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Livelihood Diversification And Its Effect On Household Poverty In Eastern Cape Province, South Africa

Author

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  • Megbowon Ebenezer
  • Mushunje Abbyssinia

    (University of Fort Hare, South Africa)

Abstract

The recently adopted 2030 SDGs shows the commitment of government of countries to reducing all forms of poverty among its citizens. Livelihoods and livelihood diversification have been identified as a tool in fighting poverty. However, relevance of livelihood diversification is an environment with robust social security programme like South Africa is unknown. The study utilized information obtained from the annual General Household Survey of South Africa carried out in 2014. Information which include demographic characteristics of households and individuals, education, health, access to public assets, ownership of private assets, household welfare, and household livelihoods among others were obtained using a structured questionnaire. A total number of 3033 households sampled from the province using a multi-stage design with probability proportionate to size was used in the study. Data were analysed using a modified Multidimensional Poverty Index which is the most recent approach to poverty assessment, descriptive statistics and Tobit regression model. The result of descriptive statistics shows that households in the province are not diversified (diversification is proxy by having other income sources), only 5.41 percent of the households have more than one sources of income. About 53 percent of diversified households are located in the urban area of the province. The descriptive statistics result also show that majority of households who are considered poor or severely poor have heads with low educational attainment and they are located in the rural area of the province. The result of Tobit regression shows that livelihood diversification is not significant in influencing household poverty in the Province. Other socioeconomic characteristics significant in influencing poverty are characteristics of head which include gender, education and employment status, access to electricity, engagement in agriculture, total income, asset score and geographical location. This study suggest among others things the need for the provincial government to initiate policies that will stimulate household economic investment, like further linking of government transfers to household investment grant. Also, there is a need for the provincial government to strengthen policies that promote affordable and accessible education, access to electricity for the poor, asset accumulation, engagement in home stead agriculture, and intensification of poverty reduction programmes in the rural areas.

Suggested Citation

  • Megbowon Ebenezer & Mushunje Abbyssinia, 2018. "Livelihood Diversification And Its Effect On Household Poverty In Eastern Cape Province, South Africa," Journal of Developing Areas, Tennessee State University, College of Business, vol. 52(1), pages 235-249, January-M.
  • Handle: RePEc:jda:journl:vol.52:year:2018:issue1:pp:235-249
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    Citations

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    Cited by:

    1. Shinice Jackson & Derek Yu, 2023. "Re-examining the Multidimensional Poverty Index of South Africa," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 166(1), pages 1-25, February.
    2. Vicky Pule & Angela Mathee & Paula Melariri & Thandi Kapwata & Nada Abdelatif & Yusentha Balakrishna & Zamantimande Kunene & Mirriam Mogotsi & Bianca Wernecke & Caradee Yael Wright, 2021. "Classroom Temperature and Learner Absenteeism in Public Primary Schools in the Eastern Cape, South Africa," IJERPH, MDPI, vol. 18(20), pages 1-17, October.

    More about this item

    Keywords

    Livelihood Diversification; Multidimensional Poverty Index; Eastern Cape Province;
    All these keywords.

    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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