Regional Food Hubs: the key to improved farm profitability and rural economic development?

Final Report for GNE11-021

Project Type: Graduate Student
Funds awarded in 2011: $15,000.00
Projected End Date: 12/31/2012
Grant Recipient: Cornell University
Region: Northeast
State: New York
Graduate Student:
Faculty Advisor:
Todd Schmit
Cornell University
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Project Information

Summary:

This project, which included a small interdisciplinary team at Cornell (Todd Schmit, Dyson School of Applied Economics and Management; Becca Jablonski, Department of City and Regional Planning; and David Kay, Department of Development Sociology/the Community and Regional Development Institute), leveraged funding from the USDA AMS (Cooperative Agreement Number 12-25-A-5568 with the Agricultural Marketing Service of the U.S. Department of Agriculture) as well as a Doctoral Fellowship from the USDA’s National Institute for Food and Agriculture (Competitive Grant No. 2012-67011-19957) to develop a best-practice methodology to evaluate the economic contributions of food hubs on their local economies and the participating farms. Through applying the methodological framework to a case study food hub in New York State, we found that food hubs increase market access for farms, particularly those that are mid-scale. Additionally, we found a gross output multiplier of 1.82, indicating that for every additional dollar of final demand for food hub products, an additional $0.82 is generated in related industrial sectors. However, the community economic impact of food hubs is not pure, as increase in final demand for food hub output diverts sales from other local wholesale and distribution businesses.

Introduction:

In the past five years, there has been a proliferation in the number and recognition of ‘food hubs’ across the United States, as well as a substantial increase in foundation and public funding to support their development. Following the U.S. Department of Agriculture’s (USDA) working definition, a food hub is a “business or organization that actively manages the aggregation, distribution, and marketing of source-identified food products primarily from local and regional producers to strengthen their ability to satisfy wholesale, retail, and institutional demand” (Barham et al. 2012, 4). Though there is a substantial and growing literature that examines food hub activities, there have been no comprehensive, data-driven economic impact assessments completed to date.

The primary objective of this project is to promote the utilization of a best-practice methodology to evaluate the economic contributions of food hubs on their local economies and the participating farms they support. This is accomplished by developing a data-driven empirical framework applicable to a variety of food hub structures. Included in this framework is a discussion of the data requirements for such an approach and a recommended methodology for collecting such data. As the USDA distinguishes a food hub from other traditional food aggregators or distributors in part based on the fact that they purchase products “primarily from local and regional producers,” the differential expenditure patterns can be modeled to determine the relative effects on the regional economy, including the impact on local agricultural sectors.

The framework developed is applied to a case study analysis of a food hub located in Upstate New York (Regional Access). Though there are limitations of generalizing the results of an individual case study to other food hubs, in contexts where food hubs exhibit similar purchasing patterns as in our case, one may be able to utilize the adjusted expenditure patterns in constructing a similar analysis. However, where food hubs are more dissimilar in terms of their activities and purchasing and sales patterns, following the complete data collection procedure proposed is advised.

The secondary objective of this project is to better understand the extent to which food hubs increase the overall demand for and consumption of local food products. And further, whether there is demand from customers to expand the availability of food hub products and services. Addressing this objective requires additional information from food hub customers. In particular, we collect additional information on the nature of customer purchases, and we analyze the extent to which these purchases represent increased demand for local goods and services, of if they instead substitute purchases from one local source for another (i.e., from wholesale distribution company to a food hub). We also collect information related to scenarios in which customers would purchase additional products from food hubs, thus providing information on the potential scalability of the food hub sector. The information collected from purchasers of food hub goods and services allows us to ascertain the direct value of food hub purchases, offsets in purchases from other sectors, and the potential for growing overall local food product demand.

