DETERMINANTS OF SAVINGS IN URBAN AND RURAL HOUSEHOLDS: CASE OF SOUTH AFRICA
DOI:
https://doi.org/10.15407/dse2021.04.151Keywords:
fixed-effects, random-effects, endogeneity, urban areas, rural areas, NIDSAbstract
Savings have been described as a significant fi nancial and economic matter and represent an essential driving force of economic growth and development. Despite this, many studies investigating the determinants of savings in South Africa have looked predominantly at the drivers of savings only at a national level, without focusing on urban and rural differences. This is critical as these localities are structurally different, with different characteristics. It is, therefore, likely that the determinants of savings in these unique geographical localities would differ, given the negative impact of past policies of marginalisation. The purpose of this paper is to examine the urban-rural disparities in savings for South African households. We used data sourced from the five waves of the National Income Dynamics Study (NIDS) observed from 2008-2017. The novelty of this study is in its application of a novel two-stage least square estimation technique which addresses possible endogeneity problems which might have plagued previous studies in this field. It was concluded from the research that the determinants of savings are different across samples (urban and rural). We found that having access to land is an important predictor of savings in rural areas where the poor live (positive and significant), but the coefficient is not significant in the urban sample. Although there was a positive correlation between income and savings across samples, but the income impact on savings is higher in absolute values for households residing in rural areas, compared to household living in urban areas. We also found that, despite the coefficient of employment being similar in the direction of the impact (positive and significant) across the samples, the magnitude of the coefficient was stronger in the rural sample. Based on the higher magnitude of the coefficient, we found that household size has more effect in urban than rural areas. The study recommends that government should design and implement policies that foster job creation, even low-skilled jobs, which will generate more income and reduce unemployment.
References
- Abu, N., Karim, M. Z., & Aziz, M. A. (2013). Low savings rates in the Economic Community of West African States (ECOWAS): The role of the political instability-income interaction. South-East European Journal of Economics and Business, 8 (2): 53-63.
- Adewuyi, A. O., Arawomo, D. F., & Bankole, A. S. (2010). What determines savings in the Economic Community of West Africa (ECOWAS)? West African Journal of Monetary and Economic Integration, 2 (2): 71-99.
- Ando, A., & Modigliani, F. (1963). The life cycle hypothesis of saving: Aggregate implications and tests. American Economic Review, 53: 55-84.
- African National Congress (ANC). (1994). The Reconstruction and Development Programme: A Policy Framework. Johannesburg: Umnyango Publications.
- Angrist, J., & Pischke, S. (2009). Mostly harmless econometrics. An empiricist’s companion. Princeton: Princetown University Press.
- Ashley, C., & Maxwell, S. (2001). Rethinking rural development. Development Policy Review, 19 (4), 395-425.
- Balde, Y. (2011). The impact of remittances and foreign aid on savings/investment in sub-Saharan Africa. African Development Review, 23: 247-262.
- Baltagi, B. (2008). Econometric analysis of panel data. 4th edition. Chichester, UK: John Riley. 9. Carroll, C., & Summers, L. (1991). Consumption growth parallels income growth: Some new evidence. In B. D. Bernheim and J. B. Shoven (Eds). National Saving and Economic Performance. Chicago University Press for NBER. Chicago, 305-43.
- Cragg, J. D., & Donald, S. G. (1993). Testing identifiability and specification in instrumental variables models. Economic Theory, 9, 222-240.
- Chipote, P., & Tsegaye, A. (2014). Determinants of household savings in South Africa: An econometric approach (1990-2011). Mediterranean Journal of Social Sciences, 5 (15): 183-190.
- De Vos, C., Obokoh, L. O., & Abiola, B. A. (2020). Determinants of savings among non-Ricardian households in South Africa. International Journal of Social Economics, 47 (11): 1329-1343.
- Friedman, M. (1957). A theory of the consumption function. Princeton: Princeton University Press.
- Hausman, J. (1978). Specification tests in econometrics. Econometrica, 46: 1251-1271.
- Horioka, C. Y., & Wan, J. (2007). The determinants of household saving in China: a dynamic panel analysis of provincial data. Journal of Money, Credit and Banking, 39 (8): 2077-2096.
- Kudaisi, V. B. (2013). Savings and its determinants in West African countries. Journal of Economics and Sustainable Development, 4 (18): 238-256.
- Loayza, N., Hebbel, K., & Serven, L. (1999). Saving in developing countries: An overview. The World Bank Economic Review, 14 (3): 393-414.
- Mahlo, N. (2011). Determinants of household savings in South Africa. The University of Johannesburg.
- May, J., & Norton, A. (1997). A difficult life: The perceptions and experience of poverty in South Africa. Social Indicators Research, 41: 95-118.
- Mbuthia, A. (2011). Households’ savings decision in Kenya. Unpublished PhD thesis, Reg No K96/10904/07.
- Modigliani, F., & Brumberg, A. (1954). Test of the life cycle hypothesis of saving. Bulletin of the Oxford Institute of Statistics, 19: 99-124.
- Mogale, I. P., Mukuddem-Petersen, J., Petersen, M. A., & Meniago, C. (2013). Household saving in South Africa: An econometric analysis. Mediterranean Journal of Social Sciences, 4 (13): 519-530.
- Nigus, H. (2015). Determinants of household saving in Gedeo Zone, Southern Ethiopia. Journal of Economics and Sustainable Development, 6 ( 7): 34-49.
- Posel, D. (2016). Intra-households transfers in South Africa. Prevalence’s, patterns and poverty. Cape Town, SALDRU, University of Cape Town. SALDRU working paper 180/NIDS Discussion paper 2016/7.
- Rehman, H., Faridi, M., & Bashir, F. (2010). Household saving behaviour in Pakistan: a case of Multan District. Pakistan Journal of Social Sciences, 30 (1): 17-29.
- SALDRU (2009). National Income Dynamics Study Wave 1: User document. Cape Town: Southern Africa Labour and Development Research Unit, University of Cape Town.
- SALDRU (2016). National Income Dynamics Study 2014-2015, Wave 4 [dataset]. Version 1.0. Cape Town: Southern Africa Labour and Development Research Unit [producer], Cape Town: DataFirst [distributor].
- South African Reserve Bank (SARB). (2012). Quarterly Bulletin, June 2012. No. 264.
- Simleit, C., Keeton, G., & Botha, F. (2011). The determinants of household savings in South Africa. Studies in Economics and Econometrics, 35 (3): 1-20.
- Von Fintel, D., & Fourie, J. (2019. The great divergence in South Africa: Population and wealth dynamics over two centuries. Journal of Comparative Economics, Elsevier, 47 (4): 759-773.
- Wakabayashi, M. & Mackellar, L. (1999). Demographic trends and household saving in China. Interim Report IR-99-057. International Institute for Applied System Analysis, Austria.
- Zwane, T. (2020). The causal effect of education on earnings in urban and rural South Africa: A further update. Demography and Social Economy, 1 (39), 79-94. https://doi.org/10.15407/dse2020.01.079
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