# Evaluation of opportunity costs in cocoa production in three ecological zones in Côte d'Ivoire

N'Golo Konaté, Auguste K. Kouakou, Yaya Ouattara, Patrick Jagoret, Yao

Sadaiou Sabas Barima

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N'Golo Konaté, Auguste K. Kouakou, Yaya Ouattara, Patrick Jagoret, Yao Sadaiou Sabas Barima. Evaluation of opportunity costs in cocoa production in three ecological zones in Côte d'Ivoire. Sustainability, 2025, 17 (16), pp.7478. 10.3390/su17167478. [hal-05415768](https://hal.science/hal-05415768v1)

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Article

# Evaluation of Opportunity Costs in Cocoa Production in Three Ecological Zones in Côte d'Ivoire

N'Golo Konaté <fnref n="1" />,* ID, Auguste K. Kouakou <fnref n="2" /> ID, Yaya Ouattara <fnref n="2" />, Patrick Jagoret <fnref n="3" />,<fnref n="4" /> and Yao S. S. Barima <fnref n="1" /> ID

## Abstract

This article examines the production costs of cocoa farming in Côte d'Ivoire, West Africa, taking into account the opportunity cost approach. To this end, surveys were conducted among 228 farmers in three regions, Bonon, Soubré and Biankouma, following an east-west gradient. The estimated costs of using family labor and land were based on the opportunity cost approach. The financial costs associated with production were also taken into account. Comparative analyses between different localities and cropping systems highlighted specific workload characteristics. Finally, a principal component analysis (PCA) was used to profile producers according to their income levels and profits. The findings showed that family labor was the main component of cocoa production costs. Prices paid to farmers did not always cover all production costs, with 38% of farmers producing at a loss, and this was contingent on the agro-ecological zone. Furthermore, the agroforestry system proved to be more economical in terms of labor than the full-sun system. These results underline the relevance of the opportunity cost approach in assessing production costs and setting cocoa selling prices. This should lead to a review of public price-setting mechanisms to ensure fair remuneration for family labor.

**Keywords:** cocoa; production cost; opportunity cost; family labor; Ivory Coast

## 1. Introduction

Agriculture is a strategic sector for many African countries. In addition to its crucial role in supporting local economies, this sector also ensures food production, thus helping to solve food security problems. While the sustainability of agriculture has long been a crucial issue for policy makers and the scientific community, it is now time to critically examine the economic viability and sustainability of farms by measuring the capacity of family farming to bear the burdens of production. The aim is to establish efficient pricing systems that adequately support farmers' incomes.

From an economic point of view, a farm is viable when the annual income generated is sufficient to cover operating costs [1]. Similarly, ref. [2] asserts that the sustainability of agriculture must be considered from the point of view of economic sustainability, which implies that income must be covered by expenses. The content of production costs therefore needs to be reconsidered to ensure a more appropriate valuation of farms.

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Academic Editor: Marco Manzone

Received: 13 February 2025

Revised: 1 April 2025

Accepted: 28 April 2025

Published: 19 August 2025

**Citation:** Konaté, N.; Kouakou, A.K.; Ouattara, Y.; Jagoret, P.; Barima, Y.S.S. Evaluation of Opportunity Costs in Cocoa Production in Three Ecological Zones in Côte d'Ivoire. *Sustainability* **2025**, *17*, 7478. https://doi.org/10.3390/su17167478

**Copyright:** © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

<footnote n="1">¹ UFR Environment, Jean Lorougnon Guédé University, Daloa P.O. Box 150, Côte d'Ivoire; byssabas@yahoo.fr</footnote>

<footnote n="2">² UFR Economic Sciences and Management, Jean Lorougnon Guédé University, Daloa P.O. Box 150, Côte d'Ivoire; augustekk@gmail.com (A.K.K.); ouattarayaya@yahoo.fr (Y.O.)</footnote>

<footnote n="3">³ CIRAD, UMR ABSys, 34398 Montpellier, France; patrick.jagoret@cirad.fr</footnote>

<footnote n="4">⁴ ESA/INP-HB, Yamoussoukro 1093, Côte d'Ivoire</footnote>

<footnote>* Correspondence: konate7ngolo@gmail.com</footnote>
In most African countries, production is essentially undertaken by the family. A large proportion of production costs, linked to the work of family members and constituting opportunity costs, do not always appear in farm financial statements. Furthermore, most studies in rural areas struggle to gather information on these costs. Indeed, ref. [3] has already highlighted the difficulties involved in estimating the cost of family labor (FL), both for economists and statisticians. Accordingly, operating accounts that do not take opportunity costs into account remain incomplete. In the specific context of cocoa farming in Côte d'Ivoire, ref. [4] also highlighted the inability of conventional economic calculations to take into account the costs associated with the use of FL and the amortization of invested capital. Contrary to a purely accounting vision, economists must take into account opportunity costs in economic evaluations, such as the cost of family labor (FLC) and the cost of using factors of production specific to the farm.

Opportunity costs are implicit costs that are not directly reflected in financial statements but which must be taken into account when calculating them [5]. For a producer, the opportunity cost is defined as the wage they forego by using their labor power on their own farm rather than selling it to other producers [6]. In this sense, ref. [7] states that it is the measure of the cost of lost opportunities, or simply the opportunity cost. From the business owner's point of view, opportunity costs represent the lost benefits of the best capital allocation compared to the one currently used [5]. In addition, opportunity costs remain important for establishing certain performance indicators, such as average company productivity [8]. To this end, an analysis of the profitability of family farms must necessarily take opportunity costs into account [9]. Hence, there is a need to develop tools to better evaluate family labor in order to more adequately determine the costs incurred.

