The effect of microloans on the subjective well-being of the poor in Gauteng

COPYRIGHT AND CITATION CONSIDERATIONS FOR THIS THESIS/ DISSERTATION o Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made You may so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use o NonCommercial — You may not use the material for commercial purposes o ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original How to cite this thesis Surname, Initial(s) (2012) Title of the thesis or dissertation PhD (Chemistry)/ M.Sc (Physics)/ M.A (Philosophy)/M.Com (Finance) etc [Unpublished]: University of Johannesburg Retrieved from: I R O (Accessed: Date) The effect of microloans on the subjective well-being of the poor in Gauteng by MMAPHEFO CHRISTINAH LEGODI A dissertation submitted in fulfilment for the degree of M in Commerce in Development Economics at the College of Business and Economics UNIVERSITY OF JOHANNESBURG Supervisor: Dr T Greyling 2017 Acknowledgement The Almighty, Jesus Christ made it possible for me to complete my research study despite all the challenges faced This minor dissertation marks the end of a long and eventful journey, during which I have learned so much and met so many wonderful people who in different ways contributed not only to my work but also to my personal growth I would like to express my sincerest gratitude to my supervisor Dr Talita Greyling, whose expertise, understanding, calmness and patience added considerably to my graduate experience I am very thankful to you for always having time for me, your quick and insightful comments on my research Thank you to my mentee Lesley Mogano for convincing me to start my postgraduate journey when I had given up hope to further my studies Thank you to my academic friends for your words of encouragement and guidance Finally I would like to thank my parents, Israel Marumo Legodi (Papa) and Mokgadi Mary Legodi (Mama), to whom I dedicate this research They always motivated and supported me to go for the highest possible education I would also like to acknowledge the support of my brother Itumeleng Legodi and sister Caroline Legodi-Mahahle I cannot thank enough my fiancé Tshililo Muedi and my daughter Omolemo for their patience, support and motivation for me to complete this research i Declaration I certify that the minor diss M C (Development Economics) at the University of Johannesburg is my independent work and has not been submitted by me for a degree at another university MMAPHEFO CHRISTINAH LEGODI ii Abstract Worldwide, poverty remains to be an obstacle to achieve sustainable development and improve the well-being of people Microloans have become a popular policy tool for poverty alleviation and is part of the larger microfinance industry It is used in many developing countries as one of the approaches in their poverty alleviation programs Microloans are based on the principle that poor people can initiate their own development out of poverty, given they have the starting capital to so The capital can be invested in income-generating activities which, it is assumed, will lead to a higher income and additional positive effects, like an increase in well-being However, others argue that the focus on income is only one aspect of poverty Other forms of deprivation, such as education, health and a lack of subjective wellbeing should also be considered The main and primary research aim of this minor dissertation is to investigate how access to microloans is related to the subjective well-being of the poor and, secondly, to investigate if the relationship with microloans is the same for both male and female borrowers To analyse these research questions we make use of a data set collected by the Gauteng City-Region Observatory (GCRO) in 2015 on the quality of life of the people in the province The results from our analysis show that microloans are negatively related to the subjective well-being of the poor, meaning that the subjective well-being of the poor in Gauteng does not improve though access to microloans This finding contravenes the notion of microloans being a policy measure to address poverty through the alleviation of poverty and improving subjective well-being For further analysis we added an interaction variable, where the microloan variable is multiplied by the gender variable We found positive and significant results which indicate that males and females who have a microloan might have different experiences regarding their subjective well-being Pursuing this matter further, we analysed and compared the results of a male and a female subsample We found that although the microloan variable is only statistically significant in the female sample, the direction of the relationship in the two subsamples differs In the male subsample the relationship between microloan and subjective