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Empowering farmers: Unveiling the economic impacts of contract farming on red chilli farmers’ income in Magelang District, Indonesia

  • Diah Angreheni , Rahim Darma EMAIL logo and Letty Fudjaja
Published/Copyright: June 27, 2024
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Open Agriculture
From the journal Open Agriculture Volume 9 Issue 1

Abstract

Contract farming is widely recognised as an empowering tool to improve the welfare of farmers in developing countries and as an institutional solution to address issues related to market failure, credit, insurance, and information. This research endeavours to scrutinise the socio-economic distinctions between farmers engaged in contract farming and those not involved in such agreements. Additionally, it seeks to identify the factors influencing farmers’ participation in contract farming schemes and assess the impact of such arrangements on the income of red chilli farmers. The study, conducted in Magelang District, included 40 respondents from contract farmers and 45 from non-contract farmers. Employing the probit model, the ordinary least square model, and the treatment effect by Heckman, the research aimed to estimate the income impacts of existing contract farming. The findings revealed a noteworthy 57.50% increase in farmers’ incomes attributed to enhanced productivity and effective product management within the context of contract farming. Moreover, contracted farmers demonstrated advanced socio-economic conditions, boasting higher levels of education, knowledge, productivity, and agricultural assets compared to their non-contracted counterparts.

Keywords: contract farming; red chilli; farmer income.

1 Introduction

Contract farming is vital for empowering farmers in developing countries by providing immediate access to resources, stable markets, and knowledge transfer [1]. Farmers benefit from essential supplies and technology in the short term, leading to increased productivity and income stability [2]. Long-term advantages include exposure to broader markets, adopting sustainable practices, and risk mitigation through insurance against crop failure. However, the success of contract farming hinges on fair and transparent agreements, necessitating effective governance and regulatory oversight to protect farmers’ rights and ensure equitable partnerships with agribusinesses [3,4].

In Indonesia, partnerships have been codified into law to enhance farmers’ bargaining position and augment their income. According to the Law of the Republic of Indonesia No. 9 of 1995, partnerships are defined as collaborations between small businesses and medium-sized or large businesses, facilitated by guidance and ongoing development provided by the latter. This cooperation adheres to mutual need, strengthening, and benefit principles. Further clarification on the concept of partnership is outlined in Government Regulation No. 744 of 1997, elucidating the ideal form of collaboration as mutually reinforcing, mutually beneficial, and mutually complementary. The objective of these partnerships, as emphasised, is to increase income and business sustainability, enhance the quality of partner group resources, scale up business operations, and foster the growth and improvement of the capabilities of independent business groups [5,6,7].

Red chilli, as a vital horticultural product, grapples with the challenge of substantial price fluctuations, exerting a considerable impact on inflation in Indonesia [8]. The volatility in pricing poses a significant hurdle for the red chilli market, creating uncertainty in the supply of raw materials for the red chilli-based food industry. One proposed solution to address this issue is the implementation of contract farming, which is considered an effective measure to mitigate the challenges associated with red chilli production. Despite this, numerous cases indicate that adopting the contract farming system does not consistently yield the intended results and, in some instances, perpetuates a systematic marginalisation of farmers. This system places farmers in intense competition with large-scale chilli core businesses, often resulting in a loss of independence and a persistent state of dependency for the farmers involved.

Contract farming is a contractual arrangement for a fixed period between farmers and companies agreed verbally or in writing before the production process begins. The company provides material or financial resources to farmers [9,10]. It establishes one or more product or process requirements to produce the agricultural landowner or farmer who gives the company legal rights to (most) crops in marketing [11]. The agreement typically outlines specific product or process requirements, delineating the agricultural landowner’s or farmer’s responsibilities. In return for these resources and adherence to stipulated conditions, the company is granted legal rights to (most) crops, facilitating their involvement in the marketing process [11]. This structured relationship sets the framework for a collaborative partnership to benefit both parties involved in the agricultural production and marketing process.

The Magelang District, a prominent red chilli production hub in Central Java Province, is pivotal in contributing to regional and national agricultural outputs. According to the data from the Bureau of Statistics (BPS) in 2020, the district accounts for a substantial 10–11% of the overall red chilli production in Central Java or approximately 1.5–2.0% of the national production total. Despite being Indonesia’s third-largest red chilli producer, following North Sulawesi and Gorontalo provinces, Central Java’s Magelang District stands out due to its significant output. However, the average productivity of red chilli in this district exhibits considerable variability, ranging from 5.49 to 7.20 tons per hectare. This fluctuation in productivity poses challenges for local farmers, as the red chilli crop is particularly susceptible to rapid rot, damage, and significant shrinkage. These inherent characteristics of the crop introduce risks associated with production, quality, and pricing for red chilli farmers in Magelang District. The substantial volume of red chilli production, combined with the challenges farmers face, underscores the need for effective strategies and interventions to enhance the resilience and sustainability of red chilli farming in the region.

The contract system is often characterised as a “dynamic partnership” between small farmers and large businesses, a mutually beneficial arrangement where both parties are intact. This system is a valuable tool for technology transfer, contributing to political and economic stability by facilitating income distribution and promoting modern agriculture [3,12,13]. It plays a significant role in establishing and sustaining partnership systems [6]. The foundation of this partnership lies in social capital, encompassing elements such as networks, trust, and norms [14,15,16]. These components strongly influence the development and sustainability of partnerships, with the farming contract serving as the cohesive force. Through contract farming, companies can efficiently organise production and marketing activities, facilitate technology transfer, and, in turn, enhance agricultural production and marketing, ultimately contributing to an increase in farmers’ income.

Numerous research consistently confirms the positive impact of contract farming on farmers’ income and their ability to enhance the cultivation and marketing of agricultural produce [12,13,17,18]. Participation in contract farming provides farmers with crucial access to agricultural inputs, equipment, machinery, credit, and technical knowledge, not only improving their agricultural practices but also reducing the uncertainty associated with earnings from farming activities [1,3,11,19–23]. Beyond the immediate economic benefits, contract farming has been shown to play a significant role in reducing absolute poverty while concurrently raising income and welfare for participating farmers [12,24,25]. This multifaceted positive impact underscores the pivotal role of contract farming in advancing not only the economic standing of farmers but also more extensive social and welfare improvements. Additionally, supporting studies reinforce the idea that contract farming positively influences the status of farmers [10,26]. As demonstrated, several studies that contract farming not only facilitates farmers’ access to agricultural resources and knowledge but also contributes to the reduction of income uncertainty in their farming businesses [27–29].