In Côte d'Ivoire, cocoa production is characterized by a constant movement of farmers in search of fertile land. This movement is mainly due to the aging of cocoa orchards and soil impoverishment, requiring additional investment to maintain production in formerly cultivated areas [10]. To optimize production, planters are turning to land that is still intact [10–12]. This phenomenon led, particularly in the 2000s, to the migration of farmers to the savannah areas and high mountains of the west of the country to grow cocoa [13]. While this migration enables farmers to take advantage of forest rents to increase yields [10], it does not guarantee a reduction in labor costs and drudgery. Production costs can vary considerably from one locality to another due to geographical specificities.

Moreover, agroforestry, which combines agriculture and forestry, is now widely promoted in cocoa farming as an innovative solution combining sustainability and productivity [14]. However, little is known about the costs associated with this technique. Indeed, the high set-up costs of agroforestry systems sometimes cast doubt on their profitability. Furthermore, ref. [15] points out that agroforestry is more labor-intensive, which can lead to higher production costs in these systems. On the other hand, it is often argued that with very high initial costs, agroforestry systems can only be profitable in the long term through diversification of income sources [16]. To ensure their short-term viability, these systems should be accompanied by compensatory measures. However, the cocoa pricing system set up by the Ivorian government does not take into account geographical constraints or specific farming practices.

In the cocoa sector, numerous initiatives have been launched in recent years to determine a fairer income for Ivorian cocoa farmers. Among them, the Living Income initiative, supported by GIZ, brings together players from the private sector, certification bodies, representatives of civil society, governments and numerous technical experts in economic sustainability. The common ambition of these initiatives is to improve the incomes of small-scale producers, enabling them to achieve a decent standard of living. A decent income is defined as a level of income that enables producers and their households to
cover their basic needs, including food, housing, education, health, transport, and clothing, and to have a safety margin with which to deal with any unforeseen circumstances [17]. Three methods for assessing the decent income threshold (or benchmark) currently exist: the Anker method; the Wageningen method (WUR), which is an adaptation of the Anker method; and the HEA method, which is used to calculate an alternative threshold. In this regard, a survey of Ivorian cocoa farmers carried out by CIRES in 2018 using the Anker method set the decent income threshold at 262,056 CFA. This implies that for a cocoa-farming household to live decently, it needs at least 262,056 CFA per month [17]. This threshold makes it possible to determine the gap between real income and decent income, with a view to implementing measures to close the gap. However, it has to be said that most studies on income estimation tend to favor an accounting approach, taking into account only the financial costs borne by producers, and neglecting the costs borne by members of the farmer's family. Such income estimates could lead to biased differences between real income and decent income, and therefore to potentially inappropriate measures.

Aware of the poverty of cocoa producers and the low prices they receive, Côte d'Ivoire and Ghana introduced the decent income differential in September 2019. This mechanism requires private companies to pay an additional $400 per tonne above the international market price in order to increase the price paid to producers (the farmgate price). Initially, this initiative seemed to work well and was supported by industry players. However, it soon ended in total failure, with private companies refusing to pay the surplus [18]. This refusal gives the impression that these companies consider this differential to be an accessory charge, rather than a structural element of producer remuneration. However, some authors argue that sustainable cocoa production requires higher prices to induce producers to commit to sustainability programs, often with additional costs [19,20]. These authors estimate that a premium of 20.5% would be necessary, well above the 4.95% offered by certification schemes (UTZ Certified) for biodiversity-friendly cocoa. In the absence of agreement among the various players, numerous studies have been carried out to estimate a vital income for cocoa producers, notably by the Living Income Community of Practice (LICoP). These studies aim to ensure the sustainability of the cocoa industry. However, one question remains: once the living wage threshold has been defined, what mechanism can be used to bridge the gap between real income and this living wage? How can we ensure the industry's sustainability if financing remains uncertain? Would it not be more appropriate to start by seeking to improve the value of farmers' work, rather than relying on income estimates that are difficult to finance? Cocoa studies too often focus on biophysical and environmental aspects while forgetting farmers' needs for economically viable farming systems [21]. This article argues that before seeking to reduce the gap between real and decent income, it is first necessary to adequately estimate the production costs actually borne by farmers. A more rigorous approach to these costs would provide a sound basis for fairer and more sustainable remuneration policies.

A study carried out in Ghana revealed that the low incomes of cocoa farmers are mainly due to low yields, themselves affected by disease, declining soil fertility and lack of appropriate inputs [22]. In addition, producers have to cope with soaring input prices on the market [18]. This situation leads to opacity in farmers' strategies, which limits their ability to invest in production cycles. If mechanisms are not put in place to internalize the opportunity costs associated with family labor, farmers may eventually turn away from this crop in favor of other, more profitable crops. The report [23] recommends adopting a contract farming approach, where negotiations between chocolate manufacturers and farmers would result in more advantageous prices. However, the impact of such an approach on long-term sustainable economic development remains uncertain. Although beneficial for farmers, it could lead to land tenure problems, marginalization of women
and unsustainable intensification of production. In the same vein, ref. [18] warns of the risk of deforestation induced by rising cocoa prices, which could compromise the long-term sustainability of the sector. Indeed, higher prices often encourage the extension of cultivated areas through land clearance, leading to overproduction and inevitably lower prices in the long term. However, price volatility is not without consequences for the country's economy. In this sense, ref. [24] states that cocoa price fluctuations have a negative impact on economic indicators such as GDP, public spending and inflation. To ensure sustainable cocoa production, it proposed creating non-customs zones, introducing export taxes to finance diversification and redistributing quota rights to discourage free riding [19]. These approaches aim to balance economic incentives with environmental and social considerations. Thus, the internalization of opportunity costs in order to value the farmer's work must be framed by clear sustainability policies to ensure balance.

