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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.
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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

Information

Type
Articles
Information
Journal of Wine Economics , Volume 15 , Issue 1 , February 2020 , pp. 71 - 94
Copyright
Copyright © American Association of Wine Economists, 2020

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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.

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