• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 1
  • Tagged with
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Wine investment, pricing and substitutes

Fogarty, James January 2006 (has links)
[Truncated abstract] 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.

Page generated in 0.0765 seconds