Thursday, April 14, 2016

51. Cost of Production and Food Security Policy In Rwanda and Burundi

Program update from Dr. Daniel Clay - with notes from Ruth Ann - this is an unofficial update report, relating specifically to Artisan Coffee Imports.
April 14, 2016
Update on the Africa Great Lakes Region Coffee Support Program (AGLC) in Rwanda, Burundi and Democratic Republic of Congo

Project Background.  The long-term viability of the coffee sector in the Africa Great Lakes region, the main source of cash income for millions of smallholder farmers and families in the region, is threatened first by increasingly prevalent antestia bug infestation (and associated potato taste defect⎼⎼PTD), and second by coffee yields that are among the world’s very lowest.  AGLC is a three-year, USAID-funded collaborative initiative led by Michigan State University that meets these combined challenges through an integrated program of applied research, farmer capacity building and policy engagement. The solution requires a public-private sector coordinated response across the entire value chain, including producers, washing stations, dry mills, exporters and the government agencies that support the sector’s growth. The goal of the program is to dramatically reduce the effects of antestia/PTD and raise farm-level productivity, two changes that will in turn improve smallholder farmer incomes and help to sustain Rwanda, Burundi and Democratic Republic of Congo's reputation for producing among the highest quality coffees in the world.  

Update on Recent Project Activities.  The AGLC team in Rwanda has recently completed the Baseline Survey of 1,024 coffee farmers in four major coffee growing regions of the country and data are now being compiled and analyzed.  Data collection in Burundi continues and is 85% complete.  

Click here to view the major sections of the 350 question household survey instrument. 
Click here to read our blog on the rigors of field interviewing in Rwanda. Field interviews are organized and conducted by our local research partners: IPAR, University of Rwanda, University of Ngozi and Polytechnic Univ. of Gitega.

The main goal of the data collection component of the program is to inform stakeholders and policy makers about the major issues facing the coffee sector. The data will help to guide farmer capacity building efforts and evidence-based policy change to improve coffee productivity and to reduce the levels of antestia/PTD in fully washed coffee exported to the US and international markets.
Initial findings on antestia/PTD include the following:
  • Roughly one third (36.9%) of coffee farmers observed antestia in their coffee trees during the previous growing season (2014-15).
  • Observation of antestia is not uniform across fields. It is concentrated in groups of trees, normally affecting a relatively small, but important percentage of trees in a given field.
  • In most cases farmers note that less than 10% of their trees are affected by antestia. 
  • 95% of affected trees contain 3 bugs.
  • Farmers have begun taking steps to reduce antestia in their coffee fields and in collaboration with the AGLC project have begun experimentation with different treatments.

  • The most common approach is through blanket spraying of their trees, though the availability and cost of pesticides remains a barrier to better antestia control.
Implementation of capacity building & outreach through public and private partners is scheduled for the coming months and will increase stakeholder awareness and provide farmers with the skills and best practices for antestia/PTD control and enhanced productivity in the field. Experimental/ demonstration plots, have been set up in 16 coffee washing station (CWS) catchment areas in all four coffee-growing regions; they will also serve as modified farmer field schools (FFS) for coffee producers in those areas. These capacity building efforts will be combined with radio broadcasts and targeted SMS messages to maximize the program’s reach across the four regions. 

Ongoing policy engagement activities are scheduled to help coffee stakeholders in Rwanda to
debate, formulate and adopt policies that will motivate producers and other actors in the coffee value chain to invest in ways that will increase smallholder farmer incomes and provide for a more sustainable future for all in the coffee sector.
Next month (May) the AGLC team will host a series of five high-level Policy Roundtables aimed at debating and considering options for changes in the sector that will address critical issues facing the coffee sector’s stakeholders. These include:
1.      Understanding farmer motivations, and encouraging farmers to invest their labor, land and cash resources to improve both yields and quality of their coffee.
2.      Ensuring producers are paid for high quality coffee, and that premiums can reach them.
3.      Optimizing pre-financing for farmers and cooperatives to enable farmers to be paid for cherry at the time of harvest and to avoid delays payment delays.
4.      Availability and effective use of pesticides, fertilizers and other inputs for controlling antestia/PTD and improving yields.
5.      Ensuring a higher proportion of coffee moves through the fully-washed, specialty coffee channel (e.g., zoning policy, farmer incentives, etc.)
Industry leaders from farmer organizations, processors, exporters and key public sector institutions will participate in the roundtable series. Findings from the AGLC baseline producer survey, experimental fields, key informant interviews and focus group discussions will be presented during these roundtable sessions and will serve as the empirical basis for informing and guiding consultations on these and other pressing policy issues. 

