Assessment of Welfare Shocks and Food Insecurity in Ephraim Mogale and Greater Tubatse Municipality Of Sekhukhune Districts, Limpopo Province, South Africa

Agboola, Peter Temitope; Oyekale, Abayomi Samuel; Samuel, Oduniyi Oluwaseun

doi:10.9790/2380-1004022332

Cited by 9 publications

(8 citation statements)

References 3 publications

(3 reference statements)

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“…This sector is the cardinal cohesive source of support and stability for the socioeconomic state of the country; hence, it is a pertinent channel for the subsistence and maintenance of most non-metropolitan towns and rural communities, which consequently accounts for 27% of the consumer's food on a weight basis [1]. However, harsh and unpredictable weather conditions have led to a significant loss of livestock in the North West, and a similar situation was reported in the Limpopo province, with different levels of shocks such as drought and high level of livestock disease [2]. This situation has consequently worsened the already precarious food security situation in the region, an experience which has also been noted in most developing countries, since climate change is a recognised global phenomenon; and developing countries are obviously more susceptible to the damaging effects due to poor adaptive capacity [3].…”

Section: Introductionmentioning

confidence: 92%

“…Willingness to pay for a product or service is expressed as the amount of money that a person is willing to pay for buying a product or service from his/her income with risk preferences, while simultaneously, keeping his/her utility constant. This can be expressed mathematically: V (y-WTP, p, q 1 ; Z) = V (y, p, q 0 ; Z) (2) where V represents the indirect utility function, y signifies income, p is a signification for the vector of prices faced by the individual, and q0 and q1 are connotations for the alternative levels of the good or quality indexes (with q1 > q0, signifying that q1 refers to better environmental quality). Furthermore, WTP values are calculated as follows:…”

Section: Willingness To Pay (Wtp)mentioning

confidence: 99%

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Farmers’ Willingness to Pay for Index-Based Livestock Insurance in the North West of South Africa

Oduniyi

Antwi

Tekana

2020

Climate

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Rural livelihoods in most developing countries are threatened by climate-related risks such as drought, flood, heat waves, storms, and so on. Although farmers have adopted several adaptation strategies, they have proven less effective than hoped. Hence, index-based livestock insurance, an innovation that significantly assists farmers to acclimatise to climate-related risks, has been proposed; and its adaptability has attracted a notable increase in other African countries. However, the success of its adoption is dependent on the inclination of the farmers to pay for the service. Accordingly, this study investigates their willingness to pay for index-based livestock insurance and its determinants, and the factors influencing the total livestock units to be insured in the North West province of South Africa. Cross-sectional data were obtained from 277 cattle farmers, drawn randomly from the study area. The contingent valuation method was applied to determine the farmers’ willingness to pay; and only 10.8% were willing to pay. Simultaneously, the Heckit sample selection model was used to analyse the data to identify the factors responsible for farmers’ willingness to pay and total livestock units to insure. The findings revealed that farmer’s experience, age, education, marital status, awareness of insurance and household dependents were statistically significant, and influenced the maximum price R600 ($42, max willingness to pay, WTP) of those who accepted index-based livestock insurance. However, by implication, the study concluded that to adopt index-based livestock insurance in the study area among the livestock farmers, there should be policies to cater for the aforementioned factors.

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Section: Introductionmentioning

confidence: 92%

Section: Willingness To Pay (Wtp)mentioning

confidence: 99%

Farmers’ Willingness to Pay for Index-Based Livestock Insurance in the North West of South Africa

Oduniyi

Antwi

Tekana

2020

Climate

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“…Head count index, food insecurity gap and severity of food insecurity were the three FGT measures used (Table 6). The food insecurity parameters used were P 0 (food insecurity incidence (headcount)), P 1 (depth food insecurity) and P 2 (severity food insecurity) [77,[84][85][86]. The results showed that the head count ratio or incidence of food insecurity within the households before and during COVID-19 were 0.47 and 0.78, respectively.…”

Section: Food Security Status Of the Respondentsmentioning

confidence: 99%

“…Furthermore, almost 50.00% of the respondents went without eating for a day, as well as having no enough food to feed the family during COVID-19, while less than 20.00% experienced this before the pandemic. The discrepancy may be due to the various disruptions caused by the pandemic conditions, such as income shocks, which limited the disposable amount spent on food, as well as disruptions in food supply chains, resulting in possible food shortages and spikes in food prices [1,33,73,[84][85][86][87]. The result showed that rural households have become more food insecure, as the disruptions due to the pandemic have affected the food supply chains, food prices and access to food.…”

