America’s farms and farmers are integral to the U.S. economy and, more broadly, to the nation’s social and cultural fabric. A healthy agricultural sector helps to ensure a safe and reliable food supply, improves energy security, and contributes to employment and economic development, traditionally in small towns and rural areas where farming serves as a nexus for related sectors from farm machinery manufacturing to food processing. The agricultural sector also plays a role in the nation’s overall economic growth by providing crucial raw inputs for the production of a wide range of goods and services, including many that generate substantial export value.
If the agricultural sector is to be accurately understood and the policies that affect its functioning are to remain well informed, the statistical system’s data collection programs must be periodically revisited to ensure they are keeping up with current realities. Perhaps the most obvious change in recent decades is that large, complex farms have grown in number and are now responsible for the majority of agricultural production in the United States. Furthermore, the traditional portrayal of farms as self-contained, family-operated businesses does not accurately characterize these entities. The goal of this study is to review, assess, and make recommendations to the U.S. Department of Agriculture’s (USDA’s) National Agricultural Statistics Service (NASS) and Economic Research Service (ERS) to help identify effective methods for collecting data and reporting information about American agriculture, given this increased complexity and other changes in farm business structure in recent decades.1
A wide range of research and policy questions create the imperative for government-collected data on farms and farming. Beyond the value of agricultural statistics in creating a complete economic profile of the country (e.g., for the National Income and Product Accounts), their role is crucial in informing policies on the environment, climate change, biodiversity, food security and safety, population health, land use planning, and natural resource management. The safety and quality of the nation’s food supply and the health and environmental impacts of production processes are among the most important policy areas that agricultural data and statistics help inform.
NASS and ERS publish statistics and reports that regularly and extensively detail the number of farms in the United States, the quantities and types of commodities they produce, the incomes of both the farm businesses and the farm households that run these businesses, and the status and conditions of the agricultural economy. To justify this public investment in the nation’s statistical system, surveys and other data collection instruments must satisfy a range of demands. The justification for data collection by USDA is particularly compelling in cases where (i) data are needed to effectively administer government programs; (ii) data are used in the analysis of policy design and impacts; (iii) data are essential for research on agriculture, health, food, and environmental concerns; or (iv) data improve the workings of markets. NASS and ERS reports and data products often serve one or more of these purposes. In order to maximize the value of data programs, there is a responsibility to make the downstream products as accessible and useful as possible to policy makers, researchers, and other data users while maintaining both privacy (individuals are only asked to reveal information that is necessary to fulfill approved tasks) and confidentiality (the information provided is only shared with appropriate individuals for approved purposes).
The centerpiece of NASS’s mandated responsibilities is to administer the Census of Agriculture, as required by law under the Census of Agriculture Act of 1997. The main objective of the Census of Agriculture is to provide an accurate portrayal of farming in the United States in terms of the number of holdings, their activities, their size distribution, and other characteristics. For the Census of Agriculture, NASS attempts to collect information from all of the nation’s farms.2 Because the Census of Agri-
2 USDA’s glossary of terms defines a farm as “a place from which $1,000 or more of agricultural products were produced and sold, or normally would have been sold, during the year.” As explained throughout the report, the way terms are defined directly affects many of the measures produced by NASS and ERS. The Glossary contained in Annex 2.1 to Chapter 2 includes definitions of key terms as used by USDA and as used in this report (and will be explained as in some cases they differ).
culture is used to produce county-level estimates, the production and land associated with each farm need to be attributed to a county or counties.
USDA is required by Congress, through authorizing or appropriations legislation, to produce statistics on a range of topics, many of which are estimated using data collected through the Agricultural Resource Management Survey (ARMS), which is jointly conducted by NASS and ERS. ERS is also mandated to publish cost-of-production information for a number of commodities. ARMS is an annual cross-sectional survey that is unique in that it collects, in a representative sample, information on (i) field-level farm practices, (ii) the farm business, and (iii) characteristics of the household operating the farm. Roughly 30,000 farms are sampled each year for ARMS, and the sampling unit for this effort is the operation-operator pair—that is, the farm operation and the associated person who runs it.
