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Article

Factors Influencing Informal Credit Access and Utilization among Smallholder Farmers: Insights from Mountainous Regions of Pakistan

by
Ayat Ullah
1,
Vladimir Verner
1,*,
Mustapha Yakubu Madaki
1,
Faizal Adams
2 and
Miroslava Bavorova
1
1
Faculty of Tropical AgriSciences, Czech University of Life Sciences Prague, Kamýcká 129, 16500 Praha-Suchdol, Czech Republic
2
College of Agriculture and Natural Resources, Kwame Nkrumah University of Science and Technology, Kumasi P.O. Box Up 1279, Ghana
*
Author to whom correspondence should be addressed.
Agriculture 2024, 14(10), 1764; https://doi.org/10.3390/agriculture14101764
Submission received: 29 August 2024 / Revised: 30 September 2024 / Accepted: 2 October 2024 / Published: 6 October 2024
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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Abstract

:
Access to credit plays an important role in the adoption of modern agricultural practices, such as better seeds, pesticides, and fertilizers, as well as in the sustainable utilization of land by smallholder farmers. This study explores the dynamics of smallholders’ access to and utilization of informal credit to manage local farming systems. The data were collected from rural households in the Dir Kohistan mountainous region of Pakistan in 2021. A bivariate probit model was employed to analyze the data from 300 randomly selected farming households. Our findings indicate that a significant proportion of respondents (70%) reported having access to informal credit, with 65% actively utilizing credit to bolster the economic viability of their farms. This study reveals various strategies that farmers employ in response to credit constraints. The majority of farmers (69%) prioritize meeting their own farm/household needs. Social networks, particularly friends, emerge as key sources of informal credit (58.1%). The results of the bivariate probit regression analysis identify positive relationships with fellow farmers and neighbors/relatives, along with a lower perceived risk, as the most significant factors influencing access to and utilization of informal credit. Therefore, our study recommends the promotion of relationships and linkages among farmers through facilitated networking events, introducing risk mitigation measures and promoting financial literacy programs to empower smallholder capacities on the credit market. Policymakers are urged to recognize the role of social relationships and consider policies that promote community credit practices for the overall financial well-being of farmers, especially in more isolated mountain areas.

1. Introduction

Agriculture in developing countries, including Pakistan, is characterized by smallholder farming systems, which are often constrained by limited access to formal credit markets, poor infrastructure, and a reliance on informal credit sources [1]. The fragmented structure of farms, with the majority being small and marginal, exacerbates the challenges in accessing formal credit, as farmers often lack collateral, credit history, and financial literacy [2]. This results in many smallholder farmers turning to informal credit markets, which play a significant role in sustaining agricultural activities in regions where formal financial institutions are either inaccessible or impose prohibitive conditions [1]. Credit, on the other hand, plays a vital role in sustainable agriculture as it facilitates access to two of the major factors of production, which are capital, both fixed and working, and general agricultural investment [3]. Credit is necessary for farmers to improve their farms by adopting modern technologies and improved agricultural inputs, thereby increasing productivity [4]. Farmers with access to credit can shift their production frontier outwards. Empirical evidence indicates that credit access positively impacts the agricultural productivity of smallholders in various countries [4,5,6] as well as technical efficiency [7].
Financial institutions have identified the allocation of credit to smallholder farmers as a challenging process in developing countries [7], including Pakistan. This perception is a consequence of the experience of financial institutions, which have considered agricultural production a high-risk investment due to the constraints associated with the seasonality of production, irregular cash flows, natural disasters, and crop and animal diseases [8,9,10]. These factors give rise to imperfections in the credit market, which in turn result in farmers with basic formal financial services remaining at approximately 10 percent of rural communities globally. This situation is the result of a number of several factors, including a lack of collateral, credit security, the limited capacity of financial service providers, and low levels of client education [11].
Given the circumstances, farmers have no choice but to rely on informal credit to sustain agricultural production and promote investment.. The term “informal credit” is used to describe loans that rely on personal relationships or social sanctions as a means of enforcement. Such loans may be obtained from family members, friends, or neighbors. Other sources, such as credit cooperatives or village funds, may also fall within the definition of informal credit. In contrast, Anderson and Francois [12] defined formal credit as loans and credits for which social ties between the lender and borrower are absent or not used to enforce repayment. Studies have reported that many farmers depend on informal credit to meet their financial needs [13].
It is thus imperative to analyze the extant informal credit arrangements, intending to formulate policy recommendations for promoting sustainable financial arrangements in agricultural and rural communities. The use of informal credit in agriculture frequently involves the procurement of essential inputs, including seeds, fertilizers, pesticides, and farming equipment. These inputs have great consequences for enhancing the productivity and sustainability of farming systems. The extant evidence suggests that informal credit can assist farmers in managing their consumption, investing in technologies that improve productivity, and mitigating the risks associated with agricultural production cycles [14,15]. For instance, smallholder farmers frequently employ informal credit to procure inputs at the outset of the planting season and repay the loans following the harvest, thereby aligning the credit cycle with their production cycles [15]. Furthermore, informal credit can provide flexibility in repayment terms, which is particularly beneficial for farmers facing unpredictable agricultural yields and income variability [16].
The existing literature on informal credit in the agricultural sector covers various aspects that were observed and documented by other scientific studies. For example, Moahid and Maharjan [17] examined the factors influencing farmers’ access to both formal and informal credit in rural areas of Afghanistan, finding that farmers face significant barriers to accessing informal credit, limiting their ability to optimize agricultural production. A study conducted by Ullah et al. [18] suggests that borrowers, compared to purchasers, are more likely to face price information asymmetry when obtaining agricultural inputs through informal credit, adversely affecting their adoption of improved agricultural technology. Khan and Hussain [19] evaluated the demand for informal credit and its underlying factors among cotton growers in Bahawalpur, Pakistan, and they found that distance, multiple visits, high transaction costs, and corruption push farmers toward informal credit instead of formal loans. Similarly, studies such as [1,18,19] have highlighted socioeconomic factors such as gender, age, household size, education level, farming experience, farm size, and income as key determinants of formal credit access. Despite these findings, the literature has rarely addressed the specific socioeconomic impacts of informal credit access in mountainous environments, particularly its utilization in agriculture.
The mountainous regions of Pakistan, like Dir-Kohistan, present additional challenges such as geographical isolation, low agricultural productivity, and high vulnerability to environmental degradation, further intensifying the reliance on informal credit systems. This study addresses a critical gap in the literature by focusing specifically on the role of informal credit in such mountainous regions, where the interplay of these challenges is most pronounced. Unlike previous studies that focus on general rural or lowland agricultural contexts, our research contributes novel insights into how socioeconomic characteristics in remote, mountainous areas shape informal credit access and utilization. These unique geographical and socioeconomic factors have been underexplored in the existing literature, making this study an important addition to the discourse on informal credit markets in developing countries. Our findings provide valuable implications for the development of agricultural credit policies tailored to the needs of smallholder farmers in mountainous regions, where access to formal credit is often highly constrained. This research thus advances the understanding of informal credit’s role in sustaining agricultural livelihoods in such challenging environments.
Therefore, this study examines the dynamics of farmers’ access to and use of informal credit for sustainable agriculture to answer two key research questions. First, what factors influence the farmers’ access to informal credit? Second, do farmers use the accessed informal credit in agriculture? The findings of this study will assist policymakers in designing targeted agricultural and rural development initiatives that promote community networking, enhance risk management strategies, and implement financial literacy programs to empower farmers in accessing and utilizing informal credit effectively.