Numerous studies evaluated in this review analyse contract farming, specifically emphasising relatively perishable commodities that experience minimal price fluctuations. Most contract farming in Indonesia is also conducted with the reciprocal support of corporations and farmers, which the government additionally supports. Nevertheless, this research focuses on contract farming in Indonesia, particularly chilli commodities susceptible to significant price variations. The companies provide the impetus for contract farming to ensure farmers receive equitable prices, maintain quality, and secure a guaranteed supply. Furthermore, this research compares the socio-economic attributes of farmers involved in contract farming and those not engaged in such activities.

This study examines the socio-economic disparities between farmers with contracts and those without contracts. The primary objectives of this study are to examine the variances, determine and assess the factors that influence farmers’ decisions to participate in contract farming, and explore the impact of contract farming on the income of red chilli farmers. This study also aims to investigate the variations, ascertain and evaluate the determinants that affect farmers’ choices to engage in contract farming, and analyse the effects of contract farming on the earnings of red chilli farmers.

This study seeks to address the multifaceted dynamics of contract farming by advocating for targeted policy interventions, promoting sustainable agricultural practices, improving farmers’ economic conditions, and encouraging a deeper understanding of the phenomenon beyond anecdotal evidence.

2 Methods

The selection of Magelang District as our research location is crucial for comprehending a fundamental element of agricultural dynamics in Central Java: the cultivation of red chillies. This district is an excellent choice for three studies since it is well-known for its significant role in red chilli growing. This makes it an ideal location for analysing the complexities of contract farming.

The survey research was conducted in three sub-districts in the Magelang district’s chilli-producing hub, explicitly targeting the company’s affiliated farmers. The respondents were chosen using a stratified systematic random selection approach, with 32% selected from each sub-district chilli farmer population list to ensure that the minimal requirement of 30% was satisfied for statistical analysis. The study included 40 partner farmers and 45 non-partner farmers. By sampling from these areas, the study aims to capture a representative cross-section of the agricultural community, ensuring a comprehensive understanding of the region’s socio-economic dynamics in contract and non-contract farming (Table 1).

Table 1

Number of chilli farmer populations and selected respondents were based on the sub-district of the chilli production centre in Malang District

Sub-district Partner (farmer) Respondent (farmer) Non-partner Respondent (farmer)
Srumbung 45 15 50 15
Kaliangkrik 20 6 25 10
Pakis 60 19 65 20
Total 125 40 140 40

The study employed a robust analytical methodology, utilising the probit model. The estimation involved employing least squares (ordinary least square [OLS]) and treatment effect methodologies by Heckman, with a particular emphasis on correcting potential selection bias in the data [30]. This meticulous approach to data analysis enhances the reliability and accuracy of the findings, shedding light on the complexities and nuances of red chilli production in the region. As a result, the study contributes valuable insights that can inform policies and practices for contract and non-contract red chilli farmers in Magelang District and serve as a model for similar agricultural contexts in Central Java.

The data collected are the age of the head of the family (years), farmer’s education (years), wife’s education (years), cultivated land (ha), number of workers working in agriculture (persons), agricultural equipment value (IDR), business income per year (IDR), non-farming income per year (IDR), total household income per year (IDR), production (kg), and annual red chilli net income (IDR).

The collected data for this study encompass diverse critical variables, each shedding light on various facets of the agricultural landscape. These variables include the age of the head of the family, providing insights into the demographic composition of the farming households. The educational background of the farmer and their spouse, measured in years of education, is an essential indicator of the knowledge and skills available within the household. The extent of cultivated land, measured in hectares, is a crucial parameter illustrating the scale of agricultural operations. The number of workers engaged in agricultural activities provides valuable information about the labour force involved. The value of agricultural equipment, quantified in the currency of Indonesian Domestic Rupiah (IDR), offers a glimpse into the technological infrastructure supporting farming operations.

The economic dimensions are also comprehensively covered, with variables such as business income per year, non-farming income per year, and total household income per year, all measured in IDR. These metrics help gauge the economic well-being of farming households, considering both agricultural and non-agricultural revenue streams. Production, measured in kilograms, and productivity, expressed as kilograms per hectare, provide a detailed understanding of the efficiency and output of red chilli cultivation. Finally, the annual net income from red chilli production, measured in IDR, encapsulates the financial returns directly associated with this specific agricultural activity. This comprehensive set of data points ensures a robust and holistic examination of the various factors influencing red chilli farming and its economic implications for households in the study area.

This study takes a comprehensive approach to analyse the socio-economic dynamics of farmers engaged in contract farming versus those who do not adopt this practice. The research employs both descriptive qualitative analysis and T-test methodologies to discern and quantify the differentiation in the socio-economic status of these two groups. The focus extends specifically to agricultural income, which serves as a crucial metric reflecting the economic well-being of farming households.

The broader context of farm income is explored by examining its connection to various productive assets within each household. As the literature outlines, agricultural income can be intricately linked to productive assets such as labour, production input, agricultural equipment, and cultivated land [31]. This approach enables a nuanced understanding of the multifaceted factors influencing income generation in the farm sector, particularly concerning contract and non-contract farming practices. By delving into the intricacies of these productive assets, the study aims to unravel the impact of contract farming on the overall income profile of farming households, contributing valuable insights to the ongoing discourse on sustainable agricultural practices and economic outcomes.

The equation of agricultural income is the following:

(1) Y = β 0 + β 1 X 1 + β 2 X 2 + β 3 X 3 + β 4 X 4 + δ I i + μ i , i = 1 , 2 , … , k ,

where Y is the agricultural income (IDR/ha), β 0 is the constant, β 1, β 2, β 3, β 4 represent coefficients, X 1 is the cultivated land (ha), X 2 is the household labour in agriculture (people), X 3 is the value of agricultural equipment (IDR), X 4 is the input cost (IDR), I i is the dummy (l i = 1 if the farmer participates in contract farming, and l i = 0 if the farmer does not participate in contract farming), and μ i is the error term.

