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How sample bias affects the assessment of wine investment returns

How sample bias affects the assessment of wine investment returns Abstract Wine investment returns can come from overall market trends or price increases with age. Because of the short wine price histories available, market and maturation effects are difficult to separate. Consequently, researchers often obtain dramatically different estimates of investment returns. We find that data sample bias may be the hidden cause of the disparate estimates. In wine auction data, the sample bias refers to a shift in the distribution of which wines are traded as a function of their age. Such sample bias in panel data sampled across many different wine labels can distort the estimation of price increases versus age and consequently impact the estimation of market trends. This analysis shows that segmenting the analysis such that the data panels contain wine labels with similar trading characteristics can lead to a more stable estimation. The analysis here looks at data from Bordeaux, Italy, Australia, and California. An Age-Period-Cohort (APC) analysis is applied to data panels from each region. Then the data in each region is segmented by a measure of popularity in order to reduce sampling bias. Data thus segmented is then re-analyzed to demonstrate the difference in estimating price appreciation lifecycles and market trends. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Wine Economics Cambridge University Press

How sample bias affects the assessment of wine investment returns

Breeden, Joseph L.
Journal of Wine Economics , Volume 17 (2): 14 – May 1, 2022
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References (33)

Publisher
Cambridge University Press
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press on behalf of American Association of Wine Economists
ISSN
1931-437X
eISSN
1931-4361
DOI
10.1017/jwe.2022.20
Publisher site
See Article on Publisher Site

Abstract

Abstract Wine investment returns can come from overall market trends or price increases with age. Because of the short wine price histories available, market and maturation effects are difficult to separate. Consequently, researchers often obtain dramatically different estimates of investment returns. We find that data sample bias may be the hidden cause of the disparate estimates. In wine auction data, the sample bias refers to a shift in the distribution of which wines are traded as a function of their age. Such sample bias in panel data sampled across many different wine labels can distort the estimation of price increases versus age and consequently impact the estimation of market trends. This analysis shows that segmenting the analysis such that the data panels contain wine labels with similar trading characteristics can lead to a more stable estimation. The analysis here looks at data from Bordeaux, Italy, Australia, and California. An Age-Period-Cohort (APC) analysis is applied to data panels from each region. Then the data in each region is segmented by a measure of popularity in order to reduce sampling bias. Data thus segmented is then re-analyzed to demonstrate the difference in estimating price appreciation lifecycles and market trends.

Journal

Journal of Wine Economics – Cambridge University Press

Published: May 1, 2022

Keywords: age-period-cohort models; auction prices; sample bias; survival analysis; wine investment; C23; D44; G11; G12; Q11

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