Economic contribution of backyard gardens in alleviating poverty in the rural communities of Bojanala Platinum district municipality, in North West Province, South Africa

Abstract

Backyard gardens has been identified as one of the possible solutions to some of the issues surrounding poverty alleviation in the Bojanala Platinum District Municipality. The main objective of the study was to determine the economic contribution of backyard gardens in alleviation of poverty in rural communities of Bojanala Platinum District Municipality in the North West Province, South Africa. The study used purposive sampling for data collection from the study respondents which enabled the researcher to select a sample with experience and knowledge about the study variables. The questionnaire used as data collection instrument was pretested, validated and subjected to reliability test to improve the efficiency of the use of the questionnaire. The collected data was sorted, coded and analysed using Statistical Package for Social Science (SPSS) Version 23.0 software. Frequency count and percentage were used to summarize the data into tables and graphs. The linear multiple regression model specification was employed to examine the demographic and socio-economic factors (predictors) that influence the generation of income from backyard gardens. Multinomial logistics regression model was also used to determine factors influencing the respondents’ objectives for the Backyard gardens, while the logit regression model was used to analyse determinants of the proportion of backyard land used for backyard farming by respondents/growers. The findings of the study are that: more females (68.2%) were involved in the study than males (31.8%); youth involved in the study were 27.7%; the majority (60.4%) of respondents are in the age group of 41-70 years of age; majority (69.5%) of respondents had matric education, 20.9% had tertiary education, and 3.6% had below matric education whilst 5.9% had no formal education; most of respondents are unemployed (86.6%); 32.2% of respondents are dependent on pension as their source of income, 12.3% depend on grant, 15% depend on monthly salaries, 0.5% depend on investments, 2.3% depend on remittance, and 18.6% depend on piece jobs, whilst 19.1% reported other source of income; majority (99%) of respondents reported that backyard garden contribute a significant proportion to both household income and food security, whilst 1.0% did not agree; 40% of the respondents could not manage to farm the whole garden area, while 60% were able to farm the entire garden area; the majority (70.9%) of respondents provide own solutions to their backyard garden challenges; majority (53.7%) of respondents reported that extension officers never visited their gardens, whilst 46.3% had extension visits on weekly, monthly and quarterly bases; 23.2% of the respondents created permanent employment while 34.1% of them created seasonal employment. The results of the OLS regression analysis showed that gender of respondents, with formal employment, ownership of a farm besides the Backyard garden (BYG) by respondent, farmers’ years of experience in farming and annual income from the sale of livestock by respondent had positive and statistically significant influence on the annual income from Backyard garden with all other factors held constant. The results of the multinomial regression analyses show that a unit change in number of years involved in backyard gardening (YRSBG) does not significantly change the odds of being classified in the 4th category of the outcome variable (Produce to help the needy, the poor, to feed the orphans, and for home based-cares around their communities = 4) relative to the first or second or third categories of the outcome variable, while controlling for the influence of the others. On the other hand a unit change in being employed (EMPLO) and involved in non-farm activities (NFA) do significantly change the odds of being classified in the 4th category of the outcome variable relative to the second or third categories of the outcome variable, while controlling the influence of the others. The Logit coefficient estimate associated with Age, Income per month from BYG, Engage in non-farm activities, Years of experience in gardening, Proportion of produce consumed, having a business plan, Own a farm besides BYG and to lease your backyard have statistically significant impact on respondents area of cultivation for BYG with other factors held constant. Policies to improve BYG in the district should be informed by the aforementioned variables from the results of the inferential analyses.