Investing in Rural Agriculture in the Face of Innovative Financial Services: Does Financial Literacy Matter in Nigeria?

Abstract

The complex nature of formal financial products and services and the frequently associated innovations occasioned by disruptive technologies inform researchers’ calls for studies on financial literacy, particularly in African rural communities. As a response to the calls, this study explores how financial literacy relates to performance, access to credit facilities, and payment preferences among smallholder rural farmers in Nigeria. Further, the rural farmers’ financial literacy level on each of the four dimensions of the Standard and Poor Global Financial Literacy criteria was assessed. A random sample was drawn from the registered rural farmers in the Central Bank of Nigeria’s Anchored Borrower’s Program for the 2022 farming year. Quantitative data were collected from rural farmers using the Standard and Poor Global Financial Literacy questionnaire. The proposed hypotheses were tested with partial least squares structural equation modeling (PLS-SEM), while descriptive statistics were used to analyze the data. The outcomes show that financial literacy significantly predicts performance, access to credit facilities, and mode of payment preferences among smallholder rural farmers. Also, the analyses of the four dimensions of financial literacy show that the farmers are more literate in risk diversification and inflation than numeracy and compound interest. It is concluded that financial literacy is cardinal to profitable investments in rural farming, and as such, there is a need for the Nigerian government and financial authorities to embark on financial literacy drive with more emphasis on numeracy and compound interest where the rural farmers are more deficient.

Plain Language Summary

Purpose: This study explored how financial literacy relates to performance, access to credit facilities, and mode payment preferences among smallholder rural farmers in Nigeria. Further, the rural farmers’ financial literacy level on each of the four dimensions of the Standard and Poor Global Financial Literacy criteria was assessed. Methods: A random sample was drawn from the registered rural farmers in the Central Bank of Nigeria Anchored Borrower Program for the 2022 farming year. The proposed hypotheses were tested with partial least squares structural equation modeling (PLS-SEM), while descriptive statistics were used to analyze the data. Conclusion: It is concluded that financial literacy significantly influences performance, access to credit facilities, and mode of payment preferences among smallholder rural farmers in Nigeria. Practical Implications of Findings: The outcomes suggest a need for the Nigerian government and financial authorities to embark on a financial literacy drive with greater emphasis on numeracy and compound interest, where the current study found rural farmers to be more deficient. Also, the current findings on Nigerian rural farmers’ mode of payment preference behavior could guide the government and financial authorities in formulating financial inclusion policies as well as helping payment card companies make strategic decisions to increase the overall performance of the payment system in Nigeria.

Keywords

investment rural farming innovative financial services financial literacy Africa

Introduction

Finance and the requisite financial management skills are needed in all spheres of agricultural activities (Safitri, 2021; Santoso et al., 2020). Financial literacy is an essential requirement for sustainable development, as contained in the 2030 Agenda set by the United Nations in 2015 (Swiecka, Terefenko, Wisniewski, & Xiao, 2021). In the view of Lusardi and Mitchell (2017), financial literacy is individuals’ ability to understand “economic information” and the use of such information to make fruitful financial decisions regarding financial planning, savings, investments, wealth creation, and debt management. Therefore, farmers, as farm entrepreneurs, require financial literacy to effectively manage their farm businesses (Paltasingh & Goyari, 2018; Safitri, 2021). For example, a farmer who intends to apply for a loan from a formal financial institution to increase productivity and performance is expected to understand the terms and conditions of the loan and also possess adequate financial management skills to utilize the loan to avoid running into a debt burden (Twumasi, Jiang, Adhikari, et al., 2022).

Frequent innovations characterize the world of financial products and services (Swiecka, Terefenko, Wisniewski, & Xiao, 2021) in the sense that there is an increasing introduction of innovative and complex payment solutions to the markets through disruptive technologies (Conrad et al., 2020; Filipiak & Walle, 2015; Riaz et al., 2022). As a result, it is argued that research is needed to understand how financial literacy affects individuals amid frequent financial innovations (Swiecka, Terefenko, Wisniewski, & Xiao, 2021). For example, it is pointed out that there is a persistent deficiency in research on financial literacy in both developed and developing countries, which negatively impacts the economy (Goyal & Kumar, 2021; Riaz et al., 2022).

Similarly, studies have pointed out that understanding the mode of payments and the factors that influence the choice of payment methods among groups of people is important for the economy (Swiecka, Terefenko, & Paprotny, 2021; Swiecka, Terefenko, Wisniewski, & Xiao, 2021). Such financial knowledge can guide the government and financial authorities in formulating financial inclusion policy as well as helping payment card companies take strategic decisions and increase the performance of the payment system in Nigeria in general (Imhanrenialena, Obi Anike, Okafor, Ike, & Obiora Okafo, 2021; Swiecka, Terefenko, & Paprotny, 2021).

Regarding the rural areas perspective, it is observed that despite the critical place of financial literacy, particularly in sustaining and improving rural farming, current studies have observed that little is known about financial literacy in the literature, particularly in rural communities in developing countries (Goyal & Kumar, 2021; Maji & Laha, 2022; Riaz et al., 2022; Twumasi, Jiang, Ding, et al., 2022). In the Nigerian context, it is reported that, based on improving financial literacy, one-third of adults who live in Nigerian rural areas are now banked, compared to two-thirds in urban areas (Enhancing Financial Innovation and Access, 2021). However, research is yet to provide insights into how the gradual acceptance of modern financial services by Nigerian rural dwellers is impacting their farm business (Imhanrenialena, Obi Anike, Okafor, & Ike, 2021; Imhanrenialena, Obi Anike, Okafor, Ike, & Obiora Okafo, 2021).

We are therefore motivated to provide insights into this phenomenon because two-thirds of the Nigerian adult population lives in rural areas, providing food for the nation (Central Bank of Nigeria, 2020; Enhancing Financial Innovation and Access, 2021). Therefore, this research has four specific objectives. First, the study aims to provide an understanding of how banked rural farmers’ financial literacy relates to their farm business performance. Second, the research seeks to shed light on the link between financial literacy and rural farmers’ access to credit facilities. The third objective is to demonstrate how the financial literacy level of Nigerian rural farmers influences the mode of payment preferences among them amid frequent innovative technology-driven payment systems. The fourth goal is to uncover how Nigerian rural farmers are performing on the four dimensions of financial literacy, namely risk diversification, inflation, numeracy, and compound interest.