The rest of the article presents the literature review, methodology, results and discussion, followed by the conclusion.

## 2. Literature Review

The concept of opportunity cost has largely dominated economic thinking over the years and has been a key element of general equilibrium theory [7]. It is considered an essential analytical tool, usable by all economic theories. Several studies have examined its measurement in different fields. The authors of [25] evaluated the opportunity cost of carbon sequestration on tropical farms. Their conclusion is that it is less costly to sequester carbon via agroforestry systems than via purely arboreal systems. Opting for an agroforestry system would therefore represent the best alternative in terms of carbon sequestration. Even in the context of environmental conservation, it is essential to take opportunity costs into account when making optimal choices. For example, ref. [26] has examined the opportunity costs of conservation. Their approach is based on a comparison between the costs of conservation and the market-induced benefits of land use. The authors of [27] point out that there is sometimes a conflict between conservation and land use. Their study evaluated the opportunity costs of conserving the Kakamega forest in western Kenya. They concluded that conservation is the best alternative, as exploiting the forest may have adverse consequences for future generations, both locally and globally. To achieve such an option, the authors recognize that understanding the local opportunity costs associated with restricting access to forest land and resources for conservation is crucial to developing cost-effective conservation programs that reduce negative impacts on poor forest-dependent populations.

In another study, ref. [28] examined the relationship between agricultural labor and migration in order to estimate the opportunity costs of agricultural labor. They observed a significant gap between the annual income of farmers and that of migrant workers, resulting in a continuing loss of rural population. Thus, the opportunity cost of farm income is equivalent to the income of migrant workers in some cases. The European Commission report [29] showed that non-agricultural household income in Ningxia, China, accounted for over 60% of the total, reaching 79.4% in 2007. The most accurate way of estimating the opportunity cost of agricultural labor is therefore to use the maximum non-farm income. Furthermore, ref. [30] analyzed the economic performance of dairy ewe farms in Spain. In their work, a monthly wage of €1000 was used to reward family labor and an interest rate of 4% for invested capital. They concluded that when opportunity costs are taken into account, the prices received do not cover costs, and 60% of the dairy farms studied are loss-making. In light of this finding, ref. [9] argued that farmers should capitalize on their own resources, such as land, labor and capital. By highlighting the potential results of allocating these resources to other uses, they could resort to those
resources with the lowest opportunity costs. In a study carried out on rubber, oil palm and sugar cane, ref. [31] used the salary of a night watchman in town of around 500,000 FCFA to estimate the opportunity cost of the labor force of one family asset per year. Similarly, ref. [32] used industrial wages to estimate the opportunity cost of family labor. As for the opportunity cost of land, they used regional rental and sale prices.

Opportunity costs can vary according to circumstances and geographical location. It is in this sense that [33] asserted that the estimation of opportunity costs must necessarily take spatial variations into account. For farms far from urban areas, there are fewer opportunities for off-farm employment. This limits the options available to farmers in these areas, reducing their opportunity costs compared to those located close to major conurbations, who benefit more from off-farm employment opportunities. This complexity underlines the need for researchers to take into account the specificities of each situation. Nevertheless, three approaches to estimating opportunity costs have been proposed by [5] to guide future research on farms. These approaches include, firstly, the estimation of the opportunity cost of the farmer's labor, which offers two alternatives. The first assumes that the second-best alternative for farmers or their family members is to work as wage earners in agriculture, enabling them to monetize their labor power with other farmers rather than on their own farms. The second option assumes that the second best solution for the farmer or family member is to be employed in other sectors due to the relatively low incomes in agriculture. In this case, the opportunity cost is estimated by the average hourly labor cost in these sectors. Next, the opportunity cost of equity is estimated from the point of view of an investor who could have invested their capital in other investments to benefit from the interest. Finally, we estimate the opportunity cost of land, which takes into account the alternative benefits of land use for the farmer. Since the farmer is the owner of the land, they have the choice of using the land for agricultural production or using it in some other way, for example, by renting or selling it. The authors of [2] also proposed three approaches very similar to those of [5]. According to those authors, the opportunity cost of land is obtained by multiplying the quantity of land in hectares by the amount of rent in the region. Next, the opportunity cost of unpaid labor is determined by multiplying the input of unpaid labor by the average agricultural wage in the region. Finally, the opportunity cost of capital is obtained by multiplying it by the interest rate. This approach respects the criterion in [3] that, to estimate the opportunity FLC, the economist must first carry out a sound analysis of the quantity of FL and its cost components.