Project Objectives:
1. Develop an inter-disciplinary methodology that combines secondary data analytic approaches with primary data collection throughout New York to evaluate regional food hubs that can be replicated across the United States;

This objective/performance target is complete; an abbreviated version of the methodology can be found below along with the economic impact results based on our case study application. The full methodological approach can be found in the USDA AMS report, to be released in the next few months (http://dx.doi.org/10.9752/MS145.09-2013). Further, we will be releasing a practitioner’s guide to conducting economic impact assessments of food hubs through the USDA AMS no later than March 2014.

2. Build the capacity of the Cornell Small Farms Program Work Team on local foods/local markets so as to develop statewide support to increase small, commercial farmers’ profitability by expanding access to markets

Unfortunately, the Cornell Small Farm Program Work Team on local foods/local markets has disbanded. The Cornell Small Farm Program revised their funding program, and now provides competitive grants rather than direct support to the work teams. Despite this, during the project period I wrote a quarterly column for the Cornell Small Farm Program Quarterly (“Faces of our Food System”) to showcase different distribution options for local food producers (see the information products at https://projects.sare.org/sare_project/GNE11-021). Additionally, as mentioned in my 2012 annual report, there are several groups that have emerged to take leadership in expanding market opportunities for producers across NYS. The American Farmland Trust (AFT), for example, has been providing leadership to expand farm-to-institution sales throughout NYS. AFT has established a tremendous advisory group (of which the Graduate Student investigator is a part) and is working to achieve many of the same objectives listed in this grant. The Northeast Sustainable Agriculture Working Group is also leading a project funded by the Merck Foundation called the Northeast Knowledge Food Ecosystem project (see: http://www.nefood.org/group/nesawgworkgroupforresearchassessments/forum/topics/northeast-food-knowledge-ecosystem) to share data and project information. The graduate student investigator is on the advisory committee for this group, which may prove a valuable tool to share information about best practice models to expand marketing opportunities for local producers.

3. Develop policy recommendations for local, state, and federal government in accordance with findings.

This objective/performance target is complete. We made five presentations to policymakers (two in New York State, and three in Washington D.C.) to disseminate our findings. The presentation to the NYS Council on Food Policy is included here.

Jablonski, B.B.R. and T.M. Schmit– “The Economic Impacts of Local and Regional Food Systems” NYS Council on Food Policy, Kinderhook, NY, 7 December 2012.

Schmit, T.M., B.B.R Jablonski, and D. Kay. “Promoting Food Hubs: Update on Farm to Market Projects in NYS.” Invited presentation, 2013 Legislative Conference, New York State Association of Counties, Albany, NY, 4 February 2013.

B.B.R. Jablonski and T.M. Schmit. “Estimating the Economic Impacts of Local Foods: Building a Methodology using Case Studies from New York.” Economic Research Service, U.S. Department of Agriculture, Washington, D.C., 28 March 2013

Jablonski, B.B.R. and T.M. Schmit. “Assessing the Economic Impacts of Regional Food Hubs: the Case of Regional Access.” Know Your Farmers, Know Your Food Task Force Meeting, U.S. Department of Agriculture, Washington, D.C. 6 August 2013.

Schmit, T.M. and B.B.R. Jablonski. Assessing the Economic Impacts of Regional Food Hubs: the Case of Regional Access.” U.S. Department of Agriculture, Agricultural Marketing Service, Washington, D.C. 7 August 2013.

Main policy recommendations
    1. 1. Food hubs increase access to ‘local’ farm products
    2. 2. Food hub facilitates expanded farm sales
    3. a. Particularly facilitates the distribution of products from mid-scale producers—key components may be the ability to sell largely ‘rural’ products to urban core, as well as access to warehousing and cold storage
    4. 3. Potential exists to expand food hub sales, but scalability is not pure, i.e., increase in number/size of food hubs will result in some diverted sales from other businesses

Cooperators

Click linked name(s) to expand
  • Susan Christopherson
  • Todd Schmit

Research

Materials and methods:
Economic Impact Analysis

To conduct an economic impact analysis, one must have information about the level of inter-industry transactions, or purchase and sales linkages. This information involves accounting relationships detailing the extent of purchases and sales of goods and services both within and among sectors of an economy. As a business buys from and sells goods and services to businesses in other sectors of the economy and to final users, the firm stimulates additional economic activity by the other businesses and within other economic sectors. Social Accounting Matrix (SAM) models are widely used by economists to measure and understand the distributional impacts or inter-industry linkages across an economy.