To achieve these objectives, this study deployed financial literacy theory to explain how financial literacy relates to the mode of payment preferences, access to credit facilities, and performance among Nigerian rural farmers. With this, the outcomes of the current study possess theoretical implications for research and policy implications for agricultural and financial authorities. First, the study confirms financial literacy theory in the Nigerian context, indicating that the proposition holds true among Nigerian rural farmers. Second, this study responds to calls in the literature for financial literacy studies, particularly in developing nations (Goyal & Kumar, 2021; Maji & Laha, 2022; Riaz et al., 2022; Twumasi, Jiang, Ding, et al., 2022). Third, the outcomes of this study will enable the Nigerian government to understand how financial literacy impacts farm business performance, access to credit facilities, and the choice of payment model among rural farmers. Such knowledge could redirect government policy on rural poverty reduction and food security. Fourth, by assessing the performance of the rural farmers in the four dimensions of financial literacy, the outcomes will help Nigerian financial authorities understand the dimensions of financial literacy that the rural farmers are performing poorly and thereby focus more attention on improving them. Fifth, the outcomes will help payment card companies make strategic decisions and increase the performance of the payment system in Nigerian rural areas.

The outcomes of this study show that financial literacy significantly predicts performance, access to credit facilities, and mode of payment preferences among smallholder rural farmers. Also, the analyses of the four dimensions of financial literacy show that the farmers are more literate in risk diversification and inflation than numeracy and compound interest.

The rest of this paper is arranged as follows:. The next part is the literature review, which entails the theoretical framework and hypothesis development. Next to this section is the methodology, where the population of the study, the sampling techniques, and the instrument are discussed. Following this part are the analyses of data and the presentation of results. The next and final part contains a discussion of the findings, the theoretical and practical implications of the findings, the limitations of the study, and a conclusion.

Theoretical Framework and Hypothesis Development

Financial Literacy Theory

It is documented in the literature that financial literacy as a concept was coined by Jumpstart Coalition for Personal Financial Literacy (Lusardi & Mitchell, 2014; Riaz et al., 2022). In a study of the economic importance of financial literacy, Lusardi and Mitchell (2014) observed that it is the conventional microeconomic proposition about saving and consumption decisions that is used to underpin the link between financial literacy and its outcomes. The microeconomic framework proposes that well-informed, rational individuals will make profitable financial decisions (Lusardi & Mitchell, 2014). For example, Delavande et al. (2008) posit that individuals will deliberately invest in the acquisition of financial knowledge to be able to identify and invest in more secure and profitable assets.

The financial literacy theory has been used as a framework in many studies. For example, Jappelli and Padula (2013) used the framework to argue that a significant relationship exists between financial literacy and wealth creation. Based on the theory, Lusardi and Mitchell (2011) argued that making financial knowledge available even to the least educated individuals will increase the individuals’ well-being by 82% of their initial wealth. Similarly, Bernheim (1998) reported that households in the United States of America that lack basic knowledge of financial matters make uninformed financial decisions in their saving pattern. Agarwal et al. (2009) found that financial “mistakes” are predominant among people with the lowest financial knowledge. Also, Song (2011) discovered in China that contributions to pension savings substantially increased among farmers when they gained knowledge of compound interest (Table 1).

Table 1.

Variables: Definition and Description.

Variable	Definition/description	Data source	References
Financial literacy	Ability to understand and profitably use economic information.	Understanding levels of inflation, diversification, simple interest and compound interest.	Klapper et al. (2014) and Lusardi and Mitchell (2017)
Subjective performance	The perception that the set goals are achieved.	Satisfaction levels with sales volume, earnings and profit.	Fowowe (2017) and Santos and Brito (2012)
Access to credit	Ability to adequately obtain loans/credit	The extent of borrowed funds in business.	Fowowe (2017)
Mode of payments	There are diverse channels of making payment.	Use of banking halls, physical cash, mobile phones, ATMs, and cards	Swiecka, Terefenko, and Paprotny (2021) and Swiecka, Terefenko, Wisniewski, and Xiao (2021)

Hypotheses Development

Financial Literacy and Performance

The ultimate aim of investments in farm businesses is to increase performance (Safitri, 2021; Twumasi, Jiang, Adhikari, et al., 2022). Some studies suggest that access to credit, good investment decisions, and higher performance are achieved through adequate financial management knowledge (Twumasi, Jiang, Adhikari, et al., 2022). Koomson et al. (2020) argue that individuals with adequate financial knowledge often have access to formal financial products and services, and this helps increase performance. Gaudecker (2015) explored the impacts of financial literacy on individuals’ decision-making regarding portfolio diversification using OLS regression and found that people who follow financial experts’ advice make better investment decisions than those who lack such assistance.

Paltasingh and Goyari (2018) examined how farmer education impacts farm productivity in the context of evolving modern technologies and reported that education significantly increases the productivity of farmers by way of adopting modern technology. Lusardi and Mitchell (2013) pointed out that poor business performance and the bad investment habit of clinging to less risky but low profit-yielding investments are often attributable to low financial literacy levels. Twumasi, Jiang, Ding, et al. (2022) reported that financial literacy significantly impacts household income in Ghana. In a study on financial literacy among Portuguese people, Oliveira et al. (2022) concluded that financial literacy can enhance return on investment. It is reported that financial literacy enables one to correctly determine both production cost and selling price and maximize profit (Gaurav & Singh, 2012; Hossain & Maji, 2021; Lusardi & Mitchell, 2017). Individuals who possess a good financial literacy level have the capability to effectively manage investments and experience lower levels of risk and high returns (Klapper et al., 2015).

H1. Financial literacy significantly relates to performance among Nigerian smallholder rural farmers.