According to Greene (2008), estimation μ in the equation using only OLS can lead to overestimation. This study uses a two-step estimate introduced by Heckman under the name Heck it models or treatment effect model to correct this correction bias.

The first step, the probit model (equation (2)), is used to calculate the inverse Mills ratio, λ i , for the correction of bias caused by independent selection problems [32]. The formula used to calculate the inverse Mills ratio is the following:

(2) I × I = β 0 + β i X i + ε i ,

where I × I is the dependent variable, β 0 is the intercept, β i is the coefficient, X i is the independent variables, and Ɛ i is the error.

The second step is to run OLS regression by entering the variable λ i in equation (3). A correlation of error terms in equation (1), μ i in equation (2), and ε i was found. The application of the treatment effect model in this study uses one assumption for bias correction, that is, the correlation of μ i and ε i is the normal distribution. The inverse Mills ratio, λ i , is included in equation (1), then the OLS regression model is the following:

(3) Y = β 0 + β 1 X 1 + β 2 X 2 + β 3 X 3 + β 4 X 4 + δ I i + β λ λ i + v i , i = 1 , 2 , 3 , 4 , … , k ,

where Y is the agricultural income (IDR/ha), β 0 is the constant, β 1, β 2, β 3, β 4 represent coefficient, X 1 is the cultivated land (hectare), X 2 is the household labour in agriculture (person), X 3 is the value of agricultural equipment (IDR), X 4 is the input cost (Rp), I i is the dummy (l i = 1 if the farmer participates in contract farming, and l i = 0 if the farmer does not participate in contract farming), λ i is the inverse Mills ratio, βλ is the coefficient of inverse Mills ratio, and v i is the error term.

3 Results and discussion

3.1 Comparison socio-economic of contract farming farmers and non-contract farming farmers

The broader context of farm income is explored by examining its connection to various productive assets within each household. As the literature outlines, agricultural income can be intricately linked to productive assets such as labour, production input, agricultural equipment, and cultivated land [31]. This approach enables a nuanced understanding of the multifaceted factors influencing income generation in the farm sector, particularly concerning contract and non-contract farming practices. By delving into the intricacies of these productive assets, the study aims to unravel the impact of contract farming on the overall income profile of farming households, contributing valuable insights to the ongoing discourse on sustainable agricultural practices and economic outcomes.

However, it is noteworthy that the company did not initially recognise the farmer group of Ngudi Mulyo Magelang, as a company grower. Instead, the company preferred the farmer group of Karya Bakti Pemalang, which already had a company status – company grower. In the operational framework, the farmer group of Ngudi Mulyo Magelang facilitates the company by coordinating with farmers and managing the flow of goods delivery and administration. Despite not being considered a formal grower, the company conducts its payment procedures for red chilli through the Ngudi Mulyo Magelang farmer group, emphasising a collaborative and mutually beneficial approach. The company follows a weekly payment schedule, ensuring a steady and predictable income for the farmers involved in red chilli production in Magelang District.

The survey results support the observable impacts of contract farming initiatives in Magelang District, which reveal that 62% of the respondents observed a substantial increase in chilli production. Moreover, in order to address the inherent difficulties in red chilli cultivation, collaborative efforts between farmers and growers have proven to be effective strategies, highlighting the concrete advantages of these alliances in enhancing agricultural output and overcoming regional obstacles. The findings of this study unequivocally confirm the capacity of contract farming arrangements in Magelang District to bring about significant changes, including increased agricultural productivity and strengthened sustainability and resilience in red chilli farming methods. Chilli farmers in the study area have notably maintained contract cultivation agreements with select companies since 2015.

The outcomes of the farmer survey unequivocally underscore the crucial role of contract farmers, who exhibit notable advantages in agricultural assets, production levels, and productivity. These contract farmers tend to reside closer to growers, are characterised by a younger and more productive age demographic, and generally have higher educational attainment than their non-contract counterparts. Table 2 provides a comprehensive overview of the distinctive characteristics of contract and non-contract farmers. The statistical analysis reveals significant differences, with contracted farmers achieving a remarkable 61.6% higher yields, 40% greater family work productivity, and a farm income that surpasses that of non-contracted farmers by 57%.

Table 2

Descriptive statistics: comparison between contract and non-contract farmers

Variable Mean t-stat Std error difference (Sig two-tailed)
Non-contract farmer Contract farmer
Age of household head (year) 52.4 41.25 −5.683 1.962 0.000***
Education of household head (year) 9.77 11.10 2.861 0.462 0.005***
Education of spouse (year) 9.02 10.63 4.117 0.389 0.000***
Cultivated land (hectare) 0.21 0.22 0.242 143.952 0.809
Distance to grower house (m) 770.57 294.87 −14.537 32.723 0.000***
Household labour in agriculture (person) 39.82 48.25 2.728 3.088 0.008***
Value of agricultural equipment (IDR 10,000) 66.29 1,047.81 252.731 38.836 0.000***
Production (tonnes) 1.14 2.08 7.728 121.720 0.000***
Productivity (tonnes/ha) 5.84 13.45 16.593 4,58.831 0.000***
Household agricultural income per annum (IDR 10,000) 3,926.90 4,931.31 3.614 2,778.950 0.001***
Household off-farm income per annum (IDR 10,000) 122.74 1,963.65 16.147 1,140.170 0.000***
Constant total household income per annum (IDR 10,000) 6,064.50 7,245.96 3.598 3,283.520 0.001***
Net income from red chilli (IDR 10,000) 2,975.61 3,853.60 3.246 2,704.460 0.002***

Note: ***significant at 1% level.

