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Is There Convergence in National Alcohol Consumption Patterns? Evidence from a Compositional Time Series Approach

Published online by Cambridge University Press:  26 February 2018

Terence C. Mills
Terence C. Mills*
Affiliation:
School of Business and Economics, Loughborough University, Ashby Road, Loughborogh, Leics LE11 3TU, U.K; e-mail: [email protected].
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Abstract

Holmes and Anderson (2017a) introduce two extensive data sets on world alcohol consumption and expenditure and with them investigate, among other things, the possible convergence of national alcohol consumption patterns using wine, beer, and spirit shares. Such share data define a composition, on which conventional statistical analysis using covariances and correlations is invalid. This note reanalyses the data using techniques appropriate for a composition and introduces a statistic that can validly track the variation in national shares around the global mean through time. This variability statistic shows that such convergence of national alcohol patterns has clearly taken place over the period 1961 to 2014 and thus confirms Holmes and Anderson's findings using a valid statistical approach. (JEL Classifications: C18, D12, L66)

Keywords

alcohol consumption sharescompositional data analysis
Type
Articles
Information
Journal of Wine Economics , Volume 13 , Issue 1 , February 2018 , pp. 92 - 98
Copyright
Copyright © American Association of Wine Economists 2018 

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Footnotes

The author is grateful for the anonymous comments of a referee.

References

Aitchison, J. (1982). The statistical analysis of compositional data (with discussion). Journal of the Royal Statistical Society, Series B 44(2), 139–177.Google Scholar
Aitchison, J. (2003). The Statistical Analysis of Compositional Data. Caldwell, NJ: Blackburn Press.Google Scholar
Anderson, K., and Pinilla, V. (with the assistance of A. J. Holmes) (2017). Annual Database of Global Wine Markets, 1835 to 2016. Wine Economics Research Centre, University of Adelaide. Available at www.adelaide.edu.au/wine-econ/databases/global-wine-history.Google Scholar
Holmes, A. J., and Anderson, K. (2017a). Convergence in national alcohol consumption patterns: New global indicators. Journal of Wine Economics, 12(2), 117–148.CrossRefGoogle Scholar
Holmes, A. J., and Anderson, K. (2017b). Annual Database of National Beverage Consumption Volumes and Expenditures, 1950 to 2015. Wine Economics Research Centre, University of Adelaide. Available at www.adelaide.edu.au/wine-econ/databases/alcohol-consumption.Google Scholar
Mills, T. C. (2007). Modelling compositional economic data. Indian Economic Journal, 55(3), 99–115.Google Scholar
Mills, T. C. (2009). Forecasting obesity trends in England. Journal of the Royal Statistical Society, Series A 172(1), 107–117.Google Scholar
Mills, T. C. (2010). Forecasting compositional time series. Quality and Quantity, 44(4), 673–690.Google Scholar
Pearson, K. (1897). Mathematical contributions to the theory of evolution. On a form of spurious correlation which may arise when indices are used in the measurement of organs. Proceedings of the Royal Society of London, Series A 60, 489–498.Google Scholar