Financial Literacy and Access to Credit Facilities

The ability of people to have adequate access to credit is suggested to be a function of financial literacy. For example, it is reported in the work of Klapper et al. (2012) that increased financial literacy would result in increased savings and access to credit, particularly in low-income societies. It is also reported in India that poor financial literacy hinders one’s access to credit in formal financial institutions (Government of India, 2019). In Ghana, Atakora (2016) argues that microcredit received by Ghanaian rural households lacks significant impacts on their earnings due to poor financial management skills, resulting in inappropriate borrowing and poor investment decisions. Twumasi, Jiang, Ding, et al. (2022) examined how financial literacy affects household income among 572 households in rural Ghana and concludes that financial literacy directly influences access to financial services.

In Indonesia, low access to formal credit is attributed to a lack of financial and banking education, among others (Bank Indonesia, 2014). Using multiple regressions and logistic analysis to test the impacts of financial literacy on access to microcredit among farmers in Indonesia, Widhiyanto et al. (2018) reported a significant link between financial literacy and microcredit accessibility, arguing that inadequate financial literacy results in the inability to possess collateral requirements to access formal credit among individuals. In Bangladesh, Hasan et al. (2021) explored how financial knowledge relates to access to finance among rural dwellers. The study reported that knowledge of financial matters such as understanding the mode of withdrawal/deposit of money and adequate knowledge of interest rates significantly influence individuals’ access to finance.

In China, Xu et al. (2020) reported a significant positive link between financial literacy and access to formal credit facilities among business owners. It is also suggested that financial literacy is capable of influencing individuals’ profitable borrowing decisions and good use of credit and debit cards (Goyal & Kumar, 2021; Hasan et al., 2021; Klapper & Lusardi, 2020). In a study among respondents in Chile, Madeira and Margaretic (2020) found a positive link between financial literacy and loan reporting accuracy. This suggests that a good debt management record is a prerequisite for access to credit facilities. For example, it is argued that a lack of adequate knowledge of the financial system can predispose individuals to accept inappropriate interest rates, which often results in default on loan repayments, low credit rating, and hindrance to future access to credit (Agarwalla et al., 2015; Klapper & Lusardi, 2020). In line with the suggestions in the literature, we argue that adequate financial literacy levels will equip Nigerian rural farmers to know where borrowing opportunities exist and borrow profitably. Therefore, it is hypothesized that:

H2. Financial literacy significantly relates to access to credit facilities among Nigerian smallholder rural farmers.

Financial Literacy and Mode of Payment Preferences

It is argued that since knowledge is an important factor in comprehending financial technological solutions, it is crucial to understand how financial literacy influences the choice of payment among consumers (Swiecka, Terefenko, Wisniewski, & Xiao, 2021). Assessing the methods of payments in Canada, Henry et al. (2017) reported that individuals who are more financially literate hold less cash and adopt more cashless methods of payments. Robb (2011) shows how financial knowledge affects credit card use. Studying the link between financial knowledge and the use of credit cards among college students, Robb (2011) found that students who possess higher financial knowledge make reasonable use of credit cards. In Poland, Swiecka, Terefenko, Wisniewski, and Xiao (2021) empirically demonstrated that knowledge of financial products and services significantly predicts the mode of payment choices among consumers. Yuwono et al. (2017) reported that knowledge of financial institutions significantly relates to the choice of financial products among farmers.

Imhanrenialena, Obi Anike, Okafor, Ike, and Obiora Okafo (2021) observed in an empirical study involving marketers of bank financial services in rural areas in Nigeria that the rural farmers that possess considerable levels of financial literacy easily adopt modern financial services. This suggests that financial literacy levels can influence the mode of payment preference. It was reported by the Indonesian Financial Services Authority (Otoritas, 2014) that the low knowledge and comprehension of financial products and services leads to the low utilization of such financial products and services among Indonesian people. In a study involving Dutch consumers, Kosse (2013) demonstrated that consumers’ confidence level in a financial system determines their choice of payment channels. We believe that financial literacy is capable of increasing one’s confidence in a financial system, which will in turn influence one’s mode of payment preferences. Prete (2022) documented that digital payment system adoption and other finance choices are significantly linked with digital and financial literacy. In Indonesia, Foster et al. (2022) found a significant positive link between financial literacy and individuals’ motivation to use a chip-based electronic money payment model. With the prevalence of innovative technology-inclined payment systems, we assume that Nigerian rural farmers’ choice of payment model will be largely influenced by their financial literacy levels. Based on this assumption, it is proposed that:

H3. Financial literacy significantly relates to the mode of payment preferences among Nigerian smallholder rural farmers.

Gaps in the Literature

The gaps discovered in the extant literature necessitated this study. For example, recent studies pointed out that there is a dearth of research on how financial literacy impacts individuals and economies around the world (Riaz et al., 2022; Twumasi, Jiang, Ding, et al., 2022), particularly in Nigeria (Imhanrenialena, Obi Anike, Okafor, Ike, & Obiora Okafo, 2021). We particularly discovered in the literature that research has yet to provide insights into how financial literacy impacts farm business performance among Nigerian rural farmers. We also found that research has yet to explore the link between financial literacy, access to credit facilities, and choice of payment model in the Nigerian rural context. Consequently, the aim of this study is to provide insights into this phenomenon.

Methods

A cross-sectional survey method was adopted in collecting quantitative data on financial literacy, performance, access to credit facilities, and mode of payment preferences among rural farmers in Nigeria. The inclusion criteria include being a farmer in rural areas and the ability of the farmers to provide valid evidence of being registered in the CBN Anchored Borrower’s Programme loan for the 2022 farming season (Central Bank of Nigeria, 2022). The population of the study was the registered 4.2 million smallholder farmers in the Central Bank of Nigeria’s Anchored Borrower’s Programme for the 2022 farming year. Taro Yamane’s (1967) method for sample size determination was used to calculate the sample for the study, as presented below:

n =____N____

1 + N {(e)}^{2}

Where the sample size is represented with n, the population is denoted with N, 1 is the constant, and the error margin (taken as .05) is denoted with e. Therefore, applying the sample size determination technique to the 4.2 million smallholder farmers, we arrived at a sample size of 400. But following the suggestion by Imhanrenialena et al. (2022) that the random sample size should be increased by 20% if high unreturned and invalid questionnaires are envisaged, we added 80 (20%) to bring the total sample size to 480.

