Question

Consider the following results of a multiple regression model of dollar price of unleaded gas (dependent variable) and a set of independent variables: price of crude oil, value of S&P500, price U.S. Dollars against Euros, personal disposal income (in million of dollars) :

Coefficient	t-statistics
Intercept	0.5871	68.90
Crude Oil	0.0651	32.89
S&P 500	-0.0020	18.09
Price of $	-0.0415	14.20
PDI	0.0001	17.32

R-Square = 97%

1. What will be forecasted price of unleaded gas if the value of independent variables are as follows:

Crude Oil = 95; S&P500 = 1775; Price of $ = 0.80 Euros; PDI = 800

1. $3.27
2. $2.66
3. $2.99
4. $3.04

2. What is the interpretation of R-Square?

1. 97% of the movement in unleaded gas price can be explained by this forecasting model.
2. 97% of the movement in unleaded gas price can be explained by changes in crude oil prices.
3. 97% of the time this forecasting model will correctly predict the price of unleaded gas.
4. the sum of squared residuals is close to 97%.

3. What is the interpretation of coefficient for S&P500?

1. Every 1 unit increase in the value of S&P500 will cause unleaded gas price to decrease by 0.2%.
2. Every 1 unit increase in the value of S&P500 will cause unleaded gas price to decrease by 0.20 cents.
3. Every 1 unit increase in the value of S&P500 will cause unleaded gas price to increase by 0.20 cents.
4. Every 1% increase in the value of S&P500 will cause unleaded gas price to increase by 0.20 cents.

4. The variable which is being forecasted is referred as:

1. independent variable
2. explanatory variable
3. exogenous variable
4. endogenous variable

5. Ideally, in forecasting what kind of correlations should exist between a set of independent variables?

1. correlation less than -1
2. correlation greater than 1
3. high correlation
4. low correlation

6. The R-square of a regression equation of a dependent variable (Y) and a set of independent variables represents:

1. the % forecasted values of the regression model that is above the actual value.
2. the % total error of the forecasting model.
3. the % movements in Y that can be explained by the forecasting model
4. the % of total residuals of the forecasting model.

Answer 1

What will be forecasted price of unleaded gas if the value of independent variables are as follows: Crude Oil = 95; S&P500 = 1775; Price of $ = 0.80 Euros; PDI = 800
=0.5871+95*0.0651+1775*(-0.0020)+0.80*(-0.0415)+800*0.0001=3.2684

What is the interpretation of R-Square?
97% of the movement in unleaded gas price can be explained by this forecasting model.

What is the interpretation of coefficient for S&P500?
Every 1 unit increase in the value of S&P500 will cause unleaded gas price to decrease by 0.20 cents.

The variable which is being forecasted is referred as:
endogenous variable

Ideally, in forecasting what kind of correlations should exist between a set of independent variables?
low correlation

The R-square of a regression equation of a dependent variable (Y) and a set of independent variables represents:
the % movements in Y that can be explained by the forecasting model