IDEAS home Printed from https://ideas.repec.org/a/eee/jfpoli/v95y2020ics0306919220301548.html
   My bibliography  Save this article

Eating to save the planet: Evidence from a randomized controlled trial using individual-level food purchase data

Author

Listed:
  • Jalil, Andrew J.
  • Tasoff, Joshua
  • Bustamante, Arturo Vargas

Abstract

Meat consumption is a major driver of climate change. Interventions that reduce meat consumption may improve public health and promote environmental sustainability. We conducted a randomized controlled trial to examine the effects of an awareness-raising intervention on meat consumption. We randomized undergraduate classes into treatment and control groups. Treatment groups received a 50-minute lecture on how food choices affect climate change, along with information about the health benefits of reduced meat consumption. Control classrooms received a lecture on a placebo topic. We analyzed 49,301 students’ meal purchases in the college dining halls before and after the intervention. We merged food purchase data with survey data to study heterogenous treatment effects and disentangle mechanisms. Participants in the treatment group reduced their purchases of meat and increased their purchases of plant-based alternatives after the intervention. The probability of purchasing a meat-based meal fell by 4.6 percentage points (p < 0.01), whereas the probability of purchasing a plant-based meal increased by 4.2 percentage points (p = 0.04). While the effects were stronger during the semester of the intervention, dietary shifts persisted and remained statistically significant through the full academic year. Our study provides evidence that an intervention based on informing consumers and encouraging voluntary shifts can effectively reduce the demand for meat. Our findings help to inform the international food policy debate on how to counter rising global levels of meat consumption to achieve climate change goals. To our knowledge, our study is the first to assess the effectiveness of an educational intervention to reduce meat consumption using such high-quality data (i.e. individual-level food purchases) over a prolonged period.