Interestingly, despite these significant differences in productivity and income, the average land area for non-contracted farmers is not statistically different from that of contracted farmers, indicating a comparable land area involvement for both groups. The survey also sheds light on the initiation of contract farming, with around 70% of the farmers reporting that the grower initially approached them. Conversely, 30% actively sought out growers to engage in contract farming. The primary motivations for joining contract farming include stable or guaranteed fixed prices (53%), assured marketing opportunities (24%), and access to information aimed at improving quality (13%). The results confirm the concrete advantages of contract farming collaborations in Magelang District, with a significant 62% rise in chilli production and practical measures taken to address obstacles in red chilli growing. The data highlight the critical and positive influence of contract farming on agricultural results and the development of a more sustainable and prosperous farming environment in the region. Conversely, farmers often hesitate to engage in contract farming because they are worried about trust issues, limited bargaining power, dependence on the market, less independence, increased input costs, and a preference for traditional farming practices. To address these challenges, it is imperative to undertake a targeted and cooperative endeavour to promote contract farming agreements that are transparent and equitable, empower farmers, and build alternative systems of support. By addressing these concerns, individuals or groups with a vested interest or concern in the matter can enhance the resilience and sustainability of small-scale farming in Indonesia, enabling it to better resist and recover from obstacles.

Based on the socio-economic research, contract farmers demonstrate better socio-economic conditions compared to the socio-economic conditions of non-contract farmers. Contracted farmers are better educated, demonstrate better knowledge, are highly productive, and exhibit more agricultural assets than non-contract farmers. The conclusion is that contract farmers are more developed and advanced compared to non-contract farmers [12]. The research results also support the better socio-economic situation of contract farmers. Contract farmers in Cambodia demonstrate productive ages and are growing farmers [12]. The production and productivity of contract farmers are better because contract farmers already demonstrate contracts with companies with higher product quality standards, making them work harder while diligently taking care of their crops according to the standards requested by the company. Similar studies show contract farming in China and Cambodia [26]. Based on the research, the apple farmers in China experienced an average increase in productivity of 47.966 kg/ha compared to non-contracted farmers, and rice farmers in Cambodia experienced an average increase in productivity of 1.65 MT/ha compared to non-contracted farmers.

The socio-economic research findings unequivocally highlight the enhanced conditions of contract farmers compared to their non-contract counterparts. Contracted farmers exhibit superior education levels, possess more extensive knowledge, showcase higher productivity, and boast a more substantial array of agricultural assets. The overarching conclusion drawn from the research is that contract farmers, as a group, are more developed and advanced regarding socio-economic indicators when contrasted with non-contract farmers. This pattern is not unique to the studied region, as similar trends have been observed in Cambodia. It reveals that contract farmers in Cambodia are not only in their productive prime but are also characterised as progressive growers [12].

Contract farmers’ productivity and production advantages can be attributed to their engagement in contractual agreements with companies that uphold stringent product quality standards. This commitment propels contract farmers to work diligently and adhere to the specified criteria, resulting in a superior output. Parallel studies in different regions, such as China, substantiate this phenomenon and found that apple farmers engaged in contract farming experienced a substantial average increase in productivity of 47.966 kg/ha compared to their non-contracted counterparts [26]. It is similarly reported in Cambodia that rice farmers racticing contract farming demonstrated an average increase in productivity of 1.65 MT/ha compared to non-contracted farmers [12]. These consistent findings underscore the positive impact of contract farming on individual farmers and the overall socio-economic landscape, emphasising the potential for such arrangements to foster agricultural development and productivity.

3.2 Econometric analysis of participation and its effect on income

The initial phase of the econometric analysis involves thoroughly examining the distinctions in the characteristics between contract and non-contract farmers. To discern the factors influencing participation in agricultural contract schemes, the researcher employs the probit model, a statistical method well-suited for modelling binary outcomes.

Table 2 presents the chi-square test results conducted as part of the probit analysis. The significance of the differences in values is determined by the p-value, where, in this case, a p-value less than 0.05 is considered statistically significant. The chi-square value of 1,224,247 further reinforces the statistical significance of the analysis. The data scrutinised in this context suggest that the model is suitable and exert a notable influence. These findings signify a robust foundation for delving deeper into the nuanced dynamics that shape farmers’ decisions to engage in contract farming, providing valuable insights into the factors influencing their participation in such agricultural schemes.

Table 3 unveils substantial disparities in the outcomes of the probit test, elucidating the influential factors shaping farmer participation in contract farming. The observed differences in characteristics between contract and non-contract farmers encompass crucial aspects such as the age of the head of the family, education levels of both the head of the family and the spouse, the geographical proximity between the farmer’s residence and the grower, the monetary value of agricultural equipment, income generated outside of farming activities, and production costs. These distinct characteristics collectively contribute to the nuanced profile of contracted farmers, giving them advantages in staying informed about the latest agricultural information and fostering collaborative knowledge-sharing partnerships. The significance of these variations underscores the intricate interplay of socio-economic and geographical factors that play a pivotal role in influencing farmers’ decisions to engage in contract farming, shedding light on the multifaceted nature of agricultural participation and partnership dynamics in the studied context.

Table 3

Result of analysis on contract farming participation by Probit Model

Variable Coef. Std. Err. Z p > {Z}
Dependent variable: Contract farming participation (Dummy)
Age of household head (year) −0.013 0.001 −11.626 0.000***
Education of household head (year) −0.023 0.006 −4.080 0.000***
Education of spouse (year) 0.066 0.007 9.826 0.000***
Cultivated land (ha) 0 0 −1.448 0.148
Distance to grower house (m) 0.001 0 14.062 0.000***
Household labour in agriculture (person) 0 0.001 −0.484 0.629
Value of agricultural equipment (IDR 10,000) 0 0 6.645 0.000***
Input cost (IDR 10,000) 0 0 5.068 0.000***
Household off-farm income per annum (IDR 10,000) 0 0 −12.979 0.000***
Constant 1.486
Pearson chi-square 6,507.090
Prob > chi-square 0
Predicted
Actual 1 0 Total
1 40 5 45
0 0 40 40
Total 40 45 85

Note: ***significant at 1% level.

Smallholder chilli farms demonstrate a preference for contract farming for a multitude of reasons. Initially, it provides farmers with a secure market and fixed price for their crops, reducing the potential dangers linked to market price changes. Additionally, contract farming facilitates the acquisition of high-quality inputs such as seeds, fertilisers, and technology, leading to enhanced yields and increased product quality. Furthermore, engagement in contract farming sometimes includes providing technical support and training, which improves the farmers’ expertise and abilities. Moreover, contract farming agreements may consist of financial facilities, enabling farmers to invest in their productivity. In addition, farmers can mitigate post-harvest losses by participating in contract farming, which provides improved market connections and access to appropriate storage and transportation infrastructure. Finally, contract farming has the potential to offer a consistent and reliable source of income, thereby minimising unpredictability and enhancing the overall well-being of farmers and their families.

