Hostname: page-component-848d4c4894-mwx4w Total loading time: 0 Render date: 2024-06-21T22:34:47.947Z Has data issue: false hasContentIssue false
  • English
  • Français

Wine Descriptions Provide Information: A Text Analysis

Published online by Cambridge University Press:  06 April 2020

Bryan C. McCannon
Bryan C. McCannon*
Affiliation:
Department of Economics, West Virginia University, P.O. Box 6025, Morgantown, WV26506; e-mail: bryan.c.mccannon@gmail.com.
Get access Rights & Permissions [Opens in a new window]

Abstract

I use a computational linguistic algorithm to measure the topics covered in textual descriptions of wine. I ask whether there is information in the text that consumers value. Wine is a prominent example of an experience good. There is substantial product differentiation in the market, and consumers only have limited information on the utility they will receive when consumed. Thus, information is expected to be valuable. Evaluating descriptions of wine produced across the United States, I use a hedonic price regression to explore whether the descriptions provide any new information not already available to the consumer. Initial results suggest that text descriptions are shown to lose their explanatory value when varietal and numerical ratings are included as controls. I then show that once the varietal, region, and numerical ratings are adequately controlled for, there is information in the descriptions that consumers value. (JEL Classifications: C81, D83, L15)

Keywords

experience goodhedonic priceLatent Dirichlet Allocationtext analysistopic modelingwine
Type
Articles
Information
Journal of Wine Economics , Volume 15 , Issue 1 , February 2020 , pp. 71 - 94
Copyright
Copyright © American Association of Wine Economists, 2020

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

I appreciate comments from Orley Ashenfelter, Josh Hall, Brad Humphreys, Adam Nowak, and seminar participants at West Virginia University and the conference participants of the American Association of Wine Economists. I also appreciate the helpful comments of an anonymous referee.

