Household vulnerability to climate change in South Africa: A multilevel regression model

ABSTRACT

This study measures the vulnerability of households to food insecurity by measuring the risk or threat posed by climate change. This is conducted using multilevel or hierarchal regression, an extension of the “Three Stage Least Squares” model. Unlike the standard ordinary least squares regression model, this model can produce estimates of different hierarchal levels and produce unbiased reliable standard errors. With a sample size of 18,444 households nested within nine provinces, the findings show that climate change is a reality in South Africa, and it poses serious threats that expose households to future food consumption inadequacies. This study also offers a deeper understanding of the different sources of vulnerability among these households. Poverty or structural-induced vulnerability emerged as the main source of vulnerability for South African households. Climate change-induced vulnerabilities were also found to be prevalent and detrimental in rural areas with Limpopo and Eastern Cape being the most vulnerable provinces.

KEYWORDS:

• Food insecurity
• sources of vulnerability
• multilevel modelling
• shocks
• South Africa

Acknowledgements

The financial support (to the first author) of the DST-NRF Centre of Excellence in Human Development at the University of Witwatersrand, Johannesburg in Republic of South Africa towards this research is hereby acknowledged. Opinions expressed and conclusions arrived at are those of the authors and are not necessarily to be attributed to the Centre of Excellence in Human Development. Comments and constructive criticisms (on the previous version of the manuscript) by two anonymous reviewers of the journal are duly acknowledged.

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1 GHS, LS, CS, IES and NIDS refer to General Household Survey, Living Conditions, Community Survey, Income and Expenditure Survey, and National Income Dynamics Study, respectively.

2 NC, EC, LP, NW, MP and FS refer to Northern Cape, Eastern Cape, Limpopo, North-West, KwaZulu-Natal, Mpumalanga, and Free State provinces, respectively.

3 Total variance is the sum of idiosyncratic and covariate variance.

Additional information

Funding

This work was supported by Wits COE Human Development: [Grant Number: SIP2020-CCHD-10].