well-being is positive, but the opposite was found in the female sample, thus emphasising that gender matters when analysing the relationship between microloans and subjective well-being Furthermore, the results show that the standard factors found to explain the subjective well-being of people are also relevant for the poor in Gauteng, the economic centre of South Africa This shows that there iii s policy intervention to improve the subjective well-being of the poor Instead, to find ways to increase the well-being of the poor, policy makers should adapt policy to fit the specific circumstances in South Africa and not blindly pursue policy measures used in other regions and countries The South African government should first understand which factors are relevant to subjective well-being and how it affects different demographic groups such as males and females within a region With this knowledge policy makers will be better equipped to take efficient policy decisions to not only improve the economic well-being, but also the subjective well-being of the poor Keywords: Subjective well-being, microloan, poverty alleviation iv Table of Contents Acknowledgement i Declaration ii Abstract iii List of tables vii List of figures viii List of abbreviations/acronyms ix CHAPTER 1: INTRODUCTION AND OVERVIEW OF THE STUDY 1.1 Introduction Background 1.2 Research Problem 1.3 Research Question 1.4 Contribution of the Study 1.5 Significance of the Study 1.6 Structure of the Minor Dissertation CHAPTER 2: BACKGROUND 2.1 Profile of the Research Area CHAPTER 3: LITERATURE REVIEW 3.1 Introduction 3.2 Conceptual Background T 3.2.2 The concept of microfinance and microloans 3.2.3 The concept of subjective well- 10 3.3 Microloans, Poverty Reduction and Subjective Well-being 11 3.3.1 Microloans and subjective well-being 11 3.3.2 Microloans and subjective well-being of males and females 13 3.3.3 The impact of microloans programmes on alleviating poverty 14 3.3.4 Questioning the Ability of Microloans for Poverty Alleviation and improving subjective well-being 18 3.3.5 The Role of Microloans in Poverty Reduction 21 CHAPTER 4: METHODOLOGY AND DATA 23 4.1 Introduction 23 v 4.2 Model Specification and Estimation Techniques 23 4.3 Data 25 4.3.1 Data and selection of variables 25 4.3.2 Selection of variables 28 4.3.2.1 Dependent variable 28 4.3.2.2 Independent variables 29 CHAPTER 5: ESTIMATION RESULTS AND DISCUSSION 36 5.1 Introduction 36 5.2 Assessing the Reliability of the Sample 36 5.2.1 Endogeneity 36 5.2.2 Correlation statistics 37 5.2.3 Multicollinearity 39 5.2.4 Heteroskedasticity 39 5.3 Results of the Whole Sample Estimated on OLS and Ordered Probit 40 5.4 Results per Gender 44 CHAPTER 6: CONCLUSION 47 REFERENCES 50 APPENDIX A: ESTIMATION RESULTS 61 A1.1 Marginal Effects 61 A1.2 IV Regression 63 APPENDIX B: DIAGNOSTIC TEST 64 B1.1 Model Specification 64 B1.2 Over Identification Test 65 B1.3 Endogeneity Test 65 vi List of Tables Table 1: D 26 Table 2: Explanation of the dependent and independent variable expected signs 29 Table 3: C 37 Table 4: C 38 Table 5: V 39 Table 6: H 40 Table 7: Estimation results for subjective well-being (w Table 8: Gender differences in subjective well-bei 42 46 vii List of Figures Figure 1: Microloan Figure 2: L “ Figure 3: Microloan P ‘ C 22 29 31 viii Berlin, M (2017) Essays on the Determinants and Measurement of Subjective Well-Being (Doctoral dissertation) Stockholm, Sweden: Stockholm University Available from: https://orcid.org/0000-0001-8302-8145 Blaauw, D & Pretorius, A (2013) The determinants of subjective well-being in South Africa an exploratory enquiry Journal of Economic and Financial Services, 6(1):179-194 Blanchflower, D.G & Oswald, A.J (2007) Hypertension and happiness across nations Journal of Health Economics, 27:218-233 Boarini, R., Johansson, A & E M.M (2006) Alternative Measures of Well Being, OECD Social, Employment and Migration Working Papers, No 33 Botha, F & Booysen, F (2013) Family functioning and life satisfaction and happiness in South African households ERSA Working Paper no.363 Bradburn, N.M & Caplovitz, D (1965) Reports on Happiness Chicago : Aldine Bruhn, M & Love, I (2009) "The Economic Impact of Banking the Unbanked: Evidence from Mexico." Policy Research Working Paper 4981 World Bank, Washington, D.C Buckley, G (1997) Microfinance in Africa: Is it either the problem or the solution? World Development, 25:1081-1093 Burjorjee, D.M., Deshpande, R & Weidemann, C.J (2002) "Supporting Women's Livelihoods Microfinance that Works for the Majority A Guide to Best Practices", United Nations Capital Development Fund, Special Unit for Microfinance http://www.uncdf.org/english/microfinance/pubs/thematic_papers/gender/supporting/par t_1.php Cassar, A., Crowley, L & Wydick, B (2007) The effect of social capital