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The following output resulted from a regression model where SAGap is seasonally adjusted Gap sales and...

The following output resulted from a regression model where SAGap is seasonally adjusted Gap sales and dpi is disposable income per capita.

Audit Trail -- Coefficient Table (Mulitple Regression Selected)
Series Description Included in Model Coefficient Standard Error T-test P-value F-test Elasticity
SAGAP Dependent - 2,867,564.78 140,536.33 - 20.40 0.00 416.34
dpi Yes 809.79 25.04 32.33 0.00 1,045.55 2.91
Audit Trail -- Correlation Coefficient Table
Series Description Included in Model SAGap dpi
SAGap Dependent 1.00 0.97
dpi Yes 0.97 1.00


Audit Trail - Statistics
Accuracy Measures Value Forecast Statistics Value
AIC 2,135.23 Durbin Watson(4) 0.43
BIC 2,137.56 Mean 1,501,041.15
Mean Absolute Percentage Error (MAPE) 34.60 % Standard Deviation 1,303,264.45
R-Square 94.59 % Max 4,253,174.95
Adjusted R-Square 94.51 % Min 123,121.77
Mean Square Error 90,711,613,878.48 Range 4,130,053.18
Root Mean Square Error 301,183.69 Root Mean Square 1,294,661.95
Theil 6.23 Ljng-Box 347.40

Multiple Choice

  • This regression model is a nonlinear model.

  • This regression model is a causal model.

  • This regression model is a multiple regression model.

  • This regression model is a lagged model.

  • None of the options are true.

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Answer #1

The dependent variable is SAGap - is seasonally adjusted Gap sales.

The explanatory variable is dpi - disposable income per capita.

Thus, there is only one explanatory variable.

This regression model is not a multiple regression model. This regression model is also not a lagged model.

There is no lag value of dpi being used for executing a given regression model.

The regression equation is:

SAGAP = -2,867,564.78 + 809.79*dpi

This regression model is not a nonlinear model.

Though regression is based on causality, it can not be interpreted as establishing cause-and-effect relationships. A statistical relationship does not imply causation.

This regression model is also not a causal model.

Hence, the correct answer is - None of the options are true.

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