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Including women in the policy responses to high oil prices: a case study of South Africa

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  • Fofana, Ismaël

Abstract

The recent surge in oil prices has created concern about its impacts on poor people in South Africa. The strong economic performance recorded over the period 1995-05 has not contributed to a substantial reduction in poverty in this country, particularly among women that tend to be overrepresented among poor households. Government management of an oil shock is important in reducing its adverse impacts in oil-importing countries. Thus, this study examines alternative policy responses to the recent high oil prices through a gender lens in South Africa. A multisector general equilibrium framework is developed to account for the energy specificities of the economy and its relationship with nonenergy sectors. In addition, male and female supplies of labor and the households’ demand for energy and nonenergy commodities are explored through a careful modeling of the household economy along with the market economy. The simulation scenarios combine increases in world prices of crude oil, petroleum products, and coal with various fiscal policy responses. Under the floating prices scenario, gross domestic product (GDP) falls compared to the baseline value driven by the inflationary effect of high energy prices and the exchange rate depreciation. Labor earnings also fall, while the gap between male and female earnings widens. The low participation of women compared to men in nonoil energy and export-oriented industries increases their vulnerability to the oil price shock. The gender employment gap also increases under the fixed petroleum price scenarios regardless of the tax-financing option. Further, fiscal policy responses are explored through the broadening of price supports to all commodities and all industries financed by an additional tax on household revenue. A government subsidy to businesses under the oil price shock shows the highest multiplier effect—higher GDP and labor earning effects—but the gap in male and female employment does not change significantly compared with that in the floating and set price scenarios. The government subsidy to businesses is decomposed by type of industry to further explore its gender employment impact. Simulation results indicate that the gender employment gap improves when the subsidy is allocated to high female-employing industries. On the other hand, providing a subsidy to industries that easily substitute capital–energy technology with low-skilled work gives the best GDP outcome. Therefore, this study shows that fiscal policy can help ensure equitable growth when an economy faces a serious challenge, such as a surge in world oil prices. This indicates that supporting industries that easily substitute the capital–energy factor and female-dominated, low-skilled work is the most efficient and gender-equitable fiscal response to high oil prices in South Africa. Given the small differences in GDP and employment results between the fiscal response scenarios with and without a focus on gender equity, the cost of investing in gender equality appears to be small.

Suggested Citation

  • Fofana, Ismaël, 2012. "Including women in the policy responses to high oil prices: a case study of South Africa," IFPRI discussion papers 1169, International Food Policy Research Institute (IFPRI).
  • Handle: RePEc:fpr:ifprid:1169
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    1. Hazilla, Michael & Kopp, Raymond J, 1990. "Social Cost of Environmental Quality Regulations: A General Equilibrium Analysis," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 853-873, August.
    2. Thurlow, James & van Seventer, Dirk Ernst, 2002. "A standard computable general equilibrium model for South Africa," TMD discussion papers 100, International Food Policy Research Institute (IFPRI).
    3. Fofana, Ismaél & Chitiga, Margaret & Mabugu, Ramos, 2009. "Oil prices and the South African economy: A macro-meso-micro analysis," Energy Policy, Elsevier, vol. 37(12), pages 5509-5518, December.
    4. Ramos Mabugu & Margaret Chitiga, 2009. "Liberalising Trade In South Africa: A Survey Of Computable General Equilibrium Studies," South African Journal of Economics, Economic Society of South Africa, vol. 77(3), pages 445-464, September.
    5. McDonald, Scott & Punt, Cecilia, 2005. "General equilibrium modelling in South Africa: What the future holds," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 44(1), pages 1-39, March.
    6. McDonald, Scott & van Schoor, Melt, 2005. "A Computable General Equilibrium (CGE) Analysis of the Impact of an Oil Price Increase in South Africa," Working Paper Series 15633, PROVIDE Project.
    7. Bergman, Lars, 1990. "Energy and environmental constraints on growth: A CGE modeling approach," Journal of Policy Modeling, Elsevier, vol. 12(4), pages 671-691.
    8. Lukasz Grzybowski & Ryan Hawthrone, 2019. "Substitution between fixed and mobile data amidst high levels of poverty and inequality," Working Papers 196, Economic Research Southern Africa.
    9. Allan P. O. Williams, 2006. "Impact of Strategies," Palgrave Macmillan Books, in: The Rise of Cass Business School, chapter 13, pages 167-181, Palgrave Macmillan.
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    Keywords

    petroleum; price shock; Gender; Fiscal policies; General equilibrium model; household economy; domestic work; time allocation;
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