Objective vs. subjective fuel poverty and self-assessed health

Manuel Llorca, Ana Rodriguez-Alvarez and Tooraj Jamasb

Energy Economics, 2020, vol. 87, issue C

Abstract: Identification of fuel poverty and its impact on individuals is a growing social issue. Classifying households using subjective measures of fuel poverty yields different results than when objective measures are used. Moreover, there are assessment-related difficulties in establishing the effects on health and wellbeing, which hinders policy design to tackle this problem. In this paper, we propose a latent class ordered probit model to control for subjectivity when analysing the influence of fuel poverty on self-reported health. This methodology is applied to a sample of 25,000 individuals in 11,000 households for the 2011–2014 period in Spain, where 5.1 million people (11% of the population) could not afford to heat their homes to an adequate temperature in 2014. The results show that poor housing conditions, low income, material deprivation, and fuel poverty, have a negative impact on health. We also find that the effect of objective fuel poverty and other poverty-related factors on health are stronger when we control for unobserved heterogeneity among individuals. Since objective measures alone may not fully capture the adverse effect of fuel poverty on health, we advocate policy approaches that combine both objective and subjective measures and its application by policymakers.

Keywords: Fuel poverty in Spain; Self-assessed health; Ordered probit; Latent class model (search for similar items in EconPapers)
JEL-codes: C01 C25 I14 I32 Q43 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (78)

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Related works:
Working Paper: Objective vs. Subjective Fuel Poverty and Self-Assessed Health (2018)
Working Paper: Objective vs. Subjective Fuel Poverty and Self-Assessed Health (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:87:y:2020:i:c:s014098832030075x

DOI: 10.1016/j.eneco.2020.104736

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