The SAM methodology’s analytical capacity lies in its ability to estimate the indirect and induced economic effects stemming from the direct expenditures associated with a change in final demand for the goods and services produced by an economy. An initial (direct) expenditure driven by a change in final demand sets in motion a cascading series of (indirect) impacts in the form of additional expenditures in other sectors by each business whose sales have increased. These direct and indirect effects are also associated with increased income to labor as a result of increased economic activity. To the extent that this additional income is spent within the local economy, there are additional multiplier effects that are commonly referred to as induced impacts. The cumulative impact across all of these affected industries determines the size of this initial type of multiplier, computed as the direct plus indirect plus induced effects divided by the direct effect.

The most commonly used SAM data and software is offered by a company called the IMPLAN Group LLC (henceforth ‘IMPLAN’). IMPLAN’s database represents the entire economy in 440 sectors. Each IMPLAN sector is represented by a single, static production function – a mathematical expression that relates the quantity of inputs required to produce that industry’s resulting output (Lazarus et al., 2002b; Liu and Warner, 2009). Initiated from a national table of accounts, IMPLAN provides a comprehensive set of balanced SAMs for every county and state in the United States. These SAMs illustrate a complete picture of the economy, accounting for all inter-industry transactions, as well as transfers to and from institutional sectors.

Addressing Previous Research

Throughout most previous research estimating the impact of local food systems, there are two main challenges that reflect the difficulty in meeting the significant data requirements to conduct rigorous economic impact assessments. The first is what O’Hara and Pirog (2013) refer to as an ‘interpretation’ challenge. Specifically, “a critical issue for measuring net economic impacts entails stipulating how the ‘opportunity cost,’ which is what would have occurred in the absence of local food sales, is defined” (p.4). As they rightly point out, measuring opportunity cost is not straight-forward, and requires information about the extent to which increased consumer purchases of locally-grown food offsets other types of purchases, changes market prices and/or supply chain characteristics, or impacts land use. There are only a handful of local food economic impact assessments that explicitly acknowledge the need to consider opportunity cost (Conner et al. 2008; Hughes et al. 2008; Gunter & Thilmany 2012; Tuck et al. 2010; Swenson 2010). However, each of these studies makes assumptions about the sectors in which there are decreased purchases (or changes in land use) as a result of increases in local food consumption–in other words, none collects the data necessary to more fully understand the opportunity costs of increased local purchases.

The second challenge is that almost all of these studies reflect the implicit assumption that local food system participants have the same patterns of expenditure as the aggregate agricultural sector data available in IMPLAN. The production functions for each sector reflect average purchase and sales patterns across all firms in the sector, without the requisite information to be able to disaggregate them by any specific characteristic (i.e., scale of operation, or marketing channel). As IMPLAN sector data represents all inter-industry linkages, the expenditure and sales patterns are more reflective of those firms that contribute a higher proportion of total output in the sector (typically, the larger firms). Given that local food system participants tend to be smaller in scale, and represent a small overall portion of agricultural sector transactions (Low & Vogel 2011), the estimates of the impacts from increased local food sales based on existing IMPLAN data may be misleading if local food system participants have different patterns of input expenditures (e.g., different production functions) and/or they purchase a different proportion of their inputs from local sources.

Methodology

IMPLAN does not include a ‘food hub’ sector within its 440 sectors. Rather, the expenditures and sales of food hubs are included within more aggregated sectors (i.e., wholesale trade). As a food hub sector is unlikely to ever exist either within IMPLAN, or in any Bureau of Economic Analysis data set, we do not construct a ‘food hub sector’ within IMPLAN, but instead model the sector based on the expenditure profile of food hubs. IMPLAN refers to this type of modeling as ‘Analysis-By-Parts’ (ABP).

