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The effect of tobacco expenditure on expenditure shares in South African households: A genetic matching approach

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  • Grieve Chelwa
  • Steven F Koch

Abstract

This paper examines whether tobacco expenditure leads to the crowding out or crowding in of different expenditure items in South Africa. We apply genetic matching to expenditure quartiles of the 2010/2011 South African Income and Expenditure Survey. Genetic matching is a more appealing approach for dealing with the endogeneity of tobacco expenditure that often plagues studies using systems of demand equations. Further, genetic matching provides transparent measures of covariate balance giving the analyst objective means of assessing match success. We find that the poorest tobacco consuming households in South Africa consistently allocate smaller budget shares towards food items than non-smoking households. Specifically, we find that dairy, fruits, nuts and oils are displaced in favour of tobacco expenditure in the two poorest quartiles. Unsurprisingly, food items are never displaced for households in the top two quartiles, given these households’ greater access to resources. Like other studies in the literature, we find that tobacco expenditure consistently crowds-in alcohol across all quartiles confirming the strong complementarities between the two.

Suggested Citation

  • Grieve Chelwa & Steven F Koch, 2019. "The effect of tobacco expenditure on expenditure shares in South African households: A genetic matching approach," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-16, September.
    • Handle: RePEc:plo:pone00:0222000
    DOI: 10.1371/journal.pone.0222000
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    References listed on IDEAS

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    1. Grieve Chelwa, 2014. "Assessing the Causal Impact of Tobacco Expenditure on Household Spending Patterns in Zambia," Working Papers 453, Economic Research Southern Africa.
    2. Muhammad Jami Husain & Biplab Kumar Datta & Mandeep K Virk-Baker & Mark Parascandola & Bazlul Haque Khondker, 2018. "The crowding-out effect of tobacco expenditure on household spending patterns in Bangladesh," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-15, October.
    3. Steven Block & Patrick Webb, 2009. "Up in Smoke: Tobacco Use, Expenditure on Food, and Child Malnutrition in Developing Countries," Economic Development and Cultural Change, University of Chicago Press, vol. 58(1), pages 1-23, October.
    4. John, Rijo M., 2008. "Crowding out effect of tobacco expenditure and its implications on household resource allocation in India," Social Science & Medicine, Elsevier, vol. 66(6), pages 1356-1367, March.
    5. Alexis Diamond & Jasjeet S. Sekhon, 2013. "Genetic Matching for Estimating Causal Effects: A General Multivariate Matching Method for Achieving Balance in Observational Studies," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 932-945, July.
    6. Pu, Cheng-yun & Lan, Virginia & Chou, Yiing-Jenq & Lan, Chung-fu, 2008. "The crowding-out effects of tobacco and alcohol where expenditure shares are low: Analyzing expenditure data for Taiwan," Social Science & Medicine, Elsevier, vol. 66(9), pages 1979-1989, May.
    7. Frederic Vermeulen, 2003. "Do smokers behave differently? A tale of zero expenditures and separability concepts," Economics Bulletin, AccessEcon, vol. 4(6), pages 1-7.
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    1. Nyagwachi, Abel Otwori & Chelwa, Grieve & van Walbeek, Corné, 2020. "The effect of tobacco- and alcohol-control policies on household spending patterns in Kenya: An approach using matched difference in differences," Social Science & Medicine, Elsevier, vol. 256(C).
    2. Nomusa Yolanda Nkomo & Mduduzi Biyase & Beatrice D. Simo-Kengne, 2023. "The Effects of Inequality on the Substitution of Essential Goods for Tobacco Smoking in South Africa," Economies, MDPI, vol. 11(6), pages 1-23, May.

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