In contrast, smallholder chilli farmers tend to abstain from contract farming arrangements for various reasons. These include apprehensions regarding trust, restricted leverage, reliance on the market, relinquishment of autonomy, escalating input expenses, and a preference for conventional farming techniques [25,33]. Their apprehensions influence their decision-making, causing them to choose agricultural methods that are more familiar and independent.

Additionally, they live closer to the grower than non-contract farmers, so it becomes the more significant reason for the participation of farmers in contract farming. Farmers who participate in contract farming demonstrate and higher value of farming equipment, incentivising non-contract farmers to participate in contract farming. With contract farming, many farmers do business other than cultivation, such as processing, fertiliser manufacturing, seed breeding, and selling agricultural equipment and materials [19,34]. Farmers who participate in contract farming will incur higher input costs so that the red chilli quality can meet the company’s quality standards [6,12].

The decision of farmers to engage in contract farming is intricately tied to two pivotal factors – the farmers’ productive age and their educational attainment. Young and highly educated farmers emerge as key players in this landscape, as their dynamism and educational background equip them with the agility needed to stay abreast of the latest advancements in information and technology within the realm of red chilli farming – the intersection of youth and education positions these farmers to navigate the evolving landscape of modern agriculture efficiently.

Furthermore, the proximity between the farmer’s residence and the grower plays a significant role in this decision-making process. As the distance between the farmer’s house and the grower diminishes, the impact on the farmer’s decision to participate in contract farming becomes even more pronounced. The proximity facilitates a robust flow of information from the grower to the farmer, particularly concerning the intricacies of contract farming. The ease of access to information becomes a crucial determinant, and farmers benefit from a substantial amount of knowledge the grower shares. In essence, this geographical closeness enhances the collaborative nature of contract farming partnerships, fostering an environment where information exchange is efficient and effective, contributing to the success and sustainability of such agricultural arrangements.

The proximity of a farmer’s residence to a grower’s house emerges as a robust predictor of participation in contract farming initiatives [12]. The likelihood of farmers engaging in contract farming significantly increases when they are in close geographic proximity to growers. This phenomenon reflects a diminished social distance between farmers and growers, indicating a more interconnected community and aligning with the grower’s interest in consolidating production in smaller, localised areas. As suggested, various selection criteria exist for becoming contract farmers, particularly concerning the availability of suitable locations for participation [26].

Moreover, contend that contract farmers are not a random sample of the overall population; they differ significantly, particularly in their impact on income. These differences encompass observable characteristics such as land size and education and non-observable traits like persistence and intelligence. The income disparity between contract farmers and other smallholders reflects not only the direct effects of the contract itself but also these inherent characteristics. This nuanced understanding underscores the complex interplay between geographical proximity, individual factors, and economic outcomes. It emphasises the need for comprehensive assessments to study contract farming dynamics and their impact on farmers’ livelihoods.

Contract farming emerges as a versatile pathway for farmers, offering more than the traditional scope of cultivation and providing a platform for diverse business ventures. Participants in contract farming benefit from the flexibility to engage in various segments of the agricultural value chain, encompassing processing, fertiliser, seed breeding, and the sale of farm equipment and materials. A critical factor influencing farmers’ decision to partake in contract farming is the meticulous consideration of production costs. These costs span a broad spectrum, from adhering to company regulations when acquiring seeds to procuring fertilizers for contract and non-contract farmers. Agricultural fertilisers, organic fertilisers, and other operational expenses associated with agricultural activities are also covered under production costs. The level of investment directed towards agricultural production inputs becomes a pivotal factor in steering farmers towards contract farming. Increased commitment and investment in these inputs heighten the likelihood of farmer participation in contract farming, highlighting the intricate relationship between production costs and the strategic choices made by farmers in navigating the agricultural landscape.

Contract farmers, driven by the imperative to meet higher quality standards set by the contracting companies, are compelled to produce superior-quality products. To offset the additional production costs associated with contract farming, provisions are made for market research, transportation, and packaging. Growers play a crucial role in this process, providing a harvest basket of contracted product packaging, offering valuable information about market prices, and covering transportation costs for the contracted products. This collaborative approach ensures the fulfilment of quality requirements. It establishes a framework where additional costs associated with contract farming are effectively managed and shared between company and farmers, fostering a symbiotic relationship within the agricultural ecosystem [35].

The second phase of the econometric analysis involves a regression using OLS to model agricultural or farming income, considering various factors such as different incomes from cultivation businesses and dummy variables representing contract farmers. Table 4 encapsulates the impact of contract farming on farm income, as indicated by treatment effect results. Significant factors influencing the augmentation of farm income include input costs, the value of agricultural equipment, and participation in contract farming. Simultaneously, household labour in agriculture and land area does not significantly influence farm income. Among these variables, three demonstrate a substantial effect in increasing income in contract farming. The results highlight the remarkable significance of the value of agricultural equipment, participation in contract farming, and input costs.

Table 4

Effect of contract farming on an agricultural income: Treatment effect results

Variable Coef. Std. Err. T p > {t}
Dependent variable: Agricultural income (IDR 10.000)
Household labour in agriculture (person) 9.961 12.158 0.819 0.415
Value of agricultural equipment (IDR 10,000) 1.989 0.356 5.587 0.000***
Cultivated land (ha) −35.244 28.468 −1.238 0.219
Input cost (IDR 10,000) 0.107 0.053 2.019 0.047**
Contract farming participation (dummy) 2,052.219 278.318 7.374 0.000***
Constant 1,008.353 1,447.817 0.696 0.489
Inverse Mills ratio 0.865 0.706 1.225 0.224
F 13.837
R² 0.684
Prob > F 0

Note: **Significant at 5% level, ***significant at 1% level.