We build two alternative ABP SAM impact assessment models using IMPLAN—one that incorporates additional data collected from farms selling to the food hub (Model 2) and one that does not (Model 1). Thus, the implicit assumption in Model 1 is that food hub farms have the same or similar production function to the default IMPLAN agricultural sector data. Whereas, in Model 2 we utilize additional data collected from farms selling to the food hub to create a distinct ‘food hub farm’ sector.

Case Study Food Hub

Given the heterogeneous structure of food hub operations and the detailed data needs required for an impact assessment, we utilize a case study approach. Regional Access, LLC (RA) was chosen for our case study due to their commitment to working directly with local farmers, their length of time in operation, the diversity of their customer base, and the size of their operation. RA was established in 1989. In 2011, it had over $6 million in sales, and employed 32 full-time equivalents. Utilizing 9 vehicles and a 25,000 square foot warehouse, RA aggregates and delivers products primarily throughout NYS. RA has over 3,400 product listings, including beverages, breads, cereals, flour, meats, produce, prepared foods, grains, and fruits and vegetables. RA purchases products directly from 96 farm vendors (86 in NYS) and 65 specialty processors (non-farm vendors), as well as from conventional sources. RA has over 600 customers, including: individual households, restaurants, institutions, other distributors, fraternities and sororities, buying clubs, retailers, manufacturers, and bakeries. RA also provides freight services to a range of businesses.

RA plays an important role connecting farmers, customers, and the community-at-large around food and agricultural issues. RA fits within USDA’s definition of a food hub given its commitment to building relationships with local farmers, managing the aggregation, distribution, and marketing of their products, and maintaining the farm’s identity.

RA provided a detailed 2011 profit and loss statement, along with estimates of the percentages expenditures in each category that were local (i.e., in NYS). Based on the data they provided and follow up discussions with the RA personnel, the hub’s expenditure categories were mapped to IMPLAN sector, value added, and other components.

Food Hub Farm Interviews

Understanding how ‘food hub farms’ interact with other sectors of the economy is important in improving the precision of an impact assessment. Accordingly, we conducted interviews with 30 food hub farms. The farms represent 35% of all farms selling to RA that were located in NYS and sold more than $100 of products to RA in 2011. Farms interviewed were located in every region in NYS except New York City and Long Island. In terms of farm sales, 37% were classified as ‘small’ ($1,000-$249,999 in gross sales), 43% were classified as ‘large’ ($250,000-$999,999 in gross sales), and 20% were classified as ‘very large’ ($1 million or more in gross sales). The distribution of farms by primary commodity category was 37% meat and livestock, 30% fruit and vegetable, and 33% value added products (including cheese, butter, yogurt, honey, maple syrup, wine and juice).

Once we complete mapping of the food hub farms expenditures and sales to the relevant IMPLAN sectors, we see that our case study farms have very different patterns of expenditure than the default food sold-farm sector within IMPLAN (see Table 4). Most importantly in terms of local economic impact, per unit of output, food hub farms spend $0.77 in the local economy versus the $0.54 in the food sold-farm sector. Food hub farms spend double as much on employee compensation as the default food sold-farm sector per unit of output ($0.24 compared to $0.12), although they spend substantially less on proprietor income ($0.06 compared to $0.16). Another way of comparing these expenditure patterns is that per unit of output, the income impact of food hub farms is $0.30 compared to $0.28 in the default IMPLAN data. Food hub farms spend $0.08 per unit of output on support activities for agriculture and forestry, compared to $0.02 in the default agriculture sector per unit of output. And, food hub farms spend $0.14 per unit of output on purchases from other local farms (both food hub farms and other farms) compared to $0.06 per unit of output in the default farm sector.

