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

95

90

80

70

605040

30

20

10

5

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

95

90

80

70

605040

30

20

10

5

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

95

90

80

70

605040

30

20

10

5

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

Tick

ets

(billio

ns)

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

Tick

ets

(bill

ions)

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 (%)

Tick

ets

(billio

ns)

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

Tick

ets

(billio

ns)

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)

Tick

ets

(billio

ns)

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

Tick

ets

(billio

ns)

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

Tick

ets

(billio

ns)

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

Tick

ets

(billio

ns)

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/