Global household energy model: a multivariate hierarchical approach to estimating trends in the use of polluting and clean fuels for cooking

Stoner, Oliver, Shaddick, Gavin ORCID: https://orcid.org/0000-0002-4117-4264 and Economou, Theo 2020. Global household energy model: a multivariate hierarchical approach to estimating trends in the use of polluting and clean fuels for cooking. Journal of the Royal Statistical Society: Series C 69 (4) , pp. 815-839. 10.1111/rssc.12428

PDF - Published Version Available under License Creative Commons Attribution. Download (1MB)

Abstract

In 2017 an estimated 3 billion people used polluting fuels and technologies as their primary cooking solution, with 3.8 million deaths annually attributed to household exposure to the resulting fine particulate matter air pollution. Currently, health burdens are calculated by using aggregations of fuel types, e.g. solid fuels, as country level estimates of the use of specific fuel types, e.g. wood and charcoal, are unavailable. To expand the knowledge base about effects of household air pollution on health, we develop and implement a novel Bayesian hierarchical model, based on generalized Dirichlet–multinomial distributions, that jointly estimates non-linear trends in the use of eight key fuel types, overcoming several data-specific challenges including missing or combined fuel use values. We assess model fit by using within-sample predictive analysis and an out-of-sample prediction experiment to evaluate the model's forecasting performance.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	?? VCO ??
Publisher:	Royal Statistical Society
ISSN:	0035-9254
Date of First Compliant Deposit:	30 July 2024
Date of Acceptance:	1 May 2020
Last Modified:	30 Jul 2024 09:00
URI:	https://orca.cardiff.ac.uk/id/eprint/170999

Actions (repository staff only)

Edit Item