Section: Implications Of the Covid-19 On The Perceived Food Insecurit...mentioning

confidence: 99%

Rising Food Prices and Farming Households Food Insecurity during the COVID-19 Pandemic: Policy Implications from SouthWest Nigeria

et al. 2022

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The government’s lockdown and restriction measures on the COVID-19 pandemic adversely altered livelihoods, commodity/food prices as well as food security status in Nigeria, especially for rural farming households. A multistage sampling technique was used to collect data from 480 rural farming households across three selected states of the SouthWest geopolitical zone of Nigeria. This research entailed rapid evaluation of the determining factors of rising food expenditure, implications for food security as well as households’ coping strategies during the COVID-19 pandemic. A structured questionnaire was used to obtain data that were analyzed using the following descriptive and inferential statistics: double-logarithmic analysis, Foster–Greer–Thorbecke (FGT) and probit regression analysis. The results showed that 60% of respondents were married, mean years spent in school was 17, mean age was 49 years, household size was 7 people and monthly income less than $200. The FGT model results for head count ratio showed that 78% of households were food insecure. The depth of food insecurity and severity before COVID-19 were 18.4% and 9.9% respectively, and 27.1% and 13.0% during the pandemic. The double-logarithmic regression revealed that household income, size, age and occupation significantly influenced the household’s food expenditure. Probit regression showed that households’ income, size, amount spent on food, and the household’s head, gender and educational level influenced its food security status. The research concluded that food security was indeed influenced by the COVID-19 pandemic among rural farming households in Nigeria. Intervention policies are needed to promote and enable sustainable livelihoods to eradicate hunger and food insecurity due to high food prices and high household sizes in relation to their low average income to enable rural farming households to economically recover and have the capacity to sustain themselves against future shocks.

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“…The probable involvement of agriculture in enlarging a country's economy has been a major issue for development economists. Several researchers have proved that the development of the entire country depends on the progress of the farming sector, which perhaps will be a conduit for rural earnings with the stipulation of property in support of conversion keen on a developed financial system (Agboola, Oyekale, & Oduniyi, 2017;Awokuse, 2009;Oduniyi, 2018). Oji-Okoro (2011) assumed that farming provides the trade and industry sector with expansion and enlargement through five inter-segmental connections.…”

Section: Introductionmentioning

confidence: 99%

Performance of Agricultural Export Products on Economic Growth in Nigeria

Amao

Antwi

Oduniyi³

et al. 2021

5005

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This research sought to explore the performance of agricultural export products on economic growth in Nigeria from 1960 to 2016. Secondary data from the National Bureau of Statistics, the Central Bank of Nigeria’s Annual Statistical Bulleting, the World Bank, and World Development Indicators were used. The Generalized Method of Moments (GMM) model was explored in this study. The findings of the study show that food and live animals, beverages, and tobacco were found to be negative but significant to agricultural exports, while agricultural exports (total) and crude materials, inedible except fats, were found to be negative and insignificant to economic growth. Animal and vegetable oils and fats were found to be positive but insignificant to economic growth. Based on the following findings, it is recommended that policies aimed at increasing the productivity and quality of agricultural products, especially those from crops, should be implemented. There is also a need to devote more resources to the production of non-export goods to increase exports. Above all, more credit should be extended to the agricultural sector with a low or zero interest rate, which may lead to a higher rate of economic growth in Nigeria.

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Assessment of Welfare Shocks and Food Insecurity in Ephraim Mogale and Greater Tubatse Municipality Of Sekhukhune Districts, Limpopo Province, South Africa

Cited by 9 publications

References 3 publications

Farmers’ Willingness to Pay for Index-Based Livestock Insurance in the North West of South Africa

Farmers’ Willingness to Pay for Index-Based Livestock Insurance in the North West of South Africa

Rising Food Prices and Farming Households Food Insecurity during the COVID-19 Pandemic: Policy Implications from SouthWest Nigeria

Performance of Agricultural Export Products on Economic Growth in Nigeria

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