Rather than considering a holistic dimension, some authors, such as [34], reduce production costs to the actual expenses incurred by the producer. Conversely, ref. [35] argued that it is impossible to dispense with the evaluation of FL, given its importance for the implementation of certain agricultural techniques. By analyzing the opportunity cost of labor on the economic profitability of fertilizer microdosing in Burkina Faso, the authors showed that this technique remains economically profitable even when these costs are taken into account. The study by [36], based on close monitoring of 30 farms over three cropping seasons in the cotton-growing zone of Central Africa, showed that family working time accounted for 58% of the working time required by the farm as a whole. To estimate the opportunity cost of family labor, it is common to use the Guaranteed Minimum Interprofessional Wage (SMIG) or local daily wages for similar work. For example, a study carried out by [37] in the south and southwest of Cameroon used a unit cost of 2000 FCFA per working day to value this labor. The results of this study showed that the opportunity cost of family labor represents 40.52% of total production costs. However, when land use costs are included, this percentage rises to 76.58%, highlighting the central role of family labor in African farming systems. This dependence on family labor reflects an economic reality where producers optimize their resources in the face of significant financial
constraints. The cost of producing a kilogram of cocoa is estimated at 824.51 FCFA/kg in southern Cameroon and 621.3 FCFA/kg in southwestern Cameroon [37]. These costs vary according to yields, which in turn are influenced by various factors, including climatic conditions and the increasing incidence of cocoa diseases. Against a backdrop of climate change and a resurgence of disease, cocoa farmers are likely to face increased production costs, compromising the profitability of their farms. The economic literature therefore highlights the need to integrate opportunity costs into farm income estimates in order to obtain a more realistic assessment of farm profitability. However, this review also highlights the lack of specific studies on Ivorian cocoa farmers, which fully justifies this investigation and the need for a deeper understanding of the economic dynamics specific to this sector.

**3. Empirical Strategy**

The methodology begins with a description of the study area, then moves on to sampling and data collection, followed by a detailed description of the study population. It concludes with the methods used to estimate the financial and opportunity costs in this article.

**3.1. Study Area**

The present study was carried out in three cocoa-producing areas in Côte d'Ivoire belonging to the network of agroforestry plots of the Cocoa4Future project observatory (https://www.cocoa4future.org/le-projet/les-zones-d-intervention, accessed on 12 Febru- ary 2025). These sites were selected according to the east-west gradient, which corresponds to the evolution of the main cocoa production zones in Côte d'Ivoire [38]. The sites are located in Bonon in the central west, Soubré in the southwest and Biankouma in the west (Figure 1). The Bonon site represents the epicenter of the second cocoa-producing zone, which saw strong production in the 1990s. The Soubré site is representative of today's cocoa production zone par excellence. Finally, the Biankouma site, in the west of the country, is considered to be the future major cocoa production zone [13,38]. This site has seen strong growth in cocoa production since 2010.

<figure><img src="image_3.png" /><figcaption>**Figure 1.** Map of the study area.</figcaption></figure>
## 3.2. *Sampling and Data Collection*

One hundred and fifty (150) cocoa farms were randomly sampled on the three sites, i.e., 50 farms per site. In order to observe certain farming practices, 78 additional farmers were selected, including 25 in Bonon, 25 in Soubré and 28 in Biankouma. These additional farmers were selected on a reasoned basis with the help of project guides and technicians. The data collection tool was a questionnaire addressed essentially to the farm manager. In practice, the farmer could call on their spouse or any other family member to answer questions for which they had no answer or information. The questionnaire covered cocoa production and purchase prices, on the one hand, and production costs for the entire production chain, from the farm to the marketing of the cocoa bean, on the other. With regard to production costs, two main pieces of information have been identified. For financial costs, information was collected on the expenses directly incurred by farmers for each operation along the production chain. For social costs and family labor, the farm income method was used. In other words, it was considered that the best opportunity lost by the family member is to be hired on another farm for similar work. Information was therefore collected on the working hours of each social category in the household (men, women and children) throughout the production chain. The daily costs attributable to these household working days were also recorded. For land, the opportunity cost represents the income that would have been earned if the land had been rented to another cocoa farmer.

## 3.3. *Description of the Study Population*

The people taken into account in the estimation of social costs are the members of the household, i.e., those who are under the responsibility of the head of the family and who do not receive remuneration for carrying out tasks on the farm. In addition, the children mentioned here are household members who sometimes accompany their parents and help them with certain tasks. Thus, a child is considered to be any person living in the household and aged 15 or under. This age bracket is chosen with reference to Article 6 of the International Labour Organization, which sets the minimum age for admission to employment at 14. However, there are exceptions for light work, which can be carried out from the age of 15, under certain conditions and with the authorization of the competent authorities.

At the same time, access to information on child labor within farming families is becoming increasingly difficult for researchers, under pressure from non-governmental organizations (NGOs) and multinationals. When this issue is raised, producers can sometimes react with a certain reticence, giving the impression that they are hiding something. During the course of this study, it was found that growers may be wary of researchers, fearing that disclosure of sensitive information could have negative consequences for themselves or their families. To obtain information on this seemingly sensitive aspect, it was therefore essential to cultivate a relationship of trust with growers over time. Despite these efforts, some of them refused to address the issue, which probably resulted in a loss of information about part of the family's work.

## 3.4. *Method for Estimating Production Costs*

Production costs are made up of two main components, financial costs and social costs. While financial costs are easy to calculate, the same cannot be said for social costs, which have to be estimated.

Financial costs include, first and foremost, the cost of external labor (OUL) contracted for a year's production. In cocoa farming, certain tasks, such as shelling, are carried out through arrangements between producers. Although this work involves the use of outside labor, it does not require the payment of a wage for the outsiders invited. Nevertheless,
carrying out this work generates higher costs, as shelling is considered a party and the owner must satisfy the guests with food and drink. The costs associated with this type of task have been accounted for as self-help costs, which are then included in the costs of formal contracts to make up the total cost of OULs.

