The Law of One Price? Price Dispersion on the Auction Market for Fine Wine

Abstract

This paper examines the strong version of the law of one price (LOOP) on the auction market for fine wine. We draw on worldwide auction prices from eight auction houses,1 covering the time period from 2000 to 2012. Employing a hedonic approach, we find significant price premiums in particular in Hong Kong and between auction companies (independent of their locations). The price premiums by far exceed the expected transaction costs, casting doubt on the existence of the strong version of LOOP in the fine wine market. Our results suggest that heterogeneity in buyer preferences may crucially contribute to the observed price dispersion. In particular, although wines suspected of being counterfeits are sold at discounts in Western markets, they fetch price premiums in Hong Kong. (JEL Classifications: Q14, G11)

Modeling Grape Price Dynamics in Mendoza: Lessons for Policymakers

“…We use an inverse demand ARDL/hedonic price model. Both hedonic models (Ashenfelter, 2017; Bekkerman and Brester, 2019; Cardebat et al, 2017; Cross, Plantinga, and Stavins, 2017) and distributed lag models (Cardebat and Figuet 2019; Gergaud, Livat, and Song, 2018; Niklas and Sadik-Zada 2019) have been widely used to investigate issues in the wine market. Following a process of backwards and forwards variable selection, the final model selected is: where P ijkt denotes the log of the real per kilogram price of grape variety i sold in region j associated with transaction k , at time t ; V i and R j denote variety and region dummies; T l is a dummy variable for payment type (i.e., cash or installments); Q v denote volume quartile dummies; is the average real price per kilogram for variety i in region j at time t – 1; H t is the total quantity of grapes harvested in Mendoza in the year of the transaction; W t is the total stock of wine in Argentina at the beginning of year t ; G t is the total stock of grape juice in Argentina at the beginning of the year of year t ; Y t denotes the year in which the transaction took place; Greek letters denote parameters to be estimated; and e ijkt is a zero mean error term.…”

Behavioural heterogeneity in wine investments

“…It is related to the intrinsic behaviour of customers who may behave emotionally and therefore may either drive prices away from their fundamental value or lead producers to adapt their pricing strategy. More recent literature has started to study this part by looking into client segmentation which may display diverging behaviour and draw different utility functions out of a bottle of fine wine (Cardebat et al, 2017). Other studies examine the effects of marketing tools on the purchase behaviour of customers and how these lead to a differentiated willingness to pay (Danner et al, 2016).…”

Looking Beyond Wine Risk-Adjusted Performance

“…The second, related to the first, comes from the illiquidity of these wines. Low liquidity leads to higher risk, but this risk is very poorly assessed (see Cardebat et al, 2017). The great advantage of the wines constituting the Liv-ex 50 is precisely their liquidity, which allows a very easy exit (resale).…”