Question Details

When there is multi collinearity in an estimated regression 


1.	One shortcoming of the use of ____ in demand analysis is that the participants are generally aware that their actions are being observed and hence they may seek to act in a manner somewhat different than normal.
a.	market experiments
b.	consumer clinics
c.	statistical (econometric) methods
d.	a and b
e.	none of the above


	

	2.	The constant or intercept term in a statistical demand study represents the quantity demanded when all independent variables are equal to:
a.	1.0
b.	their minimum values
c.	their average values
d.	0.0
e.	none of the above


	

	
3.	Novo Nordisk A/S, a Danish firm, sells insulin and other drugs worldwide.Activella, an estrogen and progestin hormone replacement therapy sold by Novo-Nordisk, is examined using 33 quarters of data
Y = -204 + . 34X1 - .17X2
		        (17.0)     (-1.71)
Where Y is quarterly sales of Activella, X1 is the Novo- advertising of the hormone therapy, and X2 is advertising of a similar product by Eli Lilly and Company, Novo-Nordisk- chief competitor. The parentheses contain t-values. Addition information is: Durbin-Watson = 1.9 and R2 = .89.

Using the data for Novo-Nordisk, which is correct?
a.	Both X1 and X2 are statistically significant.
b.	Neither X1 nor X2 are statistically significant.
c.	X1 is statistically significant but X2 is not statistically significant.
d.	X1 is not statistically significant but X2 is statistically significant.
e.	The Durbin-Watson statistic shows significant problems with autocorrelation

		

4.	In which of the following econometric problems do we find Durbin-Watson statistic being far away from 2.0?
a.	the identification problem
b.	autocorrelation
c.	multicollinearity
d.	heteroscedasticity
e.	agency problems

	

5.	When there is multi collinearity in an estimated regression equation,
	a.	the coefficients are likely to be small.
	b.	the t statistics are likely to be small even though the R2 is large.
	c.	the coefficient of determination is likely to be small.
	d.	the problem of omitted variables is likely.
	e.	the error terms will tend to have a cyclical pattern.

6.	When two or more "independent" variables are highly correlated, then we have:
a.	the identification problem
b.	multicollinearity
c.	autocorrelation
d.	heteroscedasticity
e.	complementary products


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