Data Collection

Research assistants were recruited to interpret and explain the question items to some of the rural farmers who had difficulty understanding the English language. The research assistants were recruited based on their ability to understand the items in the questionnaire and the local languages of the respondents. The questionnaire was administered on market days and Sundays in the localities, when most of the farmers do not go to their farms. We addressed the incidence of unreturned copies of the questionnaire by encouraging the respondents to answer and drop the questionnaire at the interview locations. This became necessary based on the interpretation assistance required by the respondents, occasioned by their low educational backgrounds and the difficult terrain of the rural areas. We, however, found 13 copies of the questionnaire to be invalid due to self-contradicting answers during sorting and coding.

Measures

The study adapted the “Standard and Poor Global Financial Literacy Questionnaire” developed by scholars at the World Bank Development Research Group and the George Washington University School of Business (Klapper et al., 2014) to measure financial literacy. The scale measures financial literacy level in four dimensions, namely, “risk diversification, inflation, numeracy (interest), and compound interest.” We used the questionnaire because it was successfully used in past research to measure financial literacy among rural farmers (Maji & Laha, 2022). The constructs for measuring payment preferences were adapted from the works of Swiecka, Terefenko, Wisniewski, and Xiao (2021) and Swiecka, Terefenko, and Paprotny (2021) which measured the choice of payment among Polish consumers. The questions were asked about the farmers’ preferred payment model.

The “subjective measure of access to finance” was adapted in the work of Fowowe (2017) to measure access to finance. Also, the subjective measures of performance were adapted from the same work by Fowowe (2017) to assess performance. We chose subjective measures of performance because objective financial measures of performance are not ideal to be used among rural farmers due to the prevalence of poor recordkeeping among them. For example, scholars have argued that objective financial measures of performance such as profit, revenue, and returns on investment (ROI) have the disadvantage of financial figures not being available or inaccurately kept, resulting in misleading outcomes (Fowowe, 2017; Santos & Brito, 2012). Therefore, subjective performance measures, which include the farmers’ satisfaction levels with their sales volume, earnings, and profit, were used.

Results

Demographic Statistics

The analysis of the demographic profile of the farmers indicates that males dominate rural farming as expected (395 or 85%), with the number of females standing at 72 (15%). The women rural farmers may either be widowed, divorced, or separated, as their number (72 or 15%) is close to the combined figure of women who are either widowed, divorced, or separated under marital status in Table 2 (82 or 17.4%). The outcomes indicate that rural farming is dominated by young adults, as the respondents in their 30s were 129 (27.6%), while those in their 40s were 187 (40%). The farmers in their 50 were only 52 or 11.1% and this low number could be explained by the use of energy-sapping crude farm implements, which is still predominant in African rural farming (see Table 2).

Table 2.

Demographic Characteristics of Respondents.

	Frequency	Percent
Gender
Male	395	85
Female	72	15
Total	467	100
Age
20 and below	12	2.6
21–29	87	18.6
30–39	129	27.6
40–49	187	40.0
50 and above	52	11.1
Total		100
Marital status
Single	97	20.8
Married	288	61.7
Divorced/separated	62	13.3
Widowed	20	4.1
Total		100
Level of education
No formal education	45	9.6
Primary school	97	20.8
O’ Level	203	43.5
ND/NCE	57	12.2
First degree/HND	50	10.7
Postgraduate	15	3.2
Total	467	100

As the results indicate, the majority of the farmers (203 or 43.5%) possess secondary education while 97 (20.8%) possess primary education with 45 (9.6%) having no formal education. The low number of Nigerian rural farmers without formal education that is registered in the Central Bank of Nigeria’s Anchored Borrower’s Programme suggests that the majority of the farmers are being excluded from the credit scheme as the majority of rural farmers are not literate (Imhanrenialena, Obi Anike, Okafor, & Ike, 2021; Imhanrenialena, Obi Anike, Okafor, Ike, & Obiora Okafo, 2021).

Analysis of the financial literacy levels among Nigerian rural farmers presented in Table 3 suggests that rural farmers are more financially literate in the dimension of inflation (257 or 55%) than in the other three dimensions. This higher understanding of inflation among the farmers may be accounted for by the fact that the effects of inflation such as an increase in the prices of goods and services are felt by everyone in an economy. The diversification dimension of financial literacy is the second area where many of the farmers (137 or 29.3) performed well. The reason the farmers understand the financial concept of diversification could be a result of the practice of cultivating more than one commodity on their farm. However, a very small number of the farmers understand numeracy (59 or 12.6%) and compound interest (14 or 3%).

Table 3.

Dimensional Financial Literacy Levels Among Nigerian Rural Farmers.

Financial literacy levels	Frequency	Percent
Risk diversification	137	29.3
Inflation	257	55.0
Numeracy (interest)	59	12.6
Compound interest	14	3.0
Total	467	100

Measurement Model

The outcomes of the analysis (see Table 4) indicate that the factor loading of each variable’s specific items is greater than the recommended benchmark of .70. The average variance extracted estimate (AVE) result supports the instrument’s validity. For example, the AVE coefficients for financial literacy, performance, access to credit facilities, and mode of payment preference are .760, .635, .825, and .846 respectively which exceed the recommended .50 threshold (Memon & Rahman, 2014). The instrument’s reliability was assessed with both composite reliability and Cronbach’s alpha. The composite reliability values for financial literacy, performance, access to credit facilities, and payment preference are .940, .839, .839, and .956. Similarly, Cronbach’s alpha values for financial literacy, performance, credit facility access, and payment preference are .924, .715, .894, and .939, respectively. These results show that the composite reliability values and Cronbach’s alpha coefficients are all significantly higher than the .70 threshold, indicating internal consistency (Henseler et al., 2012). The result from the variance inflation factor (VIF) analysis shows that all factor-level VIFs from the collinearity test are less than 3.3, an indication that the model is free from common method bias (Kock, 2015).

Table 4.

Confirmatory Factor Analysis.

