Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-28T03:03:17.610Z Has data issue: false hasContentIssue false
  • English
  • Français

Auction-Price Dynamics for Fine Wines from Age-Period-Cohort Models*

Published online by Cambridge University Press:  07 November 2017

Joseph L. Breeden Open the ORCID record for Joseph L. Breeden [Opens in a new window]  and
Sisi Liang
Joseph L. Breeden*
Affiliation:
auctionforecast.com, 1600 Lena St., Suite C24, Santa Fe, New Mexico, 87505
Sisi Liang
Affiliation:
auctionforecast.com, 1600 Lena St., Suite C24, Santa Fe, New Mexico, 87505; e-mail: sisi.liang@auctionforecast.com.
*
e-mail: breeden@prescientmodels.com or breeden@auctionforecast.com (corresponding author).
Get access Rights & Permissions [Opens in a new window]

Abstract

In an attempt to expand the understanding of auction-price dynamics for fine wines, an age-period-cohort (APC) algorithm is applied to a database of 1.5 million auction results to quantify key drivers of these price dynamics. APC algorithms are designed to separate price appreciation with the age of the wine from overall wine-market conditions as well as to adjust for the unique value of specific vintages. In this context, the APC modeling provides a kind of Hedonic modeling, with specific controls regarding specification errors.

The analysis was segmented by Château Lafite Rothschild, Bordeaux excluding Lafite, and Burgundy so that we could test specific events related to Château Lafite Rothschild. The results show price dynamics versus the ages of the wines and allow for the measurement of long-term price-appreciation potential. Environment functions versus auction dates quantify the “Lafite Bubble” and suggest past correlation to Chinese stock-market indices. An analysis of wine ratings versus price quantifies their nonlinear relationship. An analysis across nine auction houses shows a significant price spread for similar wines. (JEL Classifications: C23, D44, G11, G12, Q11)

Keywords

age-period-cohort modelsauction pricesBordeauxBurgundyLafitewine investment
Type
Articles
Information
Journal of Wine Economics , Volume 12 , Issue 2 , May 2017 , pp. 173 - 202
Copyright
Copyright © American Association of Wine Economists 2017 

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 would like to thank Karl Storchmann (the editor) and the reviewer for their insightful comments and encouragement.

