The second presentation Artisan Coffee Group made at the Dublin World of Coffee Expo "Business" seminar room was an update on the new data from Rwanda on cost of production for farmers. The research comes about as a result of Ruth Ann Church's dual role on the Africa Great Lakes Coffee (AGLC) support program. The project has implemented a baseline study, producing the data used in the presentation. Ruth Ann is the monitoring and evaluation coordinator for Michigan State University and she is eligible for that role due to her status as a masters student in the Community Sustainability department. Ruth Ann is writing her masters project this summer on "Understanding Cost of Production of Coffee in Rwanda." So the Dublin venue was a perfect opportunity to share what has been learned so far.
A key point about the research is that this is knowledge that can help us pay farmers more. At Artisan, we maintain that only when the costs in the entire supply chain are well understood, can management decisions at any point be made wisely and with true sustainability as a goal. Understanding the costs of the farmer are often the toughest for stakeholders to grasp for a number of reasons:
- Public data and credible research on costs to produce for smallholders in tiny countries is rare.
- Little research is even available on the methodologies for conducting cost to produce studies.
- Farmers, especially smallholder farmers, many of whom are illiterate, do not keep careful records of costs, making traditional cost accounting systems unhelpful.
- Coffee farmers are located in very remote places. Travel to reach them and identifying them is time-consuming.
- Coffee farmers speak local languages, like Kinyarwanda in Rwanda.
- There is great variety in the types of coffee farmers, the methods and practices they use, the plants and environmental conditions in which coffee is grown.
- In other words, conducting good research on farmers costs is expensive.
The sections of the presentation were as follows:
1. Methodology of the baseline study
2. Components
of cost of production (CoP)
3. Factors
driving costs of production
4. Understanding declining farmer motivation to produce coffee.
1. Methodology
The AGLC baseline Survey was conducted early in 2016 on a sample
of 1,024 households randomly selected from listings of 16 coffee washing
stations (CWS) geographically dispersed across four major coffee-growing
districts representing Rwanda’s four agricultural provinces (see map).
 |
| Map: Rwanda - Sampled districts, washing stations (red dots), households (white dots). Source: Nathan Clay, AGLC staff. |
The
selected districts are Rutsiro (Western Province), Huye (Southern Province),
Kirehe (Eastern Province), and Gakanke (Northern Province). The guiding
objective of the Sector/CWS selection was to maximize geographic dispersion of
the four CWSs in each district and also to ensure that the four would include
two that are cooperatively owned and operated and two that are privately owned
and operated. From the farmer listings at each of the CWSs, 64 farmers were
randomly sampled for study, totaling 1,024 (16 CWS x 64 HH) coffee producing
households in all.
The survey instruments were developed at the farm household and field levels. Sections of the questionnaire covered a diversity of topics, not only cost of production. The questionnaires were translated to Kinyarwanda and programmed for Samsung 7” tablets using CSPro Mobile software, and pretested in the field. Ten experienced enumerators were hired and were trained just prior to the pretest. Immediately following the pretest a series of debriefing sessions was organized and the survey instruments were revised based on the pretest results. The ten enumerators worked for 6 weeks in the field to complete the 1,024 farmer interviews, all at the farmers' homes and in their fields.
2. Components of Cost of Production (CoP)
Three major components make up our cost of production value:
- Labor: Household (unpaid) labor and wage labor (by task).
- Equipment, such as pruning shears, sprayers, masks, etc.
- Purchased inputs (mulch, fertilizer, pesticide, etc.)
Splitting out the labor component into household labor vs. wage labor, a breakdown of the average CoP is as follows:
| Cost of Production Item | RWF | $US | % of total |
| Mean value of household labor: | 35,868 | 45 | 33% |
| Mean value of wage labor: | 44,313 | 56 | 41% |
| Mean value of equipment used: | 7,506 | 10 | 7% |
| Mean value of purchased inputs: | 19,838 | 25 | 18% |
| Total: for the 2015 season | 107,527 | 136 | 100% |
Dividing the total costs per household by the KGs each farmer produced (see table below), we calculate the average CoP per KG cherry. KG cherry is the production unit that is most common across all coffee producers globally.
| A. Cost of Production, RWF (cash value) | B. Total harvest 2015 (KG) mean | C. CoP RWF per KG cherry |
| 104,479 | 1025 | 177 |
Converting RWF into $ we have $ .22/KG cherry.
Converting KG into lbs, we have $ .10/lb cherry.
These values are important in the Rwandan context, since the government board that sets the floor price for cherry at the beginning of each season uses a value for the farmers' cost to produce in its calculations. Today they are using 80 RWF/KG cherry, less than half of our estimate.
3. Factors Driving Cost of Production
The presentation continued with a discussion of drivers of cost of production, such as the number of trees, gender and percent of household income coming from coffee. As expected, the number of trees is found to be the most important driver. As the number of trees increases, CoP per KG cherry declines. (See chart below.)
Female heads of household in our sample had significantly higher CoP than the average at 205 RWF/KG cherry.
Percent of income coming from coffee is a significant driver when the percent drops below 25%. Then the CoP rises steeply to about 277 RWF/KG cherry. Once the percent of income from coffee is above 25%, however, CoP remains at about 150 RWF/KG cherry.
4. Understanding Declining Farmer Motivation
In this section of the presentation Ruth Ann showed analysis from other AGLC team members, namely from Dr. Dan Clay. The "discovery" in the data is that largeholder farmers (those with 1000+ trees) are not investing in coffee in Rwanda at the levels one would predict. Thus the gross margins (profits) per KG cherry for the largeholder farmers are below the margins mid-range farmers are receiving. (See chart below.)
Shown another way, in the bar chart below one can see that mid-range farmers produce more than their share of coffee given the percent share they have of trees. Largeholder farmers on the other hand, are producing significantly less KG of cherry than one would hope given their numbers of trees.
We explain the phenomenon in the above two charts with the explanation that largeholders are "divesting" from coffee because the returns are not there. They have other choices. There is a lack of financial motivation for these largeholders to spend their resources in coffee. We propose that a policy remedy is to raise the floor price of cherry to cover costs of production and provide a level of profit per KG cherry that is comparable to the competing rural products, such as banana and raising livestock.[Thank you to Michigan State University for its generous support for my travel funds to get to Dublin.]
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