Predictive model of per capita household organic waste based on socioeconomic and demographic variables in populations under 70,000 inhabitants
DOI:
https://doi.org/10.47187/perf.v1i36.392Keywords:
Household solid waste, Robust regression, Predictive modelling, Socio-economic factors, Organic waste, Waste managementAbstract
Waste management planning in small settlements lacks locally calibrated data. This study develops and validates a predictive model for per capita household organic waste production in 15 Ecuadorian settlements under 70,000 inhabitants. A sample of 1,195 households was analysed. Scaled Principal Component Analysis (PCA) reduced dimensionality. A Generalised Linear Model (GLM) with Gamma distribution and log-link outperformed ordinary least squares methods. Household income was the strongest positive predictor (z = 35.50). Household size showed a negative relationship, confirming domestic economies of scale. Low socio-economic strata generated more organic waste per capita than higher strata. Gamma-family models provide reliable tools for waste collection system design in heterogeneous, data-scarce contexts.
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