Costs and returns to New England farmers in the farm-to-institution supply chain

1. Identify farmers’ supply chain transaction costs for direct, intermediated, and coordinated FtI supply chains.

The objective was achieved in part for direct and intermediated supply chains, but not for coordinated supply chains.  We were unable to identify any farmers who sold through co-operatives in New England who explicitly sell to institutions and were willing to be interviewed.  Ongoing results from this objective and the corresponding performance targets were shared with FINE (Farm to Institution New England) partners. 

1.2 We did not meet the performance target to purchase USDA ARMS (Agricultural Resource Management Survey) 2011 Cost And Returns report data.  The USDA ARMS 2011 Cost and Returns Survey did include a separate question that asked producers to report their sales to institutional purchasers. However, the USDA ARMS 2011 Cost and Returns Survey results will not be useful for our research.  The ARMS Cost and Returns Surveys are designed to elicit detailed information on large commodity growers’ costs and returns.  This has several implications.  The survey sample is weighted towards “commodities” states, or states that produce the nation’s bulk of wheat, corn, cotton, sugar beets, soybeans, etc., and hog, cattle, poultry production.  More farmers in these states are included in the sample.  No New England, or even northeastern, states are large scale producers of the commodities of interest, so these states are included in the sample according to a decreased weight. 

Related to this weighted sampling method, there were so few producers reporting any sales to institutions that ERS is unable to provide anonymous results to us because of the small sample size and reliability of the estimates.  Further, even if we did have access to a sufficiently large set of anonymous results, questions have been raised as to whether the results from a sample weighted towards large scale commodity producing states will be valuable in drawing inferences about our population of producers in New England. ERS will not share the ARMS data when those data could be used for inferences for which the data are not suited.

1.3 We identified and interviewed 11 farmers who shared extensive financial information about their farm operations, and two additional farmers who were interested in discussing their experiences with costs and returns in farm to institution markets but were not willing to share financial information. The team identified potential farmers to interview and the appropriate means of conducting those interviews.  Several unanticipated questions came up during the process of identifying potential farmer interviewees, particularly the issue of how FINE could be included in collecting farmer information in a way that satisfies the University of Massachusetts’ Internal Review Board (IRB) requirements for confidentiality.  The end result of the concerns about confidentiality involve the process of identifying farmers, the different stages at which different people have access to information that has been collected, and how the final list of farmers will be determined.

In coordination with the metrics team, it was  determined that Ms. Fitzsimmons and Mr. Allison would identify key FINE leaders, Ms. Fitzsimmons would speak directly with these individuals to build a list of potential farmer interviewees, and then the metrics team and  Ms. Fitzsimmons, and Dr. Lass would review this list to determine the farmers to prioritize.  This list of potential interviewees would include all farmers that leaders identified, and would include farmers from a range of farm size, products, location, marketing channel, etc.

Ms. Fitzsimmons and Mr. Allison identified key individuals from the FINE leadership team and individual FINE members.   Ms. Fitzsimmons wrote an email request and two attachments (one brief, one detailed) to describe the nature of the request and proposed outcomes, and Mr. Allison sent out the email request to this group.  Ms. Fitzsimmons followed up with individuals. 

The list of potential farmer interviewees will be available to the FINE metrics team, but once the list has been narrowed to those identified to be interviewed, the list and raw interview results will only be accessible to Ms. Fitzsimmons and Dr. Lass. 

The process of identifying farmers agreed to above, and the success in connecting with farmers, asking for a commitment to be interviewed, and then setting an interview date, was more challenging than anticipated.  Because we asked for an introduction, but were not able to share information with FINE about which farmers responded to the introduction and which did not, our ability to follow up was very limited.  The response rate to the introductions was very low, so the inability to ask FINE members to assist with follow up with particular farmers was a challenge.

1.4. – 1.8.  Mail interview questions to farmers one month in advance; Send farmers reminder postcard and email two weeks in advance; Make a reminder call to farmers one week in advance; Interview farmers; Compensate farmers.   These steps all went smoothly.

1.9.  Compile and analyze ARMS data and interview data on supply chain costs, using multinomial, conditional and mixed logistic regression models to determine probabilities associated with market choices. For the reasons described under objective 1.2 above, we will not be doing this.

