ECON 5370 EXAM 2: CHAPTER 4, 5, & 6. Built around real course units and objectives!

ECON 5370 EXAM 2: CHAPTER 4, 5, & 6.
Built around real course units and objectives!
Question 1
In a regression equation, one may measure the accuracy of the estimation by:
a. Estimating the standard deviation of the errors of prediction
b. Calculating the standard deviation of the errors of prediction
c. All of the above
d. Calculating the standard error of the estimate
e. A and b only (b and d only) - answer: e: a and b only (calculating the standard deviation
of the errors of prediction & calculating the standard error of the estimate)


Question 2
In addition to prediction, one purpose of regression analysis is:
a. To measure the overall "fit" of the model to the sample observations
b. To test whether the slope parameter β is equal to some particular value
c. To test whether the slope parameter β is equal to zero
d. B and c
e. None of the above - answer: d:b and c (to test whether the slope parameter β is equal to
some particular value
& to test whether the slope parameter β is equal to zero)


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


Question 4
Appendix:
in regression analysis, the existence of a high degree of intercorrelation among some or all
of the explanatory variables in the regression equation constitutes:
a. A simultaneous equation relationship
b. Heteroscedasticity
c. Multicollinearity
d. Nonlinearities
e. Autocorrelation - answer: c: multicollinearity


Question 5
Appendix:
In regression analysis, the existence of a significant pattern in successive values of the
error term constitutes:
a. Autocorrelation
b. Nonlinearities
c. Multicollinearity
d. A simultaneous equation relationship
e. Heteroscedasticity - answer: a: autocorrelation


Question 6
Appendix:
The identification problem in the development of a demand function is a result of:
a. The variance of the demand elasticity
b. The consistency of quantity demanded at any given point

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, c. The negative slope of the demand function
d. The simultaneous relationship between the demand and supply functions
e. None of the above - answer: d: the simultaneous relationship between the demand and
supply functions


Question 7
Appendix:
When two or more "independent" variables are highly correlated, then we have:
a. The identification problem
b. Complementary products
c. Heteroscedasticity
d. Autocorrelation
e. Multicollinearity - answer: e: multicollinearity


Question 8
Appendix:
When using a multiplicative power function (y = a x1b1x2b2x3b3) to represent an economic
relationship, estimates of the parameters (a, and the b's) using linear regression analysis
can be obtained by first applying a ____ transformation to convert the function to a linear
relationship.
a. Reciprocal
b. Double-logarithmic
c. Cubic
d. Semilogarithmic
e. Polynomial - answer: b: double-logarithmic


Question 9
Caution must be exercised in using regression models for prediction when:



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