2. Theoretical Framework

This study is theoretically grounded in Credit Rationing Theory and Social Capital Theory. These theories provide a comprehensive framework for examining the factors influencing informal credit access and its utilization in agricultural contexts. As postulated by Stiglitz and Weiss [20], the Credit Rationing Theory posits that information asymmetry between borrowers and lenders frequently results in credit rationing, whereby prospective borrowers are denied loans despite their willingness to pay higher interest rates. Informal credit addresses market imperfections that may arise from moral hazard, adverse selection, or limited commitment. Furthermore, the inability of farmers to provide collateral and the high access costs due to a lack of credit history, financial illiteracy, and insecure property titles result in many poor households being excluded from the formal credit market [11]. In the context of agriculture, this theory provides insight into the reasons why farmers may turn to informal credit sources. The creditworthiness of a farmer is contingent upon a number of variables, including the household head’s age and farming experience, education level, and income. Older and more experienced farmers are often perceived as less risky. At the same time, higher education and income levels can mitigate lenders’ concerns about repayment, thereby improving access to informal credit [20]. Furthermore, landholding size serves as a quasi-collateral in informal lending, thereby reducing the perceived risk for lenders and facilitating access to credit. Access to input markets and contact with agricultural extension services are essential for the productive use of credit, as they provide the necessary resources and knowledge for effective agricultural investments. These economic factors align with the Credit Rationing Theory by highlighting how personal and financial attributes influence credit access and utilization.
The Social Capital Theory, articulated by Bourdieu [21] and Putnam [22], emphasizes the importance of social networks and relationships in economic transactions. Social capital plays a crucial role in informal credit systems in rural farming systems. The term ‘informal credit’ can be broadly classified into two categories: cost-free credit and transactional credit. In many instances, friends, affluent villagers, and family members provide cost-free credit, typically a modest sum with an established or unestablished repayment period [14]. These features makes informal credit readily accessible. Transactional credit is obtained from input suppliers, traders, wholesalers, moneylenders, and land mortgages, which typically entails a high interest rate and a lack of transparency [11]. Active participation in village meetings enhances social ties and trust, increasing the likelihood of securing informal loans. Positive relationships with other farmers, neighbors, and relatives bolster social capital, making it easier for farmers to access informal credit based on trust and mutual support [21,22]. Moreover, social capital influences the perceived risk associated with borrowing. Farmers embedded in strong social networks may feel more secure about their ability to repay loans, reducing the perceived risk and encouraging the use of credit for productive agricultural investments [23,24]. By integrating Credit Rationing Theory and Social Capital Theory, this study comprehensively examines how economic and social factors affect informal credit access and utilization, providing valuable insights for policy development to enhance sustainable agricultural practices.

