Measuring the Impact of Credit on the Welfare of Rural Farmers in Akwa Ibom State, Nigeria

Majority of the poor in Nigeria lack access to basic financial services which are a sine qua non for improved livelihood. In most cases, they are often excluded from formal opportunities for financial services leaving them only with informal alternatives. But credit availability to the poor in the rural areas is critical to reducing poverty. An empirical study was conducted to measure the impact of agricultural credit of the welfare of farmers. Multistage sampling procedure was employed to select the farmers. Questionnaires were employed to collect data. Multiple regression analysis and chow test were for analyses. Results revealed that the mean age and years of education of farmers were 12 and 31 years respectively. Findings also showed that the most critical factors impacting the welfare of farmers were marital status, marriage type, educational level, farm size, off-farm income, labour, type of enterprise, labour and access to modern farming inputs. Policies to encourage human capital development of rural farmers would be a rational decision. 
 


Introduction
Many low-income nations neglect adequate social security laws and also lead to a vicious spiral of suffering, amid overall economic prosperity, which does not meet essential human needs. The poverty faced by the third-world countries like Nigeria was enormous and ongoing, according to Isiaka (2015). Therefore, it is important to encourage poor people to support poor development. Chronic suffering will continue, and citizens will either be removed from prosperity or add to the development of income without themselves being gained from it, without empowerment. Diagne and Zeller (2001) observed that, due to their alleged failures to satisfy the loan terms, the disadvantaged have for many years been seen as poor credit and as a consequence excluded from credit and savings facilities. Poverty does not constitute a particular cause or circumstance. It is a collection of poverty, including a lack of financial resources, lack of goods access and a lack of speech. IMF (2019) announced that investing in financial inclusion is one route to support women and the vulnerable harness their ability to control their own economic futures. Awotide et al., 2015 suggested that increasing production by access to credit is a quick way to improve farmers' welfare. With loans paid to farmers through the government credit programme, it is evident that the poor will use loans with increasing food and incomes to boost their health. While the importance of credit in growing agricultural production and enhancing well-being has been reported by Siddiqi et al., (2004), Saboor et al., (2009)  agricultural credit policies and programs which will reduce the vulnerability of farmers. This research was also carried out to assess the effect of credit on farmers' welfare.

Study Area
The thesis took place in the state of Akwa Ibom, Nigeria. It ranges from 4°33' to 4°53' north latitude and 7°25' to 8°25' east latitude. In the tropical climate, the state is characterized by the overwhelming green features of plants, shrubs and oil palm trees. The State borders Abia, Cross River, River States and the Atlantic Ocean to the north, east, west and south respectively. The annual precipitation varies from 2000 to 3000 mm. The region is usually agricultural and is highly dependent on precipitation. The overall state land area is 7.249 km2 and the population density is 680 people per km2. It has six ADP districts, namely:-Uyo, Eket, Ikot Ekpene, Abak, Oron and Etinan, in line with the National Population Council, 2006. It has an estimated population of 3,9 million. The condition consists of two seasons: -in the dry and rainy seasons.

Sampling and Data Collection Procedure
In this analysis, the representative farmers used multi-stage sampling techniques. First, because of the domination of beneficiaries in the integrated farmers system, the Uyo Agricultural Development Program (ADP) region is deliberately chosen (a credit scheme of the state government) Secondly, 10 households each were randomly chosen from IFS recipients and non-recipients. Finally, six farmers were randomly chosen from the Uyo farming area to make up a total of 120 farmers (each one of the beneficiaried and non-beneficiaries). Using questionnaire, primary data were obtained. Multiple regression and chow statistics were used in the computational methods used for this research. The chow F-statistics was computed following Onyenweaku 1997 and Olomola 1998 and have been used in Etim, 2017 Where ∑ 1 2 and K1 are the error sum of square and degree of freedom respectively for the beneficiaries sample, ∑ 2 2 and K2 are the error sum of square and degree of freedom respectively for the non-beneficiaries sample and ∑ 3 2 and K3 are the error sum of square and degree of freedom respectively for the pooled data and; Where ∑ 4 2 and K4 are the error sum of square and degree of freedom respectively for the pooled data with a dummy-variables are as earlier defined.