The mandates handed to NASS and ERS typically specify the type of information required, but not how that information should be generated. As such, the agencies have considerable latitude in how they collect data from different kinds of farms and how statistics on their activities and finances are produced. For this reason, efforts to improve or streamline the Census of Agriculture, ARMS, or other surveys—in terms of content, questionnaire structure, and design—are unlikely to hinder the agencies’ ability to fulfill their mandates.
Furthermore, USDA has considerable flexibility to explore nonsurvey sources of data, such as tax and Farm Service Agency records, which have already been used to improve a number of their data products. Mandates to NASS and ERS generally do not constrain the use of administrative, commercial, Web-based, or other sources that could complement or, in some cases, possibly substitute for elements of the current survey-centric apparatus. Indeed, given the kinds of information on the agricultural sector that have high value to stakeholders, expanding the breadth and diversity of data sources from which statistics are constructed represents a natural evolution for the statistical agencies measuring the sector.
THE ESSENTIAL PERSPECTIVE OF DATA PROVIDERS: BURDEN, RESPONSE RATES, AND DATA ACCURACY
When assessing a data collection infrastructure, key considerations are the burden imposed on respondents and the accuracy of the statistics produced. Minimizing the burden placed on survey respondents is a matter of deep concern at statistical agencies for several reasons. The most obvious reason is that time is a valuable productive resource, and thus mitigating respondent burden reduces the total cost of data collection. Another important motivation for reducing burden is provided by survey
research,3 which suggests that increased burden may reduce the willingness of farmers to respond to the entire survey (unit nonresponse), to respond to particular questions (item nonresponse), or to give careful and accurate responses (measurement error). A high level of respondent burden therefore can have a deleterious effect on the robustness of findings and conclusions based on analyses of the resulting data. Minimizing respondent burden is an especially pressing challenge in today’s climate of declining survey response rates and increasing survey costs.
Compared with small farms, large farm operations—where the roles and relationships among multiple owners and managers and the operations they oversee are more difficult to unambiguously identify—have been found to exhibit lower response rates to ARMS and Census of Agriculture questionnaires. Several of the recommendations in this report are intended to reduce this respondent burden by making information requests clearer, with the overarching motivation of seeking to increase the accuracy and interpretability of the information collected.
WHAT IS A COMPLEX FARM?
As complex farms have become commonplace, the traditional portrayal of farms as self-contained, family-operated businesses no longer accurately characterizes the entities responsible for the majority of agricultural production in the United States. There is no set definition of a “complex farm.” Rather, multiple factors place farms along a spectrum of complexity. Among these factors are the operational and management organization of a farm business, the number and diversity of commodities produced, and the amount of vertical integration in the business. The following dimensions of operational complexity, as well as how these complexities affect the collection of data from farms, are identified and discussed in this report:
- Farm size. Larger farms often have multiple (and sometimes non-operating) owners, multipart management structures, complicated legal entities and relationships, and multiple commodity enterprises operating in far-flung locations.
- Geographic dispersion. Beyond the operational and management complexities created, the geographic dispersion of complex farming operations presents data collection and reporting challenges. For example, widely dispersed operations add to the difficulty of assigning the production of a single farm to specific locations, which is required for widely used county-level statistics.
- Multifarm, multibusiness (including value-added) operations. When several operations are overseen by a single management entity that shares capital and other inputs, it can be difficult to isolate the prices and quantities of inputs and outputs associated with any one operation.
- Farm-connected “nonfarm” output. Measurement may be further complicated when a business’s activities straddle farm and nonfarm production, especially when the latter is closely linked to the former. Determining where to draw the line when reporting production or income is sometimes difficult, both for the business and for the data collector.
- Use of hired managers and labor-contracting entities. Hired and family labor are both treated as employees of a farm, but contract labor is not. Consequently, data collected on two operations that acquire labor differently will not be comparable; the farm that contracts its labor will appear to have fewer employees than an otherwise similar farm that hires directly.