on group loan repayment: evidence from field experiments Economic Journal, 117:85-106 Chibba, M (2009) Financial Inclusion, Poverty Reduction and the Millennium Development Goals European Journal of Development Research, 21:16-50 Chowdhury, A (2009) Microfinance as a Poverty Reduction Tool A Critical Assessment United Nations, Department of Economic and Social Affairs (DESA) Working Paper (89) Chowdhury, M.R., Mosley, P & Simanowitz, A (2004) The social impact of microfinance Journal of International Development, 16:291-300 Ciravegn D T ‘ Working Paper, Costa Rica M M E C I F Clark, A.E & Oswald, A.J (1994) Unhappiness and Unemployment The Economic Journal, 104(424):648-659 Cohen, J (1988) Statistical power analysis for the behavioural sciences (2nd ed.) Hillsdale, NJ: Lawrence Earlbaum Associates Coleman, B (1999) The impact of group lending in northeast Thailand Journal of Development Economics, 45:105-141 51 Crooker, K & Janet N.J (1998) Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 44(2):195-224 Cull, R., Demirgỹỗ-Kunt, A & Morduch, J (2006) Financial performance and outreach: A global analysis of leading microbanks Economic Journal, 117(517):107-133 Cummins, R.A (2003) A Model for the Measurement of Subjective Well-Being through Domains, draft, Melbourne: School of Psychology, Deakin University DBSA (Development Bank of Southern Africa) (2005a) Development Report Overcoming Und A E J , 2005 Demirgỹỗ-Kunt, A (2014) Presidential Address: Financial Inclusion Atlantic Economic Journal, 42(4):8-356 DFID (Department of International Development) (1999) Sustainable Livelihoods and Poverty Elimination: Background Briefing Available from: www.ids.ac.uk: http://www.ids.ac.uk/livelihoods.html (accessed 2/07/2014) Diener, E (2002) Will Money Increase Subjective Well-being? Social Indicators Research, 57:119-169 Diener, E., Emmons, R A., Larsen, R J & Griffin, S (1985) The Satisfaction With Life Scale Journal of Personality Assessment, 49(1), 71-75 Diener, E., Oishi, S., & Lucas, R E (2012) Subjective Well-Being: The Science of Happiness and Life Satisfaction In The Oxford Handbook of Positive Psychology, (2 Ed.) Oxford University Press doi: 10.1093/oxfordhb/9780195187243.013.0017 Diener, E., Suh, E.M., Lucas, R.E & Smith, H.E (1999) Subjective well-being: three decades of progress Psychol Bull, 125:276 302 Di Tella, R., MacCulloch, R.J & Oswald, A.J (2001) Preferences over inflation and unemployment: Evidence from surveys of happiness American Economic Review, 91:335341 Dolan, P & P T M ring well-being for public policy: preferences or Journal of Legal Studies, 37:5-31 Duflo, E., Glennerster, R., & Kremer, M (2008) Using randomization in development economics research: A toolkit In T P Schultz & J Strauss (Eds.), Handbook of development economics (Vol 4) Amsterdam: Elsevier Duvendack, M., Palmer-Jones, R., Copestake, J.G., Hooper, L., Loke, Y., Rao, N (2011) What is the evidence of the impact of microfinance on the well-being of poor people? London: EPPI-Centre Social Science Research Unit, Institute of Education, University of London Easterlin, R.A (1974) D E G I H L “ E E I P A David and M.W Reder (Eds.), Nations and Households in Economic Growth: Essays in Honour of Moses Abramovitz (New Yok and London: Academic Press: 1974) 52 Eid, M & Diener, E (2004) Global judgments of subjective wellbeing: situational variability and long-term stability Social Indicators Research, 65:245-277 Ellis, A., Blackden, M., Cutura, J., MacCulloch, F & Seebans, H (2007) Gender and Economic Growth in Tanzania: Creating Opportunities for Women Washington, D.C.: World Bank Fasoranti, M (2010) The influence of micro-credit on poverty alleviation among rural dwellers: A case study of Akoko North West Local Government Area of Ondo State African Journal of Business Management, 4(8): 1438-1446 Ferrer-i-Carbonell, A & Frijters, P (2004) How important is methodology for the estimates of the determinants of happiness? The Economic Journal, 114:641-659 Frey, B.S & Luechinger, S (2007) Concepts of Happiness and their Measurement Metropolis, Verlag, 219-237 Frey, B.S & Stutzer, A (2002) "What can an economist learn from happiness research?" Journal of Economic Literature, 40(3):402-435 Frijeters, P & Beatton, T (2008) The mystery of the U-shaped relationship between happiness and age National Centre for Econometric Research Working Paper Series Gauteng City-Region Observatory (GCRO) (2015) The city-region review Johannesburg: Global Print Gerdtham, U.G., & Johannesson, M (2001) The relationship between happiness, health, and socio-economic factors: results based on Swedish micro data The Journal of SocioEconomics, 30(6), 553-557 George, L.K (2006) Perceived quality of life In R.H Binstock & L.K George (Eds.), Handbook of aging and the social science (pp 320-335) Academic press G LK E -being: a review of the literature and an agenda for future rese Aging, Money, and Life Satisfaction: Aspects of Financial Gerontology, Cutler N.E., Gregg D.W & Lawton M.P.