Note from Ruth Ann on Cost of Production (CoP):
A key component of the project is to create cost of production measures from primary data from the farmers. With 2048 survey responses, the averages should give a fairly clear indication of what it is costing farmers to farm coffee, despite the known challenges of poor farmer recall and high variability in the dozens, if not hundreds, of factors that help determine cost of production.  My masters thesis (in Community Sustainability from MSU) will be one analysis of the CoP data from the Rwanda baseline survey (n=1024). I've chosen to look specifically at the major determinants of CoP, and then focus on these farm characteristics:
  • male/female ownership
  • number of trees
  • percent of household income from coffee
  • household income diversity
The objectives of the project will drive further analysis of the CoP data, (well beyond my masters project) including calculation of gross margins, the marginal value of productivity (MVP) per hour of labor and MVP per hectare of land.  The latter two metrics are similar to net-revenue-per-hour-of-labor and net-revenue-per-ha-of-land, which are metrics recommended by Christoph Montagnon of RD2 Vision.

We also expect to plot cost of production vs. number of trees on an X - Y chart and then overlay a floor price of cherry (farm gate price) line. We'll do this for both countries. Publicly available charts like this for any country are rare to non-existent. Below is the short list of research I've seen that comes close.
  • Trademark East Africa and Integrity Research did this using a bar chart, not an X-Y,  using data from their 2012 research in Burundi. 
  • Catholic Relief Services delved deep into the CoP topic with their 2012 Borderlands project, but instead of charting CoP vs. # trees, they analyzed about  12 salient determinants of CoP to create three different CoP segments for the population (NariƱo  in Colombia). Great work.
  • Committee on Sustainability Assessment (COSA) may have the kind of X - Y charts by country of which I'm speaking for countries where they have worked - which do not include Rwanda or Burundi yet. I believe they have the data to do it, but I haven't seen it. They have large roaster clients funding their work, so they may not be able to publish all their results to the world.
Wondering what on earth this graph is and how it could possibly help farmers? Check back here towards the end of May...

Tuesday, April 5, 2016

50. Cost of Production Building Blocks

April 5, 2016
WARNING! This is a pretty geeky researcher post. Non-geeks may want to pass.

The data is in from the 1024 household surveys of Rwandan farmers. All 350 questions, which turns into close to 800 variables. It is a large database. The 10 enumerators worked for 10 weeks, working 5 days/week, 7am until 7pm each day, two interviews per day to complete the interviews. (See this post for an up close view of an enumerator's day.) Cleaning and re-coding the data has taken a couple weeks by a team of researchers, some highly experienced in this type of work in SPSS, and some less so (like me). Now we're starting to build the formulas in SPSS that will actually start to analyze what the farmers have told us.

Here's what the beginning of my formulas to calculate cost of production look like:

Looks fun, eh? We have seven cultivation variables (e.g. weeding, pruning, fertilizing, etc.) for both household labor and wage labor. We have one variable for harvest labor (both paid and unpaid), and one for sorting labor (paid and unpaid). Transportation variables include both time required to transport cherry and time required to transport parchment, and fees paid for hired help and fares. To these variables we will add whatever the farmer reported on 10 different types of equipment and 6 types of consumables (pesticide, fertilizer, mulch,...).

In short, the level of detail is serious for this attempt to quantify and understand farmer's cost to produce. Stay tuned for what we learn as we get these formulas going.