3. Methodology

3.1. Study Site Description

The study area is situated within the Dir Kohistan region, which is characterized by the challenging topography of the Hindu Kush Himalayan mountains (Figure 1). The region is located in the northern part of the Dir Upper district within the Khyber Pakhtunkhwa province. The mountainous region is characterized by a topography with a high degree of slope, a rich forest resource base, and a diverse range of residential zones [25]. The geographical coordinates of the area range from 35°09′ to 35°47′ N latitude and 71°52′ to 72°22′ E longitude, encompassing an area of 1670.54 km2.
The mean annual temperature of the area exhibits a range of 0 to 32 °C, while its elevation spans from 1677 to 5750 m. Due to its elevated position, the Dir Kohistan region is subject to frequent precipitation, with an average annual rainfall between 1000 and 1600 mm [26,27]. The fertile croplands in this terrain are predominantly utilized for the cultivation of staple crops, including maize, wheat, beans, potatoes, and a variety of vegetables. The predominant agricultural practice is terrace cultivation under rain-fed conditions. However, this region faces considerable challenges related to agriculture, including a decline in soil fertility, a reduction in cropland, and a limited adoption of agricultural technologies [28].
Our research focuses on understanding the dynamics of access to informal credit and its utilization in the context of smallholder farming systems, with a particular emphasis on the current financial practices and challenges prevalent in the Dir Kohistan region. This region was chosen for in-depth research due to its unique geographical and socioeconomic characteristics, which have been underexplored in studies on informal credit. Dir Kohistan, a mountainous area in Pakistan, presents distinct challenges, such as geographical isolation, limited infrastructure, and restricted access to formal credit markets. These factors make the region highly reliant on informal credit networks, providing a valuable case study for understanding how smallholder farmers in similar rural and remote contexts across the developing world navigate financial constraints. The local culture is characterized by strong family bonds, which play a pivotal role in shaping the financial market environment. The cooperative spirit within the community further influences the dynamics of informal credit, fostering mutual support and resource-sharing among farmers. In the absence of formal financial sources, farmers in the Dir Kohistan region heavily rely on informal channels for credit. These informal networks, which are deeply embedded in the fabric of the community, often serve as crucial support structures for farming systems development. The dependence on these informal ties is not only transactional; it reflects the complex interplay of trust, reciprocity, and shared values within a community [16].

3.2. Household Survey

A thorough household survey was conducted in the Dir Kohistan region between February and April 2021 to understand the socioeconomic, farm-related, and institutional dynamics of smallholder farming systems. The objective of this survey was to obtain information from farmers regarding their farming practices, their perceptions of the factors influencing their decision-making processes, and the challenges they encounter on a daily basis.
Since the official data on the total number of households in the region were not available, a farmer registry was developed for the Dir Kohistan valley with the assistance of the local agricultural extension department. From this registry, 300 households were randomly selected using a simple random sampling technique, ensuring each household had an equal chance of being included in this study. This sample size was determined to capture a diverse range of farming practices and household characteristics, providing robust insights into the dynamics of smallholder farming in the region. The data were collected via a comprehensive questionnaire designed by experts with meticulous attention to detail. Prior to the administration of the main survey, the questionnaire underwent a rigorous pretesting phase conducted by trained enumerators, which facilitated the implementation of necessary adjustments based on field insights. The primary respondents were the heads of the households. The survey enlisted the support of eight enumerators who were fluent in the local languages to facilitate effective communication with respondents. The use of local enumerators was deliberate, in alignment with the research objective of conveying this study’s purpose to each respondent in their native language and securing written consent. Furthermore, the deployment of local enumerators proved advantageous, as they were already established figures within the farming community, thereby fostering trust and facilitating data collection more efficiently [29]. The whole process of data collection was conducted under the close supervision of the lead author, who possesses a profound understanding of the study region as he has served as a community development officer in the area since 2018 and played a pivotal role in accelerating the data collection process. This long-standing community engagement facilitated ease of access and contributed to the survey’s overall success and credibility [28].

