the labour market and the access to the welfare system more in line with the actual ones. This context of pandemic may however become an important opportunity of reflection on the methodology we use in Italy to define the absolute poverty phenomenon. In particular, the closure of shops and consequent limitations to individuals¿ consumption expenditure raised several doubts on the capability of a definition of poverty relying on the households¿ consumptions (as the absolute poverty does) of effectively identify the effects of the actual crisis on the levels of household wellbeing. Using a unique dataset merging the Household Budget Survey data and administrative records provided by the Italian Social Security Institute (INPS) and the Italian Ministry of Economics and Finance, we want to propose here a new and more reliable measurement of poverty, which improves the actual definition of absolute poverty and considers a potential combination of households¿ consumption expenditure with some elements of their income and wealth.
The contribution of this research project to the literature is twofold.
First, we use for the first time nowcasting techniques to micro-simulate the effects of the COVID-19 pandemic on Italian households¿ incomes. Nowcasting techniques have been already used to simulate the pandemic impact on income inequality in Ireland and Luxembourg (Sologon et al., 2020; O¿Donoghue et al., 2020), but these countries have been slightly affected by the COVID-19 outbreak and their governments introduced less severe restrictive measures. As a further contribution to the literature, taking advantage from the distinctive information contained in the AD-SILC dataset, we develop month-by-month hypotheses on wages, employment status and the access to the welfare system in the adopted microsimulation model.
Second, we propose a new measurement of absolute poverty which relies on a combination of households¿ income, consumption, and wealth levels. The definition of a new income-consumption-wealth absolute poverty indicator is made possible by means of a unique dataset obtained merging various waves of the Italian HBS survey (up to 2019), INPS administrative records containing information on labour incomes and social transfers, and fiscal declarations data provided by the Ministry of Economics and Finance covering households¿ wealth and missing income sources (e.g. capital incomes, private pension plans). Residual income sources (e.g. intra-household transfers, scholarships) are finally obtained from IT-SILC survey data through imputation techniques. The resulting dataset is named AD-HBS.
The AD-HBS dataset has many important advantages for the scopes of this research. First of all, it records detailed income, consumption expenditure, and wealth information for a representative sample of individuals and households, making it possible to compare the joint distribution of the three different dimensions of well-being. Also, while it is not a panel dataset, the 6-year time span of repeated cross sections may shed some light on the evolution of the three concepts in the recent past (the occupational history of interviewed people is instead fully available). Most importantly, it allows to use all household-level available information to conceive a poverty indicator which improves on the limits of consumption measures considering households¿ income and wealth levels.
While it has been widely acknowledged that income, consumption and wealth provide useful insights on poverty (Fisher et al., 2015; Stiglitz et al., 2009) and several studies present evidence on income- and consumption-based poverty measures (Cutillo et al., 2020; Meyer and Sullivan, 2012; Meyer and Sullivan, 2013), the joint consideration of all three measures of well-being is a relatively underdeveloped field of research. Some examples in this direction include Garner et al. (2013) and Fisher at al. (2021) for the US and Headey (2008) for Australia, but only the latter is explicitly focused on poverty and any of them take advantage from the use of administrative data. We thus propose to extend this area of research to the Italian context using both administrative and survey data. Referring to the absolute poverty, a crucial indicator for the Italian welfare system, this research project is also expected to provide relevant policy suggestions.
Cutillo A., Raitano M., Siciliani I. (2020). Income-based and consumption-based measurement of absolute poverty: insights from Italy. Social Indicators Research. https://doi.org/10.1007/s11205-020-02386-9
Fisher J., Johnson D.S., Smeeding T.M. (2015). Inequality of Income and Consumption in the US: Measuring the Trends in Inequality from 1984 to 2011 for the Same Individuals. Review of Income and Wealth 61(4), 630-650.
Fisher J.D., Johnson D.S., Smeeding T.M., Thompson J.P. (2021). Inequality in 3¿D: Income, Consumption, and Wealth. Review of Income and Wealth. https://doi.org/10.1111/roiw.12509
Garner T.I., Short K.S. (2013). A Multi-dimensional Measure of Economic Well-Being for the US: The Material Condition Index.
Headey B. (2008). Poverty is low consumption and low wealth, not just low income. Social Indicators Research 89(1), 23-39.
Meyer B.D., Sullivan, J.X. (2012). Identifying the disadvantaged: Official poverty, consumption poverty, and the new supplemental poverty measure. Journal of Economic Perspectives 26(3), 111-136.
Meyer B.D., Sullivan, J.X. (2013). Winning the war: Poverty from the Great Society to the Great Recession. NBER Working Papers 18718.
O¿Donoghue C., Sologon D.M., Kyzyma I., McHale J. (2020). Modelling the Distributional Impact of the COVID-19 Crisis, Fiscal Studies 41(2), 321-336.
Sologon D.M., O¿Donoghue C., Kyzyma I. et al. (2020). The COVID-19 Resilience of a Continental Welfare Regime-Nowcasting the Distributional Impact of the Crisis, LISER Working paper 2020-14.
Stiglitz J.E., Sen A., Fitoussi J.P. (2009). Report by the Commission on the measurement of economic performance and social progress.