The outcomes of the analysis suggest that these three variables contribute significantly to the increase in income, with the overall effect of contract farming accounting for 57.50%. This underscores the substantial impact of contract farming, particularly with company partners. Notably, the results project that farmers who embrace contract farming experience a considerable increase in agricultural income by IDR 624,516,068. This numerical representation underscores the tangible economic benefits reaped by farmers participating in contract farming arrangements, providing valuable insights into the financial implications of such partnerships within the agricultural sector.

The comprehensive multiple linear regression analysis yields valuable insights, affirming that certain variables significantly influence farm income within the context of contract farming. Notably, the key determinants emerging from the study are the value of agricultural equipment, production costs, and participation in contract farming. Among the four variables assessed for their impact on increasing income in contract farming, it is evident that the value of agricultural equipment, participation in contract farming, and production costs exhibit noteworthy significance. On the contrary, neither the extent of household labour engaged in contract farming nor the area of land cultivated substantially impacted the growth of agricultural income in the Magelang district. Farmers who cultivate intensive crops, such as red chilli, typically employ many family labourers on a small land area. In this study, for instance, farmers managed a land area of 0.20 ha with tiny data variations; therefore, the land area has no statistically significant influence on the regression analysis. These findings provide a nuanced understanding of the specific factors that contribute to the economic outcomes of contract farming in the region, elucidating the complex interplay between various variables and their distinct roles in shaping the financial dynamics of farmers engaged in contract farming arrangements.

The impact of contract farming on farms’ income is discernible through significant influences on the augmentation of agricultural income and the farm assets farmers own. Specifically, there is a notable increase in the value of farm equipment and input costs, contributing to the overall rise in income. This resonates with findings from a study on farmers in Cambodia, where agricultural equipment, cultivated land, and participation in contract farming were identified as factors influencing the increase in farm income. Extending beyond the local context, international studies corroborate the positive financial outcomes associated with contract farming [12]. Noteworthy examples are contract participants in dairy farming in Vietnam [19], participants in contract farming of shallots and apples in China [26], participants in organic coffee contract farming in Uganda [36], and multinational contract farming case studies [37]. These collective findings underscore the global validity of the positive correlation between contract farming participation and increased income, highlighting the potential of contract farming as a catalyst for enhanced financial prosperity in diverse agricultural settings.

The symbiotic relationship between contract farming and companies engaging in such arrangements manifests as a powerful mechanism for securing markets, facilitating agricultural technology transfer, enhancing access to agricultural inputs, and ultimately bolstering the bargaining power of farmers to achieve better yields. The study focused on contract farming between red chilli farmers and a company in Magelang District resonates with the findings of several prior studies. Collectively, these studies emphasise the potential for unity and complementarity between contract farming initiatives and companies or farmer organisations. Through contract farming, farmers gain the assurance of a guaranteed market for their products, forging a collaborative bond that not only secures their market position but also empowers them with increased bargaining leverage [38]. This interdependence exemplifies how strategic agricultural partnerships can contribute to the sustainability and prosperity of farmers and companies involved, creating a win–win scenario within the complex farm production and marketing landscape [39].

The contract farming model employed by the company partner stands out as an inclusive and encompassing system. Probit model statistical analysis reveals that productive assets, such as agricultural household labour and agricultural size, do not significantly determine farmer participation. This means that both small- and large-scale farmers can participate in the contract, irrespective of the size and capacity of their productive assets. This inclusive approach contrasts with the challenges often associated with conventional contract farming, where literature highlights companies’ preference for medium- and large-scale farmers due to easier regulation, coordination, and management of contracts at this scale [40,41]. Transaction costs are also lower when dealing with medium- and large-scale farmers, contributing to the preference for this category.

However, the company deviates from this trend by not excluding small farmers from contract participation. While working with small farmers may incur higher management costs, Indofood, a farmer-owned entity, prioritises inclusivity. The company operates with a broader business goal, aiming for profitability and social impact. The company embraces a more community-centric and inclusive approach by not excluding small farmers, recognising the diverse landscape of agricultural participants, and striving for a balance between economic viability and social responsibility.

4 Conclusion

Contracted farmers emerge as a more developed and advanced cohort, showcasing superior socio-economic conditions compared to their non-contracted counterparts. This disparity is marked by contracted farmers possessing higher levels of education, enhanced knowledge, heightened productivity, and a more extensive array of agricultural assets. The partnership with the company provides contracted farmers with increased bargaining power, translating into higher profits. Contract farmers adhere to elevated quality standards, aligning with the company’s stringent requirements. This commitment to quality is complemented by provisions for market research, efficient transportation, and meticulous packaging, effectively offsetting the additional production costs associated with contract farming. The study’s findings underscore the prominence of contract farming partnerships in cultivating staple foods or horticultural crops for local and national consumption. Beyond its specific focus, this study offers a methodology to discern the causal factors influencing farming contracts on red chilli farms’ performance and farmers’ income. The insights from this research provide valuable groundwork for future studies within agricultural products, fostering a deeper understanding of the dynamics shaping the outcomes of contract farming arrangements.

Acknowledgments

The authors sincerely appreciate all individuals and organisations that contributed to this research. They are particularly grateful to the Ministry of Agriculture of the Republic of Indonesia for granting permission and providing a scholarship to support this study. Furthermore, we express our deep gratitude to the Directorate General of Higher Education and the Ministry of Education and Culture of the Republic of Indonesia to the supervising lecturers, whose constant support and direction played a crucial role in successfully guiding this research to completion.

  1. Funding information: The thesis research was supported financially by the Ministry of Agriculture, the Directorate General of Higher Education, and the Ministry of Education and Culture in completing this study.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and consented to its submission to the journal, reviewed all the results, and approved the final version of the manuscript. RD and DA contributed to conceptualisation, methodology, writing – review and editing, funding acquisition; DA and LF contributed to data collection; and LF contributed to investigation and data analysis.

  3. Conflict of interest: Authors state no conflict of interest.

  4. Data availability statement: The datasets generated for the study’s data analysis are accessible from the corresponding author upon reasonable request.

