Alcohol Consumption
Allyson Cady
Dave Klotz
Brandon DeMille
Chris Ross
Data
• Total alcohol
– Beer
– Wine
– Spirits
• Yearly data, from 1935-1999
• Gallons of ethanol consumption, per
capita
Alcohol Consumption
3.0
Prohibition ended in 1935
2.5
2.0
1.5
1.0
0.5
0.0
35
40
45
50
55
60
65
70
ALLALCOHOL
BEER
75
80
85
90
WINE
SPIRITS
95
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
War-time Drinking
WWII
3.0
Vietnam
Persian Gulf
2.5
2.0
1.5
1.0
0.5
0.0
35
40
45
50
55
60
65
70
ALLALCOHOL
BEER
75
80
85
90
WINE
SPIRITS
95
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): 1935 1999
Included observations: 65 after adjusting endpoints
Convergence achieved after 30 iterations
Backcast: 1923 1934
Variable
Coefficient Std. Error t-Statistic Prob.
C
0.012423 0.007874 1.577789 0.1199
MA(1)
0.202583 0.102955 1.967686 0.0537
MA(4)
0.200271 0.038070 5.260578 0.0000
MA(9)
0.532056 0.038013 13.99652 0.0000
MA(12)
-0.367795 0.077569 -4.741518 0.0000
R-squared
0.480532
Mean dependent var
Adjusted R-squared 0.445900
S.D. dependent var
S.E. of regression
0.040654
Akaike info criterion
Sum squared resid
0.099166
Schwarz criterion
Log likelihood
118.5427
F-statistic
Durbin-Watson stat 1.510219
Prob(F-statistic)
Inverted MA Roots
.83 -.42i
.83+.42i
.79
.50 -.86i
.50+.86i -.10 -.91i -.10+.91i -.43+.70i
-.43 -.70i -.80+.57i -.80 -.57i
-.99
0.012668
0.054615
-3.493621
-3.326361
13.87567
0.000000
Model- Total Alcohol
0.3
Residual
Actual
Fitted
0.2
0.1
0.2
0.0
0.1
-0.1
-0.2
0.0
-0.1
35 40 45 50 55 60 65 70 75 80 85 90 95
Model- Beer
Dependent Variable: DLNBEER
Method: Least Squares
Date: 05/26/03 Time: 19:33
Sample(adjusted): 1935 1999
Included observations: 65 after adjusting endpoints
Convergence achieved after 12 iterations
Backcast: 1922 1934
Variable
Coefficient Std. Error t-Statistic Prob.
C
0.010879 0.005165 2.106321 0.0393
MA(1)
0.338015 0.057139 5.915627 0.0000
MA(8)
0.482068 0.073578 6.551768 0.0000
MA(13)
-0.346007 0.000297 -1163.471 0.0000
R-squared
0.559543
Mean dependent var
Adjusted R-squared 0.537881
S.D. dependent var
S.E. of regression
0.028555
Akaike info criterion
Sum squared resid
0.049740
Schwarz criterion
Log likelihood
140.9672
F-statistic
Durbin-Watson stat 1.867790
Prob(F-statistic)
Inverted MA Roots
.85 -.42i
.85+.42i
.84
.44+.78i
.44 -.78i
.14+.88i
.14 -.88i -.39+.91i
-.39 -.91i -.68 -.54i -.68+.54i -.95 -.29i
-.95+.29i
0.011038
0.042006
-4.214377
-4.080568
25.83085
0.000000
Model- Beer
0.20
Residual
Actual
Fitted
0.15
0.10
0.05
0.15
0.00
0.10
-0.05
0.05
-0.10
0.00
-0.05
-0.10
35 40 45 50 55 60 65 70 75 80 85 90 95
Model- Spirits
Dependent Variable: DLNSP
Method: Least Squares
Date: 05/26/03 Time: 19:46
Sample(adjusted): 1935 1999
Included observations: 65 after adjusting endpoints
Convergence achieved after 16 iterations
Backcast: 1923 1934
Variable
Coefficient Std. Error t-Statistic Prob.