Next, the costs of agricultural inputs were accounted for. In addition, all farmer-owned equipment was inventoried, with its purchase price and useful life, in order to calculate depreciation. Finally, the last component of the financial costs concerns the cost of the OUL when the plot was created. For this cost, a 30-year depreciation is used, as the life expectancy of a cocoa plantation is between 25 and 30 years [39]. However, these data are not exact, as for plantations over 30 years old, the current farmers are not necessarily those who originally planted them. In this case, the regional average of these costs has been imputed to these farms.

To evaluate the FLC, this article adopts the opportunity cost approach. Opportunity costs in family farming are often implicit costs that are not directly measurable in monetary terms. One of the challenges is to identify all the opportunity alternatives available to farmers. These may include options such as wage labor on other farms, labor in other sectors, capital investment in other sectors, leasing farmland to third parties, etc. The opportunity costs associated with each option must then be measured in order to select the best alternative. However, this can be particularly difficult in practice due to the many uncontrollable factors specific to farmers that can influence the value of alternative opportunities. Indeed, farmers’ level of training, experience and skills in accessing other, more advantageous opportunities can make all the difference. To simplify the calculation and ensure a more objective estimate of opportunity costs, the first approach proposed by [5] has been adopted. This approach assumes that the second-best alternative for farmers is to work as salaried employees in agriculture. Although this method is the simplest, it corresponds well to the minimum reward that could be attributed to family labor. The advantage of such an approach is that it avoids calculating exaggerated opportunity costs that may not reflect reality in the farmer’s environment.

The process began by identifying all the tasks involved in the production chain. Next, the working times and costs associated with each task for men, women and children were determined. In practice, the daily costs in the region were used as the opportunity cost. Let us take the example of a farm where different tasks have to be carried out to ensure production. Men’s working time, noted $t_m$, is determined by the sum of the product of the number of men $N_{mi}$ involved in each task $i$ and the number of days $D_{mi}$ needed to complete that task. Similarly, the working time of women and children, $t_w$ and $t_c$, is calculated. Thus, the working time of men is determined as follows:

$$t_m = \sum_{i=1}^{I} N_{mi} D_{mi}, \qquad (1)$$

This means that the total working time of a farm can be expressed as follows:

$$T = \sum_{i=1}^{3} t_i, \qquad (2)$$

with $t_i$ the working time of each social category (men, women and children). This measure, expressed in man-days (Mdr), reflects the amount of human labor invested in cocoa production.

Once working times are known, opportunity costs can be calculated on the basis of daily costs. The opportunity cost of men, noted $CO_m$, is determined by the sum of the products of the daily cost of men for each task, noted $cd_i$, by the time spent by men on each
task, noted $t_{mi}$. The opportunity cost of women and children is determined by the same process. Formally, this translates into the following:

$$CO_m = \sum_{i=1}^{I} cd_i t_{mi} \quad (3)$$

The total opportunity cost, TCO, for each operator is the sum of the opportunity costs of men $CO_m$, women $CO_w$ and children $CO_c$, namely,

$$TCO = CO_m + CO_w + CO_c \quad (4)$$

The cost of land was assessed on the basis of regional rental prices, obtained by interviewing growers and resource persons such as the heads of growers’ associations. This approach was adopted because, in the production zones, we are in the second or even third generation of producers. As a result, heirs often do not remember the cost of the land, even when it was acquired by purchase.

Once production costs have been estimated, a minimum break-even point will be determined. This involves comparing the average cost of producing one kilogram of cocoa with the average purchase price on the market. The aim is to identify the purchase price that generates sufficient income to cover production costs. The cost of producing one kilogram of cocoa is calculated by dividing the total cost of production by the total quantity of cocoa produced. This break-even point represents the point at which the business becomes viable. If the purchase price falls below this threshold, producers will incur losses, making their business unviable in the long term. It is therefore essential that the purchase price not only equals, but ideally exceeds, this cost of production in order to guarantee a profit margin and enable producers to reinvest in their operations and maintain a decent standard of living. Profitability depends not only on covering costs but also on the ability to generate profits that will ensure the sustainability of the cocoa sector.

# 4. Results

## 4.1. Social Division of Labor

The results in Table 1 show that one hectare of cocoa requires 92.31 Mdr for men, 16.79 Mdr for women and 24.46 Mdr for children. In total, each farmer mobilizes 133.56 Mdr per year to cultivate one hectare of cocoa. Men are currently the most active in the production process. Of the 228 farmers surveyed, 207 (91%) work with their families on their cocoa farms. The remaining 21 (9%) hire sharecroppers or contract workers for farm work. Family work is virtually non-existent among the latter. Only 60 farmers (26%) agreed to comment on the issue of child labor.

<table><caption>**Table 1.** Estimated working times.</caption><thead><tr><th>Variables</th><th>Comments</th><th>Average</th><th>Standard Deviation</th></tr></thead><tbody><tr><td>Work time men/ha/year (Mdr)</td><td>207</td><td>92.31</td><td>56.80</td></tr><tr><td>Women's working hours/ha/year (Mdr)</td><td>166</td><td>16.79</td><td>16.02</td></tr><tr><td>Child labor hours/ha/year (Mdr)</td><td>60</td><td>24.46</td><td>22</td></tr><tr><td>Total working time/ha/year (Mdr)</td><td>207</td><td>133.56</td><td>-</td></tr></tbody></table>

Source: Authors based on survey data.

