Agricultural Finance and Economic Growth: Evidence From Nigeria

Okunlola, Funso Abiodun; Osuma, Godswill Osagie; Omankhanlen, Ehimare Alexander

doi:10.3846/btp.2019.43

Cited by 9 publications

(12 citation statements)

References 10 publications

(16 reference statements)

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“…Majority of the respondents 39.13% belonged to the age group of between (31-40) years, 30% of the respondents were aged between (41-50) years, 20% haviing less than 30 years while 10.87% were above 50 years (table 3). Similar results were revealed by a study conducted by [18] and [16]. Based on their findings, majority of rural farmers were in the middle class age hence considered as active working age category.…”

Section: Analytical Techniquessupporting

confidence: 88%

Determinants of Credit Access Among Smallholder Dairy Farmers in Kinangop Sub-County, Kenya

Ongwech¹,

Gor²,

Otiende³

2020

epra

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Dairy farming plays a major role in the Kenyan agricultural sector as it is dominated by smallholder farmers who contribute approximately 80 per cent of the total milk production. In Kinangop Sub County, there are many credit service providers however, not all smallholder dairy farmers have benefited from such services, instead smallholder dairy farmers have continued to experience challenges such as limited access to financial services. This study therefore analyzed the determinants of credit access among smallholder dairy farmers in Kinangop Sub-County using a binary logistic regression model. Following this, the marginal effects of the predictor variables on the likelihood of accessing credit were estimated. A total of 230 respondents were sampled from a population of 35,840 smallholder dairy farmers using both stratified and simple random sampling techniques and both structured and semi structured questionnaires were used to collect data. The study adopted descriptive survey research design. Descriptive analysis revealed that majority: 59.57% of smallholder dairy farmers were males, 69.57% were married and had a mean age of 39.4 years. The average household size was 4 members per household. Formal schooling was also attained by the respondents, majority having an average of about 8 years of schooling. On average farmers had 2 dairy cattle per household, produced 341litres of milk per month and had 11 years of farming. The binary logistic regression analysis and the marginal effect calculation revealed marital status, years of schooling, savings frequency, dairy farming, primary occupation, financial education, association membership and number of dairy cattle as the significant determinants of credit access. The study therefore concluded that there were significant determinants of credit access in the study area and recommended that formulating policies geared towards enhancing educational attainment of farmers would be vital in enhancing credit accessibility to farmers in the study area. There is also need for the Government and other stakeholders to encourage dairy farmers to join farmer based associations and eliminate stringent collateral barriers and bureaucracies that tend to discourage smallholder dairy farmers from accessing and participating in different credit schemes. KEY WORDS: Credit access, Determinants, smallholder dairy farmers, Kinangop Sub-County.

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Section: Analytical Techniquessupporting

confidence: 88%

Determinants of Credit Access Among Smallholder Dairy Farmers in Kinangop Sub-County, Kenya

Ongwech¹,

Gor²,

Otiende³

2020

epra

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“…This result discloses that government investment on agriculture is too inconsequential to guarantee food security at the moment in Nigeria. This result agrees with the findings of Okunlola et al (2019) whose study revealed that agricultural financing in Nigeria has not affected economic growth significantly.…”

Section: Trend Analysissupporting

confidence: 92%

“…In the same manner human capital development or formal education and knowledge of farmers, marital status and extension services were the significant factors that influence the growers' productivity after embracing a maintenance system of cultivation. Okunlola et al (2019) researched on the effect of agricultural financing on economic growth of Nigeria using Autoregressive Distributed Lag (ARDL) technique and data from 1981 to 2017. The study revealed that expenditure on agriculture was statistically insignificant and could not positively influence economic growth.…”

Section: Empirical Literaturementioning

confidence: 99%

Agricultural Financing to Guarantee Food Safety in an Emerging Nation: A Case Study of Nigeria

Omodero

Ehikioya

2022

Business: Theory and Practice

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Investment in agriculture is very crucial in the present situation of Nigeria. The effort to overcome food insecurity can only be efficacious if steps in the right direction will be taken. At this juncture in the Nigerian economic history, the right step to take is to adequately finance agriculture in order to ensure sufficient food production and safety that will save the future of the country. This study emphasizes on investment in agriculture to guarantee food security in Nigeria. Several other studies focus on the numerous challenges food production in Nigeria suffer, however, it is important to come to a conclusion that agriculture requires huge financial investment to thrive. This study examines the impact of agricultural financing and output on food production using data from 2007−2019. The regression result reveals that agricultural output is significant and positive in affecting food production and safety but agricultural financing is immaterial in guaranteeing sufficient food production in the country. This result gives evidence that investment in the agricultural sector will be the solution to food insecurity in Nigeria. The government is by this study encouraged to increase the budget on agriculture in order to boost food supply and safety in the country.

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“…The stepwise regression method was proposed to test the interactions between variables, highlighting this regression analysis method [91]. The impact of agricultural output on economic growth was explored using the dynamics of the different technical approaches that stepwise regression can provide [92]. Additionally, the interaction effect between economic growth and environmental pollution in Wuhan in China was studied using the stepwise regression method by selecting critical indicators of economic growth and environmental pollution [93].…”

Section: Emprical Methodsmentioning

confidence: 99%

Analysis of Potential Factors Influencing China’s Regional Sustainable Economic Growth

Sun

Agyeman

et al. 2021

Applied Sciences

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The purpose of this article is to screen out the most important factors affecting China’s economic growth. Based on a literature review and relevant financial theoretical knowledge, China’s economic growth factors are selected from international and domestic aspects. Four methods, including least squares estimation, stepwise regression, ridge regression estimation, and Lasso regression, are used to screen and optimize 12 variables and analyze the degrees of influence empirically. The study finds that consumption levels and the development of the tertiary industry play significant roles in promoting China’s economic growth. Additionally, financial development and industrialization promote China’s economic growth, although in a gradual manner.

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Agricultural Finance and Economic Growth: Evidence From Nigeria

Cited by 9 publications

References 10 publications

Determinants of Credit Access Among Smallholder Dairy Farmers in Kinangop Sub-County, Kenya

Determinants of Credit Access Among Smallholder Dairy Farmers in Kinangop Sub-County, Kenya

Agricultural Financing to Guarantee Food Safety in an Emerging Nation: A Case Study of Nigeria

Analysis of Potential Factors Influencing China’s Regional Sustainable Economic Growth

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