Modes of solid waste management and household health outcomes

Abstract

Poorly managed waste impacts negatively on water bodies and the atmosphere; and may limit the quality of human life. This study evaluates the effect of waste management on health outcomes, using nationally representative data of 16,772 households in Ghana. I employ the endogenous switching regression (ESR) and maximum simulated likelihood (MSL) techniques to respectively control for the endogeneity in waste management and also account for the heterogeneity effect in the modes of waste management. The results show that the private mode of waste management reduces the log number of days hospitalized due to ill-health and log of total household health expenditure per AEU by −1.56 and −2.48, respectively. The differential analysis indicates that while prompt collection of waste improves health outcomes, burning and indiscriminate dumping exacerbate health outcomes. The results of the study support the need to increase awareness and formulate sustainable strategies that prioritize waste management to enhance environmental quality.

Keywords:

• waste management methods
• health outcomes
• multinomial treatment effects model
• Ghana

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Sensitization on waste management is implemented to create awareness on human health. The variable is binary that takes on a value of one if the household is exposed to waste management and zero otherwise.

2 A falsification test certifies the admissibility of the selection instrument as a valid instrument: if a variable is an appropriate selection instrument, it will affect the choice of waste management, but it will not affect the health outcomes variables (Di Falco and Veronesi 2013). The results indicate that the instrument can be considered as valid, given that it is statistically significant in all the choice of waste management equations, but not significant in the health expenditure and number of days suffered from ill health equations (Table A1).

3 The ATT represents the effect of improved waste management method (private) on health outcomes of households that use private waste management methods.

4 The ATU represents the effect of public waste management method on health outcomes of households that use the public waste management method.

5 When the factor-loading parameter, ${\lambda }_j$ is positive (negative), treatment and outcome are positively (negatively) correlated through unobserved characteristics; i.e. there is positive (negative) selection, with $\gamma$ and $\lambda$ the associated parameter vectors, respectively.

6 The model was estimated using the Stata command mtreatreg with 200 simulation draws.

7 I use the OECD adult equivalent scale which is given by 1 + 0.7( A–1) + 0.5C, where A and C represent the number of adults and children in a household, respectively.

8 A referendum on December 27, 2018 approved the creation of six additional regions bringing the number of administrative regions in Ghana to sixteen.

9 Binned scatterplots are an informative and versatile way of visualizing relationships between variables (www.michaelstepner.com/binscatter).

10 The ATT measures the mean difference between the actual health outcomes (log number of days suffered from ill health and log of total household health expenditure per AEU) of private waste management households and what they would have achieved in terms of their health outcomes if they had adopted public waste management method.