3.3. Data Analysis

A bivariate probit model was employed to document the relationship between access to informal credit and subsequent credit utilization for agricultural activities. This model choice is appropriate for examining the joint determination of two binary outcomes [30]. The responses from the household survey were processed using STATA version 14. The bivariate probit model allows for the discernment of the factors influencing both access to informal credit and subsequent utilization in agricultural activities among the surveyed households. The dependent variables in the model are binary, with 1 indicating access to informal credit and the use of credit in agriculture and 0 representing the absence of these actions.
The model can be represented by the unobserved latent variables as follows:
Y1 = X1 + ɛ1
Y2 = X2 + ɛ2
The bivariate probit model specifies the outcomes as follows:
Y 1 = 1   i f   Y 1 > 0 0   i f   Y 1 ≤ 0
Y 2 = 1   i f   Y 2 > 0 0   i f   Y 2 ≤ 0
Marginal effects for the joint probability is calculated as follows:
P ( Y 1 = 1   and   Y 2 = 1 ) Φ
Here, Y1 is the access to informal credit, and Y2 is the use of informal credit in agriculture. Φ represents the cumulative distribution function of the standard normal distribution, X1 to Xk are independent variables, and ɛ1 and ɛ2 are error terms. This model enables the simultaneous analysis of factors influencing access to informal credit and the subsequent use of credit in agricultural activities among the surveyed households.
Prior to estimating the bivariate probit model, the variance inflation factor (VIF) test was performed to test for multicollinearity among the covariates. The explanatory variables have values less than 10 (Table A1), which denotes that the covariates are not correlated. Therefore, we included them in the model estimation.

3.4. Specification of Selected Variables

Our investigation into the role of households in accessing and utilizing informal credit within the agricultural sector was guided by a comprehensive examination of ten key factors. Each variable was selected based on its relevance to agricultural contexts and potential influence on farmers’ financial behaviors, as evidenced by the existing literature. It was anticipated that the age of the household head, which represents the accumulated wisdom and decision-making process, will positively impact access to credit and use in agriculture, which aligns with findings from previous studies [30,31,32]. Furthermore, it was hypothesized that higher levels of education will enhance community members’ access to credit and use in agriculture, as education fosters awareness of the benefits of informal credit within the community [31,33]. It was anticipated that household size will significantly influence both access to credit and use in agriculture. This hypothesis is based on the assumption that larger families often translate to increased social relationships [14,34]. Additionally, the landholding size was taken into consideration, with the hypothesis that farmers with larger landholdings may demonstrate a higher level of participation in informal credit utilization due to their more profound involvement in agricultural activities [14,34].
Monthly income was examined to understand its role in shaping farmers’ likelihood of participating in informal credit arrangements. Active participation in community meetings, as suggested by previous studies [14,34], is explored as a factor influencing community engagement in informal credit access. Positive relationships among farmers and with neighbors and relatives are recognized as crucial social dynamics impacting participation in informal credit arrangements [14,34]. Access to input markets was examined for its potential influence on farmers’ participation in informal credit, given the significance of inputs in agriculture [14,35]. Considering the behavioral aspect, perceived risk is evaluated to understand how farmers’ perceptions of uncertainty about repayment may influence their decisions to participate in informal credit arrangements [36]. Lastly, the role of extension services in facilitating farmer participation in informal credit arrangements was explored [37].

3.5. Research Hypotheses

Previous studies documented that socioeconomic variables are key determinants of access to credit [1,19]. We hypothesized that these factors similarly impact informal credit access in the context of smallholder farmers in Pakistan.
H1: 
Socioeconomic factors such as age, education level, household size, farming experience, farm size, and income significantly influence farmers’ access to informal credit in mountainous regions.
Informal credit networks often rely on trust and social connections [19]. Therefore, we hypothesized that farmers who have stronger relationships within their communities (e.g., with fellow farmers or local leaders) are more likely to access informal credit.
H2: 
Farmers with stronger social networks are more likely to access informal credit.
Informal credit plays a significant role in sustaining agricultural activities, especially when formal credit is inaccessible [17]. We hypothesized that farmers who obtain informal credit will primarily allocate it towards agriculture to meet their farming needs.
H3: 
Farmers who access informal credit are more likely to use it for agricultural purposes.

4. Results

4.1. Descriptive Statistics

Table 1 presents the descriptive statistics of the variables used in our study, providing insights into the characteristics of the sample population and key factors under consideration for the analysis. The average age of the household head is 40.60 years, reflecting the mature composition of the sample, with a standard deviation of 12.12. Education levels, measured in years of formal education, show an average of 3.54 years with a standard deviation of 4.19, suggesting a diverse educational background within the sample. Household size, indicating the total number of family members, averages at 12.44, with a standard deviation of 3.90, portraying variations in family structures among participants. Farming experience, a crucial factor in agricultural contexts, exhibits an average of 26.82 years, accompanied by a standard deviation of 10.36, reflecting the substantial expertise within the sample. Landholding size, measured in acres, records an average of 3.00 with a standard deviation of 2.98, shedding light on the distribution of agricultural land among participants. The average monthly income of the households surveyed is PKR 25,045.9. For context, the national average monthly salary in Pakistan was approximately PKR 46,000 in 2024, highlighting that the surveyed households generally earn below the national average [38]. Participation in monthly village meetings is captured by the variable “Meeting participation”, with an average of 0.51, denoting that, on average, approximately half of the farmers actively engage in these meetings. Positive relationships with other farmers, neighbors, and relatives are reflected in the variables “Farmers relationship” and “Neighbors/relatives relationship” with averages of 0.82 and 0.71, respectively. Access to input markets is measured through the variable “Input market access”, exhibiting an average of 0.62, suggesting a moderate level of access among participants. Perceived risk, representing uncertainty about repayment, demonstrates an average of 0.61, indicating a balanced perception among participants. Finally, “Extension contact”, indicating contact with agricultural extension services, records an average of 0.36, suggesting that, on average, a significant portion of the sample has limited contact with extension services.
These descriptive statistics provide a comprehensive overview of the sample characteristics, laying the groundwork for further analysis of the factors influencing informal credit access and utilization within the agricultural sector.