- Multiple and dispersed asset ownership. The presence of more than one person involved in ownership or management complicates the attribution of production and income and makes linking a farm business with a farm household less straightforward.
- Management and decision-making structures. Farms range in structure from those run by a single “principal” operator to those operating as part of a large corporate entity. In the more complex cases, decision-making responsibilities for different aspects of the business are distributed across multiple parties.
DEFINING FARMS, FARMERS, AND FARMING
Better measurements of the complex farms responsible for the majority of contemporary agricultural production in the United States can yield more informative answers about important agricultural policy issues. Measuring complex farms accurately and consistently requires carefully specified definitions. In line with the day-to-day use of the word and current practice at statistical agencies, the definition of a farm should focus on the productive entity as a business engaged in clearly specified types of activities:
For conceptual purposes, the National Agricultural Statistics Service and Economic Research Service should define a farm as an establishment (single unit with a legal or informal management structure) that (1) has its principal or secondary activity in farming with the production of agricultural products and biological assets such as seeds or animals; and (2) for which
full economic data on key business variables, such as costs and revenues, can be collected and made available. (Recommendation 4.2)4
This definition, which is similar to USDA’s approach of associating a farm with a management unit, is intended to help unravel the structure of some common types of complex holdings. Defining a farm in this way means that the number of farms in the economy and their average size, as measured by a statistical agency, partly depends on how farmers organize their businesses.
Distinguishing among the different levels of a business operation becomes crucial for the purpose of establishing sampling units on which to base surveys and then for interpreting the resulting data.
The U.S. Department of Agriculture should consider adopting definitions of (1) farm establishment as a business establishment engaged in farming and (2) farm business as a collection of business establishments with at least one farm establishment linked by common ownership or control. (Recommendation 5.1)
The farm business, defined as a farm or farms sharing a common management structure, includes both cases where one business owns and operates one establishment (a simple farm business) and cases where one business owns and operates a group of establishments (a complex farm business). Currently, whether respondents consider their productive activities to be one farm or more is at their discretion and open to interpretation. Giving guidance to farmers by using clear definitions, while also taking steps to increase the likelihood that data collection aligns with the way farmers organize their businesses, is important for reducing farmers’ confusion about how to report information.
Defining the farmer as the owner of the business entity signals the importance of those who are responsible for decisions made on the farm and who bear all the financial risks. Risk management is an important aspect of U.S. farm policy, implying that this is an important identifying characteristic of a farmer. However, to characterize and understand agricultural production, both ownership and management are of interest. Folding both into one category under the term producer is one solution. In 2017, NASS introduced this term to replace the term operator, and has used it to indicate any person involved in decision making, whether in day-to-day farm management or as absentee owners who may only be involved sporadically in investment or hiring decisions.
4 Not all report recommendations are included in this summary. The recommendation numbering refers to the chapter in which each recommendation can be found in the report. In this case, Recommendation 4.2 is the second recommendation in Chapter 4.
As with identifying the farm itself, minimal guidance is currently given on how to identify the farm operator, the person making day-to-day decisions or, if multiple operators are involved, the principal operator. Identifying the principal operator, as is requested for ARMS, can be particularly challenging when different people have primary responsibilities for distinct aspects of the farm, such as the management of marketing and the management of crop production, as well as in cases of spouses or partnerships. This vagueness can create confusion for respondents, even if they are making an earnest effort to match their responses to the intent of the question. Interpreting the resulting survey data also requires assumptions about how respondents have understood the terms used in the survey instrument. The way units of measurement are understood ultimately affects statistics on the number of farms, the size and scope of the farm sector, and the farm population.
Because not all establishments owned by a business involved in farming are necessarily farms, another issue arises concerning accounting boundaries. The essence of the problem, and an important source of complexity in agricultural production, is that farming activities take place within a larger food and agriculture supply chain. When policies or programs require information on overall agricultural production in the United States, as opposed to what happens “on the farm,” some farming and agricultural activities—carried out by establishments that are not classified in a statistical framework as farms but instead as agricultural support firms, food processing companies, or retailers—should be considered within the scope.