C
0.011952 0.013801 0.865997 0.3899
MA(1)
0.210494 0.039468 5.333299 0.0000
MA(4)
0.361197 0.051499 7.013642 0.0000
MA(9)
0.456485 0.067899 6.723014 0.0000
MA(12)
-0.349441 0.096900 -3.606184 0.0006
R-squared 0.529189
Mean dependent var
0.012178
Adjusted R-squared 0.497802
S.D. dependent var
0.093814
S.E. of regression
0.066482
Akaike info criterion
-2.509955
Sum squared resid
0.265195
Schwarz criterion
-2.342694
Log likelihood
86.57354
F-statistic
16.85995
Durbin-Watson stat 1.560509
Prob(F-statistic)
0.000000
Inverted MA Roots
.82+.44i
.82 -.44i
.79
.51+.85i
.51 -.85i -.09 -.89i -.09+.89i -.46 -.70i
-.46+.70i -.80+.58i -.80 -.58i
-.96
Model- Spirits
0.4
Residual
Actual
Fitted
0.4
0.2
0.0
-0.2
-0.4
35 40 45 50 55 60 65 70 75 80 85 90 95
0.2
0.0
-0.2
-0.4
Model- Wine
Dependent Variable: DLNWINE
Method: Least Squares
Date: 05/26/03 Time: 19:50
Sample(adjusted): 1935 1999
Included observations: 65 after adjusting endpoints
Convergence achieved after 20 iterations
Backcast: 1924 1934
Variable
Coefficient Std. Error t-Statistic
C
0.022948 0.013878 1.653610
MA(4)
0.711925 0.000400 1781.703
MA(11)
-0.257302 0.057245 -4.494751
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
Inverted MA Roots
.45+.76i
-.67 -.73i
0.439531
0.421451
0.076113
0.359182
76.71418
2.309783
.81
-.15 -.80i
-.78 -.30i
Prob.
0.1033
0.0000
0.0000
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
.75 -.59i
.75+.59i
.45 -.76i
-.15+.80i -.67+.73i
-.78+.30i
0.023382
0.100067
-2.268129
-2.167772
24.31080
0.000000
Model- Wine
0.4
Residual
Actual
Fitted
0.2
0.0
0.3
-0.2
0.2
-0.4
0.1
-0.6
0.0
-0.1
-0.2
-0.3
35 40 45 50 55 60 65 70 75 80 85 90 95
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
0.3
0.2
0.1
0.0
-0.1
-0.2
35 40 45 50 55 60 65 70 75 80 85 90 95 00 05 10
ALLTIM ETOTAL
Forecast- Beer
0.20
0.15
0.10
0.05
0.00
-0.05
-0.10
35 40 45 50 55 60 65 70 75 80 85 90 95 00 05 10
ALLTIM EBEER
Forecast- Spirits
0.4
0.2
0.0
-0.2
-0.4
35 40 45 50 55 60 65 70 75 80 85 90 95 00 05 10
ALLTIM ESPIRITS
Forecast- Wine
0.4
0.2
0.0
-0.2
-0.4
-0.6
35 40 45 50 55 60 65 70 75 80 85 90 95 00 05 10
ALLTIM EWINE
Forecasts in Gallons per Capita
3.0
2.5
2.0
1.5
1.0
0.5
0.0
40
50
60
70
ALLALCOHOL
BEER
80
90
SPIRITS
WINE
00
10
Forecast Results
• All forecasts show a similar pattern, with
gradual increases expected in the future
1999 Consumption
2010 Forecast
Expected Change
Expected Percent Change
Total
2.21 gallons
2.52 gallons
0.31 gallons
14.0%
Beer
1.25
1.40
0.15
12.0%
Spirits
0.64
0.73
0.09
14.1%
Wine
0.32
0.44
0.12
37.5%
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