4.2. Credit Access and Its Utilization in Agriculture

A total of 210 respondents, or 70% of the sample, reported having access to informal credit within the agricultural context. This indicates that a substantial portion of the sample engages with credit mechanisms. Further delving into credit utilization in agriculture, 195 respondents reported actively using credit for agricultural purposes, accounting for 65% of the total sample. This highlights a significant proportion of the sample leveraging credit to support their agricultural activities. Examining the adequacy of the credit received, 100 respondents, or 33% of the total, reported receiving an amount they deemed adequate for their agricultural needs. This finding underscores the varied perceptions among respondents regarding the sufficiency of the credit amounts obtained for farming. It suggests that there is a notable prevalence of informal credit access and utilization within the agricultural sector, with a significant proportion of respondents actively using credit to support their farming activities.

4.3. Strategies in Covering Farm-Related Expenses in Case of Credit Scarcity

This study delved into the diverse strategies employed by respondents to address farm-related expenses in instances where credit was deemed inadequate. Among the respondents who showed that credit was inadequate, 15% reported opting to work extra hours, showcasing a commitment to supplementing income through increased labor efforts. Additionally, a significant majority, constituting 69% of the sample, embraced a strategy of partial fulfillment of their needs, demonstrating a pragmatic and prioritized approach to managing expenses without sufficient credit. Furthermore, 16% of the respondents engaged in a multi-connection initiative, highlighting a diversified and proactive approach to address the challenge of inadequate credit by exploring multiple avenues. These findings underscore the resourcefulness and adaptability of individuals within the agricultural context, showcasing a range of strategies employed to ensure the fulfillment of farm-related expenses when faced with limitations in credit access.

4.4. Main Sources of Farm-Related Credit

This study documented the principal sources of credit utilized by respondents for agricultural activities (Figure 2). A relatively modest proportion of the sample (8.6%) reported family and close relatives or resource-rich farmers as their main source of credit. These findings reflect the less important role that family ties and wealthy peers play in providing financial support for the development of local farming systems. In contrast, a substantial majority (58.1%) of farmers relied on friends as their primary source of credit, underscoring the importance of social networks in providing financial resources within the farming community. Additionally, one in four farmers (24.8%) reported drawing credit from multiple sources, illustrating a diversified approach to securing financial support for their agricultural activities. These findings highlight the intricate network of relationships and channels through which individuals access informal credit to meet their agricultural financial needs.

4.5. Conditions Required by Money Lenders to Provide Loans to Farmers

This study also examined the conditions set by lenders when extending loans to individuals involved in agricultural activities. Notably, 27% of the respondents reported that lenders imposed conditions related to agreed timing for loan disbursement or repayment. This finding suggests that a considerable proportion of borrowers were subject to specific timing agreements when accessing credit. In contrast, a significant majority of our respondents (73%) reported securing loans without specified conditions. This prevalent practice indicates that a substantial portion of borrowers within the agricultural context accessed credit without being subject to explicit terms or requirements. These results underscore the diverse nature of loan provision practices observed among the study participants, with some borrowers experiencing conditions tied to timing while others enjoyed a more flexible and condition-free borrowing process.

4.6. Factors Influencing Access to Informal Credit and Its Utilization in Agriculture

Appropriate diagnostic tests including the likelihood ratio χ2 test and the likelihood ratio (rho = 0) were used to validate the model fit and the explanatory power of the bivariate probit regression model. The likelihood ratio test (rho = 0) with an χ2 (1) value of 94.844 is significant at 1%, implying the presence of cross-correlation between the residuals of the credit access and utilization equations. Therefore, estimating the two models simultaneously is justified. Meanwhile the likelihood ratio χ2 (22) values of 99.65 is significant at the 1% level, which shows that the covariates explain the variations in the response variable, hence the model fits the data.
The bivariate probit regression analysis revealed three significant factors influencing both the access to and utilization of informal credit in agriculture. Positive relationships with fellow farmers demonstrated a substantial impact, with a coefficient of 1.261 for access to informal credit and 0.632 for its use in agriculture, both statistically significant at the 1% level (Table 2). Similarly, positive relationships with neighbors and relatives exhibited significant effects, with a coefficient of 0.692 for access to informal credit and 0.688 for its use in agriculture, both statistically significant at the 1% levels, respectively. Additionally, a lower perceived risk significantly influenced both access to and the use of informal credit, as indicated by coefficients of −0.382 and −0.323, both statistically significant at the 5% level. These findings underscore the importance of social relationships and risk perception in the dynamics of informal credit within the agricultural context.