Constructs	Loading	VIF	AVE	Compose reliability	Cronbach’s alpha
	>.7	<3.3	>.5	>.8	>.7
Financial literacy			.760	.940	.924
Risk diversification	.884
Inflation	.891	1.433
Numeracy (interest)	.866	2.453
Compound interest	.847	1.171
Agribusiness performance			.635	.839	.715
Sales volume	.837	1.245
Profit making	.812	1.333
Satisfaction with earnings	.740	2.215
Access to credit facilities			.825	.839	.894
Access to loan	.937	1.801
Availability of collateral	.927	1.524
Repay loans to get new ones	.859	2.225
Payment preferences			.846	.956	.939
Banking halls	.934	1.804
Cash payments	.901	1.563
Mobile phone cash transfers	.916	1.536
Cards/ATM services	.927	1.745

Note. VIF = variance inflation factor; AVE = variance extracted estimate.

To test for discriminant validity, the heterotrait-monotrait (HTMT) ratio of correlations method was used (see Table 5). The average heterotrait-heteromethod correlation was discovered to be relative to the average monotrait-heteromethod correlation. The obtained values from the HTMT ratio of correlations analysis are less than the recommended HTMT critical value of 0.85 (Henseler et al., 2012; Kline, 2005). With this result, discriminant validity is established. The model fit estimation was assessed with the standardized root mean square residual (SRMR). The obtained SRMR value of 0.071 is less than the recommended 0.08 benchmark (Hu & Bentler, 1998) and this indicates a good model fit. Furthermore, the obtained values of 210.213 and 0.902 for chi-square and normal fit index (NFI) respectively which both exceed the 0.90 benchmark further support the model fit (see Table 6).

Table 5.

Discriminant Validity.

	Access to credit facility	Agribusiness performance	Financial literacy
Access to credit facility
Agribusiness performance	0.790 [0.703, 0.865]
Financial literacy	0.767 [0.655, 0.8220]	0.788 [0.703, 0.850]
Payment preferences	0.785 [0.700, 0.849]	0.695 [0.617, 0.788]	0.775 [0.695, 0.833]

Table 6.

Model Fit.

	Estimated
SRMR	0.071
Cmin/df	2.191
d_G	0.5884
χ²	210.213
NFI	0.902

Note. SRMR = standard root mean square residual; Cmin/df = chi-square value/degree of freedom; dG = distance Geodesic; NFI = normal fit index.

Test of Hypotheses

The proposed three hypotheses were tested using the partial least squares structural equation modeling (Smart PLS 3.0). The hypotheses are stated in alternative forms. The independent variable is financial literacy while performance, access to credit, and mode of payment preferences are the dependent variables (see Table 7 and Figure 1).

Table 7.

Path Coefficient Table for the Test of Hypotheses.

	Variables	Path co-efficient	SD	T-statistics	p Values	R ²	F ²	Q ²	Decision
H_o1	Financial literacy → Agribusiness performance	0.791	0.040	19.520	.000	.625	1.666	0.368	Significant
H_o2	Financial literacy → Access to credit facility	0.781	0.081	9.644	.000	.611	1.567	0.489	Significant
H_o3	Financial literacy → Payment preferences	0.808	0.066	12.233	.000	.653	1.884	0.544	Significant

Figure 1.

Model for financial literacy, agribusiness performance, access to credit facilities, and payment preferences among rural farmers.

The proposed influence of financial literacy on performance among rural farmers is tested in H1. The outcomes show a significant direct link between financial literacy and performance among rural farmers (β = .791, T-value = 19.520 > 1.96, p-value = .000 < .05, and R² = .625). The co-efficient value of .791 implies that financial literacy significantly relates to performance among rural farmers. The R² of .625 indicates that a 62.5% variance in performance is explained by financial literacy among rural farmers.

The results in H2 also suggest a significant relationship between financial literacy and access to credit facilities among rural farmers (β = .781, T-value = 9.644 > 1.96, p-value = .000 < .05, and R² = .611). The co-efficient value of .781 implies a significant positive relationship between financial literacy and access to credit facilities among rural farmers. The R² of .611 is an indication that a 61.1% variance in access to credit facilities among Nigerian rural farmers is explained by the farmers’ financial literacy level.

The findings in H3 show a significant direct relationship between financial literacy and mode of payment preferences among smallholder rural farmers (β = .808, T-value = 12.233 > 1.96, p-value = .000 < .05, and R² = .653). The co-efficient value of .808 implies a significant positive relationship between financial literacy and payment preferences among rural farmers. As the R² value of .653 suggests, financial literacy accounts for a 65.3% variance in payment preferences among rural farmers (see Table 7).

Discussion of Findings

Following frequent innovative and complex nature of financial products and services that resulted in calls for research into financial literacy, particularly among rural farmers in developing countries (Goyal & Kumar, 2021; Maji & Laha, 2022; Riaz et al., 2022; Twumasi, Jiang, Adhikari, et al., 2022), the current study assesses how financial literacy influences performance, access to credit facilities and mode of payment preferences among rural farmers in Nigeria. The outcome of hypothesis 1 indicates that financial literacy significantly predicts performance among rural farmers. This outcome contradicts the popular belief among Nigerians that financial literacy is not making an impact on farm business in rural areas (Imhanrenialena, Obi Anike, Okafor, & Ike, 2021). However, the result aligns with similar work by Twumasi, Jiang, Ding, et al. (2022) that suggested that financial literacy significantly impacts household income in rural areas in Ghana. Individuals with adequate financial knowledge often have access to formal financial products and services which help them in increasing performance (Koomson et al., 2020; Twumasi, Jiang, Adhikari, et al., 2022). For example, Twumasi, Jiang, Adhikari, et al. (2022) argue that adequate financial management knowledge can result in increased access to credit, good investment decisions, and higher performance.

This current outcome in the Nigerian context implies that Nigerian rural farmers who possess adequate financial literacy levels are able to deploy their knowledge of financial matters to correctly determine actual production cost and selling, price and maximize profit. This is also another indication that financial literacy helps Nigerian rural farmers in identifying viable borrowing opportunities as well as in assessing the terms and conditions of the loans. The farmers can use such borrowed funds to acquire modern farm inputs to improve productivity and earnings.

