We use a statistical micro matching procedure to obtain a synthetic dataset to investigate the risk of fuel poverty in small areas. Specifically, we link 19,174 homes with Energy Performance Certificates (EPCs) in the Italian province of Treviso with information - from the General Census of Population and Housing and Household Budget Survey - about the socio-economic features of the families that most likely inhabit them. Based on this original dataset, we find that poor housing is as important as low income and the use of natural gas in determining fuel poverty. In particular, the risk of fuel poverty is increased by i) the energy inefficiency of the home; ii) the size of the home in relation to household size; iii) the lower total household expenditure. Conversely, the risk decreases when the main heating is natural gas and/or the home is endowed with renewable energy sources. Our results show that information in EPCs, matched at the micro level with the socio-economic data usually available from administrative sources or surveys, can be used to identify - on the one hand - the individual households and the municipal areas risking fuel poverty, and - on the other - the most effective policy options to tackle the phenomenon.
Mapping fuel poverty risk at the municipal level. A small-scale analysis of Italian Energy Performance Certificate, census and survey data
Riccardo Camboni;Paola Valbonesi
2021
Abstract
We use a statistical micro matching procedure to obtain a synthetic dataset to investigate the risk of fuel poverty in small areas. Specifically, we link 19,174 homes with Energy Performance Certificates (EPCs) in the Italian province of Treviso with information - from the General Census of Population and Housing and Household Budget Survey - about the socio-economic features of the families that most likely inhabit them. Based on this original dataset, we find that poor housing is as important as low income and the use of natural gas in determining fuel poverty. In particular, the risk of fuel poverty is increased by i) the energy inefficiency of the home; ii) the size of the home in relation to household size; iii) the lower total household expenditure. Conversely, the risk decreases when the main heating is natural gas and/or the home is endowed with renewable energy sources. Our results show that information in EPCs, matched at the micro level with the socio-economic data usually available from administrative sources or surveys, can be used to identify - on the one hand - the individual households and the municipal areas risking fuel poverty, and - on the other - the most effective policy options to tackle the phenomenon.File | Dimensione | Formato | |
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Energy_Policy_2021_CCMV.pdf
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