Question Details

A study of expenditures on food in cities 



1.	Using a sample of 100 consumers, a double-log regression model was used to estimate demand for gasoline.  Standard errors of the coefficients appear in the parentheses below the coefficients.

Ln Q = 2.45 -0.67 Ln P + . 45 Ln Y  - .34 Ln Pcars
		(.20)     (.10)        (.25)
	
Where Q is gallons demanded, P is price per gallon, Y is disposable income, and Pcars is a price index for cars.  Based on this information, which is NOT correct?
a.	Gasoline is inelastic.
b.	Gasoline is a normal good.
c.	Cars and gasoline appear to be mild complements.
d.	The coefficient on the price of cars (Pcars) is insignificant.
e.	All of the coefficients are insignificant.

		

2.	In a cross section regression of 48 states, the following linear demand for per-capita cans of soda was found:  Cans = 159.17-102.56 Price + 1.00 Income + 3.94Temp

 	Coefficients	Standard Error	t Stat
Intercept	159.17	94.16	1.69
Price	-102.56	33.25	-3.08
Income	1.00	1.77	0.57
Temperature	3.94	0.82	4.83

	R-Sq = 54.1%     R-Sq(adj) = 51.0%

From the linear regression results in the cans case above, we know that:
a.	Price is insignificant
b.	Income is significant
c.	Temp is significant
d.	As price rises for soda, people tend to drink less of it
e.	All of the coefficients are significant

	


3.	A study of expenditures on food in cities resulting in the following equation:
	Log E = 0.693 Log Y + 0.224 Log N
whereE is Food Expenditures; Y is total expenditures on goods and services; and N is the size of the family. This evidence implies:
a.	that as total expenditures on goods and services rises, food expenditures falls.
b.	that a one-percent increase in family size increases food expenditures .693%.
c.	that a one-percent increase in family size increases food expenditures .224%.
d.	that a one-percent increase in total expenditures increases food expenditures 1%. 
e.	that as family size increases, food expenditures go down.
				

	4.	All of the following are reasons why an association relationship may not imply a causal relationship except:
a.	the association may be due to pure chance
b.	the association may be the result of the influence of a third common factor
c.	both variables may be the cause and the effect at the same time
d.	the association may be hypothetical
e.	both c and d


	


5.		In regression analysis, the existence of a significant pattern in successive values of the error term constitutes:
a.	heteroscedasticity
b.	autocorrelation
c.	multicollinearity
d.	nonlinearities
e.	a simultaneous equation relationship



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