Review of the financial data provided by the agricultural resource management survey

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Agricultural Finance Review

ISSN: 0002-1466

Article publication date: 27 July 2012

545

Citation

Moss, C.B., Featherstone, A.M. and Wilson, C.A. (2012), "Review of the financial data provided by the agricultural resource management survey", Agricultural Finance Review, Vol. 72 No. 2. https://doi.org/10.1108/afr.2012.42172baa.001

Publisher

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Emerald Group Publishing Limited

Copyright © 2012, Emerald Group Publishing Limited


Review of the financial data provided by the agricultural resource management survey

Article Type: Guest editorial From: Agricultural Finance Review, Volume 72, Issue 2

Data on the financial condition of the farm sector are important on several levels. From a policy perspective, data on the effects of proposed agricultural, environmental and macroeconomic policies may affect policy formulations. From an academic perspective, the availability of data shapes faculty research programs throughout the Land Grant System and other research institutions. At the beginning of the second decade of the twenty-first century, the Agricultural Resource Management System (ARMS) is the primary source of data on the financial condition of the farm sector serving both needs. ARMS is the successor of the Farm Cost and Return Survey (FCRS) which provided an annual system of production accounts for a variety of crop and livestock enterprises from 1975 through 1996. ARMS includes several of the goals inherited from the FCRS, but also expanded the survey to include information on the financial position of the farm firm as well as information on the well-being of the farm household.

According to a Google Scholar search (May 17, 2012) using “USDA ARMS data”, since 2012, 520 articles and patents appeared with those terms. From 2011 to 2012, 1,290 documents appeared with those terms. Using anytime as the period of time for the search, 18,200 documents appeared. Thus, the use of the ARMS data is far reaching and the importance of having accurate data is unquestionable.

In August 2010, the Economic Research Service formed a panel to review the assumptions and implications of the financial statements generated by ARMS, the last such review occurred in the early 1990s. Since then, several changes have occurred in the US farm sector. In the 1990s, the agricultural sector was coming off a period of financial stress. In addition, since the early 1990s, the structure of agriculture has changed substantially. The sector has seen an increased level of supply chain integration. Agricultural policy changed significantly with the introduction of the passage of the Federal Agricultural Improvement and Reform (FAIR) Act of 1996 that provided for some degree of decoupling of production from farm payments (Schmitz et al., 2010). Those changes in farm bill and subsequent modifications have placed increased emphasis on crop insurance as an important safety net with the advent of revenue based products. Further, tax considerations such as accelerated depreciation and Section 179 capital expensing have become increasingly important.

Given these changes, the panel reviewed the ARMS process for measuring the farm level financial statements and the ability to measure the financial position of the industry. Sub-objectives included:

  1. 1.

    A review of ARMS’ mission and the farm financial information deemed important to fulfill ARMS’ goals.

  2. 2.

    Issues regarding data collection procedures for information important for financial statements.

  3. 3.

    The policy content and accounting principles of the farm balance sheets and income statements generated from ARMS.

  4. 4.

    Other financial statements or information that either could be collected or generated using data already collected.

  5. 5.

    Dissemination and recommendations for communicating ARMS information.

The panel quickly recognized that ARMS provides valuable information key to understanding the evolving farm situation in the USA. ARMS is unique because of its national coverage while maintaining coverage of a variety of farm types and sales classes that are important for the analysis of agricultural policy. Further, the panel recognizes that ARMS is a multi-faceted multi-objective survey such that collection of data on the financial condition of agriculture is one of several data purposes served.

This issue of the Agricultural Finance Review is composed of ten theme papers that develop some of the critical issues raised by the panel and provide the basis of recommendations and future research needs. The first of these papers by Kuethe and Morehart provide an overview of ARMS including a brief history and the design of ARMS. The paper also presents the multiple objectives that the USDA attempts to fulfill with the survey, the uses of ARMS, and how the data are accessed.

The following two papers examine the challenges of observing and reporting the financial condition of the farm firm given the increasing complexity of the farm sector. Moss, Klinefelter, and Gunderson explicitly develop the accounting issues raised by the increasing complexity of the farm sector. These accounting issues are viewed within the context of who the users of the financial information are and what facets of that information will be most useful to those identified users. Featherstone, Wood, Herbel, and Langemeier provide a more detailed discussion of some of the operational changes occurring in the farm sector. For example, the evolution from the sole proprietorship to super farm situations where sole proprietorships are merged into a larger operation with complicated ownership arrangements, or organizations based on several generations (i.e. father, children and grandchildren where the father is no longer involved).

