Alcohol Consumption Allyson Cady Dave Klotz Brandon DeMille Chris Ross

Data Total alcohol –Beer –Wine –Spirits Yearly data, from Gallons of ethanol consumption, per capita

Alcohol Consumption Prohibition ended in 1935

Why alcohol consumption? Big industry with big money (approx. $70 billion in 1997, an increase of 17% from 5 years prior) Health issues Drunk driving and other alcohol related deaths We are college students We recently went through a period of war

WWIIVietnamPersian Gulf War-time Drinking

War-time Dummy Originally, we were planning to include a dummy variable to capture a wartime/non-wartime trend Although this kind of variable is useful in explaining the past, it doesn’t help with forecasting The dummy variable was left out of all models

Data is evolutionary To get rid of the evolutionary properties, –Take log –First difference  Results in percentage change in each period After doing this, the data becomes much more stationary

Modeling First attempts used ARMA techniques, but found that MA processes worked better Similar model found for all data sets

Model- Total Alcohol Dependent Variable: DLNALLALC Method: Least Squares Date: 05/26/03 Time: 19:26 Sample(adjusted): Included observations: 65 after adjusting endpoints Convergence achieved after 30 iterations Backcast: VariableCoefficientStd. Errort-StatisticProb. C MA(1) MA(4) MA(9) MA(12) R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) Inverted MA Roots i i i i i i i i i i -.99

Model- Total Alcohol

Model- Beer Dependent Variable: DLNBEER Method: Least Squares Date: 05/26/03 Time: 19:33 Sample(adjusted): Included observations: 65 after adjusting endpoints Convergence achieved after 12 iterations Backcast: VariableCoefficientStd. Errort-StatisticProb. C MA(1) MA(8) MA(13) R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) Inverted MA Roots i i i i i i i i i i i i

Model- Beer

Model- Spirits Dependent Variable: DLNSP Method: Least Squares Date: 05/26/03 Time: 19:46 Sample(adjusted): Included observations: 65 after adjusting endpoints Convergence achieved after 16 iterations Backcast: VariableCoefficientStd. Errort-StatisticProb. C MA(1) MA(4) MA(9) MA(12) R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) Inverted MA Roots i i i i i i i i i i -.96

Model- Spirits

Model- Wine Dependent Variable: DLNWINE Method: Least Squares Date: 05/26/03 Time: 19:50 Sample(adjusted): Included observations: 65 after adjusting endpoints Convergence achieved after 20 iterations Backcast: VariableCoefficientStd. Errort-StatisticProb. C MA(4) MA(11) R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) Inverted MA Roots i i i i i i i i i i

Model- Wine

Summary of Models Total Alcohol: C, MA(1), MA(4), MA(9), MA(12) Beer: C, MA(1), MA(8), MA(13) Spirits: C, MA(1), MA(4), MA(9), MA(12) Wine: C, MA(4), MA(11)

Forecast- All alcohol

Forecast- Beer

Forecast- Spirits

Forecast- Wine

Forecasts in Gallons per Capita

Forecast Results All forecasts show a similar pattern, with gradual increases expected in the future 1999 Consumption2010 ForecastExpected ChangeExpected Percent Change Total2.21 gallons2.52 gallons0.31 gallons14.0% Beer % Spirits % Wine %

Conclusions Americans are expected to increase their alcohol consumption by 14% over the period from 1999 to 2010 –Wine is expected to see the largest percentage increase –Beer is expected to see the largest absolute increase Increased consumption could lead to more difficulties with drunk driving, health issues, etc. –Awareness will become increasingly critical in the near future

The End