The outcome of hypothesis 2 shows that financial literacy significantly predicts access to credit facilities among Nigerian rural farmers. We found congruence between this outcome and the work of Xu et al. (2020) which found a significant positive link between financial literacy and access to formal credit facilities among business owners in China. The result also conforms to findings by Twumasi, Jiang, Adhikari, et al. (2022) that suggest that financial literacy directly predicts access to financial services among households in rural Ghana. Similarly, this result also aligns with the work of Widhiyanto et al. (2018) that argue that inadequate financial literacy results in the inability to possess the collateral to access credit among individuals. In the same vein, this result aligns with a study in Bangladesh where Hasan et al. (2021) reported that the knowledge of financial matters such as adequate knowledge of interest rates significantly influences individuals’ access to finance.

The reason for this result may be that the rural farmers are able to use their financial literacy capability to increase savings which in turn increases their access to credit facilities. Increased savings brightens one’s chance to qualify for loans. Also, the use of financial knowledge to identify the sources of loans and understand the associated conditionality may account for the ability of rural farmers to have more access to credit for their farming business. Financially literate rural farmers may not accept inappropriate interest rates that are capable of resulting in loan repayment constraints, low credit ratings, and hindrance to future access to credit. Another reason why financial literacy significantly predicts access to credit among Nigerian rural farmers may be that financial knowledge equips rural farmers with better risk management which minimizes loan repayment defaults and increases the chances for future loans.

The proposed H3 was confirmed, indicating a significant relationship between financial literacy and mode of payment preferences among Nigerian rural farmers. This outcome suggests that the more financially literate a rural farmer is, the better the choice of mode of payment (digital payment) the farmer will make. This result contradicts the work of Ullah et al. (2022) that found no significant direct relationship between individuals’ financial skills and their desire to use the mobile payment model in Pakistan. For example, Ullah et al. (2022) argue that the financial skills of individuals do not influence their adoption of the mobile payment model except through the mediating role of the perceived usefulness of the payment model.

However, this result is in line with studies conducted in Canada (Henry et al., 2017) and Poland (Swiecka, Terefenko, Wisniewski, & Xiao, 2021) that suggested that financial literacy predicts payment choices among consumers. The reason Nigerian farmers’ mode of payment preferences are influenced by financial literacy may be that the financially literate ones are able to understand the benefits of adopting modern payment methods such as the absence of theft/robbery of cash. For example, mobile phone payment eliminates the incidence of theft/robbery of cash and the transaction is very convenient to do. We also found congruence between this result and the work of Kosse (2013) which demonstrated that Dutch consumers’ confidence level in the financial system determines their choice of payment channels. This suggests that with the prevalence of innovative technology-inclined payment system in Nigeria, the farmers’ confidence and the resultant choice of payment model is influenced by financial literacy.

Theoretical Implication of Findings

The positive link found between financial literacy and payment preferences, access to credit, and performance among Nigerian rural farmers has many theoretical implications. First, this study confirms the microeconomic framework that underpins this study in the Nigerian context, which suggests that rational and well-informed individuals make informed and profitable financial decisions (Lusardi & Mitchell, 2014). This suggests that Nigerian rural farmers who are financially literate adopt digital payment options, access loans, and invest profitably in their farm business.

Second, this study fills an important gap in the literature by responding to the calls by researchers for studies on financial literacy (Goyal & Kumar, 2021; Riaz et al., 2022) which possess a big challenge to economic development (Riaz et al., 2022). Third, this current study contributes to agribusiness literature in African rural areas by shifting the research focus from the dominant topic of agricultural financing to the neglected role of financial literacy in rural farming business sustainability. As attested to by Matewos et al. (2016), continues lack of adequate financial literacy knowledge in developing African countries impedes the effective formulation and implementation of financial policies and programs.

Practical Implications of Findings

The outcomes of this study have important policy implications for government and financial authorities.

First, the current findings on Nigerian rural farmers’ mode of payment preference behavior could guide the government and financial authorities in formulating financial inclusion policies to drive financial inclusion in rural areas. This can be achieved by initiating financial literacy policies and programs that will increase the financial literacy levels among rural dwellers. Second, the outcome can help financial technology firms and payment card companies in taking strategic decisions to increase the overall performance of the payment system in Nigeria. Third, the positive link found between financial literacy and access to credit and farmers’ performance might motivate the government to initiate strategies to improve financial literacy in order to increase farm business performance in Nigerian rural areas. Fourth, the outcomes of this study that indicate that rural farmers are more literate in risk diversification and inflation than numeracy and compound interest can provide directions for Nigerian governments’ financial inclusion policies, and financial institutions’ strategies to improve the overall financial literacy level among rural farmers. Taken together, the Nigerian government should pay urgent and serious attention to financial literacy, particularly in rural areas through financial education. This will increase overall food production in Nigeria, and reduce poverty among rural dwellers.

Limitations and Suggestions for Future Research

This research provides novel insights into how financial literacy impacts performance, access to credit facilities, and mode of payment preference among Nigerian rural farmers. However, it is important to disclose the study’s limitations and suggest areas for future research. First, this study did not investigate gender differences in how financial literacy impacts farm business in Nigerian rural areas. Therefore, it will be interesting if future research provides such insights. Second, the data for this research were collected using self-report measures and there is the possibility that the respondents might have either understated or exaggerated their financial literacy experiences in their farm business. To overcome this challenge, we advise future researchers, if possible, to use secondary data where the rural farmers will not be directly contacted for data collection. Third, this research only investigated the impact of financial literacy on rural farm businesses. We suggest that future researchers should replicate this research in Nigerian urban areas to uncover how financial literacy is impacting businesses in urban areas.

Conclusion

This study concludes that financial literacy significantly predicts performance, access to credit facilities, and mode of payment preferences among rural farmers in Nigeria. This contribution to the development of rural farming in Nigeria is important as it shifts research attention from the dominant topics of diversification, land use, agricultural policies/program, and agricultural loans to the neglected area of financial literacy among rural farmers. Also, this study shows that the farmers are more literate in risk diversification and inflation than numeracy and compound interest. The findings of this study have opened up new research areas in the quest to increase financial literacy among rural farmers. Therefore, it is suggested as a follow-up, that further studies should explore the role of financial socialization in increasing financial literacy among rural farmers in Africa.

