title: The causal relationship between socioeconomic factors and alcohol consumption: a Granger-causality time series analysis, 1950-1993.
abstract: OBJECTIVE
  This article examines the relationships between social, demographic and economic factors that influence alcohol consumption.
  
  
  METHODS
  The effects of each factor on alcohol consumption and on each other is examined using a Granger-causality time series framework. Specifically, causal determinations are made between per capita alcohol consumption, social and demographic variables consisting of the age structure of the male population, female labor force participation rates, marital instability and educational accomplishment, and the economic variables consisting of the real price of alcohol, median household income and income inequality. Causal equations are determined from identified bivariate relationships and combined into one structural equation predicting alcohol consumption.
  
  
  RESULTS
  The findings indicate that the economic variables are Granger-caused by the social or demographic changes over the past four decades and, therefore, have little direct influence on alcohol consumption. The structural equation predicts over 95% of the variance in alcohol consumption.
  
  
  CONCLUSIONS
  This work indicates that economic factors have little direct influence on alcohol consumption but, rather, reflect or are a conduit for changes in social and demographic variables. Excluding economic variables as predictors of per capita ethanol consumption results in little substantive change when estimating alcohol consumption.
authors.affiliation: Prevention Research Center, Berkeley, California 94709, USA.
authors.forename: G L
authors.initials: GL
authors.lastname: Brinkley
mesh_terms: D000367:Age Factors; D000428:Alcohol Drinking / Q000191:economics / Q000453:epidemiology*; D015984:Causality; D005260:Female; D006801:Humans; D008297:Male; D015999:Multivariate Analysis; D012737:Sex Factors; D012959:Socioeconomic Factors; D014931:Women, Working / Q000706:statistics & numerical data