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Calf and Yearling Prices in the Western United States: Spatial, Quality, and Temporal Factors in Satellite Video Auctions

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  • Blank, Steven C.
  • Saitone, Tina L.
  • Sexton, Richard J.

Abstract

This paper investigates spatial, quality, and temporal factors impacting prices of calves and yearlings in the western United States using satellite video auction data and a hedonic regression framework. Prices received by western ranchers are discounted by approximately the costs of shipping cattle to the Midwest for processing. Other key results include identifying the presence of temporal price premiums for seller-offered forward contracts, providing new estimates of the marginal value associated with key quality attributes and management practices and finding support for the price benefits of third-party quality certification. We also link variability in estimated valuations for value-added attributes to the stage of the cattle cycle.

Suggested Citation

  • Blank, Steven C. & Saitone, Tina L. & Sexton, Richard J., 2016. "Calf and Yearling Prices in the Western United States: Spatial, Quality, and Temporal Factors in Satellite Video Auctions," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 41(3), pages 1-23.
    • Handle: RePEc:ags:jlaare:246175
    DOI: 10.22004/ag.econ.246175
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    Cited by:

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    3. Allan F. Pinto & Brittney K. Goodrich & William Kelley & Max Runge, 2023. "Price determinants of bred heifers: Do reputations matter?," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 71(1), pages 5-23, March.
    4. McKendree, Melissa G.S. & Tonsor, Glynn T. & Schulz, Lee L., 2021. "Management of Multiple Sources of Risk in Livestock Production," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 53(1), pages 75-93, February.
    5. Leslie J. Verteramo Chiu & Loren W. Tauer & Yrjo T. Gröhn, 2022. "Pricing efficiency in livestock auction markets: A two‐tier frontier approach," Agricultural Economics, International Association of Agricultural Economists, vol. 53(S1), pages 139-151, November.
    6. Elham Rahmani & Mohammad Khatami & Emma Stephens, 2024. "Using Probabilistic Machine Learning Methods to Improve Beef Cattle Price Modeling and Promote Beef Production Efficiency and Sustainability in Canada," Sustainability, MDPI, vol. 16(5), pages 1-19, February.

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