Transcript Movie Theatre Attendance in Regards to Economic Factors

Movie Theatre Attendance
Based on Economic Factors
Movie Theatre Attendance in
By: Madison Kerr
Regards to Economic Factors
By: Madison Kerr
Hypothesis
• That movie theatre attendance is not
influenced by economic factors.
Movie Industry
Economy
Economic Goods
• Two types of goods:
– Normal
• People buy less of in harsh times
– Inferior
• People buy more of in harsh times
Economic Factors vs Movie Attendance
•
•
•
•
•
•
•
•
•
Recession
Real GDP per Capita
Unemployment Rate
Stress Index
Consumer Sentiment
Velocity of Money
S&P 500
Total Public Debt
Disposable Personal
Income
Not Normal Data
Probability of Recession
Probability Plot of Recession probability
Normal - 95% CI
99
Mean
StDev
N
AD
P-Value
95
90
Percent
80
70
60
50
40
30
20
10
5
1
-50
-25
0
25
50
Recession probability
75
100
10.06
22.14
17
3.760
<0.005
Not Normal Data
Total Public Debt
Probability Plot of Total Public Debt (mill)
Normal - 95% CI
99
Mean
StDev
N
AD
P-Value
95
90
Percent
80
70
60
50
40
30
20
10
5
1
0
5000000
10000000
15000000
Total Public Debt (mill)
20000000
7863564
2982727
17
0.985
0.010
Not Normal Data
Stress Index
Probability Plot of Stress Index
Normal - 95% CI
99
Mean
StDev
N
AD
P-Value
95
90
Percent
80
70
60
50
40
30
20
10
5
1
-3
-2
-1
0
Stress Index
1
2
3
0.02688
0.8763
17
0.994
0.010
Not Normal Data
Unemployment Rate
Normal Data
S&P 500 End Values
Parametric vs Non-Parametric
Regressions
Scatterplot of Tickets (billions) vs Recession probability
1.6
Fits
Regress
Lowess
Tickets (billions)
1.5
1.4
1.3
1.2
0
10
20
30
40
50
Recession probability
60
70
80
R sq= 0.1%
Parametric vs Non-Parametric
Regressions
Scatterplot of Tickets (billions) vs Real GDP per Capita
1.6
Fits
Regress
Lowess
Tickets (billions)
1.5
1.4
1.3
1.2
40000
42500
45000
Real GDP per Capita
47500
50000
R sq=57%
Parametric vs Non-Parametric
Regressions
Scatterplot of Tickets (billions) vs Unemployment Rate (%)
1.6
Fits
Regress
Lowess
Tickets (billions)
1.5
1.4
1.3
1.2
4
5
6
7
8
Unemployment Rate (%)
9
10
R sq=8%
Parametric vs Non-Parametric
Regressions
Scatterplot of Tickets (billions) vs Stress Index
1.6
Fits
Regress
Lowess
Tickets (billions)
1.5
1.4
1.3
1.2
-1.0
-0.5
0.0
0.5
1.0
Stress Index
1.5
2.0
2.5
R sq=17.6%
Parametric vs Non-Parametric
Regressions
Scatterplot of Tickets (billions) vs Total Public Debt (mill)
1.6
Fits
Regress
Lowess
Tickets (billions)
1.5
1.4
1.3
1.2
5000000
7500000
10000000
12500000
Total Public Debt (mill)
15000000
R sq=26.8%
Parametric vs Non-Parametric
Regressions
Scatterplot of Tickets (billions) vs SP500
1.6
Fits
Regress
Lowess
Tickets (billions)
1.5
1.4
1.3
1.2
500
750
1000
SP500
1250
1500
R sq=43.9%
Parametric vs Non-Parametric
Regressions
Scatterplot of Tickets (billions) vs Velocity of Money
1.6
Fits
Regress
Lowess
Tickets (billions)
1.5
1.4
1.3
1.2
1.6
1.7
1.8
1.9
2.0
Velocity of Money
2.1
2.2
R sq=30.2%
Parametric vs Non-Parametric
Regressions
Scatterplot of Tickets (billions) vs Consumer Sentiment
1.6
Fits
Regress
Lowess
Tickets (billions)
1.5
1.4
1.3
1.2
60
70
80
90
Consumer Sentiment
100
110
R sq=5.1%
Non-Parametric Correlation
- Kendall
• Null: x and y are independent
vs
Alternative: x and y are dependent in some way
• Test stat: Tau
– Tau > 0 = positively correlated
– Tau < 0 = negatively correlated
– Tau = 0 = no correlation
Kendall’s Tau:
Ticket Sales vs…
Recession Prob :
z = 0.414
p-value = 0.6789
Tau = 0.075
Fail to reject null and conclude there isn’t
sufficient evidence that there is a correlation
between ticket sales and the probability of a
recession.
Kendall’s Tau:
Ticket Sales vs…
Real GDP per capita:
z = 0 p-value = 1
Tau = 0
Fail to reject null and conclude there isn’t
sufficient evidence that there is a correlation
between ticket sales and real GDP per capita.
Kendall’s Tau:
Ticket Sales vs…
Unemployment rates:
z = -0.4968 p-value = 0.6193
Tau = -0.09
Fail to reject null and conclude there isn’t
sufficient evidence that there is a correlation
between ticket sales and unemployment rates.
Kendall’s Tau:
Ticket Sales vs…
Stress Index:
z = 0.6613
p-value = 0.5084
Tau = 0.119
Fail to reject null and conclude there isn’t
sufficient evidence that there is a correlation
between ticket sales and stress levels.
Kendall’s Tau:
Ticket Sales vs…
Consumer Sentiment:
z = 0.992 p-value = 0.3212
Tau = 0.179
Fail to reject null and conclude there isn’t
sufficient evidence that there is a correlation
between ticket sales and consumer sentiment.
Kendall’s Tau:
Ticket Sales vs…
Velocity of money:
z = 0.0827
p-value = 0.9341 Tau = 0.0149
Fail to reject null and conclude there isn’t
sufficient evidence that there is a correlation
between ticket sales and velocity of money.
Kendall’s Tau:
Ticket Sales vs…
S&P 500 Index:
z = -0.248
p-value = 0.804 Tau = -0.0448
Fail to reject null and conclude there isn’t
sufficient evidence that there is a correlation
between ticket sales and end value of S&P 500
Index.
Kendall’s Tau:
Ticket Sales vs…
Public Debt:
z = -0.5787
p-value = 0.5628 Tau = -0.1044
Fail to reject null and conclude there isn’t
sufficient evidence that there is a correlation
between ticket sales and public debt.
Kruskal-Wallis Test
Kruskal-Wallis
• Null: Tau1 = Tau2 = Tau3 … = Tauk
vs
Alternative: Atleast one Tau differs
Test stat = H
Kruskal-Wallis Results
• Because no correlation between any of the
variables, it is no surprise that all KW tests
resulted in a failure to reject the null
hypothesis.
Conclusion
• Movie theatre attendance not influenced by
economic factors
Works Cited
Economic Data
http://research.stlouisfed.org/fred2/
Movie Theatre Data
http://www.the-numbers.com/market/