Hostname: page-component-78c5997874-s2hrs Total loading time: 0 Render date: 2024-11-11T04:24:09.409Z Has data issue: false hasContentIssue false
  • English
  • Français

The Combination of Lab and Field Experiments for Benefit-Cost Analysis

Published online by Cambridge University Press:  19 January 2015

Stéphan Marette ,
Jutta Roosen  and
Sandrine Blanchemanche
Stéphan Marette
Affiliation:
Economic department INRA, UMR Economie Publique
Jutta Roosen
Affiliation:
Technische Universitaet Muenchen
Sandrine Blanchemanche
Affiliation:
INRA, Metarisk
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

This article explores the combination of laboratory and field experiments in defining a welfare framework and the impact of different regulatory tools on consumer behaviors. First, an overview of strengths and weaknesses raised by the experimental literature show that, for food consumption, lab and field experiments may be complementary to each other. The lab experiment elicits willingness to pay useful for determining per-unit damages based on well-informed, thoughtful preferences, while the field experiment determines purchase/consumption reactions in real contexts. Second, the analytical approach suggests how to combine the results of both lab and field experiments to determine the welfare impact of different regulatory tools such as labels and/or taxes. Third, an empirical application focuses on a lab and a field experiment conducted in France to evaluate the impact of regulation on fish consumption. Estimations for the French tuna market show that a per-unit tax on tuna and/or an advisory policy lead to welfare improvements.

Keywords

regulationinstrumentslab and field experimentsfood consumptionFrance
Type
Article
Information
Journal of Benefit-Cost Analysis , Volume 2 , Issue 3 , 25 August 2011 , pp. 1 - 36
Copyright
Copyright © Society for Benefit-Cost Analysis 2011