Footnotes

Appendix: Questionnaire

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Imhanrenialena Ogbemudia Benedict

Data Availability Statement

The research datasets analyzed in this study are available on request through the corresponding author.

References

Agarwal

Driscoll

Gabaix

Laibson

(2009). The age of reason: Financial decisions over the lifecycle with implications for regulation. Brookings Papers on Economic Activity, 2, 51–101.

Agarwalla

S. K.

Barua

S. K.

Jacob

Varma

J. R.

(2015). Financial literacy among working young in urban India. World Development, 67, 101–109.

Atakora

(2016). Measuring the effectiveness of financial literacy programs in Ghana. International Journal of Management and Business Research, 3, 135–148.

Bank Indonesia. (2014). Financial inclusion booklet. Department of Development Financial Access and Small and Medium Enterprises, Bank Indonesia.

Bernheim

(1998). Financial illiteracy, education, and retirement saving . In Mitchell

O. S.

Schieber

(Eds.), Living with defined contribution pensions (pp. 38–68). University of Pennsylvania Press.

Central Bank of Nigeria. (2020). The national financial inclusion strategy. https://www.cbn.gov.ng/Out/2020/CCD/2019%20Annual%20Report%20of%20the%20National%20Financial%20Inclusion%20Strategy%20Implementation.pdf

Central Bank of Nigeria. (2022). An update on Anchor Borrowers Programme. https://www.thecable.ng/cbn-anchor-borrowers-programme-gulped-n57-9bn-in-two-months

Conrad

Gamuchirai

Pepukai

P. C.

Rumbidzai

(2020). Financial inclusion, nutrition and socio-economic status among rural households in Guruve and Mount Darwin districts, Zimbabwe. Journal of International Development, 33, 86–108. https://doi.org/10.1002/jid.3513

Delavande

Rohwedder

Willis

(2008). Preparation for retirement, financial knowledge and cognitive resources (Working Paper No. 2008-190). MRRC. http://www.mrrc.isr.umich.edu/publications/papers/pdf/wp190.pdf

10.

Enhancing Financial Innovation and Access (EFInA). (2021). EFInA access to financial services in Nigeria: 2020 survey. https://a2f.ng/wp-content/uploads/2021/06/A2F-2020-Final-Report.pdf

11.

Filipiak

Walle

Y. M.

(2015). The financial literacy gender gap: A question of nature or nurture? (Discussion Papers No. 176). Courant Research Centre: Poverty, Equity and Growth.

12.

Foster

Sukono Johansyah

M. D.

(2022). Analysis of the effect of financial literacy, practicality, and consumer lifestyle on the use of chip-based electronic money sing SEM. Sustainability, 14(32), 1–17.

13.

Fowowe

(2017). Access to finance and firm performance: Evidence from African countries. Review of Development Finance, 7, 6–17.

14.

Gaudecker

H.-M. V.

(2015). How does household portfolio diversification vary with financial literacy and financial advice? The Journal of Finance, 70(2), 489–507.

15.

Gaurav

Singh

(2012). An inquiry into the financial literacy and cognitive ability of farmers: Evidence from rural India. Oxford Development Studies, 40(3), 358–380.

16.

Government of India. (2019, January–December). All India debt and investment survey NSS 77th round. http://mospi.nic.in/sites/default/files/publication_reports/Report%20no.%20588-AIDIS-77Rm-Sept.pdf

17.

Goyal

Kumar

(2021). Financial literacy: A systematic review and bibliometric analysis. International Journal of Consumer Studies, 45(1), 80–105.

18.

Hasan

Hoque

(2021). How does financial literacy impact on inclusive finance? Financial Innovation, 7(1), 1–23.

19.

Henry

C. S.

Huynh

K. P.

Welte

(2017). Method-of-payments survey results (Staff Discussion Paper 2018–17). Bank of Canada.

20.

Henseler

Ringle

C. M.

Sarstedt

(2012). Using partial least squares path modeling in advertising research: Basic concepts and recent issues. In Okazaki

(Ed.), Handbook of research on international advertising. Edward Elgar.

21.

Hossain

Maji

S. K.

(2021). Antecedents of financial literacy: Evidences from West Bengal, India. Business Insight, 8(1), 16–36.

22.

Bentler

P. M.

(1998). Fit indices in covariance structure modeling: Sensitivity to under parameterized model misspecification. Psychological Methods, 3(4), 424–453.

23.

Imhanrenialena

B. O.

Obi-Anike

O. H.

Okafor

C. N.

Ike

R. N.

(2021). Potential for indigenous communication systems to improve financial literacy: Evidence from Nigeria. Enterprise Development and Microfinance, 32(1), 123–139.

24.

Imhanrenialena

B. O.

Obi-Anike

O. H.

Okafor

C. N.

Ike

R. N.

Obiora-Okafo

(2021). Addressing financial inclusion challenges in rural areas from the financial services marketing employee emotional labor dimension: Evidence from Nigeria. Journal of Financial Services Marketing, 27(2), 136–146. https://doi.org/10.1057/s41264-021-00107-y

25.

Imhanrenialena

B. O.

Ogohi

D. C.

Ebhotemhen

Chukwu

B. I.

Oforkansi

E. S.

(2022). Exploring how social capital and self-esteem shape career success among women in a patriarchal African society: The case of Nigeria. International Journal of Manpower, 43(8), 1804–1826. https://doi.org/10.1108/IJM-07-2021-0410

26.

Jappelli

Padula

(2013). Investment in financial literacy and saving decisions. Journal of Banking and Finance, 37, 2779–2792.

27.

Klapper

Lusardi

(2020). Financial literacy and financial resilience: Evidence from around the world. Financial Management, 49(3), 589–614.

28.

Klapper

Lusardi

Panos

(2012). Financial literacy and the financial crisis (Working Paper Series No. 17930). National Bureau of Economic Research (NBER). http://www.nber.org/papers/w17930

29.

Klapper

Lusardi

van Oudheusden

(2014). The standard and poor global financial literacy survey. World Bank.

