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Effect of government quality grade labels on consumer demand for pork chops in the short and long run

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  • Lusk, Jayson L.
  • Tonsor, Glynn T.
  • Schroeder, Ted C.
  • Hayes, Dermot J.

Abstract

Despite ample evidence of pork quality variability, at present there are few signals that would incentivize growers to produce higher quality pork. Using split-sample, choice experiment data from a nationwide online survey of U.S. pork chop eaters, this research determines changes in pork chop demand in response to a potential change in U.S. government policy that would introduce a new pork quality grading system based on color scores. Our simulations include novel short-run projections in which the conditional and latent class logit models are inverted to yield inverse demand curves. The inverse demand curves are used to calculate equilibrium prices and pork revenue given a fixed supply of different pork qualities. We supplement these calculations with a more traditional “long run” analysis in which prices are fixed and quantities of different qualities adjust. Compared to the status quo (control) of no quality grades, we find that two grading systems based on alternative nomenclatures (Select, Choice, Prime vs. Good, Better, Best) both have the potential to increase pork chop sales and revenue to the pork industry; however, we also find that if only the highest quality is labeled, revenue could fall as the increase in demand for the higher quality is offset by the fall in demand for the lower qualities. Results also highlight important heterogeneity in consumer preferences, and although sensory studies strongly suggest redder pork chops are more highly preferred, there remains a non-trivial share of consumers who prefer whiter pork even after quality grade labeling. Overall, this study offers several insights that can help inform labeling and quality grading policies.

Suggested Citation

  • Lusk, Jayson L. & Tonsor, Glynn T. & Schroeder, Ted C. & Hayes, Dermot J., 2018. "Effect of government quality grade labels on consumer demand for pork chops in the short and long run," ISU General Staff Papers 201804260700001615, Iowa State University, Department of Economics.
  • Handle: RePEc:isu:genstf:201804260700001615
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    Cited by:

    1. Thies, Annika Johanna & Altmann, Brianne Andrea & Countryman, Amanda & Smith, Colton & Holloway, Maggie & Nair, Mahesh N., 2024. "Reducing food waste: How beef color influences consumer buying decisions," GEWISOLA 64th Annual Conference, Giessen, Germany, September 25–27, 2024 364731, GEWISOLA.
    2. Altmann, Brianne A. & Anders, Sven & Risius, Antje & Mörlein, Daniel, 2022. "Information effects on consumer preferences for alternative animal feedstuffs," Food Policy, Elsevier, vol. 106(C).
    3. Liu, Ruifeng & ,, 2021. "What We Can Learn from the Interactions of Food Traceable Attributes? a Case Study of Fuji Apple in China," 2021 Conference, August 17-31, 2021, Virtual 315916, International Association of Agricultural Economists.
    4. Afyaa Alessa & Himanshu Shee & Tharaka De Vass, 2025. "Leveraging Milk-Traceability Technologies for Supply-Chain Performance: Evidence from Saudi Dairy Firms," Sustainability, MDPI, vol. 17(13), pages 1-25, June.
    5. Wenjing Nie & David Abler & Liqun Zhu & Taiping Li & Guanghua Lin, 2018. "Consumer Preferences and Welfare Evaluation under Current Food Inspection Measures in China: Evidence from Real Experiment Choice of Rice Labels," Sustainability, MDPI, vol. 10(11), pages 1-15, November.
    6. Mihai Dinu & Silviu Ionuț Beia & Simona Roxana Pătărlăgeanu & Alina Florentina Gheorghe & Irina Denisa Munteanu & Mihail Dumitru Sacală, 2025. "Exploring the Impact of Wheat Prices and Annual Income on Pig Carcass Prices in European Countries: A Spatial Panel Regression Analysis," Agriculture, MDPI, vol. 15(21), pages 1-14, October.
    7. Yu Jiang & H. Holly Wang & Shaosheng Jin, 2023. "Mobilising the public to fight poverty using anti‐poverty labels in online food markets: Evidence from a real experimental auction," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(1), pages 168-190, February.
    8. Nie, Wenjing & Abler, David & Li, Taiping, 2021. "Grading attribute selection of China's grading system for agricultural products: What attributes benefit consumers more?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 93(C).
    9. Liwen Ling & Dabin Zhang & Shanying Chen & Amin W. Mugera, 2020. "Can online search data improve the forecast accuracy of pork price in China?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 671-686, July.
    10. Bazzani, Claudia & Scarpa, Riccardo & Begalli, Diego & Capitello, Roberta, 2025. "Reporting nutritional information on wine packaging: Does it affect consumers’ choices? Evidence from a choice experiment in Italy," Food Policy, Elsevier, vol. 131(C).
    11. Lingling Xu & Xixi Yang & Linhai Wu & Xiujuan Chen & Lu Chen & Fu-Sheng Tsai, 2019. "Consumers’ Willingness to Pay for Food with Information on Animal Welfare, Lean Meat Essence Detection, and Traceability," IJERPH, MDPI, vol. 16(19), pages 1-22, September.
    12. Elliott J. Dennis & Glynn T. Tonsor & Jayson L. Lusk, 2021. "Choosing quantities impacts individuals choice, rationality, and willingness to pay estimates," Agricultural Economics, International Association of Agricultural Economists, vol. 52(6), pages 945-962, November.
    13. Dimitris Skalkos & Ioanna S. Kosma & Eleni Chasioti & Thomas Bintsis & Haralabos C. Karantonis, 2021. "Consumers’ Perception on Traceability of Greek Traditional Foods in the Post-COVID-19 Era," Sustainability, MDPI, vol. 13(22), pages 1-17, November.
    14. Aaron M. Shew & Heather A. Snell & Rodolfo M. Nayga & Mary C. Lacity, 2022. "Consumer valuation of blockchain traceability for beef in the United States," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 44(1), pages 299-323, March.
    15. Li, Liqing & Long, Dede, 2024. "Who values urban community gardens and how much?," Food Policy, Elsevier, vol. 126(C).
    16. Francisco Scott, 2023. "An Experimental Analysis of Quality Misperception in Food Labels," Research Working Paper RWP 23-11, Federal Reserve Bank of Kansas City.

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