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Backgrounder: Measuring Farm Profits

OTTAWA, July 20, 2009 — As numerous newspaper surveys have shown, Canadians like to know how their income stacks up against those in similar lines of work. Now that kind of information can be made available to farmers across Canada. A new report by the Canadian Agri-Food Policy Institute (CAPI) explores several ways to use such data to assess farmer profitability.

The report, called Measuring Farm Profitability and Financial Performance, recommends that the federal government publish "disaggregated" farm income information, reporting profits by farm size and type, and by province. In the past, the government has published only aggregated farm income numbers. But these reports were too broad to give an accurate or useful accounting of an individual operation's profitability. They also don't reveal trends within the industry, such as the movement toward fewer but larger farms.

The report identifies 13 performance measures that could be reported within the next year, and recommends that several others be considered for future reporting. This information can benefit farmers, governments, and lenders:

  • It will show primary producers how profitable their farms are compared to neighbouring producers with similar operations. With this information, many producers can turn their attention to aspects of the operation requiring attention to improve competitiveness and profitability;
  • It will help the government make policy decisions with more accurate information on how distinct segments of the farm sector are faring. At the time of developing the report, the federal government based farm policy decisions on just a single aggregated number; and,
  • More precise data will make it easier for lenders and accountants to help primary producers improve their bottom lines, having a better understanding of individual farm operations.
The impetus for the report can be traced back to a CAPI paper published in November 2005, Factors Affecting Current and Future Farm Income Prospects: A Synthesis Report. The authors noted that "aggregate net farm income is not a measure of profitability for business focused farms." The shortcoming can be explained by a series of transformations that have been underway in Canadian agriculture for many years: the substitution of capital for labour, the resulting decrease in farm numbers, the number of farms that are either part-time operations or are secondary income operations, and the expansion in size of the average farm.

While aggregated income data may have once adequately described the state of the industry, farming is now a much more diverse business, one that cannot be easily summed up by aggregated numbers. Broad-based data fail to give policy-makers the information they need to evaluate how specific sectors are performing.

Recognizing the limitations of the current system, CAPI organized a series of consultations with industry stakeholders. The meetings were held in the spring of 2008 at separate workshops in Abbottsford B.C., Guelph, Ontario, Saint-Hyacinthe, Quebec, Regina, Saskatchewan, and Winnipeg, Manitoba. At the consultations, CAPI worked with participants — farmers, lenders, and government representatives — to discuss the strengths and weaknesses of various performance measures, and which measures should be reported on an ongoing basis. The stakeholders expressed strong agreement on the utility of a number of measures and concepts introduced at the workshops. They widely agreed that timely information should be provided on profitability and financial performance by distinct type of farm operation in each region, and recognized that performance measures will drive farmers' behaviour and governments' policy decisions.

The workshop participants examined 20 proposed performance measures and chose 13 that should be developed further and published:

  • Gross margin and gross margin efficiency - without program payments;
  • EBITDA/sales (contribution margin);
  • Operating profit margin (EBIT/sales);
  • Net income — without program payments;
  • Operating expense ratio;
  • Interest coverage;
  • Return on assets (EBIT/assets) - without program payments;
  • Return on equity;
  • Current ratio;
  • Working capital ratio;
  • Debt structure;
  • Leverage (debt to equity); and,
  • Equity position.
This CAPI project is timely. Recently, Statistics Canada and Agriculture and Agri-Food Canada (AAFC) began providing some farm income information on a disaggregated basis. In 2008, AAFC released farm income estimates that included per farm income by size, and per farm income by farm type, including farms classified as producers of grains and oilseeds, horticulture, cattle, dairy, hogs, and for the average of all farm types. For example, in terms of farm size, the average per farm income for farms earning a gross income over or more than $1 million was just under $260,000. Farms grossing between $500,000 and $1 million had a net income of just over $125,000. Net incomes went down from there for smaller farms. In terms of farm type, in 2007 the grains and oilseeds sector earned slightly more than $54,000 in net income per farm. Horticulture earned $71,000, dairy $99,000, cattle $2,300, and hogs $638.

Working with these two federal departments, the CAPI project is designed to take this process a step further, recommending that farm income by size and type be reported regularly, and that several other performance measures be considered for future reporting. For example, based on the 2008 consultations, Measuring Farm Profitability and Financial Performance concludes that there are least four new options for reporting by farm type that can be implemented with no further study:

  • Reporting on Business Segments: The primary unit of reporting of farm profitability and financial performance is on a farm type basis, with 2 or 3 different farm sizes for each farm type.
  • Reporting on a Provincial Basis: The performance measures by farm type are provided on a provincial basis, with the understanding that this reporting may need to include multiple provinces for some farm types due to the limited number of specific farm type operations in a province.
  • Reporting More than the Median or Average Values: For each performance measure a median (or average) is provided as well as measures such as specific percentile rankings (e.g., 25% and 75%) or quartiles.
  • Reporting on Trends: For each performance measure for any farm type, trend data on the reported measures is provided.
The next step in the process is to consider the timing and frequency of the publication of the disaggregated income data and how it will be made available to farm producers and media. Suggestions have been made to create an interactive web-based information delivery system that would allow producers and lenders to key in their own data for benchmark purposes.
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