30.

Klapper

Lusardi

van Oudheusden

(2015). Financial literacy around the world. Standard & Poor’s ratings services global financial literacy survey. World Bank.

31.

Kline

R. B.

(2005). Principles and practice of structural equation modeling (2nd ed.). Guilford Press.

32.

Kock

(2015). One-tailed or two-tailed P values in PLS-SEM? International Journal of e-Collaboration, 11(2), 1–7.

33.

Koomson

Villano

R. A.

Hadley

(2020). Effect of financial inclusion on poverty and vulnerability to poverty: Evidence using a multidimensional measure of financial inclusion. Social Indicators Research, 149, 613–639.

34.

Kosse

(2013). The safety of cash and debit cards: A study on the perception and behaviour of Dutch consumers. International Journal of Central Banking, 9(4), 77–98.

35.

Lusardi

Mitchell

O. S.

(2011). Financial literacy and retirement planning in the United States. Journal of Pension Economics and Finance, 10(4), 509–525.

36.

Lusardi

Mitchell

O. S.

(2013). The economic importance of financial literacy: Theory and evidence (Working Paper Series No. 2014-001). GFLEC.

37.

Lusardi

Mitchell

O. S.

(2014). The economic importance of financial literacy: Theory and evidence. Journal of Economic Literature, 52, 5–44.

38.

Lusardi

Mitchell

O. S.

(2017). How ordinary consumers make complex economic decisions: Financial literacy and retirement readiness. Quarterly Journal of Finance, 7(3), 175–193.

39.

Madeira

Margaretic

(2020). The impact of financial literacy on the quality of self-reported financial information. Journal of Behavioral and Experimental Finance, 34, 100660.

40.

Maji

S. K.

Laha

(2022). Financial literacy and its antecedents amongst the farmers: Evidence from India. Agricultural Finance Review, 83(1), 124–143. https://doi.org/10.1108/AFR-01-2022-0009

41.

Matewos

K. R.

Navkiranjit

K. D.

Jasmindeep

(2016). Financial literacy for developing countries in Africa: A review of concept, significance and research opportunities. Journal of African Studies and Development, 8(1), 1–12.

42.

Memon

A. H.

Rahman

I. A.

(2014). SEM-PLS analysis of inhibiting factors of cost performance for large construction projects in Malaysia: Perspective of clients and consultants. The Scientific World Journal, 2014(65158), 1–9.

43.

Oliveira

T. F.

Gomes

A. L.

Jorge

S. V.

Capela

T. V.

(2022). Financial literacy: An exploratory analysis in Portugal. Studies in Business and Economics, 17(2), 252–269.

44.

Otoritas

J. K.

(2014). Survey on Indonesian financial literacy index survey. Otoritas Jasa Keuangan (OJK).

45.

Paltasingh

K. R.

Goyari

(2018). Impact of farmer education on farm productivity under varying technologies: Case of paddy growers in India. Agricultural and Food Economics, 6(1), 1–19.

46.

Prete

A. L.

(2022). Digital and financial literacy as determinants of digital payments and personal finance. Economics Letters, 213, 110378.

47.

Riaz

Khan

H. H.

Sarwar

Ahmed

Muhammad

Reza

Ul Haq

S. M. N.

(2022). Influence of financial social agents and attitude toward money on financial literacy: The mediating role of financial self-efficacy and moderating role of mindfulness. SAGE Open, 12(3), 1–16.

48.

Robb

(2011). Financial knowledge and credit card behavior of college students. Journal of Family and Economic Issues, 32, 690–698.

49.

Safitri

K. A.

(2021). An analysis of Indonesian farmer’s financial literacy. Studies of Applied Economics, 39(4), 85–105.

50.

Santos

J. B.

Brito

L. A. L.

(2012). Toward a subjective measurement model for firm performance. Brazilian Administrative Review, 9, 95–117.

51.

Santoso

Asmara

Abidin

(2020). Measuring the financial literacy of farmers’ food crops in the poor Area of Madura, Indonesia. European Journal of Agriculture and Food Sciences, 2(6), 1–5. https://doi.org/10.24018/ejfood.2020.2.6.138

52.

Song

(2011). Financial illiteracy and pension contributions: A field experiment on compound interest in China (Berkeley Working Paper). University of California.

53.

Swiecka

Terefenko

Paprotny

(2021). Transaction factors’ influence on the choice of payment by Polish consumers. Journal of Retailing and Consumer Services, 58(102264), 1–13.

54.

Swiecka

Terefenko

Wisniewski

Xiao

(2021). Consumer financial knowledge and cashless payment behavior for sustainable development in Poland. Sustainability, 13(11), 6401.

55.

Twumasi

M. A.

Jiang

Adhikari

Adu Gyamfi

Asare

(2022). Financial literacy and its determinants: The case of rural farm households in Ghana. Agricultural Finance Review, 82(4), 641–656.

56.

Twumasi

M. A.

Jiang

Ding

Wang

Abgenyo

(2022). The mediating role of access to financial services in the effect of financial literacy on household income: The case of rural Ghana. SAGE Open, 12(1), 1–13.

57.

Ullah

Kiani

U. S.

Raza

Mustafa

(2022). Consumers’ intention to adopt m-payment/m-banking: The role of their financial skills and digital literacy. Frontiers in Psychology, 13, 873708.

58.

Widhiyanto

Nuryartono

Harianto

Siregar

(2018). The analysis of farmers’ financial literacy and its’ impact on microcredit accessibility with interest subsidy on agricultural sector. International Journal of Economics and Financial Issues, 8(3), 148–157.

59.

Shi

Rong

Yuan

(2020). Financial literacy and formal credit accessibility: Evidence from informal businesses in China. Finance Research Letters, 36, 101327.

60.

Yamane

. (1967), Statistics: An introductory analysis, (2nd ed.). Harper and Row.

61.

Yuwono

Suharjo

Sanim

Nurmalina

(2017). Analisis deskriptif atas Literasi keuangan pada kelompok tani. EKUITAS. Jurnal Ekonomi Dan Keuangan, 1(3), 407. https://doi.org/10.24034/j25485024.y2017.v1.i3.2400