Suggested Citation

  • Jalil, Andrew J. & Tasoff, Joshua & Bustamante, Arturo Vargas, 2020. "Eating to save the planet: Evidence from a randomized controlled trial using individual-level food purchase data," Food Policy, Elsevier, vol. 95(C).
  • Handle: RePEc:eee:jfpoli:v:95:y:2020:i:c:s0306919220301548
    DOI: 10.1016/j.foodpol.2020.101950
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306919220301548
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.foodpol.2020.101950?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. James G. MacKinnon & Matthew D. Webb, 2018. "The wild bootstrap for few (treated) clusters," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 114-135, June.
    2. Farrow, Katherine & Grolleau, Gilles & Ibanez, Lisette, 2017. "Social Norms and Pro-environmental Behavior: A Review of the Evidence," Ecological Economics, Elsevier, vol. 140(C), pages 1-13.
    3. Timothy G. Conley & Christopher R. Taber, 2011. "Inference with "Difference in Differences" with a Small Number of Policy Changes," The Review of Economics and Statistics, MIT Press, vol. 93(1), pages 113-125, February.
    4. Richard H. Thaler & Cass R. Sunstein, 2003. "Libertarian Paternalism," American Economic Review, American Economic Association, vol. 93(2), pages 175-179, May.
    5. Esther Duflo & Emmanuel Saez, 2003. "The Role of Information and Social Interactions in Retirement Plan Decisions: Evidence from a Randomized Experiment," The Quarterly Journal of Economics, Oxford University Press, vol. 118(3), pages 815-842.
    6. James G. MacKinnon & Matthew D. Webb, 2018. "The wild bootstrap for few (treated) clusters," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 114-135, June.
    7. Jacob Goldin & Ithai Z. Lurie & Janet McCubbin, 2019. "Health Insurance and Mortality: Experimental Evidence from Taxpayer Outreach," NBER Working Papers 26533, National Bureau of Economic Research, Inc.
    8. Brigitte C. Madrian, 2014. "Applying Insights from Behavioral Economics to Policy Design," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 663-688, August.
    9. David Roodman & James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2019. "Fast and wild: Bootstrap inference in Stata using boottest," Stata Journal, StataCorp LP, vol. 19(1), pages 4-60, March.
    10. James G. MacKinnon & Matthew D. Webb, 2017. "Wild Bootstrap Inference for Wildly Different Cluster Sizes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 233-254, March.
    11. Pascaline Dupas, 2011. "Do Teenagers Respond to HIV Risk Information? Evidence from a Field Experiment in Kenya," American Economic Journal: Applied Economics, American Economic Association, vol. 3(1), pages 1-34, January.
    12. Schubert, Christian, 2017. "Green nudges: Do they work? Are they ethical?," Ecological Economics, Elsevier, vol. 132(C), pages 329-342.
    13. Cass R. Sunstein & Richard H. Thaler, 2003. "Libertarian paternalism is not an oxymoron," Conference Series ; [Proceedings], Federal Reserve Bank of Boston, vol. 48(Jun).
    14. Eric P. Bettinger & Bridget Terry Long & Philip Oreopoulos & Lisa Sanbonmatsu, 2009. "The Role of Simplification and Information in College Decisions: Results from the H&R Block FAFSA Experiment," NBER Working Papers 15361, National Bureau of Economic Research, Inc.
    15. James G. MacKinnon & Matthew D. Webb, 2019. "Wild Bootstrap Randomization Inference for Few Treated Clusters," Advances in Econometrics, in: Kim P. Huynh & David T. Jacho-chávez & Gautam Tripathi (ed.), The Econometrics of Complex Survey Data, volume 39, pages 61-85, Emerald Publishing Ltd.
    16. Hunter, Erik & Röös, Elin, 2016. "Fear of climate change consequences and predictors of intentions to alter meat consumption," Food Policy, Elsevier, vol. 62(C), pages 151-160.
    17. Robert Jensen, 2010. "The (Perceived) Returns to Education and the Demand for Schooling," The Quarterly Journal of Economics, Oxford University Press, vol. 125(2), pages 515-548.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Romain Espinosa & Anis Nassar, 2021. "The Acceptability of Food Policies," Post-Print halshs-03210654, HAL.
    2. de Boer, Joop & Aiking, Harry, 2021. "Climate change and species decline: Distinct sources of European consumer concern supporting more sustainable diets," Ecological Economics, Elsevier, vol. 188(C).
    3. Isabel Miguel & Arnaldo Coelho & Cristela Maia Bairrada, 2020. "Modelling Attitude towards Consumption of Vegan Products," Sustainability, MDPI, vol. 13(1), pages 1-17, December.
    4. David Arthur Cleveland & Quentin Gee & Audrey Horn & Lauren Weichert & Mickael Blancho, 2021. "How many chickens does it take to make an egg? Animal welfare and environmental benefits of replacing eggs with plant foods at the University of California, and beyond," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 38(1), pages 157-174, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Matthew D. Webb & James MacKinnon & Morten Nielsen, 2021. "Cluster–robust inference: A guide to empirical practice," Economics Virtual Symposium 2021 6, Stata Users Group.
    2. Dorner, Matthias & Görlitz, Katja, 2020. "Training, wages and a missing school graduation cohort," IAB-Discussion Paper 202028, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    3. James MacKinnon & Morten Ørregaard Nielsen, 2022. "Cluster-Robust Inference: A Guide to Empirical Practice," CREATES Research Papers 2022-08, Department of Economics and Business Economics, Aarhus University.
    4. Damian Clarke & Kathya Tapia-Schythe, 2021. "Implementing the panel event study," Stata Journal, StataCorp LP, vol. 21(4), pages 853-884, December.
    5. James G. MacKinnon, 2019. "How cluster‐robust inference is changing applied econometrics," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 52(3), pages 851-881, August.
    6. Hansen, Bruce E. & Lee, Seojeong, 2019. "Asymptotic theory for clustered samples," Journal of Econometrics, Elsevier, vol. 210(2), pages 268-290.
    7. Ozturk, Orgul D. & Frongillo, Edward A. & Blake, Christine E. & McInnes, Melayne M. & Turner-McGrievy, Gabrielle, 2020. "Before the lunch line: Effectiveness of behavioral economic interventions for pre-commitment on elementary school children's food choices," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 597-618.
    8. Bezu, Sosina & Binyaruka, Peter & Mæstad, Ottar & Somville, Vincent, 2021. "Pay-for-performance reduces bypassing of health facilities: Evidence from Tanzania," Social Science & Medicine, Elsevier, vol. 268(C).
    9. Ban, Radu & Gilligan, Michael J. & Rieger, Matthias, 2020. "Self-help groups, savings and social capital: Evidence from a field experiment in Cambodia," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 174-200.
    10. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2021. "Wild Bootstrap and Asymptotic Inference With Multiway Clustering," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 505-519, March.
    11. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2020. "Testing for the appropriate level of clustering in linear regression models," Working Paper 1428, Economics Department, Queen's University.
    12. Buenstorf, Guido & Koenig, Johannes, 2020. "Interrelated funding streams in a multi-funder university system: Evidence from the German Exzellenzinitiative," Research Policy, Elsevier, vol. 49(3).
    13. Blake Shaffer, 2019. "Location matters: Daylight saving time and electricity demand," Canadian Journal of Economics, Canadian Economics Association, vol. 52(4), pages 1374-1400, November.
    14. Carpenter, Christopher S. & Gonzales, Gilbert & McKay, Tara & Sansone, Dario, 2020. "Effects of the Affordable Care Act Dependent Coverage Mandate on Health Insurance Coverage for Individuals in Same-Sex Couples," IZA Discussion Papers 13119, Institute of Labor Economics (IZA).
    15. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2022. "Fast and Reliable Jackknife and Bootstrap Methods for Cluster-Robust Inference," Working Paper 1485, Economics Department, Queen's University.
    16. García-Ramos, Aixa, 2021. "Divorce laws and intimate partner violence: Evidence from Mexico," Journal of Development Economics, Elsevier, vol. 150(C).
    17. Arrieta, Johar & Florián, David & López, Kristian & Morales, Valeria, 2020. "Policies for Transactional De-Dollarization: A Laboratory Study," Working Papers 2020-011, Banco Central de Reserva del Perú.
    18. Ghesla, Claus & Grieder, Manuel & Schubert, Renate, 2020. "Nudging the poor and the rich – A field study on the distributional effects of green electricity defaults," Energy Economics, Elsevier, vol. 86(C).
    19. Lauren E. Jones & Kevin Milligan & Mark Stabile, 2019. "Child cash benefits and family expenditures: Evidence from the National Child Benefit," Canadian Journal of Economics, Canadian Economics Association, vol. 52(4), pages 1433-1463, November.
    20. Obergruber, Natalie & Zierow, Larissa, 2020. "Students’ behavioural responses to a fallback option - Evidence from introducing interim degrees in german schools," Economics of Education Review, Elsevier, vol. 75(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jfpoli:v:95:y:2020:i:c:s0306919220301548. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://www.elsevier.com/locate/foodpol .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/foodpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.