References

Blanchemanche, S., Marette, S., Roosen, J. and Verger, P. (2010). ‘Do not Eat Fish More Than Twice a Week’. Rational Choice Regulation and Risk Communication: Uncertainty Transfer from Risk Assessment to Public. Health, Risk and Society 12 (3): 271–292.CrossRefGoogle Scholar
Bureau, J.C., Marette, S. and Schiavina, A. (1998). Non-Tariff Trade Barriers and Consumers' Information: The Case of EU-US Trade Dispute on Beef. European Review of Agricultural Economics 25: 437-462.Google Scholar
Chang, J.B., Lusk, J.L., and Norwood, F.B. (2009). How Closely Do Hypothetical Surveys and Laboratory Experiments Predict Field Behavior? American Journal of Agricultural Economics 91:518-534.Google Scholar
Crespi, J. and Marette, S. (2001). How Should Food Safety Certification Be Financed? American Journal of Agricultural Economics 83: 852-861.Google Scholar
Disdier, A.-C. and Marette, S. (2010). The Combination of Gravity and Welfare Approaches for Evaluating Non-Tariff Measures. American Journal of Agricultural Economics 92: 713-726.Google Scholar
EFSA (European Food Safety Authority) (2004). Opinion of the Scientific Panel on Contaminants in the Food Chain on a Request from the Commission Related to Mercury and Methylmercury in Food. EFSA Journal 34, 1-14. http://www.efsa.eu.int (accessed February 2006).Google Scholar
EPA (U.S. Environmental Protection Agency) (2004). What You Need to Know About Mercury in Fish and Shellfish. Washington D.C. http://www.epa.gov/waterscience/fishadvice/advice.html (accessed March 2006).Google Scholar
Falk, A. and Heckman, J.J. (2009). Lab Experiments are a Major Source of Knowledge in the Social Sciences. Science 326(5952): 535-538.Google Scholar
FranceAgriMer (2009). “Bilan Annuel 2008 – Consommation des Produits de la Pêche et de l’Aquaculture.” Direction Marchés, Etudes et Prospective, Paris, France.Google Scholar
FSA (U.K. Food Standards Agency) (2003). Mercury in fish: your questions answered, http://www.food.gov.uk/multimedia/faq/mercuryfish/?version=1 (accessed April 2006).Google Scholar
FSAI (Food Standards Authority of Ireland) (2004). FSAI Issues Guidelines on Consumption of Shark, Swordfish, Marlin and Tuna, http://www.fsai.ie/news/press/pr_04/pr20040318.asp (accessed April 2006).Google Scholar
FSANZ (Food Standards Australia New Zealand) (2004). “Mercury in Fish”, http://www.foodstandards.gov.au/whatsinfood/mercuryinfish.cfm (accessed April 2006).Google Scholar
Hahn, R. and Tetlock, P. (2008). Has Economic Analysis Improved Regulatory Decisions? Journal of Economic Perspectives 22: 67-84.CrossRefGoogle Scholar
Hahn, R. (2010) Designing Smarter Regulation with Improved Benefit-Cost Analysis. Journal of Benefit-Cost Analysis Vol. 1: Iss. 1, Article 5: 1-17.Google Scholar
Health Canada (2002). Advisory-Information on mercury levels in fish. http://www.hc-sc.gc.ca/english/protection/warnings/2002/2002_41e.htm (accessed March 2006).Google Scholar
Huffman, W. E, Rousu, M.C., Shogren, J.F., and Tegene, A. (2003). The Public Good Value of Information from Agribusinesses on Genetically Modified Food. American Journal of Agricultural Economics 85: 1309-1315.Google Scholar
Huffman, W.E, Rousu, M.C., Shogren, J.F., and Tegene, A. (2007). The Effects of Prior Beliefs and Learning on Consumers’ Acceptance of Genetically Modified Food. Journal of Economic Behavior and Organization 63: 193-206.Google Scholar
INSEE (Institut National de la Statistique et des Etudes Economiques) (1999). Mode de vie des personnes selon l'âge et le sexe, Paris. http://www.insee.fr/fr/ffc/chifcle_fiche.asp?ref_id=NATTEF02316&tab_id=34 (accessed October 2010).Google Scholar
Kagel, J. H. and Roth, A.E. (2000). The Dynamics of Reorganization in Matching Markets: A Laboratory Experiment Motivated by a Natural Experiment. Quarterly Journal of Economics 115, 201-35.Google Scholar
Levitt, S. and List, J.A. (2007). What do Laboratory Experiments Measuring Social Preferences Reveal About the Real World. Journal of Economic Perspectives 21(2): 153-174.CrossRefGoogle Scholar
Lusk, J.L., Pruitt, J.R. and Norwood, B. (2006). External Validity of a Framed Field Experiment. Economics Letters 93: 285–290.Google Scholar
Lusk, J.L. and Shogren, J.F. (2007). Experimental Auctions. Methods and Applications in Economic and Marketing Research. Cambridge University Press, Cambridge, UK.Google Scholar
Lusk, J.L. and Marette, S. (2010). Welfare Effects of Food Labels and Bans with Alternative Willingness to Pay Measures. Applied Economic Perspectives & Policy 32(2): 319-337.Google Scholar
Lusk, J.L. and Schroeder, T.C. (2004). Are Choice Experiments Incentive Compatible : A Test with Quality Differentiated Beef Steaks. American Journal of Agricultural Economics 86(2): 467-482.Google Scholar
Lusk, J.L., House, L. O., Valli, C., Jaeger, S.R., Moore, M., Morrow, B., Traill, W.B. (2005). Consumer Welfare Effects of Introducing and Labeling Genetically Modified Food. Economics Letters 88: 382-388.Google Scholar
Lusk, J.L. and Norwood, F.B. (2009). Bridging the Gap between Laboratory Experiments and Naturally Occurring Markets: An Inferred Valuation Method. Journal of Environmental Economics and Management 58: 236–250.Google Scholar
