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From Farm Income to Food Consumption: Valuing USDA Data Products

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  • Lusk, Jayson L.

Abstract

Tightening budgets and increased calls for accountability have sparked efforts to determine the value of U.S. Department of Agriculture (USDA) data products. This report surveys the social science literature on the value of public data, explores the research on the value of USDA data, and describes a framework for prioritizing data collection and reporting. There are a number of motivations for the public provision of information, such as public-good and externality argu-ments, the potential to improve market efficiency and resource allocation, and the desire to reduce information asym-metries and inequities, which suggest a potential under-provision of market information by the private sector. The value of information is related to the ability of producers, speculators, and consumers to make decisions that better correspond with reality. A wide variety of empirical approaches have been used to study the value of information, and the advantages and disadvantages of each are explored. Researchers have used market-reaction tests most often to assess the value of USDA commodity information. The extant literature consistently shows that such data provides valuable information to market participants. Although numerous studies provide indirect evidence that USDA data offer significant economic value, prior research has largely refrained from quantifying the value of data in a way that can be compared with costs. A proposed framework for data product prioritization requires decision-makers to weight the relative merits of different factors affecting the value of data collec-tion and dissemination. The framework can be used to provide qualitative guidance and quantitative, relative rankings of alternative data products. The last section of the report offers recommendations for further research, understanding the extent of data product use across Federal agencies and streamlining data products to more closely match how and when they are most useful.

Suggested Citation

  • Lusk, Jayson L., 2016. "From Farm Income to Food Consumption: Valuing USDA Data Products," C-FARE Reports 266593, Council on Food, Agricultural, and Resource Economics (C-FARE).
  • Handle: RePEc:ags:cfarer:266593
    DOI: 10.22004/ag.econ.266593
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    2. Tianyang Zhang & Ziran Li, 2022. "Can a rational expectation storage model explain the USDA ending grain stocks forecast errors?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 313-337, March.
    3. Rotem Zelingher & David Makowski & Thierry Brunelle, 2020. "Forecasting impacts of Agricultural Production on Global Maize Price [Prévision des impacts de la production agricole sur les prix mondiaux du maïs]," Working Papers hal-02945775, HAL.
    4. Rotem Zelingher & David Makowski, 2022. "Forecasting Global Maize Prices From Regional Productions [Prévision des prix mondiaux du maïs à partir des productions régionales]," Post-Print hal-03764942, HAL.
    5. Rotem Zelingher & David Makowski & Thierry Brunelle, 2020. "Forecasting impacts of Agricultural Production on Global Maize Price [Prévision des impacts de la production agricole sur les prix mondiaux du maïs]," CIRED Working Papers hal-02945775, HAL.

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