The next two papers examine keeping ARMS relevant. Blank and Klinefelter examine factors that will keep ARMS relevant from the farmer’s viewpoint. They divide the issues into shortcomings of the current survey including the choice and reporting of leading indicators, and the reports generated for use by farmers. The last possibility includes distributional information that could be used to compare the performance of individual farms with a set of comparable firms (sort of a Dunn and Bradstreet for agriculture). Featherstone, Park, and Weber take up three slightly different challenges to ARMS:

  1. 1.

    possible difficulties with changing sample nonresponse;

  2. 2.

    the ability to draw panels from ARMS; and

  3. 3.

    the possibilities of expanding the production cost components of ARMS.

Each of these affect the research uses of ARMS in slightly different ways. Sample nonresponse may bias the data generated by ARMS, particularly if the nonresponse is systematic (i.e. more frequent for larger firms). Panel difficulties have been a perennial point of discussion since the same group of farmers is not sampled each year. Finally, detailed data on production is limited in its periodicity and scope.

The next two papers develop the emerging issues that affect how ARMS values the financial position the farm sector. Ellinger, Ahrendsen, and Moss examine some of the difficulties associated with the balance sheet and income statement. They address difficulties associated with asset valuation including the increasing popularity of capital leases, treatment of prepaid expenses and accruals, and the nebulous relationship between tax treatments such as Section 179 and modified accelerated cost recovery allowances under the tax code. Briggeman, Koenig, and Moss then examine the relationship between the debt position of agriculture derived from ARMS compared with the debt position that is observed by reports filed by lenders (for example, commercial bank filings with the Federal Reserve System and reports filed with the Farm Credit Administration).

Given this structure, the panel then turned to the uses of ARMS data. Ahrendsen and Katchova examine the use of ARMS data to generate financial ratios that can be used by farmers and policy makers to analyze the implications of agricultural policies and other events on the financial well-being of the farm sector. They explicitly analyze ratios reported by ARMS’ web tool. Along the same lines, Barnard and Nordquist analyze the generation of additional financial statements such as changes in statement of financial condition or flow of funds statements.

Background information

Before summarizing the major findings, it is important to understand some of the background information important to understanding the panel process. In addition, it is important to understand previous work on ARMS.

The ARMS methodology has developed a well-reasoned sampling methodology to collect the information. It is important to realize that the focus of this panel did not examine the methods of sampling. Recently, the National Research Council (2008) completed an in-depth review involving ERS and NASS to consider changes to that collection process.

At the most basic level the Agricultural Resource Management Survey (ARMS) is an integrated collection mechanism that gathers information necessary to perform an annual assessment of the US agriculture from production practices including conservation and chemical practices to the financial condition of farm enterprises and the farm household. It is a multiphase survey with Phase I conducted from May through July that collects information on crop and livestock production and the value of sales. These data are used to screen participants for eligibility in the other phases. Phase II, a field-based survey, focuses on production practices, resource use, and cost of production. Phase II is conducted between September and December. Finally, Phase III conducted between February and April collects information on farm finance, and the operating and household characteristics.

The ARMS is used to meet a variety of agricultural and environmental policy needs. From the financial perspective, the collection of cost of production data is mandated by the USA. Title 7, Chapter 35A, Subchapter II, paragraph 1441a that requires a cost of production study for wheat, feed grains, cotton, and dairy. The ARMS also supports the National Income Accounts (NIA) by proving detailed information on farm expenses and non-commodity sources of income. However, for the purposes of this panel the most relevant use of ARMS is to:

[…] help determine net farm income of farmers and ranchers and provide data on the financial situation of farm and ranch businesses, including debt levels […] help determine the characteristics and financial situation of farm and ranch operations and their households, including information on management strategies and off-farm income (National Research Council, p. 16).

As discussed, the ARMS is a multiple objective survey mandated to address cost of production, cash receipts for the National Income Accounts and to determine the net farm income and financial situation of farm and ranch businesses. In addition, there is information collected on the farm households to address farm family well-being. At the same time, the organizational structure of the production agriculture sector is changing. Does it make sense to use the current ARMS process for gathering data for all business entities? As an example, some farm records systems collect farm family consumption data. While that makes sense for individual sole proprietorships, it is not clear what this information would mean for partnerships and/or family corporations that consist of multiple entities. These challenges deal with accounting for activities associated with various stakeholders and accurately representing vertical integration. Allocating income, expenses, assets, and debt becomes increasingly challenging as these complexities become more common. In addition to these considerations, farm size and commodity specialization also present challenges.

Much of the information from ARMS is shared with various stakeholder groups in numerous forms. Some stakeholders have significant understanding of the ARMS, while others have very limited understanding. Are there more efficient ways to convey to the general public what ARMS is? Are there more efficient ways to present to the profession what ARMS is?

