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Demand and Supply Analysis of Farm, Farmer and Farm Family Data

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  • Poon, Kenneth
  • Weersink, Alfons
  • Deaton, Brady J., Jr.

Abstract

Canadian governments collect data on the agricultural sector through a variety of surveys, income tax filings, and support program applications. The definition of a census farm provides the benchmark to estimate aggregate commodity supply which is most critical to analyze and forecast commodity prices. Prices are also collected and made available, but there is growing concern about the lack of price data for contracted commodities. The farm and rural population characteristics are also adequately portrayed through the linkage of the Census of Agriculture with the long-form Census of Population (up to 2006) and the voluntary National Household Survey in 2011. Agriculture and Agri-Food Canada’s typology captures different size and motivation for units of production, but broad inferences on the sector based on this characterization must recognize that it is only for unincorporated farms. These farms tend to be smaller and represent a shrinking percentage of the sector. In contrast, incorporated farms are becoming common place and produce the majority of farm cash receipts. The growing complexity within agricultural production units extends to the relationships with these units back to input suppliers and forward to processors. These components of the supply chain are becoming intricately linked over time and these linkages cannot be presently described with the publically available data on the sector. As the heterogeneity in the agricultural sector grows, the data and information demanded for various analytical and administrative purposes grows along with it. The demands for data to determine the need, design, and evaluation of public policy are simultaneously narrower and greater than the broad requirements by private and public users for aggregate production numbers. Farm support programs are meant as a safety net for viable farms in times of unexpected need so the first step involves assessing financial health and identify farms that are “normally competitive” from the ones that are never competitive. Information from an income statement and balance sheet are required along with input and output levels by farm units over time. No single data set supplies all the data necessary to determine need and effect of farm support programs. Performance measures based on tax data are limited to production margin so this data, while detailed in many respects, lacks information on assets/liabilities, inputs /outputs, and demographics. The latter may become important if future support programs are to target “active” farms. The proposal to consider the individuals behind a unit of production in the determination of support eligibility would drive a large gap between data demands and the current supply of publically provided data. The potential change reflects the growing heterogeneity of the agricultural sector. The initial focus on the unit of production was appropriate for all users of the data. The unit of production was the farm and it was generally operated by a single farmer and it supported a single farm family. This no longer generally applies. This growing heterogeneity forces the objectives of agricultural policy to be clearly specified, i.e. efficiency vs. equity, but the political rhetoric has yet to catch up with the changes as the terms farm, farmer, and farm family are interchanged as if they were still one. The growing distinction between them may result in changes in the nature of the data collected on the sector.

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Bibliographic Info

Paper provided by Structure and Performance of Agriculture and Agri-products Industry (SPAA) in its series Working Papers with number 114094.

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Date of creation: Jul 2011
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Handle: RePEc:ags:spaawp:114094

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Web page: http://servsas.fsaa.ulaval.ca/index.php?id=12482&L=1

Related research

Keywords: data demand; data supply; farm heterogeneity; policy; Agricultural and Food Policy; Community/Rural/Urban Development;

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  1. David R. Just & Steven A. Wolf & David Zilberman, 2006. "Effect of information formats on information services: analysis of four selected agricultural commodities in the USA," Agricultural Economics, International Association of Agricultural Economists, vol. 35(3), pages 289-301, November.
  2. M. Timko & R. M. A. Loyns, 1989. "Market Information Needs for Prairie Farmers," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 37(4), pages 609-627, December.
  3. Suzanne Thornsbury & Kathy Davis & Tara Minton, 2003. "Adding Value to Agricultural Data: A Golden Opportunity," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 25(2), pages 550-568.
  4. Wolf, Steven & Just, David & Zilberman, David, 2001. "Between data and decisions: the organization of agricultural economic information systems," Research Policy, Elsevier, vol. 30(1), pages 121-141, January.
  5. Kislev, Yoav & Peterson, Willis, 1982. "Prices, Technology, and Farm Size," Journal of Political Economy, University of Chicago Press, vol. 90(3), pages 578-95, June.
  6. Babcock, Bruce A., 1990. "Value of Weather Information in Market Equilibrium (The)," Staff General Research Papers 10592, Iowa State University, Department of Economics.
  7. David R. Just & Steven A. Wolf & Steve Wu & David Zilberman, 2002. "Consumption of Economic Information in Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(1), pages 39-52.
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