2. Identify supply chain transaction returns, including those returns that satisfy farmers’ non-financial goals, for direct, intermediated, and coordinated FtI supply chains. These objectives were met for direct and intermediated supply chains, but not for coordinated supply chains as described in Objective 1 above.

2.1. Share ongoing results and solicit feedback on research methods and strategies with FINE partners during FINE Metrics Team conference calls and bi-annual FINE gatherings.

Results from the interviews were communicated to the FINE Metrics Advisory Team throughout the project.  These results have also been used to inform the development of FINE’s 2016 Producer Survey, which will be distributed via a snowball sample through state agencies of agriculture in all six New England states to all producers in New England in early 2016.  Preliminary results have also been discussed with Massachusetts Farm to School staff, who undertook a similar study recently.  In 2015, FINE conducted a Distributor Survey, and results from this research that will contribute to questions on future Distributor Surveys, as well.  Preliminary results have been communicated to staff from the John Merck Fund, which funds farm to institution projects in New England.  

2.2.         ARMS Data – purchase USDA ARMS 2011 Cost And Returns report data – see above.

2.3.         Develop interview questions, including questions eliciting non-sales related returns to farmers, such as increased access to customers, farm tours, CSA sign-ups, etc.

We developed questions, and added an additional objective to test the survey instrument by conducting a pilot interview.  The pilot interview lasted a little over three hours.  The farmer spent a significant amount of time looking at files (both paper and computer) to find accurate answers to our questions.  The farmer was very generous with his time, and among the helpful outcomes of this pilot was a comprehensive list of documents to suggest that interviewees have on hand for the interview.

For further discussion of the instrument design and design process, see Objective 3.3 below.

2.4. – 2.10 Interviews - Work with FINE to identify farmers to be interviewed; Mail interview questions to farmers one month in advance; Send farmers reminder postcard and email two weeks in advance; Make a reminder call to farmers one week in advance; Interview farmers.  For the most part, these steps went smoothly.  See Objective 1.3 above.

2.9. Mail farmer compensation – As per University of Massachusetts guidelines, we compensated farmers directly, in cash, upon the conclusion of the interview.  This method entailed some inconvenience and risk on the part of the interviewer, who was required to travel with large quantities of cash, but was otherwise a very streamlined process.

2.10. Compile and analyze ARMS data and interview data on supply chain returns, using multinomial, conditional.  Removed from project, as per 1-3. Above.

3. Identify other causal factors that relate to supply chain transactions, including farmer preferences, farmer socio-demographic characteristics and farm characteristics.

We included questions intended to elicit farmers’ preferences for the social outcomes attributed to Farm to Institution programs. Results suggest that farmers do, in general, express preferences for these outcomes.  The next question, which this research is not able to explore, is the extent to which these preferences impact farmer decisions to sell to institutions, and prices that farmers choose to charge in this market.  One farmer did explicitly say that, when selling to institutions, he chose a lower price than he otherwise would for wholesale markets.

In addition, we identified three emerging topics that relate to transactions in this supply chain.  The first topic is the development of a number of non-profit and for-profit organizations that have developed online ordering platforms that minimize many of the transaction costs associated with farmers and buyers interacting in this market.  The second topic is the increased chance that farmers will be in violation of Federal Department of Labor Wages and Hours regulations as a direct result of new farm activities that farmers may engage in to sell to institutional markets, including aggregating product from other farmers and processing product.  The final topic is the role of engaging in value-added processing for the farm to institution market.  We developed extension and outreach materials to guide farmers in their choices regarding two of these issues, and a Case Study to explore the third.  

3.1. – 3.2. and 3.4 - 3.10, please see repeated Objectives above in Objectives 1 and 2.

3.3.         Develop interview questions, including questions eliciting social preferences

We designed the survey to meet many goals.  The survey instrument is intended to be compatible with existing USDA surveys and reports and IRS forms, and additionally include questions that address costs and returns not currently gathered in these existing instruments.  There were multiple purposes for this intention.  Primarily, we hoped to make straightforward comparisons to existing data for those fields that are included in both existing instruments and our instrument.  Farmers were able to refer to forms that they have already completed in order to answer many of our questions, which streamlined the process and make the interviews go more quickly.  Finally, the questions are designed to complement the existing instruments so that they may be easily inserted into future federal instruments and/ or may serve as a pilot for potential questions, should USDA decide to begin soliciting farm to institution data in future surveys.  