(eds) (New York, NY: Springer) Ghana Statistical Service (GSS) (2007) Pattern and Trends of Poverty in Ghana 1991-2006, Accra: Ghana Statistical Service Goetz, A.M & Gupta, R.S (1996) Who takes the credit? Gender, power, and control over loan use in rural credit programs in Bangladesh World Development, 24(1):45-63 Gokhale, K (2009) A Global Surge in Tiny Loans Spurs Credit Bubble in a Slum Wall Street Journal 13 August Available at: http://www.wsj.com/articles/SB125012112518027581 Graham, C & Pettinato, S (2002) Happiness and Hardship: Opportunity and Insecurity in New Market Economies Washington, D.C.: The Brookings Institution Press Greyling, T & Tregenna, F (2017) 'Construction and analysis of a composite quality of life index for a region of South Africa.' Social Indicators Research Gujarati, D.N & Porter, D.C (2009) Basic Econometrics New York: McGraw Hill Book Co 53 G N B &“ C , C (2007) Factors Explaining the Rating of Microfinance Institutions Nonprofit and Voluntary Sector Quarterly, 36:439-464 Hahn, J & Hausman, J W I Economics American Economic Review, 93:118-125 D C E Hair, J.F., Tatham, R.L & Anderson, R.E (1998) Multivariate data analysis (5th ed.) Upper Saddle River, NJ: Pearson/Prentice Hall Haq, M., Skully, M T & Pathan, S (2009) Efficiency of Microfinance Institutions: A Data Envelopment Analysis, Asia-Pacific Financial Markets Available at SSRN: http://ssrn.com/abstract=1405709 Hartog, J & Oosterbeek, H (1997) Health, wealth and happiness: why pursue a higher education? Economics of Education Review, 17(3):245-256 Hashemi, S.M., Schuler, S.R & ‘ AP ‘ empowerment in Bangladesh World Development, 24(4):635-653 Haughton, J & Khandker, S.R (2009) Handbook on poverty and inequality Washington,DC:WorldBank.http://documents.worldbank.org/curated/en/48808146815717 4849/Handbook-on-poverty-and-inequality Headey, B.W & Wearing, A.J (1992) Understanding Happiness: A Theory of Subjective WellBeing Melbourne: Longman Cheshire H JF H C subjective well-being Economic Modelling, 20:331-60 Helliwell, J., Layard, R & Sachs, J (eds.) (2013) World happiness report The Earth Institute, Columbia University Hermes, N & Lensink, R (2007) The empirics of microfinance: What we know? The Economic Journal, 117 (1):1-10 Higgs, N.T (2007) Measuring and understanding the well-being of South Africans: Everyday quality of life in South Africa Social Indicators Research, 81:331-356 Honohan, P (2008) Cross-country variation in household access to financial services Journal of Banking and Finance, 32(11):2493 2500 Horley, J & Lavery, J (1995) Subjective well-being and age Social Indicators Research, 34(2):275-282 Hossain M (1988) Credit for alleviation of rural poverty: the Grameen Bank in Bangladesh IFPRI Research Report 65 Washington, DC: International Food Policy Research Institute Howell, R.T &Howell, C.J (2008) The relation of economic status to subjective well-being in developing countries: A meta-analysis Psychological Bulletin, 134(4):536-560 Hulme, D (2000) Impact assessment methodologies for microfinance: Theory, experienceand better practice World Development, 28:79-98 Hulme, D & Mosley, P (1996) Finance against Poverty Volume 1, London: Routledge 54 Husain, A.M (1998) Poverty alleviation and empowerment: The Second Impact Assessment “ B‘AC ‘ D P B‘AC ‘ E D ILO (1997) Gender poverty and employment: Turning capabilities into entitlements Geneva: International Labour Organisation (ILO) Inglehart, R.F., Norris, P & Welzel, C (2002) Gender equality and democracy, Comparative Sociology, 1:45-321 Jacobs, P., Hart, T., Matshe, I & Baiphethi, M (2010) Agrarian Reform and Poverty Reduction in South Africa Jain, P.S (1996) Managing credit for the rural poor: Lessons from the Grameen Bank World Development, 24(1):79 89 Jaffer, J (1999) Microfinance and the Mechanics of Solidarity Lending: Improving Access to Credit through Innovations in Contract Structure Harvard Law School, Olin Centre for Law, Economics and Business, Working paper No 254 Johnson, S & Rogaly, B (1997) Microfinance and poverty reduction UK and Ireland: UK: Oxfam Jones, B.G (2006) Explaining poverty: A critical realist approach Oxford: Routledge Kabeer, N (1999) Resources, Agency, Achievement: Reflections on the Measurement of W E Development as Change, 30(3):64-435 Kaboski, J.P & Townsend, R.M (2005) Policies and Impact: An Analysis of Village Microfinance Institutions." Journal of the European Economic Association, 3(1):1-50 Kaboski, J.P & Townsend, R.M (2009) The Impacts of Credit on Village Economies mimeo, http://www.nd.edu/jkaboski/impactofcredit.pdf Karlan, D & Zinman, J (2009) Expanding