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Drinking patterns within households: the estimation and interpretation of individual and group variables

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  • Nigel Rice
  • Matthew Sutton

Abstract

Levels of alcohol consumption tend to be similar for individuals living in the same household. This may be because: (a) individuals with similar characteristics collect in households (correlated effects); (b) individuals in the same household are influenced by common factors (exogenous effects); and/or (c) the consumption levels of an individual directly influences the consumption levels of other individuals in the same household (endogenous effects). Whichever of these three possibilities is the principal reason underlying household clustering of consumption levels has important policy implications. In this paper we propose a testing strategy to distinguish between the three types of effect in a cross‐sectional data‐set. Allowing for exogenous or endogenous effects shows that the significant socio‐economic gradient in a model containing only individual variables arises because of misspecification. However, because we find significant evidence of correlated effects, we cannot identify whether it is endogenous or exogenous effects which give rise to statistically significant group level variables. The results indicate the possible pitfalls of omitting group level influences.Copyright © 1998 John Wiley & Sons, Ltd.

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  • Nigel Rice & Matthew Sutton, 1998. "Drinking patterns within households: the estimation and interpretation of individual and group variables," Health Economics, John Wiley & Sons, Ltd., vol. 7(8), pages 689-699, December.
    • Handle: RePEc:wly:hlthec:v:7:y:1998:i:8:p:689-699
    DOI: 10.1002/(SICI)1099-1050(199812)7:8<689::AID-HEC385>3.0.CO;2-W
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    3. Petter Lundborg, 2007. "Smoking, information sources, and risk perceptions—New results on Swedish data," Journal of Risk and Uncertainty, Springer, vol. 34(3), pages 217-240, June.
    4. Shuo Shi & Lu Zhang & Guohua Wang, 2023. "Bridging the Digital Divide: Internet Use of Older People from the Perspective of Peer Effects," Sustainability, MDPI, vol. 15(15), pages 1-16, August.
    5. Ana Balsa & Carlos Díaz, 2018. "Social interactions in health behaviors and conditions," Documentos de Trabajo/Working Papers 1802, Facultad de Ciencias Empresariales y Economia. Universidad de Montevideo..
    6. Francetic, Igor & Meacock, Rachel & Sutton, Matt, 2022. "Understanding Concordance in Health Behaviours among Couples: Evidence from the Bowel Cancer Screening Programme in England," Journal of Economic Behavior & Organization, Elsevier, vol. 201(C), pages 310-345.
    7. Haque, Samiul & Abedin, Naveen & Fakir, Adnan M. S. & Hannan, Rafe & Alam, Rafa, 2019. "Effects of smoking on agricultural productivity," 2019 Annual Meeting, July 21-23, Atlanta, Georgia 291149, Agricultural and Applied Economics Association.
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    9. Moscone, Francesco & Knapp, Martin & Tosetti, Elisa, 2007. "Mental health expenditure in England: A spatial panel approach," Journal of Health Economics, Elsevier, vol. 26(4), pages 842-864, July.
    10. Schmidt, Christoph M. & Tauchmann, Harald, 2011. "Heterogeneity in the intergenerational transmission of alcohol consumption: A quantile regression approach," Journal of Health Economics, Elsevier, vol. 30(1), pages 33-42, January.
    11. Christoph M. Schmidt & Harald Tauchmann, 2010. "Heterogeneity in the Intergenerational Transmission of Alcohol Consumption – A Quantile Regression Approach," Ruhr Economic Papers 0186, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.

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