DISCUSSION PAPER 08.05THE ECONOMICS OF WINE: PRICING, QUALITY AND RATE OF RETURN
PART I: INTRODUCTION*
School of Economics and Commerce
The University of Western Australia
DISCUSSION PAPER 08.05
* This is the front matter and Chapter 1 of my PhD thesis The Economics of Wine: Pricing, Quality and Rate of Return, UWA, 2006. The full thesis is available as Discussion Papers 08.05 to 08.09.Life Cycle
This thesis consists of six chapters, and the main research contributions are contained in chapters two through five inclusive. The topics addressed in each chapter are distinct, but related, and the specific contributions to knowledge made by the different chapters are related to: (i) understanding more fully the nature of the demand for alcohol; (ii) explaining the relationship between reputation characteristics and consumers’ willingness to pay for wine; (iii) estimating the rate of return to Australian wine; and (iv) using financial analysis to reveal the risk diversification benefits available by including wine in an investment portfolio. The details of each contribution are briefly outlined below.
Chapter 2 discusses the nature of the demand for alcohol. The demand for alcoholic beverages is an area much studied, and there are numerous studies estimating the own-price elasticity of alcoholic beverages. A review of relevant published studies indicates reported: beer own-price elasticity estimates range from -.02 to -3.00, with a mean estimate value of -.46, and standard deviation of -.41 (n = 139); wine own-price elasticity estimates range from -.05 to -3.00, with a mean estimate value of -.72, and standard deviation of .53 (n = 140); and spirits own-price elasticity estimates range from -.01 to -2.18, with a mean estimate value of -.74, and standard deviation of .47 (n = 136). Chapter 2 contributes to understanding the demand for alcohol, not by adding yet another set of elasticity estimates to an already substantial literature, but by providing a framework through which all known own-price elasticity estimates can be understood. Specifically, a meta-regression framework is employed to study previously published own-price elasticity estimates. This framework allows the effect of model design attributes to be isolated, and the underlying trend in consumer responses to price changes to be identified.
Chapter 3 is concerned with understanding the relationship between the price a consumer is willing to pay for a bottle of wine, and the underlying attributes embodied in the wine. The approach used to investigate this relationship is the hedonic price equation approach. The model developed in the chapter starts from first principles, and unlike other studies in this field considers both supply and demand issues. In the chapter particular attention is given to the possible role of reputation characteristics, and the question of whether OLS is a suitable estimation approach. Specifically, the chapter shows: bottle age, regional reputation, varietal reputation, investment reputation, and quality reputation, all have a significant impact upon price. Subjective expert quality ratings on the other hand are shown to be not valued by consumers. These findings are at odds with those presented in other research, and possible reasons for the different results are explored.
Wine investment is a topic which has received much attention in the media, yet, in Australia, it is a topic little understood. It is perhaps so little understood because to date access to systematic and reliable price information has been limited. As such, before starting to investigate the return to wine, it was first necessary to create a database of wine prices. The database of wine prices created is unique, and is based on the price information contained in the computer system of the largest wine auction house in Australia, Langton’s. The database created is used as the basis for the investigation into the rate of return to wine presented in Chapter 4.
The percentage return to wine i, at time t -- ignoring for a moment issues of storage costs, sales commissions, and insurance -- can be expressed as: where is the price of wine i in period t. The return to a portfolio of wine in any given period is some average of the n individual returns, and from such information, if desired, a wine price index can be constructed. Unfortunately, wine sales are infrequent, and all n wines are not sold in all periods. So, while there is an underlying price process for each wine, we observe prices only at infrequent and irregular intervals. The challenge is therefore, to describe the underlying but unobserved price path of wine from limited information. There are many approaches to estimating price change in such situations, and in Chapter 4 a variety of approaches are canvassed. The actual approach chosen to estimate the return to wine is the adjacent period hedonic price equation approach. In the chapter estimates of the quarterly return to wine are presented for the period 1989Q4 to 2000Q4. Following a discussion of the estimated return to wine, the chapter considers the investment performance of wines of different price, variety, and vintage.
The contributions made in Chapter 5 towards furthering understanding of the investment properties of wine are a natural extension of the analysis presented in Chapter 4. Specifically, Chapter 5 considers wine investment under two distinct sets of investment conditions. The first set of investment conditions may be thought of as representing the conditional setting, and the second set of investment conditions may be thought of as representing the unconditional setting. In the conditional setting the question of optimal asset allocation between different wine asset is considered. In the unconditional setting the question of optimal asset allocation between wine and other financial assets is considered. The framework used to investigate the optimal asset allocation question in both the conditional and unconditional setting is the mean-variance efficient frontier framework. In the chapter, results are reported for a range of different investment approaches, and for investment decisions made using two different estimators of expected returns.