Marette, S. (2010). Consumer Confusion and Multiple Equilibria. Economics Bulletin 30 (2): 1120-1128.Google Scholar
Marette, S. and Crespi, J. (2003). Can Quality Certification Lead to Stable Cartel. Review of Industrial Organization, 23 (1): 43-64.Google Scholar
Marette, S., Lusk, J. and Roosen, J. (2010). Welfare Impact of Information with Experiments: The Crucial Role of the Price Elasticity of Demand. Economics Bulletin 30 (2): 1585-1593.Google Scholar
Marette, S., Roosen, J., and Blanchemanche, S. (2008a). Health Information and Substitution between Fish: Lessons from Laboratory and Field Experiments. Food Policy 33: 197-208.Google Scholar
Marette, S., Roosen, J., and Blanchemanche, S. (2008b). Taxes and Subsidies to Change Eating Habits when Information is not enough: An Application to Fish Consumption. Journal of Regulatory Economics 34: 119-143.Google Scholar
Marette, S., Roosen, J., and Blanchemanche, S., Verger, P. (2008c). The Choice of Fish Species: An Experiment Measuring the Impact of Risk and Benefit Information. Journal of Agricultural and Resource Economics 33: 1-18.Google Scholar
Masters, W. A. and Sanogo, D. (2002). Welfare Gains from Quality Certification of Infant Foods: Results from a Market Experiment in Mali. American Journal of Agricultural Economics 84: 974-989.Google Scholar
Robinson, L.A. and Hammitt, J.K. (2011). Behavioral Economics and the Conduct of Benefit-Cost Analysis: Towards Principles and Standards. Journal of Benefit-Cost Analysis 2(2) Article 5: 1-48.Google Scholar
Roe, B.E and Just, D.R. (2009). Internal and External Validity in Economics Research: Tradeoffs between Experiments, Field Experiments, Natural Experiments, and Field Data. American Journal of Agricultural Economics 91: 1266-1271.Google Scholar
Roosen, J. and Marette, S. (2011) Making the ‘Right’ Choice based on Experiments: Regulatory Decisions for Food and Health. European Review of Agricultural Economics forthcoming.Google Scholar
Roosen, J., Marette, S., Blanchemanche, S., Verger, P. (2007). The Effect of Product Health Information on Liking and Choice. Food Quality and Preference 18: 759-770.Google Scholar
Roosen, J., Marette, S., Blanchemanche, S. and Verger, P. (2009). Does Health Information Matter for Modifying Consumption? A Field Experiment Measuring the Impact of Risk Information on Fish Consumption. Review of Agricultural Economics 31: 2-20.CrossRefGoogle Scholar
Rousu, M. C. and Shogren, J. F. (2006). Valuing Conflicting Public Information. Journal of Agricultural and Resource Economics 31: 642-652.Google Scholar
Rousu, M.C. and Lusk, J. L. (2009). Valuing Information on GM Foods in a WTA Market: What Information is most Valuable? AgBioForum 12(2): 226-231.Google Scholar
Rousu, M.C. and Corrigan, J. R. (2008). Estimating the Welfare Loss to Consumers When Food Labels Do Not Adequately Inform: An Application to Fair Trade Certification. Journal of Agricultural & Food Industrial Organization 6(1): Article 3.Google Scholar
Rousu, M.C., Huffman, W. E., Shogren, J. F., and Tegene, A. (2004). Estimating the Public Value of Conflicting Information: The Case of Genetically Modified Foods. Land Economics 80: 125-135.Google Scholar
Rousu, M.C., Huffman, W.E., Shogren, J.F., and Tegene, A. (2007). Effects and Value of Verifiable Information in a Controversial Market: Evidence from Lab Auctions of Genetically Modified Food. Economic Inquiry 45: 409-432.Google Scholar
Sasaki, T. D., Becker, V., Janssen, M.A. and Neel, R. (2011). Does Greater Product Information Actually Inform Consumer Decisions? The Relationship Between Product Information Quantity and Diversity of Consumer Decisions. Journal of Economic Psychology 32: 391-398.CrossRefGoogle Scholar
Shimshack, J.P., Ward, M.B. and Beatty, T.K.M (2007). Mercury advisories: Information, education, and fish consumption. Journal of Environmental Economics and Management 53: 158-179.Google Scholar
Smith, V.K. and Moore, E.M. (2010). Behavioral Economics and Benefit Cost Analysis. Environmental and Resource Economics 46: 217-234.Google Scholar
Sugden, R. (2009). Market Simulation and the Provision of Public Goods: a NonPaternalistic Response to Anomalies in Environmental Evaluation. Journal of Environmental and Economic Management 57: 87–103.Google Scholar
Teisl, M. F., Roe, B., and Hicks, R. L. (2002). Can Eco-labels Tune a Market? Evidence from Dolphin-Safe Labeling. Journal of Environmental Economics and Management 43: 339-359.Google Scholar
Verbeke, W. (2005). Agriculture and the Food Industry in the Information Age. European Review of Agricultural Economics 32: 347-368.Google Scholar
Verger, P., Houdart, S., Marette, S., Roosen, J. and Blanchemanche, S. (2007). Impact of a Risk-Benefit Advisory on Fish Consumption and Dietary Exposure to Methylmercury in France. Regulatory Toxicology and Pharmacology 48: 259–269.Google Scholar
Wansink, B., Sonka, S. and Hasler, C. (2004). Front-Label Health Claims: When Less is More. Food Policy 29: 659-667.Google Scholar