5. Discussion

The descriptive statistics presented in Table 1 provide a comprehensive overview of the sample population and key variables pertinent to our study, emphasizing critical socioeconomic factors. The mature composition of the household heads aligns with findings in rural development studies indicating that age significantly impacts decision making in agricultural practices [39]. The diversity in educational levels underscores the ongoing challenges in educational access in rural areas, which is in line with studies emphasizing the correlation between educational attainment and agricultural productivity [40]. The large household sizes found in our study suggest potential labor availability but also stress on resources, a common trend in rural agrarian economies [41]. It is noteworthy that the substantial farming experience reported in our study indicates a deep reservoir of practical knowledge, which is essential for sustainable farming practices [37]. The average small landholding size found in our study, coupled with income disparities, mirrors the fragmented land ownership and income variability typical in developing regions [42]. Moderate participation in village meetings and positive social relationships indicate the importance of social capital in rural community dynamics [43]. Access to input markets (average of 0.62) and perceived risk (average of 0.61) demonstrate the critical role of market accessibility and risk perception in influencing agricultural investments [44]. Finally, our study revealed an absence of extension contact, underscoring the necessity for enhanced agricultural advisory services. This is consistent with the literature advocating for increased extension support to boost agricultural innovation and productivity [45]. These insights underscore the multifaceted nature of rural livelihoods and the intricate interplay of socioeconomic factors shaping agricultural outcomes.
This study highlights the critical role of informal credit access and usage within the agricultural sector, with most respondents accessing informal credit and actively using it for agricultural purposes. Our findings confirm that H3 farmers who access informal credit are more likely to use it for agricultural purposes. These findings align with the existing literature that emphasizes the importance of informal credit in rural areas, where formal financial services are often limited [46]. The adequacy of credit remains a significant concern, with many respondents believing that the credit they received was insufficient. For sufficient credit, such farmers stressed easy access to formal credit. This resonates with the quotation: “The informal credit I get is always insufficient. I use informal credit because I can’t afford formal credit. I am poor and perhaps may not be able to repay the loan on time to formal or either to informal sources. I am very scared of taking out loans. The government should help the poor and helpless. We should be given easy access to formal credit so that we can afford to buy everything needed for farming” When faced with inadequate credit, most of the respondents opted for a partial fulfillment of their needs, highlighting their pragmatic approach. Additionally, the reliance on social networks is evident in our study, where most respondents cited friends as their main credit source, demonstrating the pivotal role of social capital [47]. The varied conditions for loan provision, with some respondents experiencing specific timing agreements, reflect the diverse nature of informal lending practices. The sentiment underscores this: “Specifies a specific time by which it (the borrowed money) must be repaid”. Moreover, strained relationships and disputes with relatives were reported as barriers to obtaining loans, impacting farming activities and leading some to abandon cultivation. This study underscores the multifaceted challenges and adaptive strategies within the agricultural context, highlighting the need for improved formal credit access and support to enhance farming systems productivity and resilience.
The bivariate probit regression analysis underscores the pivotal role of social capital in determining access to and utilization of informal credit in agriculture. The substantial coefficients (Table 2) for positive relationships with fellow farmers highlight how strong social ties facilitate financial support mechanisms within rural communities. This finding aligns with our hypothesis, emphasizing the importance of social networks in informal credit acquisition. It also aligns with the existing literature suggesting that social networks significantly enhance economic activities in agrarian contexts by providing both material and informational resources [48,49]. Farmers often rely on trusted relationships to secure informal credit, which may not be available through formal financial institutions. The farmers’ sentiment exemplifies this finding: “Due to a dispute with my relatives and strained relationships, they do not lend me money. Consequently, I am unable to meet the essential needs for my farming. My land is situated by the river, and I cannot construct protective walls or stone barriers around the field because of the lack of a loan. Despite preparing my land for cultivation and putting in one or two years of hard work, the water washes away my crops. Frustrated, I have now ceased cultivation. I have been growing poplar trees for the past four years. If I can sell the poplar wood this year or the next, I will endeavor to prepare my land again for cultivation”. Strengthening social cohesion among farmers can thus be a strategic focus to improve credit access and agricultural productivity.
Positive relationships with neighbors and relatives also emerged as significant informal credit access and use determinants. This emphasizes the broader community’s role in providing financial support, further illustrating the embeddedness of economic activities in social structures [50]. The importance of familial and neighborly support networks in rural areas is well-documented, showing that these relationships often serve as safety nets in times of financial need [51]. The farmers’ ability to leverage these networks can mitigate risks and sustain agricultural activities even in the absence of formal credit systems. This is reflected in the field observations: “My land is situated along the riverbank, and often floods sweep it away. Right now, my friends cannot lend me enough money to build protection walls. I have to manage with what I have and with what my friend can lend me”. These findings suggest that policies aimed at strengthening community ties and enhancing mutual support mechanisms could be beneficial in promoting financial resilience and agricultural productivity.
The analysis also reveals that perceived risk significantly negatively influences both access to and use of informal credit. This suggests that higher perceived risks deter both the offering and acceptance of credit within informal networks. Farmers’ reluctance to take on debt due to fears of repayment challenges is a critical barrier, as highlighted by the sentiment: “I am poor and perhaps may not be able to repay the loan on time. I am very scared of taking out loans. The government should help the poor and helpless. We should be given easy access to formal credit so that we can afford to buy everything needed for farming”. This insight aligns with studies showing that risk perceptions heavily influence borrowing behaviors in rural economies [52]. Lowering perceived risks, perhaps through better risk management strategies and improved extension services, could enhance credit uptake and utilization, fostering more resilient agricultural practices. Overall, these findings stress the intertwined nature of social dynamics and risk perception in shaping the informal credit landscape in agriculture.
The results from the bivariate probit analysis in Table 2 demonstrate that while social capital factors such as relationships with fellow farmers and neighbors significantly influence both access to and the utilization of informal credit in agriculture, certain demographic and socioeconomic variables (e.g., age, education, farming experience) did not yield significant effects. These results suggests that, contrary to our hypothesis, these socioeconomic variables (e.g., age, education, farming experience) do not play a critical role in determining informal credit access in this context. The non-significance of these factors could be explained by the entrenched reliance on informal social networks in rural areas, where credit access is less dependent on individual attributes and more influenced by trust and mutual support within communities [53,54]. Age and education, though traditionally thought to affect financial decisions, may not play a critical role in informal credit arrangements, as these networks tend to prioritize long-standing relationships and shared community risks rather than formal indicators of creditworthiness [55]. Moreover, farming experience may have limited influence due to the lack of formal record-keeping or collateral-based lending mechanisms, which contrasts with formal credit systems that place greater weight on such variables [56]. These findings highlight the critical importance of social relationships over personal or economic factors in rural financial behaviors, underscoring the need for policies that strengthen community networks to enhance financial resilience.