A related boundary issue is that farms may engage in secondary activities that are not farming but, rather, food processing or retail activities closely linked with farming. Cheese making and roadside or farmers market stalls selling farm produce are examples.
These sectoral overlaps mean that a census of farm establishments is not a census of exclusively farming or agricultural activities, because some of the included farms also engage in a subset of activities outside farming, some of which could get misreported. Meanwhile, some farming and agricultural activities take place in establishments that are not classified in a statistical framework as a farm but instead as an agricultural support firm, a food processing company, or a retailer. It would be desirable for some purposes—such as for the national income and product accounts, in which a complete, non-double-counted accounting of farming or farm product retailing is required—to extend survey coverage to include these secondary or smaller activities.
Here again, currently used definitions give considerable flexibility to respondents about how to report the data, which has implications for data accuracy, interpretability, and respondent burden. Therefore:
In line with statistics for other parts of the economy for classifying a business as a farm or as an entity operating in a nonfarming sector with secondary activities in farming, the National Agricultural Statistics Service and the Economic Research Service should apply clear rules based on the nature of the business’s principal productive activities. (Recommendation 4.1)
This recommendation does not imply that only entities classified as farms with farming as a primary activity are of interest to NASS and ERS. On the contrary, the agencies should be interested in all businesses engaging in farm activities, even if those are minority activities. To maintain comparability over time, counting farming activities in businesses that are classified in sectors other than farming becomes even more important when production shifts from simple to complex farm operations.
In addition to agriculture, an agribusiness complex has been created in the United States and other large economies. This means that agricultural policies, as well as environmental policies that target farming, have effects on sectors other than farming and agriculture. To give policy makers and the public insight into these interdependencies, developing statistics on this agribusiness complex is important. This can be done with a methodology based on the input-output tables of the national accounts (and their satellite accounts) that link farming to activities in other sectors:
The National Agricultural Statistics Service, the Census Bureau, and the Bureau of Economic Analysis should report on the size of the agribusiness complex and its components in terms of income, employment, and environmental impacts and develop a program that harnesses existing data collection efforts to create a new satellite account for reporting on food and agriculture industries. (Recommendation 4.4)
Finally, policy makers and researchers are not only interested in farms and farmers but also in farm households, because household dynamics influence the behavior of the farmer and operation of the farm. A well-known example is when investment decisions are made by farmers over long time horizons, where their supply responses to policies are influenced by whether or not they have a successor. This interest in the total income and well-being of the farmer and the farm household, which factors into ERS mandates, is especially relevant for family farms. On very large farms and in complex farm businesses, the family dimensions are relatively less important to the functioning and stability of the operation. Such organizations are more like big family firms in other sectors. The NASS and ERS definition of a farm household—as those who share dwelling units with principal farm operators of family farms—is consistent with the way the term “household” is used more broadly across the statistical system.
A DATA COLLECTION STRATEGY FOR IMPROVING THE MEASUREMENT OF COMPLEX FARM OPERATIONS
When considering the appropriate statistical unit for measuring complex farm operations, the motivating question should be, what is the measurement objective? Conceptually, there are three types of statistical units that can come into play, each with a distinct emphasis:
- the business: the farm operation (later redefined as a statistical enterprise/establishment)
- the people: individual farmers and farm households
- the land: farmland, subdivided into fields
Linkages exist between each of these statistical units. For example, ownership, decision making, and employment are associated with the business and the individuals and households involved; and the business is associated with a geospatial coordinate(s). Designing sample frames that maintain reliable linkages between statistical units should be a high priority for a data collection program, because such linkages can be used to indirectly generate representative samples of statistical units across different frames. The USDA already has a well-established sampling frame methodology that deals with some of the complexity brought on by the presence of multiple statistical units that are all of interest.
