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Food Price Elasticities for Policy Interventions: Estimates from a Virtual Supermarket Experiment in a Multistage Demand Analysis with (Expert) Prior Information

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  • Liana Jacobi
  • Nhung Nghiem
  • Andrés Ramírez‐Hassan
  • Tony Blakely

Abstract

Food price elasticities (PEs) are essential for evaluating the impacts of food pricing interventions to improve dietary and health outcomes. This paper innovates the use of experimental purchasing data from a recent New Zealand virtual supermarket experiment to estimate PEs for a large set of disaggregated foods across major food groups relevant for food policies in a Bayesian multistage demand framework. We propose the use of available prior information to elicit prior demand parameter assumptions that are consistent with published PEs and economic assumptions and are weighted according to expert knowledge, increasing precision in PE inference and policy predictions, and yielding somewhat stronger price effects.

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  • Liana Jacobi & Nhung Nghiem & Andrés Ramírez‐Hassan & Tony Blakely, 2021. "Food Price Elasticities for Policy Interventions: Estimates from a Virtual Supermarket Experiment in a Multistage Demand Analysis with (Expert) Prior Information," The Economic Record, The Economic Society of Australia, vol. 97(319), pages 457-490, December.
    • Handle: RePEc:bla:ecorec:v:97:y:2021:i:319:p:457-490
    DOI: 10.1111/1475-4932.12640
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    1. Dreze, Jacques H, 1976. "Bayesian Limited Information Analysis of the Simultaneous Equations Model," Econometrica, Econometric Society, vol. 44(5), pages 1045-1075, September.
    2. Nhung Nghiem & Tony Blakely & Linda J Cobiac & Amber L Pearson & Nick Wilson, 2015. "Health and Economic Impacts of Eight Different Dietary Salt Reduction Interventions," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-18, April.
    3. Richard Tiffin & Matthieu Arnoult, 2010. "The demand for a healthy diet: estimating the almost ideal demand system with infrequency of purchase," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 37(4), pages 501-521, December.
    4. Panagiotis Kasteridis & Steven T. Yen & Cheng Fang, 2011. "Bayesian Estimation of a Censored Linear Almost Ideal Demand System: Food Demand in Pakistan," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(5), pages 1374-1390.
    5. Tony Blakely & Nhung Nghiem & Murat Genc & Anja Mizdrak & Linda Cobiac & Cliona Ni Mhurchu & Boyd Swinburn & Peter Scarborough & Christine Cleghorn, 2020. "Modelling the health impact of food taxes and subsidies with price elasticities: The case for additional scaling of food consumption using the total food expenditure elasticity," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-17, March.
    6. Hunt Allcott & Benjamin B Lockwood & Dmitry Taubinsky, 2019. "Regressive Sin Taxes, with an Application to the Optimal Soda Tax," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(3), pages 1557-1626.
    7. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    8. Jarociński, Marek & Marcet, Albert, 2019. "Priors about observables in vector autoregressions," Journal of Econometrics, Elsevier, vol. 209(2), pages 238-255.
    9. Cliona Ni Mhurchu & Helen Eyles & Murat Genc & Peter Scarborough & Mike Rayner & Anja Mizdrak & Kelechi Nnoaham & Tony Blakely, 2015. "Effects of Health-Related Food Taxes and Subsidies on Mortality from Diet-Related Disease in New Zealand: An Econometric-Epidemiologic Modelling Study," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-17, July.
    10. Cliona Ni Mhurchu & Helen Eyles & Chris Schilling & Qing Yang & William Kaye-Blake & Murat Genç & Tony Blakely, 2013. "Food Prices and Consumer Demand: Differences across Income Levels and Ethnic Groups," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-12, October.
    11. Imbens, Guido W., 2014. "Instrumental Variables: An Econometrician's Perspective," IZA Discussion Papers 8048, Institute of Labor Economics (IZA).