6. Conclusions and Recommendations

6.1. Conclusions

This research uniquely highlights the underexplored dynamics of informal credit in a mountainous region like Dir-Kohistan, adding new insights to the broader discourse on credit access in geographically isolated and vulnerable environments. This study analyzes farmers’ access to informal credit and usage for sustainable agriculture. With a substantial 70% reporting access to informal credit, farmers actively leverage credit (65%) to support their agricultural activities. Diverse strategies emerge for addressing inadequacies in credit, with 15% opting for increased labor, 69% prioritizing needs, and 16% engaging in multi-connection initiatives. Social networks, especially friends (58.1%), play a crucial role in credit sources. The findings from the bivariate probit regression analysis offer valuable insights into the determinants of access to and utilization of informal credit in the agricultural sector. Positive relationships with fellow farmers and neighbors/relatives emerged as significant factors positively influencing both the access to and use of informal credit. Furthermore, a lower perceived risk significantly impacted the likelihood of accessing and utilizing informal credit.

6.2. Recommendations

These findings contribute to the existing literature by offering specific policy recommendations for regions where formal credit access is limited, providing a framework for supporting smallholder farmers in similar contexts globally. This study recommends cultivating and strengthening positive relationships among farmers and communities through facilitated networking events by extension services and agricultural programs to enhance social ties, fostering a supportive environment for informal credit access. Mitigating perceived risks associated with informal credit requires targeted interventions such as educational programs and awareness campaigns. Policymakers are advised to recognize the importance of social relationships in the agricultural credit landscape and consider developing policies supporting community-based lending practices to enhance the overall financial well-being of farmers.

6.3. Limitations of this Study

This study is subject to certain limitations. It focuses exclusively on informal credit access and utilization and does not consider farmers’ access to formal credit markets. Further research could investigate the interaction between formal and informal credit systems to gain a more comprehensive understanding of credit access in agriculture.

Author Contributions

Conceptualization, A.U., M.B., M.Y.M. and V.V.; methodology, A.U.; software, A.U.; validation, A.U., M.Y.M. and F.A.; formal analysis, A.U.; investigation, A.U.; resources, M.B. and V.V.; data curation, A.U. and M.Y.M.; writing—original draft preparation, A.U. and V.V.; writing—review and editing, V.V.; visualization, A.U. and V.V.; supervision, M.B.; project administration, M.B.; funding acquisition, M.B. and V.V. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Faculty of Tropical AgriSciences, grant numbers 20233102 and 20243103.

Institutional Review Board Statement

Ethical review and approval were waived for this research because the data were collected anonymously and no personal identifiable information was gathered.

Data Availability Statement

The authors confirm that the data supporting the findings of this study will be available from the corresponding author upon reasonable request.