By using a combined frame of farm businesses and individuals, NASS and ERS track the linkages between the two. This structure works well for simple farms, but measurement issues arise when operation complexity increases. When farms are complex, so that there is no longer perfect overlap between the business unit, the household, and the location, this ambiguity makes it difficult for NASS and ERS to accomplish their missions of providing policy makers, researchers, and producers with reliable estimates of agricultural production activity.
The first step in creating an integrated data collection strategy that can deal with complex cases more systematically is to create a Farm Register. Of course, USDA already has a farm list, which embeds many of the characteristics that are required. However, the existence of multifarm, multibusiness operations, along with the complexity of the management and decision-making structure of these businesses, requires modifications to the current combined establishment-household list-frame approach.
To address the above-described ambiguity that results when farms consist of more than a single-unit farm establishment, the proposed approach would simplify sampling by maintaining separate lists of farms, farm operators, and land holdings, so that the sample unit selected can be the one that is optimal for measuring that characteristic. For instance, information on
off-farm income is best obtained from a household-type survey, rather than a survey that targets farms.
The National Agricultural Statistics Service should expand on its list frame to create a Farm Register that provides an ongoing enumeration of all farm establishments in the United States. (Recommendation 5.2)
This Farm Register would be similar to the current NASS list frame, but it would focus on the enumeration of farms as businesses and the characteristics of those businesses. It would be an “evergreen” product, regularly updated as new information becomes available.5 Survey-specific list frames would be drawn from the Farm Register at a single point in time to support individual statistical programs, including the Census of Agriculture and ARMS.
The Farm Register should follow a farm establishment/farm business structure (as defined above) similar to that of the Census Bureau’s Business Register. A farm establishment would be the smallest unit that can report agricultural production, including revenue, expenses, and employment. Each establishment would have an industrial classification, corresponding to its primary activity; however, for the reasons articulated above, secondary activities would also be identified.
Consistent with the above recommendation that NASS and ERS be more prescriptive in their designation of statistical units, a farm business would encompass a collection of farm establishments that are linked by ownership and control:
All farm establishments in the Farm Register should be linked to a farm business. In most cases, farm businesses will include only one farm establishment, but they may include more than one. (Recommendation 5.5)
The following information should be maintained on the Farm Register for each farm establishment:
- primary North American Industry Classification System codes for the farm establishment,
- commodity output flags (North American Product Classification System6),
- name and address of farm,
- other geolocation indicator,
5 Regular, although not continuous, updating of the Farm Register makes sense. NASS is aware of this, because it keeps its area frame’s “found” farms separate from the currently listed farms for the purpose of estimation.
6 Product classification is often more complicated in agriculture than in heavily capital-based industries because its primary asset is land, the utilization of which is more flexible.
- size indicator (sales, number of employees), and
- linkage variables (e.g., Employer Identification Number).
The farm business designation corresponds to a statistical enterprise in Census Bureau nomenclature.
The purpose of the agriculture statistics programs in NASS and ERS is to cover all farm activity, regardless of the industry of the statistical unit. The Farm Register may therefore contain enterprises and establishments that do not have agriculture as a primary activity. For instance, an enterprise that is primarily engaged in processing farm products may also operate its own farms. Although most of that enterprise’s value added could be associated with processing, and thus classified as manufacturing, the farming activity still needs to be captured.
Given the requirement to produce statistics on the financial well-being of farm households, the farm register would include linkages between the statistical units (farms or individuals) and households. USDA already identifies some people associated with farm operations, such as those involved with decision making, employment, ownership, and contacts for surveys. However, this is not done systematically or completely, as the aim in the past has been to identify a principal operator among all the persons involved with a farm.
Ideally, a household/individual frame would include the households of all the operators. The operators enumerated are not necessarily the same as the people who should be listed as contacts for survey purposes.