Food Hub Customer Surveys

RA’s customers were surveyed using an online survey to better understand the extent to which purchases from RA increase the demand for locally-grown farm products and offset purchases from other sectors. At the time of the survey, RA customers numbered 110 households and 547 businesses. Of these respondents, 57 households and 186 businesses responded to the online survey. To improve the response rate for business customers, follow up phone interviews were attempted with those customers who did not respond online. An additional 62 surveys were completed, increasing the total number of responses received to 305 (46% response rate), with 80% from business customers and 20% from individual households.

RA’s business customers are very diverse. They reported average annual gross sales of $5.7 million (median = $515,000, n=101), with a range from $3,000 to $414 million. On average, they have been in business 13 years (median = 8 years), although this ranged from new to over 130 years in operation (n=151). The average number of fulltime employee equivalents was 15 (median = 4, n=145). Business customers were also asked to identify the function their business most often performs; accordingly, 2% identified themselves as distributors, 3% as grocery/meal delivery service providers, 9% as processors/manufacturers, 11% as wholesalers, 25% as restaurants, 34% as retailers, and 17% as other—including bakery, fraternity/sorority house, caterer, coffee shop, farmers’ market vendor, and institutional cafeteria (n=245).

Impact Analysis: Increase in Final Demand for Food Hub Products

To understand the impact of an increase in final demand for RA food hub products and the extent of differential economy-wide impacts from the two models, we consider a scenario in which an exogenous shock increases final demand for food hub products and services by $1,000,000. The only difference between the allocation of the shock in Models 1 and 2 is that in Model 1 all local farm purchases by RA are allocated to the default agricultural sector IMPLAN data, whereas in Model 2, RA farm purchases are allocated to the food hub farm sector.

In addition to the positive shock, we consider a simultaneous negative shock to the wholesale trade sector in order to account for the opportunity cost. The customer survey results reveal that, on average, 49.39% of businesses decreased their purchases from other distributors due to their purchases from RA. Of those who reported decreasing purchases from other distributors, the average decrease was 23.09%. Accordingly, a negative shock of $114,042 was applied to the wholesale trade sector.

The above represents an abbreviated version of our methodological approach. Complete information will be made available via the USDA AMS report as soon as it is released. When the report is made public, a link will be provided here.

Research results and discussion:

The study developed a replicable empirical framework to conduct impact assessments for food hub organizations. By collecting detailed expenditure and sales information from food hubs, an economic impact assessment was conducted to estimate the multiplier effects of a change in final demand for food hub products. By using data from the farms supplying products to the hub, we provide more accurate assessments than that available using secondary data.

Our particular application considered Regional Access (RA), a food hub operating in upstate New York that purchases and markets food products from farms and agribusinesses primarily in NYS. Importantly, we demonstrate that the farms selling to the food hub have differential production functions than those constructed using an aggregate NYS farm sector with available secondary data. From a comparative modeling exercise, we show that the estimated multiplier effects to the farm sector are nearly 8% lower when using the default data and, overall, result in a total output multiplier that is biased downward by 4%. To the extent that the goal of a stimulus to the food hub sector is to support rural economies, capturing more accurate inter-industry linkages of farms that work with food hubs is important.

Results from the model incorporating food hub farm specific data show a gross output multiplier of 1.82, indicating that for every additional dollar of final demand for food hub products (and no opportunity cost), an additional $0.82 is generated in related industrial sectors. However, using customer data, we estimate that for every $1 increase in final demand for food hub products, a $0.11 net offset in purchases from other sectors occur. In other words, the purchase of the food hub’s products resulted in decreased demand for other wholesale products. After applying the additive negative shock, the net output multiplier is 1.63, reducing the gross multiplier by over 10%. Future impact assessments on food hubs should importantly consider opportunity costs.

