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Access to credit by the poor in South Africa: Evidence from Household Survey Data 1995 and 2000

  • Francis Nathan Okurut

    ()

    (Department of Economics, University of Botswana)

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    This study specifically investigated the factors that influenced access by the poor and Blacks to credit in the segmented financial sector in South Africa, using income and expenditure survey data from 1995 and 2000. The study sheds light on the extent of financial sector deepening through household participation especially among the poor and Blacks, in the context of the fight against poverty. In this study, three types of credit were identified. Formal credit was defined to include debts from commercial banks (including mortgage finance and car loans), semi-formal credit included consumption credit (for household assets such as furniture and open accounts in retail stores), and informal credit specifically referred to debts from relatives and friends.Multinomial logit models and Heckman probit models with sample selection were used for analytical work. The results suggest that the poor and Blacks have limited access to the formal and semi-formal financial sectors. At the national level, access to bank credit is positively and significantly influenced by age, being male, household size, education level, household per capita expenditure and race (being Coloured, Indian or White). Being poor has a negative and significant effect on formal credit access. Semi-formal credit access is positively and significantly influenced by household size, per capita expenditure, provincial location (Eastern Cape, Northern Cape, Free State and North West) and being Coloured. The negative and significant factors in determining access to semi-formal credit include being male, rural location, being poor and being White. Informal credit access is negatively and significantly influenced by education level and race (being Coloured or White). Among the poor, access to bank credit is positively and significantly influenced by being male, provincial location (Western Cape, Gauteng and Mpumalanga) and being Coloured. Access to semi-formal credit is positively and significantly determined by household per capita expenditure, provincial location (Western Cape, Northern Cape, North West and Gauteng) and being Indian. Access to informal credit by the poor is positively and significantly influenced by provincial location (Kwazulu Natal and Gauteng). Within the black population, access to bank credit is positively and significantly influenced by age, being male, household per capita expenditure and education level. Semi-formal credit access by Blacks is positively and significantly influenced by household size, household per capita expenditure, education level and provincial location (Eastern Cape, Northern Cape, Free State and North West). However being male, poor and located in a rural area negatively affected access to semi-formal credit by Blacks. Informal credit access by Blacks is negatively influenced by education level, but positively influenced by being located in the Western and Eastern Cape. These findings confirm that improving access to organized credit markets (i.e formal and semi-formal credit markets) by the poor and Blacks, remains important in the fight against poverty.

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    File URL: http://www.ekon.sun.ac.za/wpapers/2006/wp132006/wp-13-2006.pdf
    File Function: First version, 2006
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    Paper provided by Stellenbosch University, Department of Economics in its series Working Papers with number 13/2006.

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    Date of creation: 2006
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    Handle: RePEc:sza:wpaper:wpapers27
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    1. Bell, Clive, 1990. "Interactions between Institutional and Informal Credit Agencies in Rural India," World Bank Economic Review, World Bank Group, vol. 4(3), pages 297-327, September.
    2. Peter Wright & Mahmud Mohieldin,, . "Formal and Informal Credit Markets in Egypt," Discussion Papers 96/2, University of Nottingham, CREDIT.
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    6. Aleem, Irfan, 1990. "Imperfect Information, Screening, and the Costs of Informal Lending: A Study of a Rural Credit Market in Pakistan," World Bank Economic Review, World Bank Group, vol. 4(3), pages 329-49, September.
    7. Stiglitz, Joseph E & Weiss, Andrew, 1981. "Credit Rationing in Markets with Imperfect Information," American Economic Review, American Economic Association, vol. 71(3), pages 393-410, June.
    8. Andrie Schoombee, 2000. "Getting South African banks to serve micro-entrepreneurs: An analysis of policy options," Development Southern Africa, Taylor & Francis Journals, vol. 17(5), pages 751-767.
    9. Bell, Clive & Srinivasan, T N & Udry, Christopher, 1997. "Rationing, Spillover, and Interlinking in Credit Markets: The Case of Rural Punjab," Oxford Economic Papers, Oxford University Press, vol. 49(4), pages 557-85, October.
    10. Reza Daniels, 2001. "Consumer Indebtedness Among Urban South African Households: A Descriptive Overview," Working Papers 01055, University of Cape Town, Development Policy Research Unit.
    11. Kochar, Anjini, 1997. "An empirical investigation of rationing constraints in rural credit markets in India," Journal of Development Economics, Elsevier, vol. 53(2), pages 339-371, August.
    12. Heckman, James J, 1990. "Varieties of Selection Bias," American Economic Review, American Economic Association, vol. 80(2), pages 313-18, May.
    13. Zeller, Manfred, 1994. "Determinants of credit rationing: A study of informal lenders and formal credit groups in Madagascar," World Development, Elsevier, vol. 22(12), pages 1895-1907, December.
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