The National Agricultural Statistics Service should create a separate list frame of farm households within the overall Farm Register that would lead to a more efficient sampling of farm households and/or persons involved in farm activities, since the household list itself can be stratified or augmented with auxiliary data. (Recommendation 5.6)
Building on the existing operator list frame maintained by NASS, the Farm Register should consist of a set of relational databases that include information on places and people and that identify households and businesses with suitable links between the two. This approach would also improve continuity between operator and household records and address problems that arise when the primary operator changes, especially in cases of spouses, two generations of operators (co-principal operators), or partnerships.
Building on this framework, the Census of Agriculture could be recast as a source of basic structural characteristics that in turn creates a sampling frame for more focused surveys. ARMS and its various subcomponents could be reformulated into an annual farm establishment survey, one that
collects the information needed for measuring the cost of production and the financial health of farms, including the information needed by the Bureau of Economic Analysis for national economic statistics. Periodic, specialized surveys can be used for any questions not needed for these purposes or for mandates that explicitly require annual collection. Some immediate benefits of such a reorganization would be a reduction in respondent burden and the ability to reallocate USDA resources toward managing the data collection needs of complex operations.
THE POTENTIAL AND LIMITATIONS OF ADMINISTRATIVE AND OTHER NONSURVEY DATA SOURCES
Survey-based products, derived from a well-designed Farm Register, can be combined with other sources of data to improve the overall quality and utility of information on the farm sector while reducing respondent burden.
Broadening the scope of data sources for the measurement of complex farm operations is consistent with efforts across the federal statistical system to increase reporting capacity by exploiting administrative, commercial, and nonstructured (including Web-based) sources. Use of nonsurvey data for the production of agricultural statistics is an approach increasingly being undertaken by statistical agencies around the globe and indeed by USDA itself; geospatial data and numerous administrative sources are prominent examples. While both NASS and ERS currently use nonsurvey data sources for statistical purposes, there is even greater potential for their use. For example, they may be used to facilitate the construction of sample frames, to validate data collected from survey instruments, to augment existing collection efforts to handle nonresponses or missing information, and to contribute to data processing through model-assisted calibration, model-based estimation, and imputation of survey responses.
As has been documented in numerous reports—most recently and prominently that of the Commission on Evidence-Based Policymaking (2017)—the use of administrative data can improve the overall efficiency of data programs by reducing agency expenditures, lowering respondent burden, encouraging the sharing of information across departments and agencies, and potentially increasing the accuracy of information based on survey data. Since administrative data are maintained to support many USDA programs, the scope of these potential applications is vast.
How effectively the federal statistical system can meet future data demands will largely depend on the extent to which data sources—survey and nonsurvey, national and local, public and private—can be combined in synergistic ways. This assertion certainly applies to NASS and ERS programs, since their current surveys alone can no longer provide all the
variables and levels of geographical detail necessary to meet the demands of agricultural research and policy making.
The U.S. Department of Agriculture should explore opportunities for record linkage at the person level to obtain information on key demographic and off-farm employment variables, and perhaps with the Internal Revenue Service on farm income and expense information. These opportunities can be explored through participation in the Federal Statistical Research Data Centers Program, a partnership between federal statistical agencies and leading research institutions that provides secure access to restricted-use microdata for statistical purposes. (Recommendation 6.1)
NASS and ERS have already developed a data access mechanism in which ARMS data are accessible for statistical purposes through a cooperative agreement with NORC at the University of Chicago. This arrangement works well for those who want to work with ARMS data alone, but it does not provide opportunities for linking with data from other agencies.
Any redesign of the Census of Agriculture and ARMS should be done with the presumption that these instruments will need to be linkable to other data sources maintained by USDA, to other statistical agencies, and even to nongovernment organizations. The key design element in the data system for promoting data linkages—for example, between household records and farm business records—is created during questionnaire design. If units of measurement are consistent, then in principle a crosswalk among a range of data sources can be maintained.
Given the work of the Commission on Evidence-Based Policymaking (2017) to improve the climate for legislative changes that would make data linking more routine across the statistical agencies, now is the time for NASS and ERS to begin mapping out a strategy to coordinate their survey and administrative data programs, both within USDA and across other key agencies such as the Census Bureau and the Bureau of Labor Statistics.