Our results also show that food hubs support the expanded availability of local farm products. Food hub farmers were asked a series of questions to determine the dollar-value of sales facilitated by services performed by RA, as well as the extent to which RA enabled their farm business to expand. Figure 1 provides a ranking of farms by total farm sales, along with the proportion of sales that were facilitated by RA. Based on this ranking, it is clear that RA is the most significant sales outlet for mid-scale farms ($150,000 – $600,000 in total revenue), and is generally less important (in terms of proportion of total sales) for either small or large/very large farms.

Overall, 60% of farmers interviewed believe their relationship with RA enabled their farm business to expand (18/30), 10% were unsure (3/30), and 30% reported that RA had not enabled their business to expand (9/30). Of the nine food hub farms that responded that RA had not enabled their business to expand, two reported that their business was not currently interested in expanding, and another five mentioned the importance of gaining access to the NYC market through RA. Only one food hub farm with over $1,000,000 in total annual gross sales responded affirmatively that RA had enabled their business to expand. Large and very large farms responded that the volume of farm product sales facilitated by RA was too small to make a significant difference in total sales or production. Other food hub farms who reported that RA did not facilitate business expansion indicated what they perceived as RA’s ‘unfocused’ marketing strategy.

Access to the New York City market was the most frequently cited reason for expanded sales, though improved market access generally was consistently reported. Even farms that were unsure about RA’s role in its expanded sales frequently cited RA’s freight service and its pick-up and delivery flexibility as the primary reasons farmers chose RA over other freight services to NYC. Others used RA’s ‘good reputation’ as a ‘values-based distributor’ to gain market access. This sentiment was particularly true among newer businesses that had not developed direct wholesale purchasing agreements with stores or restaurants.

RA’s warehouse capacity was also cited as facilitating business expansion for farms too small to have significant cooler or storage space. Many farmers keep frozen meat or storage crops (potatoes, root vegetables) at RA’s warehouse, retrieving them periodically to sell through winter markets, CSAs, or wholesale outlets. As a result of access to additional storage, some farmers reported putting more acres into operation specifically for storage crops as a way to increase winter (year-round) farm income.

Business customers were asked a series of questions to better understand the extent to which their purchases from RA displaced other purchases and/or expanded their total purchases of locally-grown or processed products. 79% of respondent reported that the existence of RA enabled their business to expand their product offerings (either in terms of type of items offered or quantity) (n=166). Of those businesses who responded that RA enabled them to expand offerings, on average, they indicated that they increased total available products by 17%, on average. Some of the open ended responses we received specific to farms include: “Regional Access provides a link to some local farmers that streamlines our procurement process. I wish some more of my local farmers would use Regional.” And, “They offer a lot of local farms and we’re able to work with local farms through one business as opposed to working with all farms separately.”

We also asked businesses if they purchased fewer products from other distributors in 2011 due to their relationship with RA. 49% reported that they purchased less product, 46% report that their purchases from RA did not impact their purchases from other distributors, and 5% reported that they did not know (n=164). For those who responded that purchases from RA decreased their purchases from other distributors, they estimated their purchases from other distributors decreased by 23% (n=69). This was the information used above to estimate opportunity costs of expanded RA sales.

43% of respondents reported that if RA did not exist that there is another similar company from which they could purchase ‘locally grown’ product, 39% reported that a similar company did not exist, and 19% responded that they did not know (n=166). 66% of respondents reported that if RA expanded its product availability (i.e., worked with farms with expanded year-round offerings, carried a more diverse selection of products, etc.) that they would purchase more product, 15% responded that they would not purchase more product, and 19% reported that they were not sure how they would respond.

Finally, business customers were asked a series of questions addressing the scalability of the food hub sector (i.e., if RA expanded its delivery routes/days, more products, etc. would the customers purchase more product). Though we know asking questions about possibility for expanded sales from RA’s customers presents a limited view of the potential to scale the food hub sector, the responses provide some clarity into the unmet demand for food hub outputs.

66% of business customers responded that they would purchase additional product, 15% said they would not, and 19% did not know (n=167). Customers were asked to elaborate on the ways in which RA could expand that would cause them to purchase additional product. The range of responses was classified into three general categories: improved logistics, lower prices; and increased product selection.