Microenterprise Credit Access: Using Randomized Supply Decisions to Estimate the Impacts in Manila Working Paper, Yale University Karlan, D & Zinman, J (2011) Microcredit in Theory and Practice: Using Randomized Credit Scoring for Impact Evaluation Science, 332(6035):84-1278 Khandker, S.R (1998) Fighting Poverty with Microcredit: Experience in Bangladesh New York: Oxford University Press Khandker, S.R (2001) Does Micro-finance Really Benefit the Poor? Evidence from Bangladesh, Asia and Pacific Forum on Poverty: Reforming Policies and Institutions for Poverty Reduction Presentation in Manila, 5-9 February 2001 Khandker, S.R (2003) Micro finance and Poverty: Evidence Using Panel Data from B W B P cy Research Paper 2945, World Bank, Washington Khandker, S.R., Samad, H.A & K Microcredit Programmes: Village-L Studies, 35(2): 96-124 ) E I B E E Journal Development 55 Kingdon, G & Kni C P manuscript JB W -Being Poverty Versus Income Poverty and Center for the Study of African Economies: University of Oxford, Kohler, H.P., Behrman, J.R & Skytthe, A (2005) Partner + children = happiness? The effects of partnerships and fertility on well-being Population and Development Review, 31(3):407445 Kondo, T (2007) Impact of Microfinance on Rural Households in the Philippines: A Case Study from the Special Evaluation Study on the Effects of Microfinance Operations of Poor Households and the Status of Women Asian Development Bank Kozma, A., Stones M.J & McNeil, J.K (1991) Psychological well-being in later life Toronto: Butterworth Laeven, L (2003) Does Financial Liberalization Reduce Financing Constraints? Financial Management, 5:5-34 Lam, K.J & Liu, P (2013) Socio-Economic Inequalities in Happiness in China and U.S Social Indicator Research, 116(2):509-533 Lapenu, C & Zeller, M (2002) Distribution, growth, and performance of the microfinance institutions in Africa, Asia and Latin America: A Recent Inventory Savings and Development, 1:87-111 Layard, R (2005) Happiness Lessons from a New Science, London: Penguin Books Levine, R (1997) Financial Development and Economic Growth, Views and Agenda Journal of economic literature, 35:688-726 Littlefield, E., Murduch, J & Hashemi, S (2003) Is Microfinance an Effective Strategy to Reach the Millennium Development Goals, CGAP, Focus Note 24 Lund, F (2008) C Town: HSRC Press “ P -T C “ G “ A Cape MacKerron, G (2012) Happiness economics from 35,000 feet Journal of Economic Surveys, 26(4):705-735 M V F M Weekly, 40(41):4416-4419 L F Economic and Political Mahdavi, M.S & Saburi, H (2003) Investigating the structure of power distribution in family Women Stud., 2:29-65 Marconi, R & Mosley, P (2005) Bolivia during the global crisis 1998-2004: Towards a macroeconomics of microfinance, Sheffield Econ Res Paper Series, 2057: 1-45 Michalos, A.C (2008) Education, Happiness and Wellbeing Social Indicators Research, 2:339-354 M V L South African Crime Quarterly, No D 56 Møller , V (2004c) Researching Quality of Life in a Developing Country: Lessons from the South African Case Institute of Social and Economic Research Rhodes University Paper prepared for the Hanse Workshop on Researching Well-being in Developing Countries, Delmenhorst, Germany, 2-4 July 2004 Møller, V (2005) Resilient or resigned? Criminal victimisation and quality of life in South Africa Social Indicators Research, 72, 263-317 Møller, D W Affairs, 39(2):177-206 Disability, and H Philosophy and Public Morduch, J (1998) Does Microfinance Really Help the Poor? New Evidence from Flagship Programs in Bangladesh New York University Department of Economics Available at j.mp/bC3Tge Mosley, P (2001) Microfinance and Poverty in Bolivia Journal of Development Studies, 101132 Mosley, P (2004) Pro-poor politics and the new political economy of stabilisation New Political Economy, 9:749-771 Mustafa, S.I., Ara, D., Banu, A., Hussain, A., Kabir, A., Mohsin, M., Yusuf, A & Jahan, S B B‘AC ‘ D Programme BRAC, Dhaka Nader, Y.F (2008) Microcredit and the socio-economic well-being of women and their families in Cairo Journal of Socio-Economics, 37(2):644-656 National Credit Regulator (2011) Literature review on small and mediu access to credit and support in South Africa National Credit Regulator, Pretoria, South Africa OECD (2011) OECD Territorial Reviews: The Gauteng City-Region Observatory, South Africa 2011, OECD publishing http://dx.doi.org/10.1787/9789264122840-en Oishi, S., Kesebir, S & Diener, E (2011) Income inequality and happiness Psychological Science, 22(9):1095-1100 Otero, M (1999) Bringing development back into microfinance Latin America: ACCION International Panjaitan-Drioadisuryo, R.D.M & Cloud, K (1999) Gender, self-employment and microcredit programs: An Indonesian case study-the challenge of significance Q Rev Econ Finance, 39: 769-779 Pinquart, M & Sorensen, S (2001) Gender