In this paper we estimate monetary and non-monetary poverty measures at two subregional levels in the region of Tuscany (Italy) using data from the ad-hoc Survey on Vulnerability and Poverty held by Regional Institute from Economic Planning of Tuscany (IRPET). We estimate the percentage of households living in poverty conditions and three supplementary fuzzy measures of poverty regarding deprivation in basic needs and lifestyle, children deprivation, and fnancial insecurity. The key feature of the survey is that it was carried out after the COVID-19 pandemic, therefore, some of the items collected focus on the subjective perception of poverty eighteen months after the beginning of the pandemic. We assess the quality of these estimates either with initial direct estimates along with their sampling variance, and with a secondary small area estimation when the formers are not sufciently accurate.
Crescenzi, F., Neri, L. (2023). Estimating fuzzy measures of deprivation at local level in Tuscany. QUALITY & QUANTITY, 1-20 [10.1007/s11135-023-01679-8].
Estimating fuzzy measures of deprivation at local level in Tuscany
Neri, Laura
2023-01-01
Abstract
In this paper we estimate monetary and non-monetary poverty measures at two subregional levels in the region of Tuscany (Italy) using data from the ad-hoc Survey on Vulnerability and Poverty held by Regional Institute from Economic Planning of Tuscany (IRPET). We estimate the percentage of households living in poverty conditions and three supplementary fuzzy measures of poverty regarding deprivation in basic needs and lifestyle, children deprivation, and fnancial insecurity. The key feature of the survey is that it was carried out after the COVID-19 pandemic, therefore, some of the items collected focus on the subjective perception of poverty eighteen months after the beginning of the pandemic. We assess the quality of these estimates either with initial direct estimates along with their sampling variance, and with a secondary small area estimation when the formers are not sufciently accurate.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/1233315