There are two primary methods of distributing the results and data from ARMS: the ARMS Web Tool (2012) (www.ers.usda.gov/briefing/arms) and the other is providing access to the survey through the NORC data enclave. To access the online web tool, you will need to click on “Tailored Reports”. The ARMS web tool has undergone a substantial makeover recently with new features added in the April 2011 and November 2011 updates. One in particular that is important is the “data dictionary”.

Summary and recommendations

The recommendations from the panel and the justification for those are found in detail in the papers that follow in this issue of Agricultural Finance Review. However, we will summarize the recommendations in three levels of importance:

  1. 1.

    Strongly recommended:

  2. 2.
    • Clarify the prepaid expenses and capital lease questions so that they are more definitive. This will help increase the accuracy of data provided and increase the interpretability of the data provided.

    • Reconsider the use of tax depreciation in the financial statements in light of the use of Section 179 depreciation. For example, in years when incomes are high, the reported income will be understated and in years when income is low, the reported income will be overstated. Research should be conducted that would develop an alternative method to tax depreciation.

    • Consider customizing the survey and data collection methods to the producer size class and farm type. This may remove some of the respondent burden.

    • USDA should commission a detailed survey of multiple entity operations to document the current importance of these operations in the US agriculture. This would provide a baseline to understand the current situation and would provide information for redesigning the data collection process for these operations. This would also provide important information for understanding how quickly the structure of the farm sector is changing in different regions of the country. It would also provide information regarding the potential implications for surveying sub-entities as compared to the entire entity.

    • Increase efforts to disseminate the ARMS results more widely. ARMS is an important tool for understanding the US production agriculture but it is an expensive endeavor. In light of current budget concerns, widespread political support will likely be important to the future of ARMS. Efforts should be undertaken to more effectively market the web took to undergraduate students, extension agents and their audiences, and industry.

    • In light of limited budgets, ARMS should develop partnering with universities to provide additional research support for improving ARMS. One mechanism to communicate would be to develop a research topic cafeteria. Topics should include updating research that supports ARMS imputation methods. It would also include other topics important to the structure and financial condition of the US production agriculture.

    • Consider adding another size category of farms; those with sales of $5 million and more.

    • Consider adding a couple of forward looking questions that address farmer expectations. These questions would be used to gage farmer sentiment with regards to the future of production agriculture. The financial statements provide an excellent picture of the current situation. However, policymakers may benefit from an understanding of future expectations.

    • Increase the collaboration with universities that have farm record systems. Given the US budget considerations, it is unlikely that panel data will be developed in the near future. Working with those universities that have record systems will allow for external validation of the methodologies to create pseudo panels.

  3. 3.

    Recommended:

  4. 4.
    • Continue to increase the value of the web tool. Provide more information on information that is already available such as the percentage of farms above certain critical levels of leverage, liquidity, positive net farm income, etc. Also consider allowing this information to be available by quartiles.

    • Consider adding a Mountain State and perhaps deleting Missouri from the 15 states with state-level data if necessary. We would recommend adding a 16th state but if not possible, then we would recommend deleting Missouri. While agriculture in Mountain States is unique, there are currently no Mountain States with detailed state-level data. This would provide an understanding of important changes in that type of agriculture., there should be a process developed for bringing states in or removing them on a periodic basis.

    • Consider collecting additional information to construct a cash flow statement. A cash flow statement may provide an early indication of financial stress in the sector by providing additional information on sector liquidity. This statement could be developed by collecting information on the sales of land and other extraordinary income.

    • Consider adding a statement of owner’s equity. Most of the information is already collected to develop this statement.

    • Review debt questions to get more information regarding interest rate paid and information on lines of credit. Often changing lines of credit and interest rates paid can be an indicator of impending financial stress.

    • Increase the number of the 21 ratios suggested by the Farm Financial Standards Council (FFSC) reported by ARMS. The FFSC ratios have become industry standards for measuring financial health and would increase the value of the ARMS to the industry.

  5. 5.

    Suggestions:

  6. 6.
    • Currently the ten regional groupings are constructed on a more vertical division of the USA Perhaps horizontal groupings instead of vertical might better align states with similar agriculture. For example, climate is more similar in horizontal regions than vertical regions.

Charles B. Moss, Allen M. Featherstone, Christine A. Wilson

References

ARMS web tool (2012), available at: www.ers.usda.gov/briefing/arms

National Research Council (2008), Understanding American Agriculture: Challenges for the Agricultural Resource Management Survey, National Academies Press, Washington, DC

Schmitz, A., Moss, C.B., Schmitz, T.G., Furtan, H.W. and Schmitz, H.C. (2010), Agricultural Policy, Agribusiness, and Rent-Seeking Behaviour, 2nd ed., University of Toronto Press, Toronto

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