## 4.2. Farmers’ Working Hours by Zone and Cropping System

The comparison of farmers’ working time by locality is illustrated by the box plot in Figure 2. The results show that production in Biankouma requires more working time than in the other two localities (124.41 Mdr). Similarly, growers in Bonon spend more time
on production (96.91 Mdr) than those in Soubré (85.22 Mdr). To confirm these disparities, a Kruskal-Wallis test (Figure 3) was carried out after checking the normality of the data, the results of which are summarized in Figure A1 in Appendix A. The results indicate that there is indeed a significant difference between the old production zones and the new zone in terms of production time. It is more difficult to produce in the new Biankouma zone than in the old Soubré and Bonon zones.

<figure><img src="image_4.png" /><figcaption>**Figure 2.** Box plot of locations versus working time.</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>**Figure 3.** Post hoc comparisons using Dunn's test.</figcaption></figure>

In addition, the comparison of farmers' working time by cropping system is illustrated by the box plot in Figure 4. The results show that the full-sun system requires more labor time (115 Mdr) than agroforestry (89 Mdr). To confirm this difference, a Mann-Whitney comparison test was carried out. The results show that there is a significant difference between the full-sun system and agroforestry. In other words, the full-sun system requires much more labor time than the agroforestry system.

<figure><img src="image_6.png" /><figcaption>**Figure 4.** Box plot of cropping systems versus time.</figcaption></figure>
### 4.3. Estimated Production Costs

The results on production costs are summarized in Table 2. For one production cycle, farmers spend an average of 182,764 CFA on OUL. The cost of the OUL at plot creation is amortized and charged to production cycles, estimated at around 10,335 CFA. Inputs cost them an average of 54,600 CFA, while the cost of production equipment amounts to 31,770 CFA. The combination of these factors gives an average financial cost of 279,465 CFA per farmer per year.

<table><caption>**Table 2.** Cocoa production costs in CFA in 2022.</caption><thead><tr><th>Variables</th><th>Comments</th><th>Mean</th><th>Standard Deviations</th></tr></thead><tbody><tr><td>Operating costs OUL</td><td>228</td><td>182,764</td><td>288,433.1</td></tr><tr><td>Input costs</td><td>228</td><td>54,598.73</td><td>61,938.02</td></tr><tr><td>Equipment depreciation</td><td>228</td><td>31,768.03</td><td>28,058.83</td></tr><tr><td>OUL creation costs</td><td>228</td><td>10,335.07</td><td>10,814.54</td></tr><tr><td><strong>Total financial costs</strong></td><td><strong>228</strong></td><td><strong>279,465</strong></td><td><strong>317,254.2</strong></td></tr><tr><td>Operating costs FL</td><td>228</td><td>543,399.2</td><td>487,124.8</td></tr><tr><td>FL creation costs</td><td>228</td><td>27,226.7</td><td>24,412.52</td></tr><tr><td>Cost of land</td><td>228</td><td>163,670</td><td>175,169</td></tr><tr><td><strong>Total social costs</strong></td><td><strong>228</strong></td><td><strong>734,295</strong></td><td><strong>573,319</strong></td></tr><tr><td><strong>Total production costs</strong></td><td><strong>228</strong></td><td><strong>1,013,760</strong></td><td><strong>725,123.5</strong></td></tr></tbody></table>

Source: Authors based on survey data.

In addition, the average cost of LF per year is estimated at 543,400 CFA. The cost of LF when the plot is created is amortized so that it can be charged to production cycles, and is estimated at around 27,225 CFA. In addition, the cost of land per year averages 163,670 CFA for each grower. The combination of these factors gives a social or opportunity cost of 734,295 CFA per farmer per year. Considering these two major components, we arrive at an average total cost of 1,013,760 CFA per farmer per year.

Table 3 shows that farmers produced an average of 1617.47 kg of cocoa in 2022. This average conceals major disparities among farmers. While the largest farmer produced 16,500 kg of cocoa per year, the smallest produced just 35 kg. There is therefore a significant gap between these two categories of producer. The average purchase price over the period was around 882 CFA, with a minimum of 800 CFA and a maximum of 925 CFA. The average production cost of one kilogram of cocoa is 964 CFA. Some growers keep their production costs to a minimum, at 224 CFA per kilogram, while for others, production is extremely expensive, costing up to 13,374 CFA per kilogram.

<table><caption>**Table 3.** Comparison of production cost and average purchase price.</caption><thead><tr><th>Variables</th><th>Minimum</th><th>Average</th><th>Maximum</th><th>Standard Deviation</th></tr></thead><tbody><tr><td>Cocoa production in kg</td><td>35</td><td>1617.47</td><td>16,500</td><td>1814.03</td></tr><tr><td>Cocoa purchase price (CFA)</td><td>800</td><td>882</td><td>925</td><td>26.70</td></tr><tr><td>Production cost/kg</td><td>224</td><td>964</td><td>13,374</td><td>1316.64</td></tr></tbody></table>

Source: Authors based on survey data.

