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Title page 1

Contents 1

Abstract 3

1. Introduction 4

2. Data 6

2.1. Measures of Energy Poverty 6

2.2. Measures of Health 7

2.3. Covariates 8

2.4. Descriptive Statistics 8

3. Empirical Approach 9

3.1. Static Random Effects Model 9

3.2. Dynamic Random Effects Model 10

3.3. Dynamic Latent Class Model 10

4. Main Results 13

4.1. Marginal Effects 13

4.2. Latent States 16

4.3. Robustness 18

4.4. Socioeconomic Gradient of Latent States and Energy prices 18

5. Conclusions 20

References 22

Tables 8

Table 1. Variable descriptions with sample statistics for pooled data 8

Table 2. Estimated average marginal effects of the SRE models 14

Table 3. Estimated average marginal effects of the DRE models 15

Table 4. Model selection criteria for the DLC model 15

Table 5. Estimated average marginal effects of the DLC model 16

Table 6. Conditional average probabilities and transition probabilities 17

Table 7. Estimated average marginal effects of the DLC model for a general index of energy deprivation 18

Table 8. Estimated average marginal effects of being in an observed state 19

Figures 11

Figure 1. Path diagram of the DLC model 11

Figure 2. Estimated average probability of each latent state at every year 17

초록보기

Energy poverty and health appear to be closely related, yet robust evidence on whether and how they mutually influence each other over time is still limited. We employ a dynamic latent class model on rich longitudinal data from the Household, Income, and Labor Dynamics in Australia Survey to uncover patterns of dynamic interdependence between energy poverty and ill-health.

Our approach integrates key modelling features, such as state dependence and time-varying unobserved heterogeneity, while also revealing and quantifying mechanisms of joint dependence over time. Unlike previous studies, our model shows that although energy poverty and ill-health seem to mutually influence each other, the effect of ill-health on energy poverty appears to be comparatively larger, suggesting that ill-health might be a stepping stone to energy poverty.

In addition, we identify three main types of individuals corresponding to different socioeconomic profiles and varying levels of vulnerability to changes in energy prices. These findings may indicate the need for targeted interventions rather than exclusive reliance on energy subsidies.

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