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Received: 2024-01-23
Revised: 2024-04-25
Accepted: 2024-05-09
Published Online: 2024-06-27

© 2024 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  148. Corrigendum
  149. Corrigendum to “Bioinformatics investigation of the effect of volatile and non-volatile compounds of rhizobacteria in inhibiting late embryogenesis abundant protein that induces drought tolerance”
  150. Corrigendum to “Composition and quality of winter annual agrestal and ruderal herbages of two different land-use types”
  151. Special issue: Smart Agriculture System for Sustainable Development: Methods and Practices
  152. Construction of a sustainable model to predict the moisture content of porang powder (Amorphophallus oncophyllus) based on pointed-scan visible near-infrared spectroscopy
  153. FruitVision: A deep learning based automatic fruit grading system
  154. Energy harvesting and ANFIS modeling of a PVDF/GO-ZNO piezoelectric nanogenerator on a UAV
  155. Effects of stress hormones on digestibility and performance in cattle: A review
  156. Special Issue of The 4th International Conference on Food Science and Engineering (ICFSE) 2022 - Part II
  157. Assessment of omega-3 and omega-6 fatty acid profiles and ratio of omega-6/omega-3 of white eggs produced by laying hens fed diets enriched with omega-3 rich vegetable oil
  158. Special Issue on FCEM - International Web Conference on Food Choice & Eating Motivation - Part II
  159. Special Issue on FCEM – International Web Conference on Food Choice & Eating Motivation: Message from the editor
  160. Fruit and vegetable consumption: Study involving Portuguese and French consumers
  161. Knowledge about consumption of milk: Study involving consumers from two European Countries – France and Portugal
https://doi.org/10.1515/opag-2022-0300
Keywords for this article
contract farming; red chilli; farmer income.
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Articles in the same Issue