    12. Tiffin, R & Arnoult, M, 2008. "Bayesian estimation of the infrequency of purchase model with an application to food demand in the UK," MPRA Paper 18836, University Library of Munich, Germany.
    13. Deaton,Angus & Muellbauer,John, 1980. "Economics and Consumer Behavior," Cambridge Books, Cambridge University Press, number 9780521296762, November.
    14. Helen Eyles & Cliona Ni Mhurchu & Nhung Nghiem & Tony Blakely, 2012. "Food Pricing Strategies, Population Diets, and Non-Communicable Disease: A Systematic Review of Simulation Studies," PLOS Medicine, Public Library of Science, vol. 9(12), pages 1-22, December.
    15. Anne Line Bretteville‐Jensen & Liana Jacobi, 2011. "Climbing the drug staircase: a Bayesian analysis of the initiation of hard drug use," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(7), pages 1157-1186, November.
    16. Nghiem, N. & Wilson, N. & Genç, M. & Blakely, T., 2013. "Understanding price elasticities to inform public health research and intervention studies: Key issues," American Journal of Public Health, American Public Health Association, vol. 103(11), pages 1954-1961.
    17. Linda J Cobiac & King Tam & Lennert Veerman & Tony Blakely, 2017. "Taxes and Subsidies for Improving Diet and Population Health in Australia: A Cost-Effectiveness Modelling Study," PLOS Medicine, Public Library of Science, vol. 14(2), pages 1-18, February.
    18. James Banks & Richard Blundell & Arthur Lewbel, 1997. "Quadratic Engel Curves And Consumer Demand," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 527-539, November.
    19. Stathis Klonaris & David Hallam, 2003. "Conditional and unconditional food demand elasticities in a dynamic multistage demand system," Applied Economics, Taylor & Francis Journals, vol. 35(5), pages 503-514.
    20. Kyrre Rickertsen & Dadi Kristofersson & Solveig Lothe, 2003. "Effects of health information on Nordic meat and fish demand," Empirical Economics, Springer, vol. 28(2), pages 249-273, April.
    21. Ashkan Afshin & José L Peñalvo & Liana Del Gobbo & Jose Silva & Melody Michaelson & Martin O'Flaherty & Simon Capewell & Donna Spiegelman & Goodarz Danaei & Dariush Mozaffarian, 2017. "The prospective impact of food pricing on improving dietary consumption: A systematic review and meta-analysis," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-18, March.
    22. Chen Zhen & Eric A. Finkelstein & James M. Nonnemaker & Shawn A. Karns & Jessica E. Todd, 2014. "Predicting the Effects of Sugar-Sweetened Beverage Taxes on Food and Beverage Demand in a Large Demand System," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(1), pages 1-25.
    23. Chib, Siddhartha & Greenberg, Edward, 1995. "Hierarchical analysis of SUR models with extensions to correlated serial errors and time-varying parameter models," Journal of Econometrics, Elsevier, vol. 68(2), pages 339-360, August.
    24. Ariane Kehlbacher & Chittur Srinivasan & Rachel McCloy & Richard Tiffin, 2020. "Modelling preference heterogeneity using a Bayesian finite mixture of Almost Ideal Demand Systems," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 47(3), pages 933-970.
    25. Craig A. Gallet, 2010. "Meat Meets Meta: A Quantitative Review of the Price Elasticity of Meat," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(1), pages 258-272.
    26. David L. Edgerton, 1997. "Weak Separability and the Estimation of Elasticities in Multistage Demand Systems," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 62-79.
    27. Griffith, Garry & I'Anson, Kym & Hill, Debbie & Lubett, ROland & Vere, David, 2001. "Previous Demand Elasticity Estimates For Australian Meat Products," Research Reports 280777, New South Wales Department of Primary Industries Research Economists.
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    1. Christine Cleghorn & Ingrid Mulder & Alex Macmillan & Anja Mizdrak & Jonathan Drew & Nhung Nghiem & Tony Blakely & Cliona Ni Mhurchu, 2022. "Can a Greenhouse Gas Emissions Tax on Food also Be Healthy and Equitable? A Systemised Review and Modelling Study from Aotearoa New Zealand," IJERPH, MDPI, vol. 19(8), pages 1-15, April.

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