The survey was also designed to be compatible with existing measures of social preferences.  This is more of a challenge, and is the primary reason for requiring a redesign of the first draft of the survey after the completion of the pilot survey.  We originally designed the social preferences section with the intent of using the results to inform a field experiment design.  To achieve this, we reviewed the literature on field experiments, and developed a survey intended to identify a robust Dictator Game to identify farmer social preferences for three social outcomes, as identified in the literature.  In the process of making this design decision, we reviewed and rejected a number of other social preference frameworks. 

4. Provide case studies for each of the three supply chains identified – direct, intermediated, and coordinated.

After discussion with our partners, it was determined that a number of case studies have already been completed that look at different farms and their farm to institution sales – notably two case studies from another NESARE funded project undertaken concurrently with ours.  Instead, we decided to produce three reports that explore emerging issues in farm to institution markets, “Federal Labor Laws and Farm to Institution Sales in New England: How to Make Sure Your Farm is in Compliance”, “Online Brokers and Farm to Institution Sales: Streamline Your Sales to Institution”, and “Processing for the Farm to Institution Market: Just Roots Community Farm and Soup.”  To provide useful information to farmers and practitioners about the issues uncovered in the interviews with farmers, we extended our research.  We interviewed farmers in New England who had been the subjects of Department of Labor Wages and Hours violation investigations, reviewed the Fair Labor Standards Act  and relevant case law, and interviewed a number of labor lawyers with expertise in agricultural labor law.  We determined the important characteristics of online brokerage platforms, identified the non-profits that offer these services to farmers, constructed a survey to elicit the relevant information and asked non-profits to fill out the survey.   Finally, we worked with a farm that is engaged in developing a value-added product line for institutional consumers and conducted an in-depth interview about the costs and returns for that product and its role in the farm operation’s long term viability.

4.1. Share ongoing results and solicit feedback on research methods and strategies with FINE partners during FINE Metrics Team conference calls and bi-annual FINE gatherings. See above Objective 1.1.

4.2. Interviews-Work with FINE to identify farmers to be interviewed and also be willing to serve as a published case study. 

In the course of identifying interviewees and clarifying the purpose of case studies, it became clear that the case studies as proposed did not advance an understanding of farm profitability in farm to institution markets in a way that has not already been demonstrated.  Instead, we have identified three different emerging topics which are important to understanding farmer profitability in these markets, and will be highlighting the experiences of the farms that have been grappling with these topics. 

Note that we were not able to identify any farms, and therefore did not interview any farmers, who coordinated (in the sense of working together as a co-operative) sales to institutions.  The categorization of “intermediated” sales was not specific enough to identify the relevant aspects of different intermediated supply channels.  However, the idea of establishing a co-operative was mentioned without prompt by three farmers; two suggested establishing a co-operative processing facility, and one suggested a sort of hiring co-operative to address labor issues.

4.3. - 4.7  See Objective 2 above.

4.8. Compile interviews into 3 case studies.  Emerging Topic Studies were completed instead, see explanation above.

4.9. Share case studies with farmers and FINE to verify accuracy.  While we did not write case studies as originally planned, after each interview, the interview notes were typed and emailed to farmers.  Farmers are given a (flexible) deadline, and asked to review the notes for accuracy, and to edit or redact any information that they consider to be identifying or proprietary. 

4.10. Distribute case studies online.  Emerging Topic Reports will be offered online through FINE and through University of Massachusetts Center for Agriculture and the Environment.

4.11. Submit case studies for publication. Emerging topics will be submitted for publication, and a paper is in preparation for submission to the Journal of Extension.

5. Provide results of this research to farmers, distributors, institutions, and FtI advocates in order to inform farmers about this potentially profitable enterprise, to support farm viability, and to enhance FtI markets.

Research results have been shared with all stakeholders in the form of Emerging Topics Reports, and workshops as described below in Publications/Outreach.  All materials are available online from the FINE website and the University of Massachusetts Center for Food, Agriculture, and the Environment website.  In addition, a FINE blog entry will be posted in March, 2016.