Comparing the average production cost of a kilogram of cocoa with the average purchase price, we can see that the production cost is 82 CFA higher than the sale price. This indicates that some farmers are struggling to cover their production costs, given the prices they receive. They are therefore producing at a loss.
Three producer profiles can be defined according to the associated level of income and profit (Figure 5). The first group of farmers, marked in red on the PCA factorial plane, is associated with production costs higher than the income generated. This group represents around 38% of farmers (Table 4). This group makes clearly negative profits and has serious difficulties covering its production costs. The second group, marked in green on the PCA factorial, represents farmers with low and medium profits. These farmers manage to cover their production costs, but make only modest profit margins. They are the most numerous among the farmers studied (61.12%). The third group, marked in blue on the PCA factorial plane, is made up of farmers with much higher profits. These farmers have optimized their production costs and are making a significant profit. However, only 0.88% of farmers are highly profitable in cocoa production.

<figure><img src="image_7.png" /><figcaption>**Figure 5.** Graphical representation of production, costs, revenues and profits according to PCA axes 1 and 2.</figcaption></figure>

<table><caption>**Table 4.** Proportions of PCA clusters.</caption><thead><tr><td>Clusters</td><td>Staff</td><td>Proportions</td></tr></thead><tbody><tr><td>Cluster1</td><td>88</td><td>38.59 %</td></tr><tr><td>Cluster2</td><td>138</td><td>60.53 %</td></tr><tr><td>Cluster3</td><td>2</td><td>0.88 %</td></tr></tbody></table>

## 5. Discussion

Our results showed that men are the most active in cocoa production. Indeed, in many cocoa-producing regions, the division of labor is often based on gender. Tasks requiring physical strength, such as cleaning cocoa fields and harvesting, are generally entrusted to men [40]. In addition, men often own the land and resources needed for cocoa production, giving them a more central and active role in farming activities [41].

Very few farmers agreed to declare the hours worked by children in the family. However, in the traditional practices of African communities, it is common for children to participate in family work from an early age. This participation is often seen as a method of learning, socialization and the transmission of skills. This reluctance to talk about child labor is due to the fact that there are strict laws against child labor, as well as mechanisms to monitor their violation. This fear of legal repression can deter them from answering questions on the subject honestly. Such a situation results in the loss of valuable information
on production costs and risks, slowing down the process of skills transfer, essential to the sustainability of cocoa production. A similar debate is taking place in Sierra Leone on the involvement of children in gold and diamond mining [42]. According to these authors, unreserved acceptance of international child labor laws could have negative implications for children and, by extension, for the communities to which they belong.

The complexity of the production process was analyzed by comparing production zones and cropping systems in terms of production time. The results showed that the workload is significantly heavier for farm families in the new Biankouma production zone than in the old Soubré and Bonon production zones. This contrasts with the argument that farmers are leaving the old cocoa loops to produce in more fertile areas because of the complexity of the work and rising costs in the old zones [10,11,13]. Although this new zone may offer more fertile land, it also requires a greater investment in labor due to the very uneven terrain. In Biankouma, there are two distinct landscapes, with savannah on one side and forest on the other. In the forest zone, the terrain is very uneven and plantations are established on mountainsides reaching up to 1000 m in altitude [43]. This makes the work more arduous for the growers, who need more workers. Furthermore, in the savannah zone, growers also have to redouble their efforts to maintain production, as cocoa is grown in less favorable conditions. Although there is no significant difference between the results for Bonon and Soubré, planters spend more time on production in Bonon than in Soubré. This disparity can be explained by local cultivation practices, where the cocoa–cashew association is favored. This technique requires regular pruning of cashew branches to ensure good aeration of the plantation, which probably increases the workload. In Soubré, where production seems less complex in terms of workload, it needs to be examined with particular care. Indeed, in this area, part of the locality is heavily affected by the cocoa swollen shoot disease [44,45], which sometimes discourages growers and leads them to turn to other crops.

The resurgence of disease can also explain the excessive increase in production costs in some cases. Indeed, when plantations are attacked by diseases such as swollen shoot, the successive death of cocoa trees encourages the development of weeds, which considerably reduces the plantation's production capacity [46,47]. In such situations, although the plantation is no longer able to ensure optimum production, the farmer nevertheless continues to invest considerable effort in maintenance, in the hope of harvesting the little cocoa needed for their livelihood. The result is a significant imbalance between the amount of work required and the small quantity of cocoa harvested. The cost to the farmer is disproportionate to the yield. In the new production zones, where plots are still being established, the situation is similar. Production has not yet reached its optimum level, while the upkeep and development of young plantations requires considerable work and resources. This installation phase, combined with yields that are still low, can also lead to a significant increase in production costs per kilogram of cocoa.

In terms of cropping systems, the results have shown that agroforestry is more labor-saving than the full-sun system. In fact, agroforestry systems are most often established by natural regeneration and may not require any additional work by the farmer [48,49]. Once these systems have been established, they can be useful in reducing the farmer's working time. In general, crops grown in full sun are more prone to weeds, requiring more time for weeding. Trees in agroforestry systems, on the other hand, can provide shade and develop competition to reduce weed growth, thus reducing the labor time required [50].