Acknowledgments

We would like to express our sincere gratitude to the farmers, extension agents, and officials of the Agriculture and Forest Department for their invaluable support and cooperation.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Table A1. Results of multicollinearity test.
Table A1. Results of multicollinearity test.
VariableVIF1/VIF
Age2.8490.351
Farming experience2.4780.404
Input market access1.580.633
Landholding size1.5530.644
Household size1.3680.731
Relations with relatives1.3480.742
Relations with other farmers1.3230.756
Education1.2880.776
Meeting participation1.2880.776
Monthly income1.2030.831
Excess to extensions1.1650.859
Perceived risk1.2330.732
Mean VIF1.556

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Agriculture 14 01764 g001
Figure 1. Location of the study site.
Figure 1. Location of the study site.
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Agriculture 14 01764 g002
Figure 2. Main sources of credit utilized in agriculture by farmers in study site (n = 210).
Figure 2. Main sources of credit utilized in agriculture by farmers in study site (n = 210).
Agriculture 14 01764 g002
Table 1. Variable definitions and descriptive statistics.
Table 1. Variable definitions and descriptive statistics.
VariableDescription of Variables and MeasurementMean (S.D.)
AgeAge of the household head (in years)40.60 (±12.12)
EducationEducation of a household head (in years)3.54 (±4.19)
Household sizeTotal number of family members in a household12.44 (±3.90)
Farming experienceTotal farming experience of the household head (years)26.82 (±10.36)
Landholding sizeTotal agricultural land owned by the household head (in acres)3.00 (±2.98)
Monthly incomeMonthly income of the household head25,045.9 (±17,341.54)
Meeting participation1 if the farmer actively participates in monthly village meetings led by key decision makers, 0 otherwise0.51 (±0.50)
Relations with relative1 if the farmer has a positive relationship with all other farmers, 0 otherwise0.82 (±0.38)
Relations with other farmers1 if the farmer has a positive relationship with all neighbors and relatives, 0 otherwise0.71 (±0.45)
Input market access1 if the individual has access to input markets, 0 otherwise0.62 (±0.48)
Perceived risk1 if the individual perceives a risk of uncertainty about repayment, 0 otherwise0.61 (±0.43)
Extension contacts1 if the individual has contacts with agricultural extension services, 0 otherwise0.36 (±0.48)
Table 2. Factors influencing the access to and utilization of informal credit in agriculture (Bivariate probit regression).
Table 2. Factors influencing the access to and utilization of informal credit in agriculture (Bivariate probit regression).
VariableAccess to Informal CreditUtilization Of Informal Credit
Coeff (S.E.)M.E. (S.E.)Coeff (S.E.)M.E. (S.E.)
Age0.005 (0.012)0.001 (0.003)0.016 (0.011)0.005 (0.004)
Education−0.033 (0.023)−0.008 (0.004)−0.014 (0.021)−0.004 (0.007)
Household size0.016 (0.027)0.004 (0.007)0.038 (0.025)0.012 (0.008)
Farming experience−0.013 (0.013)−0.003 (0.003)−0.012 (0.012)−0.004 (0.004)
Landholding size0.032 (0.038)0.008 (0.010)−0.038 (0.033)−0.012 (0.010)
Monthly income−0.029 (0.101)−0.007 (0.026)0.053 (0.091)0.017 (0.029)
Extension contacts−0.139 (0.188)−0.036 (0.049)0.033 (0.176)0.010 (0.056)
Relations with relative0.692 (0.205) ***0.179 (0.051)0.688 (0.196) ***0.222 (0.058)
Relations with other farmers1.261 (0.233) ***0.329 (0.051)0.632 (0.227) ***0.203 (0.069)
Meeting participation−0.319 (0.204)−0.083 (0.052)−0.307 (0.186) *−0.097 (0.058)
Input market access0.017 (0.213)0.004 (0.055)0.282 (0.204)0.089 (0.064)
Perceived risk−0.382 (0.209) **−0.094 (0.056)−0.323 (0.191) **−0.083 (0.049)
Constant−0.423 (1.164) −1.733 (1.058)
Diagnostic tests
Number of observations300
LR χ2 (22)99.65 ***
LR test of rho χ2 (1)94.84 ***
Log likelihood−259.222
Notes: S.E.—Standard Error, M.E.—Marginal Effect; *** Significant at 1%, ** Significant at 5%, * Significant at 1%.
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Ullah, A.; Verner, V.; Madaki, M.Y.; Adams, F.; Bavorova, M. Factors Influencing Informal Credit Access and Utilization among Smallholder Farmers: Insights from Mountainous Regions of Pakistan. Agriculture 2024, 14, 1764. https://doi.org/10.3390/agriculture14101764

AMA Style

Ullah A, Verner V, Madaki MY, Adams F, Bavorova M. Factors Influencing Informal Credit Access and Utilization among Smallholder Farmers: Insights from Mountainous Regions of Pakistan. Agriculture. 2024; 14(10):1764. https://doi.org/10.3390/agriculture14101764

Chicago/Turabian Style

Ullah, Ayat, Vladimir Verner, Mustapha Yakubu Madaki, Faizal Adams, and Miroslava Bavorova. 2024. "Factors Influencing Informal Credit Access and Utilization among Smallholder Farmers: Insights from Mountainous Regions of Pakistan" Agriculture 14, no. 10: 1764. https://doi.org/10.3390/agriculture14101764

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