A microsimulation of spatial inequality in energy access: A Bayesian multi-level modelling approach for urban India

TL;DR

This paper introduces a Bayesian multi-level microsimulation model to analyze spatial inequality in energy access in Indian cities, providing detailed insights into fuel use patterns among low-income households.

Contribution

It develops a novel microsimulation approach using Bayesian modeling to reveal spatial energy use disparities in Indian urban areas, incorporating socio-cultural and spatial factors.

Findings

Model estimates align with survey data.

Identifies spatial disparities in energy access.

Supports targeted policy interventions.

Abstract

Access to sustained clean cooking in India is essential to addressing the health burden of indoor air pollution from biomass fuels, but spatial inequality in cities can adversely affect uptake and effectiveness of policies amongst low-income households. Limited data exists on the spatial distribution of energy use in Indian cities, particularly amongst low-income households, and most quantitative studies focus primarily on the effect of economic determinants. A microsimulation approach is proposed, using publicly available data and a Bayesian multi-level model to account for effects of current cooking practices, local socio-cultural context, and spatial effects. This approach offers previously unavailable insight into the spatial distribution of fuel use and residential energy transition within Indian cities. Uncertainty in the modelled effects is propagated through to fuel use estimates. The model is applied to four cities in the south Indian states of Kerala and Tamil Nadu, and comparison against ward-level survey data shows consistency with the model estimates. Ward-level effects exemplify how wards compare to the city average and to other urban area in the state, which can help stakeholders design and implement clean cooking interventions tailored to the needs of households.