Reference no: EM13246096
1. 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
2. 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
3. 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. autocorrelation
b. a simultaneous equation relationship
c. nonlinearities
d. heteroscedasticity
e. multicollinearity
4. When using a multiplicative power function (Y = a X1b1 X2b2 X3b3) to represent an economic relationship, estimates of the parameters (a, b's) using linear regression analysis can be obtained by first applying a ___________ transformation to convert the function to a linear relationship.
a. semilogarithmic
b. double-logarithmic
c. reciprocal
d. polynomial
e. cubic
5. The correlation coefficient ranges in value between 0.0 and 1.0.
a. true
b. false
6. The coefficient of determination ranges in value between 0.0 and 1.0.
a. true
b. false
7. The coefficient of determination measures the proportion of the variation in the independent variable that is "explained" by the regression line.
a. true
b. false
8. The presence of association between two variables does not necessarily imply causation for the following reason(s):
a. the association between two variables may result simply from pure chance
b. the association between two variables 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. a and b
e. a, b, and c
9. The estimated slope coefficient (b) of the regression equation (Y = a + bX) measures the _____________ change in Y for a one _______ change in X.
a. percentage, unit
b. percentage, percent
c. unit, unit
d. unit, percent
e. none of the above
10. The standard deviation of the error terms in an estimated regression equation is known as:
a. coefficient of determination
b. correlation coefficient
c. Durbin-Watson statistic
d. standard error of the estimate
e. none of the above
11. In testing whether each of the independent variables (Xs) in a multiple regression equation is statistically significant in explaining the dependent variable (Y), one uses the:
a. F-test
b. Durbin-Watson test
c. t-test
d. z-test
e. none of the above
12. One commonly used test in checking for the presence of autocorrelation when working with time series data is the _______________.
a. F-test
b. Durbin-Watson test
c. t-test
d. z-test
e. none of the above
13. The method which generally provides more complete information in estimating demand is:
a. the consumer survey
b. market experimentation
c. a statistical demand analysis
d. the consumer clinic
e. the barometric method
14. Demand functions in the multiplicative form are most common for all of the following reasons except:
a. elasticities are constant over a range of data
b. ease of estimation
c. exponents of parameters are the elasticities of those variables
d. marginal impact of a unit change in an individual variable is constant
15. 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
c. the negative slope of the demand function
d. the simultaneous relationship between the demand and supply functions
e. none of the above
16. Consider the following linear demand function where QD = quantity demanded, P = selling price, and Y = disposable income:
QD = -36 -2.1P + .24Y
The coefficient of P (i.e., -2.1) indicates that (all other things being held constant):
a. for a one percent increase in price, quantity demanded would decline by 2.1 percent
b. for a one unit increase in price, quantity demanded would decline by 2.1 units
c. for a one percent increase in price, quantity demanded would decline by 2.1 units
d. for a one unit increase in price, quantity demanded would decline by 2.1 percent
e. none of the above
17. Consider the following multiplicative demand function where QD = quantity demanded, P = selling price, and Y = disposable income:
QD = 1.6 P-1.5 Y.2
The coefficient of Y (i.e., .2) indicates that (all other things being held constant):
a. for a one percent increase in disposable income, quantity demanded would increase by .2 percent
b. for a one unit increase in disposable income, quantity demanded would increase by .2 units
c. for a one percent increase in disposable income quantity demanded would increase by .2 units
d. for a one unit increase in disposable income, quantity demanded would increase by .2 percent
e. none of the above
18. 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
19. 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
20. In a _____________ demand function involving price as one of the explanatory variables, the point price elasticity is a function of the values of these explanatory variables.
a. linear
b. multiplicative
c. a and b
d. none of the above