Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-27T01:47:27.765Z Has data issue: false hasContentIssue false

Don't Judge a Wine by Its Closure: Price Premiums for Corks in the U.S. Wine Market

Published online by Cambridge University Press:  07 May 2019

Anton Bekkerman
Affiliation:
Department of Agricultural Economics and Economics, Montana State University, 306 Linfield Hall, Bozeman, MT 59717, USA; e-mail: [email protected].
Gary W. Brester
Affiliation:
Department of Agricultural Economics and Economics, Montana State University, 306 Linfield Hall, Bozeman, MT 59717, USA; e-mail: [email protected].

Abstract

For many purchases, consumers often possess only limited information about product quality. Thus, observable product characteristics are used to determine expected quality levels when making purchase decisions. We use more than 1 million weekly scanner-level observations from grocery stores across ten U.S. markets between September 2009 and August 2012 to examine how consumers value a wine bottle's closure type (i.e., cork or screw cap). We focus on lower-priced wines—those with sale prices less than $30 per 750 milliliter bottle—to more accurately evaluate decisions of consumers for whom seeking additional information about wine quality is likely more costly than the benefits derived from that information. Using both pooled ordinary least squares and quantile regressions to estimate price premiums for bottles with corks or screw caps, we find that U.S. consumers are willing to pay, on average, approximately 8% more (about $1.00) for a bottle of wine that has a cork closure. In addition, we show that the size of this premium increases as wine prices decline. (JEL Classifications: D81, M31, Q11)

Type
Articles
Copyright
Copyright © American Association of Wine Economists 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

The authors thank Kate Fuller, Hamish Gow, Carly Urban, Clint Peck, and participants of the economics seminar series at Lincoln University (Lincoln, New Zealand) as well as Karl Storchmann and an anonymous reviewer for helpful comments on this project. This work was partially supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, Hatch Multi-state project MONB00095.

