Abstract

Food poverty constitutes a key dimension of material deprivation, particularly during periods of high inflation, when rising prices erode purchasing power and disproportionately affect economically vulnerable populations. This study investigates regional and sub-group disparities in food poverty across Italy over the period 2021–2023, characterised by an unprecedented surge in food prices. The analysis is based on microdata from the Italian Household Budget Survey (HBS) conducted by ISTAT.
The inflationary shock examined in this study occurred against a background of already fragile household conditions. The cumulative effects of successive economic downturns and sustained increases in living costs significantly weakened household welfare, with income losses and higher expenditures weighing most heavily on those already at risk of deprivation. Importantly, inflation did not affect households uniformly. In 2022, household-specific inflation estimates show that those in the lowest expenditure quintile experienced substantially higher inflation rates than households in the highest quintile, highlighting the strongly regressive nature of recent price dynamics.
A central mechanism underlying this unequal impact lies in the structure of household consumption. Lower-income households allocate a significantly larger share of their budgets to essential goods, particularly food, making them more exposed to increases in the prices of basic necessities. Beyond reducing purchasing power, this exposure limits households’ ability to adapt. Vulnerable groups face tighter budget constraints, lower liquidity, and fewer opportunities to substitute products or reduce expenditure, resulting in a heightened risk of food deprivation when prices rise.
The empirical analysis is conducted at multiple spatial scales—national, regional, and by municipality size—and is disaggregated across key vulnerable demographic groups, including elderly individuals living alone, single-parent households, families with multiple children, foreign-born populations, and residents of different urban contexts. A key methodological contribution of the study concerns the estimation of sampling variability for sub-national food poverty indicators. Given the complex survey design of the HBS and the non-linear nature of poverty measures, standard asymptotic variance estimators may be unreliable, particularly for small population domains. To address this issue, we implement resampling techniques that allow for valid statistical inference when estimating poverty indicators at regional and sub-group levels.
The results reveal pronounced territorial heterogeneity in food poverty incidence, with consistently higher levels observed in southern regions and in smaller municipalities. Bootstrap-based confidence intervals confirm that many of these differences across regions and demographic groups are statistically significant. Overall, the findings underscore the importance of integrating robust sub-national and distribution-sensitive analyses into official statistical systems and social policy monitoring frameworks. Reliance on national averages alone risks obscuring substantial inequalities in the cost-of-living burden and in access to adequate food across territories and population groups.