differences in self-concept and psychological well-being in old age: a meta-analysis Journals of Gerontology, 568:195-213 Pitt, M.M & K “ T I G -Based Credit Programs onPoor Households in Bangladesh: Does the Gender of Participants Matter? Journal of Political Economy, 106:958-996 57 Pitt, M.M., Khandker, S., Choudhury, O & M M and the Health Status of Children in Rural Bang 44:87-118 C P P International Economic Review, Pitt, M.M.S., Khandker, R., McKernan, S & L MA C P P and Reproductive Behavior in Low Income Countries: Are the Reported Causal Relationships the Result of Heterogen B Demography 33: 1-21 PlaNet (2008) National Impact Survey of Microfinance in Egypt Egypt: PlaNet Finance Available at: http://www.microfinancegateway.org/p/site/m/template.rc/1.9.45558/ Powdthavee, N (2007) Happiness and the standard of living: The Case for South Africa Warwick Economic Research Papers No 675 Powdthavee, N (2003) Unhappiness and Crime: Evidence from South Africa University of Warwick, No 685 Warwick Economic Research Papers Department Of Economics Pronyk, P.M., Hargreaves, J.R & Morduch, J (2007) Microfinance Programmers and Better Health The Journal of the American Medical Association, 16:1925-1927 Robinson, M (2001) The Microfinance Revolution: Sustainable finance for the poor Washington, DC: The World Bank Rogaly, B (1996) Microfinance evangelism, 'destitute women', and the hard selling of a new anti-poverty formula Development in Practice, 6(2):100-112 Roodman, D & Morduch, J (2009) The Impact of Microcredit on the Poor in Bangladesh: Revisiting the Evidence Working Paper no 174 Washington, DC: Center for Global Development, June Schoombee, A (2004) South African banks and the unbanked: progress and prospects South African Journal of Economics, 72(3):581-603 Schuler, S.R., Hashemi, S.M & ‘ AP T B E contraceptive use World Development, 25(4):563-575 Seekings, J & Nattrass, N (2005) Class, Race and Inequality in South Africa, Yale University Press, New Haven Sen, A (1987) Commodities and Capabilities Amsterdam: North-Holland World Bank 2000 World Development Report 2000/2001: Attacking Poverty Washington, DC: World Bank Sinclair, H (2012) Confessions of a microfinance heretic: How microlending lost its way and betrayed the poor San Francisco, CA: Berrett-Koehler Publishers Smith, A (1776) An Inquiry into the Nature and Causes of the Wealth of Nations Project Gutenberg e books Smyth, R., Nielsen, I & Zhai, Q (2010) Personal Well-being in Urban China Social Indicators Research 95:231-251 58 Statistics South Africa (2014) Poverty Trends in South Africa: An Examination of Absolute Poverty between 2006 and 2011 Pretoria: Statistics South Africa Statistics South Africa (2017) Poverty Trends in South Africa: An Examination of Absolute Poverty between 2006 and 2015 (Report No 03-10-06) Pretoria: Statistics South Africa Steptoe, A., Deaton, A & Stone, A (2015) Subjective Well-being, Health, and Aging The Lancet, 385:48- 640 Stevenson, B & Wolfers, J (2009) The paradox of declining female happiness American Economic Journal: Economic Policy, 1(2):190-225 Stewart, R., van Rooyen, C., Korth, M., Chereni, A., Rebelo Da Silva, N & de Wet, T (2012) D micro-credit, micro-savings, and micro-leasing serve as effective financial inclusion interventions enabling poor people, and especially women, to engage in meaningful economic opportunities in low- and middle- income countries A systematic review of the L EPPI-Centre, Social Science Research Unit, Institute of Education, University of London Stock, J H., Wright, J H & Yogo, M I G M Statistics, 20:518-529 M A“ W I W Journal of Business and Economic Stroebe, W & Stroebe, M S (1987) Bereavement and health New York: Cambridge University Press “ A T ‘ I A Economic Behavior and Organization, 54(1):89-109 I H Journal of Taylor, M., Jenkins, S & Sacker, A (2009) Financial Capability and Well-Being: Evidence from the BHPS [Occasional Paper Series 34] Essex, UK: Financial Services Authority Van der Berg, S., Burger, R., Louw, M & Yu, D (2005) Trends in poverty and inequality since the political transition Bureau for Economic Research, Dept of Economics University of Stellenbosch 1/2005 Van Praag, B.M.S., Frijters, P & Ferrer-i-Carbonell, A (2003) The anatomy of subjective well-being Journal of Economic Behavior and Organization 51, 29-49 Veenhoven, R (2010) Life is Getting Better: Societal Evolution and Fit with Human Nature Social Indicators Research, 97: 105 122 http://dx.doi.org/10.1007/s11205-009-9556-0 Waldron, S (2010) Measuring Subjective Wellbeing in the UK ONS Report 2010 Watson, D., Clark, L A & Tellegen, A (1988) Development and validation of brief measures of positive and negative affect: The PANAS Scales Journal of Personality and Social Psychology, 54, 1063-1070 Wilkinson, R & Pickett, K (2009) Income