Abstract
Does poor health increase the likelihood of energy poverty or vice versa creating a vicious poverty trap? We use data from the Household, Income and Labour Dynamics of Australia (HILDA) survey from 2005–2018 to explore if these two processes are dynamically related across a number of subjective and objective measures of physical and mental health as well as subjective and objective measures of energy poverty. We employ univariate dynamic models, introduce controls for initial conditions, and explore inter-dependence between energy poverty and health using a dynamic bivariate probit model. Our results show that controlling for initial conditions impacts on the magnitude and significance of the lagged coefficients. We only find cross-dependency effects between energy poverty and health for subjective measures of energy poverty. This suggests that individuals’ feelings about being in energy poverty may impact on their health leading to poor health/energy poverty traps. Targeting individuals in financial stress/debt may be one way to reduce these poor health/energy poverty traps.
Highlights
The inability to access energy is a global issue that currently affects approximately 30% of the world’s population (Halff et al 2014)
We find mixed evidence for cross-dependency effects between energy poverty and poor health which are dependent upon how both energy poverty and health are measured
We find stronger evidence of cross-dependency effects for subjective measures of energy poverty whereas we do not find cross-dependency effects with health and objective measures of energy poverty
Summary
The inability to access energy is a global issue that currently affects approximately 30% of the world’s population (Halff et al 2014). We control for initial conditions (columns 2, 4 and 6 in Table 5), past poor general health is only statistically significant for the subjective measures of fuel poverty (no pay bills and no heat) but not for low income/high cost definition. Lagged poor mental health is statistically significant for the subjective measures of energy poverty for the naïve specification and when controlling for initial conditions. Regarding the likelihood of reporting poor general health (Table 8), in our naïve specification where we do not control for initial conditions, fuel poverty in the previous period is associated with the likelihood of poor general health only for the subjective measures (nopaybills and noheat). 0.0062 0.60*** 0.094* 0.55*** − 0.0027* − 0.0085 − 0.098* 0.087 − 0.15*** 0.19*** − 1.08*** 12.9*** Yes Yes Yes 0.039 0.56*** 1.07*** 0.088* − 19,670.5 48,510
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