Complete information on our findings will be made available via the USDA AMS report as soon as it is released. When the report is made public, a link will be provided here.

Research conclusions:

The major impact of our results is to show that food hubs (at least based on our case study) do positively impact local farms (particularly those that are mid-scale). We are now in the process of developing a practitioner’s guide to conducting economic impact assessments of food hubs. We anticipate that this guide will be released before the 2nd National Food Hub Convening in March, and that attendees will use it to: 1) evaluate the feasibility/potential impact of a food hub in their community; 2) assess the impact of existing food hubs to the local community, as well as to participating farmers.

Participation Summary

Education & Outreach Activities and Participation Summary

Participation Summary

Education/outreach description:

Publications:

In addition to the below outreach/extension publications, there are several academic articles that are in the process of being drafted and should be submitted to journals later this year.

Outreach/Extension Publications:

During the project period, I wrote a quarterly column for the Cornell Small Farm Program Quarterly (“Faces of our Food System”) to showcase different distribution options for local food producers (see: https://projects.sare.org/sare_project/GNE11-021).

Schmit, T.M., B.B.R. Jablonski, and D. Kay. 2013. “Assessing the Economic Impacts of Regional Food Hubs: the Case of Regional Access.” Cornell University. September.
Presentations:

In addition to the below, presentations are scheduled for 9 October, 2013 to the Sustainable Agriculture & Food Systems Funders Network (http://www.safsf.org/) as well as for the 2nd Annual National Food Hub Conference (23-24 March, 2014, Raleigh, NC).

Jablonski, B.B.R. and T.M. Schmit– “The Economic Impacts of Local and Regional Food Systems” NYS Council on Food Policy, Kinderhook, NY, 7 December 2012.
Schmit, T.M., B.B.R Jablonski, D. Kay. “Promoting Food Hubs: Update on Farm to Market Projects in NYS.” Invited presentation, 2013 Legislative Conference, New York State Association of Counties, Albany, NY, 4 February 2013.

Jablonski, B.B.R., T.M. Schmit, and D. Kay. “New Research on Food Hubs: Building a Methodology to Assess Economic Impact.” Invited presentation, Northeast Sustainable Agriculture Working Group Annual Meeting, Saratoga Springs, NY, 11 February 2013.

B.B.R. Jablonski and T.M. Schmit. “Estimating the Economic Impacts of Local Foods: Building a Methodology using Case Studies from New York.” Economic Research Service, U.S. Department of Agriculture, Washington, D.C., 28 March 2013

Jablonski, B.B.R. and T.M. Schmit. “The Effect of ‘local’ and ‘scale’ in Local Agri-food Systems.” Selected Paper, Association of American Geographers Annual Conference, Los Angeles, CA, 10 April 2013.

Schmit, T.M. and B.B.R. Jablonski. “Purchasing Patterns for Local Food Producers: Estimating Economic Impacts.” Invited Presentation, An Open Forum to Strengthen Collaborations between Research, Outreach, and Education for the Northeast Food System, The Northeast Regional Center for Rural Development, 31 May 2013.

Jablonski, B.B.R. and T.M. Schmit. “Local’ Producers’ Production Functions and their Importance in Estimating Economic Impacts.” Selected Paper, Agriculture, Food, and Human Values Society Annual Meeting, East Lansing, MI, 20 June 2013.

Jablonski, B.B.R. and T.M. Schmit. “Local’ Producers’ Production Functions and their Importance in Estimating Economic Impacts.” Selected Paper, Northeastern Agricultural and Resource Economics Association, Ithaca, NY, 24 June 2013.

Jablonski, B.B.R. “Telling Your Story: Quantifying the Economic Impacts of Local Food Systems.” Selected Paper, Applied Agricultural Economics Association, Graduate Student Extension Competition, Washington, D.C., 4 August 2013.