References

Ashenfelter, O. (1989). How auctions work for wine and art. Journal of Economic Perpectives, 3(3), 23–36.Google Scholar
Ashenfelter, O. (2008). Predicting the quality and prices of Bordeaux wine. Economic Journal, 118(529), F174–F184.CrossRefGoogle Scholar
Bailey, M. J., Muth, R. F., and Nourse, H. O. (1963). A regression method for real estate price index construction. Journal of the Amercian Statistical Association, 58, 933–942.CrossRefGoogle Scholar
Breeden, J. L. (2010). Reinventing Retail Lending Analytics: Forecasting, Stress Testing, Capital and Scoring for a World of Crises. London: Risk Books.Google Scholar
Breeden, J. L., and Canals-Cerda, J. (2016). Consumer Risk Appetite, the Credit Cycle, and the Housing Bubble. Philadelphia: Federal Reserve Bank of Philadelphia.Google Scholar
Breeden, J. L., Bellotti, A., Leonova, E., and Yablonski, A. (2015). Instabilities using Cox PH for forecasting or stress testing loan portfolios. Credit Scoring and Credit Control Conference XIV. Edinburgh.Google Scholar
Burton, B. J., and Jacobsen, J. P. (2001). The rate of return on investment in wine. Economic Inquiry, 39, 337–350.CrossRefGoogle Scholar
Cardebat, J.-M., Figuet, J.-M., and Paroissien, E. (2014). Expert opinion and Bordeaux wine prices: An attempt to correct biases in subjective judgments. Journal of Wine Economics, 9(3), 282–303.Google Scholar
Cardebat, J.-M., and Livat, F. (2016). Wine experts' rating: A matter of taste? International Journal of Wine Business Research, 28(1), 43–58.Google Scholar
Cardebat, J.-M., and Paroissien, E. (2015). Standardizing expert wine scores: An application for Bordeaux en primeur. Journal of Wine Economics, 10(03), 329–348.Google Scholar
Cox, D. R., and Oakes, D. O. (1984). Analysis of Survival Data. London: Chapman and Hall.Google Scholar
Di Vittorio, A., and Ginsburgh, V. (1996). Des enchères comme révélateurs du classement des vins. Les grands crus du Haut-Médoc. Journal de la Société Statistique de Paris , 137, 19–49.Google Scholar
Dimson, E., Rousseau, P. L., and Spaenjers, C. (2015). The price of wine. Journal of Financial Economics, 118(2), 431–449.Google Scholar
Fama, E. F., and French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33, 3–56.Google Scholar
Financial Accounting Standards Board. (2016). Financial Instruments—Credit Losses (Topic 326): Measurement of Credit Losses on Financial Instruments.Google Scholar
Fogarty, J. J. (2010). Wine investment and portfolio diversification gains. Journal of Wine Economics, 5, 119–131.Google Scholar
Fogarty, J. J., and Sadler, R. (2014). To save or savor: A review of approaches for measuring wine as an investment. Journal of Wine Economics, 9(3), 225–248.Google Scholar
Ginsburgh, V. (1998). Absentee bidders and the declining price anomaly in wine auctions. Journal of Political Economy, 106(6), 1302–1319.Google Scholar
Haeger, J. W., and Storchmann, K. (2006). Prices of American pinot noir wines climate, craftsmanship, critics. Agricultural Economics, 35, 67–78.Google Scholar
Hodgson, R. T. (2008). An examination of judge reliability at a major U.S wine competition. Journal of Wine Economics, 3, 105–113.Google Scholar
Holford, T. (1983). The estimation of age, period, and cohort effects for vital rates. Biometrics, 39(2), 311–324.CrossRefGoogle ScholarPubMed
Holford, T. (2005). Age-period-cohort analysis. In Everitt, B., and Howell, D. (eds.), Encyclopedia of statistics in behavioral science, v. 1. Chichester: John Wiley & Sons, Ltd, 33–38.Google Scholar
Jones, G. V., and Storchmann, K. (2001). Wine market prices and investment under uncertainty: An econometric model for Bordeaux crus class. Agricultural Economics, 26(2), 115–133.CrossRefGoogle Scholar
Kempf, A., and Memmel, C. (2006). Estimating the global minimum variance portfolio. Schmalenbach Review, 58(4), 332–348.Google Scholar
Masset, P., and Henderson, C. (2010). Wine as an alternative asset class. Journal of Wine Economics, 5, 87–118.Google Scholar
Masset, P., and Weisskopf, J. (2010). Raise your glass: Wine investment and the financial crisis. AAWE Working Paper No. 57, http://www.wine-economics.org/dt_catalog/working-paper-no-57/.Google Scholar
Reuter, J. (2009). Does advertising bias product reviews? An analysis of wine ratings. Journal of Wine Economics, 4(2), 125–151.CrossRefGoogle Scholar
Rosen, S. (1974). Hedonic prices and implicit markets: Product differentiation in pure competition. Journal of Political Economy, 82(1), 34–55.Google Scholar
Sanning, L. W., Shaffer, S., and Sharratt, J. (2008). Bordeaux wine as a financial investment. Journal of Wine Economics, 3(1), 51–71.Google Scholar
Schmid, V. J., and Held, L. (2007). Bayesian age-period-cohort modeling and prediction—BAMP. Journal of Statistical Software, 21(8), 1–15.Google Scholar
Storchmann, K. (2012). Wine economics. Journal of Wine Economics, 7(1), 1–33.Google Scholar
Tutz, G., and Schmid, M. (2016). Modeling Discrete Time to Event Data. Springer Series in Statistics. New York: Springer.Google Scholar