References

Ali, H. H., Lecocq, S., and Visser, M. (2008). The impact of gurus: Parker grades and En Primeur wine prices. Economic Journal, 118(529), F158–F173.CrossRefGoogle Scholar
Ali, H. H., Lecocq, S., and Visser, M. (2010). The impact of gurus: Parker grades and En Primeur wine prices. Journal of Wine Economics, 5(1), 22–39.CrossRefGoogle Scholar
Ashenfelter, O. (2008). Predicting the quality and prices of Bordeaux wine. Economic Journal, 118(529), F174–F184.CrossRefGoogle Scholar
Ashenfelter, O., and Jones, G. V. (2013). The demand for expert opinion: Bordeaux wine. Journal of Wine Economics, 8(3), 285–293.CrossRefGoogle Scholar
Bederson, B. B., Jin, G. Z., Leslie, P., Quinn, A. J., and Zou, B. (2018). Incomplete disclosure: Evidence of signaling and countersignaling. American Economic Journal: Microeconomics, 10(1), 41–66.Google Scholar
Bester, H., and Dahm, M. (2018). Credence goods, costly diagnosis, and subjective evaluation. Economic Journal, 128(611), 1367–1394.CrossRefGoogle Scholar
Blei, D. M., Ng, A. Y., and Jordan, M. L. (2003). Latent Dirichlet Allocation. Journal of Machine Learning, 3, 993–1022.Google Scholar
Brown, A. L., Camerer, C. F., and Lovallo, D. (2012). To review or not to review? Limited strategic thinking at the movie box office. American Economic Journal: Microeconomics, 4(2), 1–26.Google ScholarPubMed
Combris, P., Lecocq, S., and Visser, M. (1997a). Estimation of a hedonic price equation for Bordeaux wine: Does quality matter? Economic Journal, 107, 390–402.CrossRefGoogle Scholar
Combris, P., Lecocq, S., and Visser, M. (1997b). Estimation of a hedonic price equation for Burgundy wine. Applied Economics, 32, 961–967.CrossRefGoogle Scholar
Crozet, M., Hood, K., and Mayer, T. (2012). Quality sorting and trade: Firm-level evidence for French wine. Review of Economic Studies, 79(2), 609–617.CrossRefGoogle Scholar
Dubois, P., and Nauges, C. (2010). Identifying the effect of unobserved quality and expert reviews in the pricing of experience goods: Empirical application on Bordeaux wine. International Journal of Industrial Organization, 28(3), 205–212.CrossRefGoogle Scholar
Dyer, T., Lang, M., and Stice-Lawrence, L. (2017). The evolution of 10-K textual disclosure: Evidence from Latent Dirichlet Allocation. Journal of Accounting and Economics, 64(2–3), 221–245.CrossRefGoogle Scholar
Gentzkow, M., and Shapiro, J. M. (2010). What drives media slant? Evidence from U.S. daily newspapers. Econometrica, 78(1), 35–71.Google Scholar
Gergaud, O., and Ginsburgh, V. (2008). Natural endowments, production technologies and the quality of wines in Bordeaux: Does terroir matter? Economic Journal, 118(529), F142–F157.CrossRefGoogle Scholar
Goldstein, R., Almenberg, J., Dreber, A., Emerson, J. W., Herschkowitsch, A., and Katz, J. (2008). Do more expensive wines taste better? Evidence from a large sample of blind tastings. Journal of Wine Economics, 3(1), 1–9.CrossRefGoogle Scholar
Grimmer, J. (2010). A Bayesian hierarchical topic model for political texts: Measuring expressed agendas in Senate press releases. Political Analysis, 18(1), 1–35.CrossRefGoogle Scholar
Hansen, S., McMahon, M., and Prat, A. (2018). Transparency and deliberation within the FOMC: A computational linguistics approach. Quarterly Journal of Economics, 133(2), 801–870.CrossRefGoogle Scholar
Hilger, J., Rafert, G., and Villas-Boas, S. (2011). Expert opinion and the demand for experience goods: An experimental approach in the retail wine market. Review of Economics and Statistics, 93(4), 1289–1296.CrossRefGoogle Scholar
Jin, G. Z., and Leslie, P. (2003). The effect of information on product quality: Evidence from restaurant hygiene grade cards. Quarterly Journal of Economics, 118(2), 409–451.CrossRefGoogle Scholar
King, G., Lam, P., and Roberts, M. E. (2017). Computer-assisted keyword and document set discovery from unstructured text. American Journal of Political Science, 61(4), 971–988.CrossRefGoogle Scholar
Landon, S., and Smith, C. E. (1998a). Quality expectations, reputation and price. Southern Economic Journal, 64(3), 628–647.CrossRefGoogle Scholar
Landon, S., and Smith, C. E. (1998b). The use of quality and reputation indicators by consumers: The case of Bordeaux wine. Journal of Consumer Policy, 20(3), 289–323.CrossRefGoogle Scholar
Lecocq, S., and Visser, M. (2006). What determines wine prices: Objective vs. sensory characteristics. Journal of Wine Economics, 1(1), 42–56.CrossRefGoogle Scholar
McCannon, B. C. (2012). The value of multiple reviews. Applied Economics, 44(12), 1521–1525.CrossRefGoogle Scholar
Moretti, E. (2011). Social learning and peer effects in consumption: Evidence from movie sales. Review of Economic Studies, 78(1), 356–393.CrossRefGoogle Scholar
Oczkowski, E. (1994). A hedonic price function for Australian premium wine. Australian Journal of Agricultural Economics, 38(1), 93–110.CrossRefGoogle Scholar
Oczkowski, E. (2001). Hedonic wine price functions and measurement error. Economic Record, 77(239), 374–382.CrossRefGoogle Scholar
Quinn, K. M., Monroe, B. L., Colaresi, M., Crespin, M. H., and Radev, D. R. (2010). How to analyze political attention with minimal assumptions and costs. American Journal of Political Science, 54(1), 209–228.CrossRefGoogle Scholar
Ramirez, C. D. (2008). Wine quality, wine prices, and the weather: Is Napa “different”? Journal of Wine Economics, 3(2), 114–131.CrossRefGoogle Scholar
Ramirez, C. D. (2010). Do tasting notes add value? Evidence from Napa wines. Journal of Wine Economics, 5(1), 143–163.CrossRefGoogle Scholar
Reinstein, D. A., and Snyder, C. M. (2005). The influence of expert reviews on consumer demand for experience goods: A case study of movie critics. Journal of Industrial Economics, 53(1), 27–51.CrossRefGoogle Scholar
Schamel, G. (2009). Dynamic analysis of brand and regional reputation: The case of wine. Journal of Wine Economics, 4(1), 62–80.CrossRefGoogle Scholar
Schwarz, C. (2018). ldagibbs: A command for topic modeling in Stata using Latent Dirichlet Allocation. Stata Journal, 18(1), 101–117.CrossRefGoogle Scholar
Tirunillai, S., and Tellis, G. J. (2014). Mining marketing meaning from online chatter: Strategic brand analysis of big data using Latent Dirichlet Allocation. Journal of Marketing Research, 51(4), 463–479.CrossRefGoogle Scholar
Weil, R. L. (2007). Debunking critics’ wine words: Can amateurs distinguish the smell of asphalt from the taste of cherries? Journal of Wine Economics, 2(2), 136–144.CrossRefGoogle Scholar
Yang, N., McCluskey, J. J., and Ross, C. (2009). Willingness to pay for sensory properties in Washington state red wines. Journal of Wine Economics, 4(1), 81–93.CrossRefGoogle Scholar