Our results showed that social costs, made up of FLC and the cost of land, account for almost 72% of total production costs. FLC in particular represents around 54% of total costs. [37] arrived at similar results in Cameroon where, according to the author, family labor accounted for 40.52% of total cocoa production costs. This implies that LF is
the main component of production costs [36,51,52]. Consequently, production costs are underestimated if opportunity costs are not taken into account, raising doubts about the fairness of producer remuneration. Our results showed that, indeed, when opportunity costs are taken into account, around 38% of farmers produce at a loss. Although the literature [37] addresses the issue of opportunity costs, it provides little information on the profits made in relation to the costs incurred. However, in other agricultural sectors, albeit different from cocoa, it has been shown that some farmers do not realize profits when opportunity costs are taken into account. For example, ref. [30] made the same finding on dairy sheep farms in Spain. According to the authors, when opportunity costs are taken into account, 60% of farmers struggle to cover their costs with the prices received and therefore make a loss. In a study carried out in Turkey, ref. [53] demonstrated that government subsidies granted to farmers to encourage the adoption of environmentally friendly practices did not cover the opportunity cost.

The minimum price received by cocoa farmers is often lower than the official campaign price, set at 900 CFA. This situation can be explained by several factors. Firstly, the isolation and remoteness of certain localities from urban centers generates high transport costs for buyers. The latter are then forced to pass on these costs in the purchase price by revising it downwards. Furthermore, even before the official price has been set, some buyers take advantage of the precarious economic situation of producers in difficulty. The latter, in a hurry to sell to meet their immediate needs, often accept prices well below the norm. Buyers speculate on price fluctuations, hoping to make a profit or, on the contrary, risking losses depending on the final price set by the authorities. However, not all producers are on the same footing. Those who are members of cooperatives or involved in certification programs often benefit from a higher price than the official campaign price. Indeed, certifications, which guarantee sustainable and ethical practices, attract buyers willing to pay more to guarantee the quality and origin of their cocoa.

In addition, the cost of producing a kilogram of cocoa is 82 CFA higher than the selling price, as if producers were subsidizing production, which raises the question of the long-term economic viability of these farms. There is therefore an imbalance between the effort invested in agriculture and the benefits obtained in return. This situation can lead to a loss of interest or disengagement from cocoa farming on the part of farmers. This is the case for Soubré planters, who are gradually turning to other crops, in this case rubber and palm. In this sense, ref. [29] asserts that in a context where opportunity costs are too high, labor productivity will be the main criterion for crop selection. Diversification can be seen as a strategy to mitigate financial risks and improve profitability, but it also highlights the growing difficulties of maintaining cocoa production under unfavorable economic conditions.

## 6. Conclusions

The aim of this study was to assess cocoa production costs in Côte d'Ivoire. The results showed that family labor is the main component of these costs, accounting for more than half of production expenses. Around 38% of farmers produce at a loss, if opportunity costs are taken into account in estimating production costs. Comparative analyses of different localities and cropping systems have enabled us to elucidate specificities in terms of workload. The results showed that cocoa is more difficult to produce in the new production zone of Biankouma than in the old production zones of Soubré and Bonon. The results also showed that agroforestry is more labor-saving than the full-sun system. These observations underline the importance of taking opportunity costs into account, at the risk of underestimating cocoa production costs and exploiting farmers' labor for the benefit of the chocolate industry. Finally, this work highlights the potential of agroforestry
systems to optimize the efficiency of cocoa production by reducing labor requirements. Thanks to our approach, this study provides a clear estimate of cocoa production costs in Côte d'Ivoire. However, a more accurate assessment would require monthly monitoring of cocoa farmers. Finally, this study underlines that agroforestry can be integrated into cocoa farming without necessarily increasing the workload of producers.

**Author Contributions:** Conceptualization, N.K., Y.O. and Y.S.S.B.; Methodology, N.K., A.K.K., Y.O. and Y.S.S.B.; Validation, N.K., A.K.K., Y.O., P.J. and Y.S.S.B.; Formal analysis, N.K.; Investigation, N.K.; Data retention, N.K.; Writing—original version, N.K.; Writing—revision and editing, A.K.K. and Y.S.S.B.; Visualization, N.K., A.K.K., Y.O., P.J. and Y.S.S.B.; Project administration, P.J. and Y.S.S.B.; Fund acquisition, P.J. All authors have read and agreed to the published version of the manuscript.

**Funding:** This study on the assessment of opportunity costs in cocoa production in three ecological zones in Côte d'Ivoire was carried out as part of the Cocoa4Future (C4F) project, which is funded by the European DeSIRA initiative under grant agreement no. FOOD/2019/412-132 and by the Agence française de développement. The C4F project pools a wide range of skills and expertise to meet the challenges of cocoa development in West Africa. It brings together a number of partners working together to place people and the environment at the heart of tomorrow's cocoa farming.

**Institutional Review Board Statement:** This work does not concern research carried out with a fetus, an embryo, a tissue or an organic fluid, a corpse or a human remains. The research involves interaction with people who are not personally targeted by the research, in order to obtain information.

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Data Availability Statement:** The data are contained in the article.

**Acknowledgments:** Our sincere thanks go to Jean-François Trébuchon, editor and coordinator of the journal *Bois et Forêts des Tropiques*; to Vincent Freycon, scientific editor of the same journal; and to Jacques Tassin, also scientific editor of *Bois et Forêts des Tropiques*. From 15 to 17 April 2024, they offered us an enriching training course on scientific publication. During this training, this work, which was only a publication project at the time, was used as a case study. Their pertinent observations and constructive comments played a key role in helping us to better orient and perfect our approach. We thank them warmly for their availability, their expertise and their contribution to the improvement of this project.

**Conflicts of Interest:** The authors declare no conflicts of interest.

## Appendix A

<figure><img src="image_8.png" /><figcaption>Figure A1. Results of the normality test.</figcaption></figure>
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