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Objective vs. Subjective Fuel Poverty and Self-Assessed Health

Author

Listed:
  • Manuel Llorca

    (Durham University Business School, Durham University)

  • Ana Rodríguez-Álvarez

    (Oviedo Efficiency Group, Department of Economics, University of Oviedo, Spain)

  • Tooraj Jamasb

    (Durham University Business School, Durham University.)

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.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Manuel Llorca & Ana Rodríguez-Álvarez & Tooraj Jamasb, 2018. "Objective vs. Subjective Fuel Poverty and Self-Assessed Health," Working Papers EPRG 1823, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
  • Handle: RePEc:enp:wpaper:eprg1823
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    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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