Result and Discussion
The summary of the socio-economic and farm specific characteristics of the beneficiaries of the integrated farmers scheme is shown in table 1. The minimum and maximum values of the age and the level of educational attainment of the beneficiaries of the integrated farmers' scheme are 23,40 and 6, 18 years respectively. Tables 4.6.1 also show that the maximum value of asset was N17, 000 whereas the largest farm size was 3.50 hectares. The tables above further reveal that the highest among of loan obtained by farmers was N420, 000.

Impact of Integrated Farmers' Scheme on the Welfare Status of Rural Farm Households
The marital status coefficient of the head of households is -0.972. This involves a reduction in the welfare status of married households by -0.972. Therefore, the benefits to single persons of 9,428 as opposed to 10,400. The explanation for this is that married couples are much bigger than smaller households and thus therefore more prone to reduce their welfare status.
The welfare standard is influenced by both polygamous or monogamous marriages. In single families, the marriage form coefficient is -0.205 indicating that in polygamous households, the welfare standard of the spouse is raised by 0.205 to 10.605, compared to 10.400. This is true since single-member houses are larger than polygamous homes, which allow the welfare level of those single-member families to increase.
The academic status coefficient is 0.121. Which means that welfare in households with a structured education of heads is increased by 0.121. The heads of households have 10.400 welfare without formal schooling. This can be due to a stronger propensity to follow better farming methods for household leaders with formal schooling than uneducated ones. This enhances agricultural production, wages and the well-being of skilled people.
The retrograde factor is 0.197 for the agricultural scale. This results in a 1.97% growth in healthcare in farm sizes in hectares. As yields are closely linked to the cultivated land, a raise in farm yield will result in income rising as poverty levels were decreased.
The multiplier of off-farm income is 0,249, which means that the levels of domestic welfare would be increased by 0,249 for each naira growth in off-farm income. This is because the rise in non-farm income offers an extra stream of family revenue and spending that eventually increases the amount of benefits. This observation is synonymous with Etim's earlier analytical results (2017).
The coefficient of regression for work in farms is 0.229 In other words, an increase in the number of people working on the farm would reduce the welfare standard by 0.229. This is because the rise in family labor, which leads to lower welfare status, is a function of bigger household sizes and greater dependence ratio. Also stated on the relevance of the usage of labor to poverty reduction were the findings by Etim et al.,(2011), Etim and Eedet (2014).
The class of business has a coefficient of 0.337 which mean that for households engaged in two or more agricultural businesses the social wellbeing of households shall be improved by 0.337 to 10.737, compared to 10.400. The explanation is that household managers working in many companies probably have additional sources of household revenue. And if a company fails, household managers involved with two or three companies are less likely than households that only have one company to lose productivity and profits. Etim and Edet (2016) findings affirm the increase in wages and reduced the rate of poverty in rural communities by embarking on multi-agriculous enterprises.
There is a 0.460 multiplier on access to new agricultural inputs. As a result, the health of households with proximity to modern agricultural inputs will rise by 0.460 to 10.860. However, the healthcare standard of households with no connection to modern agricultural inputs is 10,40. This is so since farmers' output and income would probably improve with a resulting decrease in malaise by utilizing modern agricultural inputs.   ***, **,* Significant @ 1%, 5%, and 10% levels respectively with t-values in Parenthesis while + indicate the lead

Conclusion
The study was conducted to measure the impact of agricultural credit scheme on the welfare of farmers. Primary data were obtained from both beneficiaries and non beneficiaries of credit scheme. From the analysis of data using descriptive statistical tools and multiple regression, the mean age of beneficiaries of the scheme was 31 years implying that they were within active and productive population. Results also showed that beneficiary farmers were literate as the mean years of education was 12 years. Findings also revealed that farmers cultivated small holdings of farmland as the average farm size was about 1 hectare. Result of multiple regression analysis revealed that the most critical factors impacting on beneficiaries welfare were education, marital status, off farm income, farm size and access to modern farming inputs.