inequality and social dysfunction Annual Review of Sociology, 35:493 511 59 Witter, R.A., Okun, M.A., Stock, W.A & Haring M.J (1984) Education and Subjective WellBeing: A Meta-Analysis Educational Evaluation and Policy Analysis Summer, 6(2):165-173 Wolday, A (2003) Microfinance in Ethiopia: Performance Challenges and Role in Poverty Reduction Association of Microfinance Institutions Occasional paper No 7, AEMFI: Addis Ababa, Ethiopia Woolard, I & Leibbrandt, M (2001) Measuring poverty in South Africa In Bhorat, H., Leibbrandt, M., Maziya, M., Van der Berg, S & Woolard, I (Eds): Fighting poverty: labour markets and inequality in South Africa Cape Town: UCT Press: 41-73 W JM O -level production functions using proxy Economics Letters, 104(3):112 114 World Bank (2000) World Development Report 2000/2001: Attacking Poverty Washington, DC: World Bank World Bank (2003) G E M Development Group, Washington, DC: World Bank D G Gender and Wright, G.A.N (2000) Microinance Systems Designing Quality Financial Services for the Poor, Zed Books Ltd., London and New York Yunus, M (2001) Banker to the Poor: The Autobiography of Muhammad Yunus, Founder of Grameen Bank New York: Oxford University Press Yunus, M (2003) Halving poverty by 2015 - We Can Actually Make it Happen The Round Table, 370:363-375 Yunus, M & Jolis, A (2003) Banker to the poor: Micro-lending and the battle against world poverty New York, NY: Public Affairs ) H B P The World Bank A the Impact of Micro-credit on Poverty and Vulnerability in T W B W DC Zeller, M (1994) Determinants of Credit Rationing: A Study of Informal Lenders and Formal Credit Groups in Madagascar World Development, 22(12):1895-1907 60 APPENDIX A: ESTIMATION RESULTS A1.1 Marginal Effects Margins _predict Very dissatisfied Dissatisfied Neutral Satisfied Very satisfied Delta-method Margin Std Err z P>z [95% Conf Interval] 0622709 1546991 1625083 4587471 1617746 33.74 55.77 56.29 118.24 57.58 0.000 0.000 0.000 0.000 0.000 058654 149262 1568494 4511429 1562677 0018454 0027741 0028872 0038798 0028097 0658877 1601362 1681671 4663514 1672815 Source: Own calculation using data form Quality of Life survey, GCRO (2015) Marginal effect dy/dx _predict _predict _predict _predict Microcredit 004432 0062 0031583 -.004888 -.0089023 Race Coloured 019386 0246967 0111771 -.0228525 -.0324073 Race Indian/Asian -.0200803 -.0315779 -.0183917 0190313 0510185 Race White -.0123492 -.0185353 -.0102287 0127133 0283999 Delta-method Std Err z P>z [95% Conf Interval] 0027893 0039 0019851 0030762 0055971 1.59 1.59 1.59 -1.59 -1.59 0.112 0.112 0.112 0.112 0.112 -.0010349 -.0014439 -.0007324 -.0109173 -.0198723 0098989 0138438 007049 0011413 0020678 006605 0076793 0030724 0080132 0093297 2.94 3.22 3.64 -2.85 -3.47 0.003 0.001 0.000 0.004 0.001 0064404 0096456 0051554 -.0385582 -.0506931 0323316 0397478 0171988 -.0071468 -.0141215 0067154 0118625 0077865 0047774 0216065 -2.99 -2.66 -2.36 3.98 2.36 0.003 0.008 0.018 0.000 0.018 -.0332422 -.054828 -.0336529 0096679 0086706 -.0069183 -.0083278 -.0031304 0283948 0933664 0038616 0061907 0036596 0036431 0100694 -3.20 -2.99 -2.80 3.49 2.82 0.001 0.003 0.005 0.000 0.005 -.0199179 -.0306688 -.0174014 0055729 0086643 -.0047806 -.0064017 -.0030559 0198536 0481355 61 _predict _predict _predict _predict _predict _predict _predict _predict Age_sq -.0000175 -.0000244 -.0000125 0000193 0000351 Age 0010123 0014161 0007214 -.0011165 -.0020334 Education years -.0008227 -.0011509 -.0005863 0009074 0016526 Health -.0227599 -.0318388 -.0162189 0251016 045716 Gender 0127621 0178529 0090944 -.0140752 -.0256343 Employment -.0039299 -.0054976 -.0028005 0043343 0078938 Marital status -.0045536 -.00637 -.0032449 0050221 0091464 Dwelling -.0430348 3.62e-06 5.04e-06 2.57e-06 3.99e-06 7.23e-06 -4.83 -4.85 -4.84 4.83 4.86 0.000 0.000 0.000 0.000 0.000 -.0000246 -.0000343 -.0000175 0000115 0000209 -.0000104 -.0000146 -7.41e-06 0000271 0000493 0003342 0004664 0002379 0003683 0006697 3.03 3.04 3.03 -3.03 -3.04 0.002 0.002 0.002 0.002 0.002 0003572 0005019 0002552 -.0018384 -.003346 0016674 0023304 0011876 -.0003945 -.0007207 0003491 0004886 0002487 0003854 0007007 -2.36 -2.36 -2.36 2.35 2.36 0.018 0.018 0.018 0.019 0.018 -.001507 -.0021085 -.0010738 000152 0002792 -.0001385 -.0001934 -.0000988 0016628 0030259 0017518 0024235 0012591 0019147 0034742 -12.99 -13.14 -12.88 13.11 13.16 0.000 0.000 0.000 0.000 0.000 -.0261933 -.0365887 -.0186867 0213487 0389067 -.0193265 -.0270888 -.0137511 0288544 0525252 0024794 0034375 0017559 0027263 0049364 5.15 5.19 5.18 -5.16 -5.19 0.000 0.000 0.000 0.000 0.000 0079026 0111155 0056529 -.0194187 -.0353095 0176216 0245904 0125359 -.0087317 -.0159591 0022153 003101 0015789 002445 0044491 -1.77 -1.77 -1.77 1.77 1.77 0.076 0.076 0.076 0.076 0.076 -.0082719 -.0115755 -.005895 -.0004579 -.0008264 000412 