Jablonski, B.B.R. and T.M. Schmit. “Local’ Producers’ Production Functions and their Importance in Estimating Economic Impacts.” Selected Paper, Applied Agricultural Economics Association, Washington, D.C. 5 August 2013.

Jablonski, B.B.R. and T.M. Schmit. “Assessing the Economic Impacts of Regional Food Hubs: the Case of Regional Access.” Know Your Farmers, Know Your Food Task Force Meeting, U.S. Department of Agriculture, Washington, D.C. 6 August 2013.

Schmit, T.M. and B.B.R. Jablonski. Assessing the Economic Impacts of Regional Food Hubs: the Case of Regional Access.” U.S. Department of Agriculture, Agricultural Marketing Service, Washington, D.C. 7 August 2013.

Project Outcomes

Project outcomes:

Described above.

Farmer Adoption

This question is not really applicable to our project. The goal was never to have more farmers market product through food hubs, but rather to assess what the impact of food hubs are to communities and participating producers. However, it is my hope that once the practitioner’s guide is made publicly available (March 2014), practitioners will be able to use this information to more accurately assess the extent to which food hubs are an appropriate intervention to support local farms in their particular community context.

Assessment of Project Approach and Areas of Further Study:

Areas needing additional study

There are many areas for future research that emerged from this project. We fully support the recommendations for future research of O’Hara and Pirog (2013) that “collective understanding of the relationship between local foods and economic development can be enhanced through improving data collection, undertaking studies on larger geographic scales…and forming a learning community to review and critique studies” (p.1).

Our results provide strong evidence that economic impact assessments of food hubs require data collection from farm participants. The challenge is that this type of data collection is time consuming and expensive; as presented, the data needs for this type of research are significant. We know that there are ongoing discussions at the National level, particularly within the USDA’s Know Your Farmer, Know Your Food Task Force about the type of data that should be collected. The USDA Agricultural Resource Management Survey (ARMS) data provide a valuable source of information on farm expenditure patterns, but the sample size for local food system participants (not to mention those selling to food hubs) is extremely small. In addition, there is not useful information on location of expenditures. This information would be extremely useful, and facilitate more regular evaluation of these types of initiatives.

This study presents information based on one case study, and the expandability of its recommendations will clearly benefit from a learning community. Recently completed studies from Fischer, et al. (2013), as well as Farm Credit Council and Farm Credit East (2013), will help to determine, for example, the extent to which RA’s expenditure pattern, as well as the expenditure pattern of food hub farms, are similar to other food hubs and participating producers. For example, how do the economic impacts of food hubs change when a hub works only with fresh product producers (i.e., no value added products)? Further, the food hub farm survey was designed to correspond to IMPLAN sectors, rather than to farm profit and loss statements. There are merits and weaknesses to this approach, and as data of this sort continues to be collected, future research to determine more standardized data protocol is extremely important – particularly to compare the results across studies.

Finally, we recommend additional research that compares different models and structures for aggregating and moving locally-grown products into different types of market outlets. Additionally, conducting market channel assessment studies similar to those conducted by Hardesty and Leff (2010) and LeRoux et al. (2010) are recommended to better understand the net impact of food hubs on participating producers, particularly in comparison to other available market outlets.

Works Cited

Barham, James, Debra Tropp, Kathleen Enterline, Jeff Farbman, John Fisk, and Stacia Kiraly. 2012. Regional Food Hub Resource Guide. Washington, D.C.: U.S. Department of Agriculture, Agricultural Marketing Service.

Conner, David, William Knudson, Michael Hamm, and H. Christopher Peterson. 2008. The Food System as an Economic Driver: Strategies and applications for Michigan. Journal of Hunger & Environmental Nutrition 3: 371–383.

Farm Credit Council and Farm Credit East, 2013. Financial Benchmark Metrics and Measurements for Regional Food Hubs. http://www.ngfn.org/resources/ngfn-cluster-calls/financial-benchmarks-for-food-hubs

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Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.