  1. Regular Articles
  2. Supplementation of P-solubilizing purple nonsulfur bacteria, Rhodopseudomonas palustris improved soil fertility, P nutrient, growth, and yield of Cucumis melo L.
  3. Yield gap variation in rice cultivation in Indonesia
  4. Effects of co-inoculation of indole-3-acetic acid- and ammonia-producing bacteria on plant growth and nutrition, soil elements, and the relationships of soil microbiomes with soil physicochemical parameters
  5. Impact of mulching and planting time on spring-wheat (Triticum aestivum) growth: A combined field experiment and empirical modeling approach
  6. Morphological diversity, correlation studies, and multiple-traits selection for yield and yield components of local cowpea varieties
  7. Participatory on-farm evaluation of new orange-fleshed sweetpotato varieties in Southern Ethiopia
  8. Yield performance and stability analysis of three cultivars of Gayo Arabica coffee across six different environments
  9. Biology of Spodoptera frugiperda (Lepidoptera: Noctuidae) on different types of plants feeds: Potency as a pest on various agricultural plants
  10. Antidiabetic activity of methanolic extract of Hibiscus sabdariffa Linn. fruit in alloxan-induced Swiss albino diabetic mice
  11. Bioinformatics investigation of the effect of volatile and non-volatile compounds of rhizobacteria in inhibiting late embryogenesis abundant protein that induces drought tolerance
  12. Nicotinamide as a biostimulant improves soybean growth and yield
  13. Farmer’s willingness to accept the sustainable zoning-based organic farming development plan: A lesson from Sleman District, Indonesia
  14. Uncovering hidden determinants of millennial farmers’ intentions in running conservation agriculture: An application of the Norm Activation Model
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  18. UrbanAgriKG: A knowledge graph on urban agriculture and its embeddings
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  22. Effects of selected biostimulants on qualitative and quantitative parameters of nine cultivars of the genus Capsicum spp.
  23. Growth, yield, and secondary metabolite responses of three shallot cultivars at different watering intervals
  24. Design of drainage channel for effective use of land on fully mechanized sugarcane plantations: A case study at Bone Sugarcane Plantation
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  28. Efficiency of rice farming in flood-prone areas of East Java, Indonesia
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  35. Exploring innovative food in a developing country: Edible insects as a sustainable option
  36. Genotype by environment interaction and performance stability of common bean (Phaseolus vulgaris L.) cultivars grown in Dawuro zone, Southwestern Ethiopia
  37. Factors influencing green, environmentally-friendly consumer behaviour
  38. Factors affecting coffee farmers’ access to financial institutions: The case of Bandung Regency, Indonesia
  39. Morphological and yield trait-based evaluation and selection of chili (Capsicum annuum L.) genotypes suitable for both summer and winter seasons
  40. Sustainability analysis and decision-making strategy for swamp buffalo (Bubalus bubalis carabauesis) conservation in Jambi Province, Indonesia
  41. Understanding factors affecting rice purchasing decisions in Indonesia: Does rice brand matter?
  42. An implementation of an extended theory of planned behavior to investigate consumer behavior on hygiene sanitation-certified livestock food products
  43. Information technology adoption in Indonesia’s small-scale dairy farms
  44. Draft genome of a biological control agent against Bipolaris sorokiniana, the causal phytopathogen of spot blotch in wheat (Triticum turgidum L. subsp. durum): Bacillus inaquosorum TSO22
  45. Assessment of the recurrent mutagenesis efficacy of sesame crosses followed by isolation and evaluation of promising genetic resources for use in future breeding programs
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  48. Near-infrared technology in agriculture: Rapid, simultaneous, and non-destructive determination of inner quality parameters on intact coffee beans
  49. The synergistic application of sucrose and various LED light exposures to enhance the in vitro growth of Stevia rebaudiana (Bertoni)
  50. Weather index-based agricultural insurance for flower farmers: Willingness to pay, sales, and profitability perspectives
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  53. Determination of C-factor for conventional cultivation and soil conservation technique used in hop gardens
  54. Empowering farmers: Unveiling the economic impacts of contract farming on red chilli farmers’ income in Magelang District, Indonesia
  55. Evaluating salt tolerance in fodder crops: A field experiment in the dry land
  56. Labor productivity of lowland rice (Oryza sativa L.) farmers in Central Java Province, Indonesia
  57. Cropping systems and production assessment in southern Myanmar: Informing strategic interventions
  58. The effect of biostimulants and red mud on the growth and yield of shallots in post-unlicensed gold mining soil
  59. Effects of dietary Adansonia digitata L. (baobab) seed meal on growth performance and carcass characteristics of broiler chickens: A systematic review and meta-analysis
  60. Analysis and structural characterization of the vid-pisco market
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  62. A brief investigation on the prospective of co-composted biochar as a fertilizer for Zucchini plants cultivated in arid sandy soil
  63. Supply chain efficiency of red chilies in the production center of Sleman Indonesia based on performance measurement system
  64. Investment development path for developed economies: Is agriculture different?
  65. Power relations among actors in laying hen business in Indonesia: A MACTOR analysis
  66. High-throughput digital imaging and detection of morpho-physiological traits in tomato plants under drought
  67. Converting compression ignition engine to dual-fuel (diesel + CNG) engine and experimentally investigating its performance and emissions
  68. Structuration, risk management, and institutional dynamics in resolving palm oil conflicts
  69. Spacing strategies for enhancing drought resilience and yield in maize agriculture
  70. Composition and quality of winter annual agrestal and ruderal herbages of two different land-use types
  71. Investigating Spodoptera spp. diversity, percentage of attack, and control strategies in the West Java, Indonesia, corn cultivation
  72. Yield stability of biofertilizer treatments to soybean in the rainy season based on the GGE biplot
  73. Evaluating agricultural yield and economic implications of varied irrigation depths on maize yield in semi-arid environments, at Birfarm, Upper Blue Nile, Ethiopia
  74. Chemometrics for mapping the spatial nitrate distribution on the leaf lamina of fenugreek grown under varying nitrogenous fertilizer doses
  75. Pomegranate peel ethanolic extract: A promising natural antioxidant, antimicrobial agent, and novel approach to mitigate rancidity in used edible oils
  76. Transformative learning and engagement with organic farming: Lessons learned from Indonesia
  77. Tourism in rural areas as a broader concept: Some insights from the Portuguese reality
  78. Assessment enhancing drought tolerance in henna (Lawsonia inermis L.) ecotypes through sodium nitroprusside foliar application
  79. Edible insects: A survey about perceptions regarding possible beneficial health effects and safety concerns among adult citizens from Portugal and Romania
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  96. Analysis of agricultural emissions and economic growth in Europe in search of ecological balance
  97. Bacillus thuringiensis strains with high insecticidal activity against insect larvae of the orders Coleoptera and Lepidoptera
  98. Technical efficiency of sugarcane farming in East Java, Indonesia: A bootstrap data envelopment analysis
  99. Comparison between mycobiota diversity and fungi and mycotoxin contamination of maize and wheat
  100. Evaluation of cultivation technology package and corn variety based on agronomy characters and leaf green indices
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  102. Phytochemical composition and insecticidal activity of Acokanthera oblongifolia (Hochst.) Benth & Hook.f. ex B.D.Jacks. extract on life span and biological aspects of Spodoptera littoralis (Biosd.)
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  105. Interannual variations of normalized difference vegetation index and potential evapotranspiration and their relationship in the Baghdad area
  106. Harnessing synthetic microbial communities with nitrogen-fixing activity to promote rice growth
  107. Agronomic and economic benefits of rice–sweetpotato rotation in lowland rice cropping systems in Uganda
  108. Response of potato tuber as an effect of the N-fertilizer and paclobutrazol application in medium altitude
  109. Bridging the gap: The role of geographic proximity in enhancing seed sustainability in Bandung District
  110. Evaluation of Abrams curve in agricultural sector using the NARDL approach
  111. Challenges and opportunities for young farmers in the implementation of the Rural Development Program 2014–2020 of the Republic of Croatia
  112. Yield stability of ten common bean (Phaseolus vulgaris L.) genotypes at different sowing dates in Lubumbashi, South-East of DR Congo
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  115. Evaluation of relative drought tolerance of grapevines by leaf fluorescence parameters
  116. Yield assessment of new streak-resistant topcross maize hybrids in Benin
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  131. The false tiger of almond, Monosteira unicostata (Hemiptera: Tingidae): Biology, ecology, and control methods
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  135. Potential influence of nitrogen fertilizer rates on yield and yield components of carrot (Dacus carota L.) in Ethiopia: Systematic review
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  138. The potential of phosphorus-solubilizing purple nonsulfur bacteria in agriculture: Present and future perspectives
  139. Minor millets: Processing techniques and their nutritional and health benefits
  140. Meta-analysis of reproductive performance of improved dairy cattle under Ethiopian environmental conditions
  141. Review on enhancing the efficiency of fertilizer utilization: Strategies for optimal nutrient management
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  143. Motivations for farmers’ participation in agri-environmental scheme in the EU, literature review
  144. Evolution of climate-smart agriculture research: A science mapping exploration and network analysis
  145. Short Communications
  146. Music enrichment improves the behavior and leukocyte profile of dairy cattle
  147. Effect of pruning height and organic fertilization on the morphological and productive characteristics of Moringa oleifera Lam. in the Peruvian dry tropics
  148. Corrigendum
  149. Corrigendum to “Bioinformatics investigation of the effect of volatile and non-volatile compounds of rhizobacteria in inhibiting late embryogenesis abundant protein that induces drought tolerance”
  150. Corrigendum to “Composition and quality of winter annual agrestal and ruderal herbages of two different land-use types”
  151. Special issue: Smart Agriculture System for Sustainable Development: Methods and Practices
  152. Construction of a sustainable model to predict the moisture content of porang powder (Amorphophallus oncophyllus) based on pointed-scan visible near-infrared spectroscopy
  153. FruitVision: A deep learning based automatic fruit grading system
  154. Energy harvesting and ANFIS modeling of a PVDF/GO-ZNO piezoelectric nanogenerator on a UAV
  155. Effects of stress hormones on digestibility and performance in cattle: A review
  156. Special Issue of The 4th International Conference on Food Science and Engineering (ICFSE) 2022 - Part II
  157. Assessment of omega-3 and omega-6 fatty acid profiles and ratio of omega-6/omega-3 of white eggs produced by laying hens fed diets enriched with omega-3 rich vegetable oil
  158. Special Issue on FCEM - International Web Conference on Food Choice & Eating Motivation - Part II
  159. Special Issue on FCEM – International Web Conference on Food Choice & Eating Motivation: Message from the editor
  160. Fruit and vegetable consumption: Study involving Portuguese and French consumers
  161. Knowledge about consumption of milk: Study involving consumers from two European Countries – France and Portugal
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