0005803 000294 0091264 0166139 0022554 0031499 0016041 0024846 0045234 -2.02 -2.02 -2.02 2.02 2.02 0.043 0.043 0.043 0.043 0.043 -.0089741 -.0125436 -.006389 0001524 0002807 -.000133 -.0001964 -.0001009 0098918 0180122 0028725 -14.98 0.000 -.0486648 -.0374047 62 _predict _predict _predict _Predict -.0602013 -.0306669 0474624 0864405 Crime 0121236 0169596 0086393 -.0133709 -.0243516 Household size 0001505 0002105 0001072 -.000166 -.0003023 Money satisfaction -.0182677 -.0255547 -.0130177 0201472 0366929 Mic*gender -.0080929 -.0113211 -.0057671 0089255 0162555 0037913 0019921 0030733 0054825 -15.88 -15.39 15.44 15.77 0.000 0.000 0.000 0.000 -.0676321 -.0345714 0414388 075695 -.0527705 -.0267624 0534861 097186 0008965 0012 0006255 0009834 0017126 13.52 14.13 13.81 -13.60 -14.22 0.000 0.000 0.000 0.000 0.000 0103665 0146077 0074133 -.0152983 -.0277083 0138806 0193115 0098654 -.0114435 -.020995 0003895 0005447 0002774 0004295 0007821 0.39 0.39 0.39 -0.39 -0.39 0.699 0.699 0.699 0.699 0.699 -.0006129 -.000857 -.0004365 -.0010079 -.0018351 0009139 0012781 000651 0006759 0012306 0010422 0013288 0006554 001143 0018285 -17.53 -19.23 -19.86 17.63 20.07 0.000 0.000 0.000 0.000 0.000 -.0203104 -.0281591 -.0143022 017907 0331091 -.0162251 -.0229502 -.0117332 0223874 0402766 0040409 0056398 0028723 0044539 0080966 -2.00 -2.01 -2.01 2.00 2.01 0.045 0.045 0.045 0.045 0.045 -.0160129 -.0223749 -.0113967 0001961 0003864 -.0001729 -.0002673 -.0001374 017655 0321247 Source: Own calculation using data form Quality of Life survey, GCRO (2015) Note: 1=Very dissatisfied,2=dissatisfied,3=Neutral,4=Satisfied,5=Very satisfied A1.2 IV Regression Instrumental variables (2SLS) Subjective well-being Coefficient Std Err Microcredit -17.07644 Number of regression obs Wald chi2(15) Prob > chi2 R-squared Root MSE z 3.339391 -5.11 = = = = = 16.306 59.82 0.0000 8.0041 P>z [95% Conf Interval] 0.000 -23.62153 -10.53135 63 Race Coloured Indian/Asian White Age_sq Age Education years Health Gender Employment Marital status Dwelling Crime Household size Money satisfaction _cons -.3482913 2993905 -.1081182 -.0034605 3452688 2878577 -.0684832 -.6630925 2.393925 4147832 1.739761 -.0821652 1107389 -.2631499 -2.477394 3599427 6110516 3152562 0007429 0724564 0593966 1134019 1718317 4822444 1626973 3127608 0513906 0332256 1006267 1.170737 -0.97 0.49 -0.34 -4.66 4.77 4.85 -0.60 -3.86 4.96 2.55 5.56 -1.60 3.33 -2.62 -2.12 0.333 0.624 0.732 0.000 0.000 0.000 0.546 0.000 0.000 0.011 0.000 0.110 0.001 0.009 0.034 -1.053766 -.8982487 -.7260091 -.0049166 2032569 1714426 -.2907468 -.9998764 1.448744 0959023 1.126761 -.1828889 0456178 -.4603746 -4.771996 3571834 1.49703 5097726 -.0020044 4872807 4042728 1537803 -.3263086 3.339107 733664 2.352761 0185585 1758599 -.0659251 -.1827928 Source: Own calculation using data from Quality of Life survey, GCRO (2015) Notes: Instrumented variable is microcredit; instruments are living standards and neighbourhood conditions APPENDIX B: DIAGNOSTIC TEST B1.1 Model specification Ramsey RESET test using powers of the fitted value of subject well -being F(3, 16306) = 2.39 Prob > F 0.0666 = Source: Own calculation using data form Quality of Life survey, GCRO (2015) Note: The null hypothesis in this test is that the model has no omitted variables Specification errors can occur due to omitted variables, including an irrelevant explanatory variable and due to incorrect functional form The omission of important control variables leads to biased estimates whereas an inclusion of irrelevant variables violates the BLUE condition (Gujarati & Porter, 2009) We used a Ramsey RESET specification test to test for model specification errors The null hypothesis could not be rejected suggesting that the model specified correctly 64 B1.2 Over identification test Tests of overidentifying restrictions: Sargan (score) chi2(1) = Basmann chi2(1) = 40.2598 (p = 40.3174 (p = 0.0000) 0.0000) Source: Own calculation using data form Quality of Life survey, GCRO (2015) B1.3 Endogeneity test Tests of endogeneity Ho: variables are exogenous Durbin (score) chi2(1) Wu-Hausman F(1,16289) = 1489.68 (p = 0.0000) = 1637.74 (p = 0.0000) Source: Own calculation using data form Quality of Life survey, GCRO (2015) 65 ... to the subjective well-being of the poor, meaning that the subjective well-being of the poor in Gauteng does not improve though access to microloans This finding contravenes the notion of microloans. . .The effect of microloans on the subjective well-being of the poor in Gauteng by MMAPHEFO CHRISTINAH LEGODI A dissertation submitted in fulfilment for the degree of M in Commerce in Development... microloans and the well-being or SWB of the poor in South Africa Therefore this minor dissertation will analyse whether there is a relationship between microloans and the SWB of the poor in Gauteng