Movie Theatre Attendance in Regards to Economic Factors
By: Madison Kerr
Movie Theatre Attendance Based on 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
1007550250-25-50
99
9590
80706050403020
105
1
Recession probability
Perc
ent
Mean 10.06StDev 22.14N 17AD 3.760P-Value <0.005
Probability Plot of Recession probabilityNormal - 95% CI
Not Normal DataTotal Public Debt
20000000150000001000000050000000
99
9590
80706050403020
105
1
Total Public Debt (mill)
Perc
ent
Mean 7863564StDev 2982727N 17AD 0.985P-Value 0.010
Probability Plot of Total Public Debt (mill)Normal - 95% CI
Not Normal Data
Stress Index
3210-1-2-3
99
9590
80706050403020
105
1
Stress Index
Perc
ent
Mean 0.02688StDev 0.8763N 17AD 0.994P-Value 0.010
Probability Plot of Stress IndexNormal - 95% CI
Not Normal Data
Unemployment Rate
Normal Data
S&P 500 End Values
Parametric vs Non-Parametric Regressions
80706050403020100
1.6
1.5
1.4
1.3
1.2
Recession probability
Ticke
ts (b
illion
s)
RegressLowess
Fits
Scatterplot of Tickets (billions) vs Recession probability
R sq= 0.1%
Parametric vs Non-Parametric Regressions
5000047500450004250040000
1.6
1.5
1.4
1.3
1.2
Real GDP per Capita
Ticke
ts (b
illion
s)
RegressLowess
Fits
Scatterplot of Tickets (billions) vs Real GDP per Capita
R sq=57%
Parametric vs Non-Parametric Regressions
10987654
1.6
1.5
1.4
1.3
1.2
Unemployment Rate (%)
Ticke
ts (b
illion
s)
RegressLowess
Fits
Scatterplot of Tickets (billions) vs Unemployment Rate (% )
R sq=8%
Parametric vs Non-Parametric Regressions
2.52.01.51.00.50.0-0.5-1.0
1.6
1.5
1.4
1.3
1.2
Stress Index
Ticke
ts (b
illion
s)
RegressLowess
Fits
Scatterplot of Tickets (billions) vs Stress Index
R sq=17.6%
Parametric vs Non-Parametric Regressions
15000000125000001000000075000005000000
1.6
1.5
1.4
1.3
1.2
Total Public Debt (mill)
Ticke
ts (b
illion
s)
RegressLowess
Fits
Scatterplot of Tickets (billions) vs Total Public Debt (mill)
R sq=26.8%
Parametric vs Non-Parametric Regressions
150012501000750500
1.6
1.5
1.4
1.3
1.2
SP500
Ticke
ts (b
illion
s)
RegressLowess
Fits
Scatterplot of Tickets (billions) vs SP500
R sq=43.9%
Parametric vs Non-Parametric Regressions
2.22.12.01.91.81.71.6
1.6
1.5
1.4
1.3
1.2
Velocity of Money
Ticke
ts (b
illion
s)
RegressLowess
Fits
Scatterplot of Tickets (billions) vs Velocity of Money
R sq=30.2%
Parametric vs Non-Parametric Regressions
11010090807060
1.6
1.5
1.4
1.3
1.2
Consumer Sentiment
Ticke
ts (b
illion
s)
RegressLowess
Fits
Scatterplot of Tickets (billions) vs Consumer Sentiment
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 … = Taukvs
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 Datahttp://research.stlouisfed.org/fred2/
Movie Theatre Datahttp://www.the-numbers.com/market/