References

Anderson, T. W., and Hsiao, C. (1981). Estimation of dynamic models with error components. Journal of the American Statistical Association, 76(375), 598606.Google Scholar
Arellano, M., and Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277297.Google Scholar
Barrodale, I., and Roberts, F. (1973). An improved algorithm for discrete l 1 linear approximation. SIAM Journal of Numerical Analysis, 10(5), 839848.Google Scholar
Brajkovich, M., Tibbits, N., Peron, G., Lund, C. M., Dykes, S. I., Kilmartin, P. A., and Nicolau, L. (2005). Effect of screwcap and cork closures on SO2 levels and aromas in a Sauvignon Blanc wine. Journal of Agricultural and Food Chemistry, 53(26), 1000610011.Google Scholar
Chamberlain, G. (1994). Quantile regression, censoring and the structure of wages. In Sims, C. (ed.), Advances in Econometrics. New York: Elsevier, 171209.Google Scholar
Constanigro, M., McCluskey, J., and Goemans, C. (2010). The economics of nested names: Name specificity, reputation, and price premia. American Journal of Agricultural Economics, 92(5), 13391350.Google Scholar
Davis, P., and Brown, V. (2011). FMI wine study: The economic impact of allowing shoppers to purchase wine in food stores. Food Marketing Institute, Arlington, VA. Available at https://www.fmi.org/docs/gr-state/fmi_wine_study.pdf (accessed 18 February 2015).Google Scholar
Godden, P. W., Francis, I. L., Field, J., Gishen, M., Coulter, A., Valente, P., Høj, P. B., and Robinson, E. (2001). Wine bottle closures: Physical characteristics and effect on composition and sensory properties of a Semillon wine. 1. Performance up to 20 months post-bottling. Australian Journal of Grape and Wine Research, 7(2), 64105.Google Scholar
Goodman, S. (2010). Purchase decisions along the supply chain. Australian and New Zealand Grapegrower and Winemaker, Issue 553, February.Google Scholar
Greene, W. (2004). The behaviour of the maximum likelihood estimator of limited dependent variable models in the presence of fixed effects. Econometrics Journal, 7(1), 98119.Google Scholar
Hausman, J., and Wise, D. (1977). Social experimentation, truncated distributions, and efficient estimation. Econometrica, 45(4), 319339.Google Scholar
Heckman, J. (1979). Sample selection bias as a specification error. Econometrica, 47(1), 153161.Google Scholar
Hodgson, R. T. (2008). An examination of judge reliability at a major U.S. wine competition. Journal of Wine Economics, 3(2), 105113.Google Scholar
Hodgson, R. T. (2009a). An analysis of the concordance among 13 U.S. wine competitions. Journal of Wine Economics, 4(1), 19.Google Scholar
Hodgson, R. T. (2009b). How expert are “expert” wine judges? Journal of Wine Economics, 4(2), 233241.Google Scholar
Janssen, M. C. W., and Roy, S. (2010). Signaling quality through prices in an oligopoly. Games and Economic Behavior, 68(1), 192207.Google Scholar
Joncheray, J. P. (1976). L’épave grecque, or étrusque, de bon-ponté. Cahiers d ’Archaéologie Subaquatique, 5, 536.Google Scholar
Jones, J. (2013). U.S. drinkers divide between beer and wine as favorite. Available at http://www.gallup.com/poll/163787/drinkers-divide-beer-wine-favorite.aspx (accessed 28 January 2016).Google Scholar
Koenker, R., and Bassett, G. (1978). Regression quantiles. Econometrica, 46(1), 3349.Google Scholar
Koenker, R., and Machado, A. (1999). Goodness of fit and related processes for quantile regression. Journal of the American Statistical Association, 94(1), 12961310.Google Scholar
Koenker, R., and d'Orey, V. (1994). A remark on algorithm AS 229: Computing dual regression quantiles and regression rank scores. Applied Statistics, 43, 410414.Google Scholar
Macku, C., and Reed, K. (2011). Factors affecting wine closure selection. Practical Winery and Vineyard Journal, Winter, 14.Google Scholar
Marin, A. B., and Durham, C. A. (2007). Effects of wine bottle closure type on consumer purchase intent and price expectation. American Journal of Enology and Viticulture, 58(2), 192201.Google Scholar
Mas, A., Puig, J., Llado, N., and Zamora, F. (2002). Sealing and storage position effects on wine evolution. Journal of Food Science, 67(4), 13741378.Google Scholar
Mueller, S., and Szolnoki, G. (2010). Wine packaging and labeling – do they impact market price? A hedonic price analysis of U.S. scanner data. 5th International Academy of Wine Business Research Conference, Feb 8–10. Auckland, NZ.Google Scholar
Oczkowski, E., and Doucouliagos, H. (2014). Wine prices and quality ratings: A meta-regression analysis. American Journal of Agricultural Economics, 97(1), 103121.Google Scholar
Parente, P. M. D. C., and Santos Silva, J. M. C. (2016). Quantile regression with clustered data. Journal of Econometric Methods, 5(1), 115.Google Scholar
Pellechia, T. (2017). 2016 U.S. wine sales give UPS and FedEx reason to smile. Forbes, 20 January 2017.Google Scholar
Skouroumounis, G. K., Kwiatkowski, M. J., Francis, I. L., Oakey, H., Capone, D., Duncan, B., Sefton, M. A., and Waters, E. J. (2005). The impact of closure type and storage conditions on the composition, colour and flavour properties of a Riesling and a Wooded Chardonnay wine during five years storage. Australian Journal of Grape Wine Research, 11(3), 369384.Google Scholar
Sovos Compliance LLC. 2018. 2018 Direct-to-Consumer Shipping Report. Available at http://go.sovos.com/rs/485-CPP-341/images/2018%20Direct-to-Consumer%20Wine%20Shipping%20Report.pdf (accessed December 2018).Google Scholar
Teague, L. (2004). Supermarket wine scout. Available at http://www.foodandwine.com/articles/supermarket-wine-scout (accessed November 2015).Google Scholar
U.S. Department of Agriculture. Economic Research Service. (2017). Current Food Expenditures Series. Available at http://www.ers.usda.gov/data-products/food-expenditure-series/ (accessed January 2019).Google Scholar
The Wine Institute. (2016). Wine consumption in the U.S. Available at https://www.wineinstitute.org/resources/statistics (accessed January 2019).Google Scholar
Wine Market Council. (2015). U.S. wine market update and insights. California Association of Winegrape Growers Summer Conference, Napa, CA, 2223 July.Google Scholar
Zikmund, W., and Babin, B. (2007). Exploring Marketing Research, 9th Edition. Thomson South-Western, Thomson Higher Education, OH.Google Scholar