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Test Bank Introduction to Econometrics 3rd Edition Complete

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Test Bank Introduction to EconomTest Bank Introduction to Econometrics 3rd Edition Complete . We know from Table 2.2 that Pr (Y  0)  0 22, Pr (Y 1) 0 78, Pr (X  0)  0 30, Pr (X 1) 0 70. So (a) ( ) 0 Pr ( 0) 1 Pr ( 1) 0 0 22 1 0 78 0 78, ( ) 0 Pr ( 0) 1 Pr ( 1) 0 0 30 1 0 70 0 70 Y X E Y Y Y E X X X                                  (b) 2 2 2 2 2 2 2 2 2 2 2 2 [( ) ] (0 0.70) Pr ( 0) (1 0.70) Pr ( 1) ( 0 70) 0 30 0 30 0 70 0 21, [( ) ] (0 0.78) Pr ( 0) (1 0.78) Pr ( 1) ( 0 78) 0 22 0 22 0 78 0 1716 X X Y Y E X X X E Y Y Y                                                Solutions to End-of-Chapter Exercises 3 ©2011 Pearson Education, Inc. Publishing as Addison Wesley (c) cov ( , ) [( )( )] (0 0.70)(0 0.78) Pr( 0, 0) (0 0 70)(1 0 78) Pr ( 0 1) (1 0 70)(0 0 78) Pr ( 1 0) (1 0 70)(1 0 78) Pr ( 1 1) ( 0 70) ( 0 78) 0 15 ( 0 70) 0 22 0 15 0 30 ( 0 78) 0 07 0 XY X Y E X X Y Y X Y X Y X Y X Y                                                             0 084,       0 084 corr ( , ) 0 4425 XY X Y X Y             2.3. For the two new random variables W  3  6X and V  20  7Y, we have: (a) ( ) (20 7 ) 20 7 ( ) 54, ( ) (3 6 ) 3 6 ( ) 3 6 0 70 7 2 E V E Y E Y E W E X E X                      (b) 2 2 2 2 2 2 var (3 6 ) 6 36 0 21 7 56, var (20 7 ) ( 7) W X V Y X Y                         (c) WV  cov (3 6X, 20 7 )Y  6 ( 7) cov (X Y, )  42 0 084    corr ( , ) 0 4425 WV W V W V               2.4. (a) 3 3 3 E X( )  0 (1 p) 1  p  p (b) ( ) 0 (1 ) 1 k k k E X    p   p  p (c) E X( )  0.3 , and var(X) = E(X 2 )−[E(X)]2 = 0.3 −0.09 = 0.21. Thus = 0.21= 0.46. 2 2 var (X)  E X( ) [E X( )]  0.30.09 0.21  0.21 0.46. To compute the skewness, use the formula from exercise 2.21: 3 3 2 3 2 3 ( ) ( ) 3[ ( )][ ( )] 2[ ( )] 0.3 3 0.3 2 0.3 0.084 E X    E X  E X E X  E X       Alternatively, 3 3 3 E X(  ) [(10.3) 0.3][(00.3) 0.7] 0.084 Thus, skewness 3 3 3  E X(  ) /  etrics 3rd Edition Complete

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,Test Bank –Introductory Econometrics: A ModernApproach, 5thEditionby Jeffrey M. Wooldridge
v v v v v v v v v v v v




With PERFECT SOLUTION AVAILABLE OF ALL CHAPTERS
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Chapter 1 v




1. Econometrics is the branch of economics that . v v v v v v v




a. studiesthe behavior of individual economic agents inmaking economic decisions
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b. developsand uses statistical methods for estimatingeconomic relationships
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c. dealswith the performance, structure, behavior, and decision-making of an economy as a whole
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d. appliesmathematicalmethods to represent economictheories andsolve economic problems.
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Econometrics is based on the development of statistical v v v v v v v




methods for estimating economic relationships, testing
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economic theories, evaluating government and business
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policies.
v




2. Nonexperimental data is called . v v v v




a. cross-sectional data v




b. time series data
v v




c. observational data v




d. panel data v




3. Which of the following is true of experimental data?
v v v v v v v v




a. Experimentaldata arecollected inlaboratory environments inthe natural sciences. v v v v v v v v v v




b. Experimentaldata cannot be collected in a controlled environment. v v v v v v v v




c. Experimentaldatais sometimes calledobservational data. v v v v v v




d. Experimentaldata is sometimes called retrospective data. v v v v v v




4. An empirical analysis relies on
v v v v v to test a theory.
v v v




a. common sense v




b. ethical considerations v




c. data
d. customs and conventions v v




5. The term ‘u’ in an econometric model is usually referred to as the
v v v v v v v v v v v v v .
a. error term v




b. parameter
c. hypothesis
d. dependentvariable v




6. The parameters of an econometric model
v . v v v v v




a. include allunobserved factors affectingthevariable being studied
v v v v v v v v

,b. describe the strength of the relationship between the variable under study and the factors affecting it
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c. refer to the explanatory variables included in the model
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d. refer to the predictions that can be made using the model
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7. Which of the following is the first step in empirical economic analysis?
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a. Collectionof data v v




b. Statement of hypotheses v v




c. Specification of an econometric model v v v v




d. Testingof hypotheses v v




8. A data set that consists of a sample of individuals, households, firms, cities, states, countries, or a
v v v v v v v v v v v v v v v v




variety of other units, taken at a given point in time, is called a(n)
v v v . v v v v v v v v v v v v




a. cross-sectional data set v v




b. longitudinal data set v v




c. time series data set
v v v




d. experimental data set v v




9. Data on the income of law graduates collected at different times during the same year is
v v v v v v v v v v v v v v v .
a. panel data v




b. experimentaldata v




c. time series data
v v




d. cross-sectional data v




10. A data set that consists of observations on a variable or several variables over time is called a data
v v v v v v v v v v v v v v v v v v




set.
v




a. binary
b. cross-sectional
c. time series v




d. experimental

11. Which of the following is an example of time series data?
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a. Data on the unemployment rates in different parts of a country during a year.
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b. Data on the consumption of wheat by 200 households during a year.
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c. Data on the gross domestic product of a country over a period of 10 years.
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d. Dataon the number of vacancies in various departments of an organization on a particular month.
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12. Which of the following refers to panel data?
v v v v v v v




a. Data on the unemployment rate in a country over a 5-year period
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b. Data on the birth rate, death rate and population growth rate in developing countries over a 10- year
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period.
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c. Data on the income of 5 members of a family on a particular year.
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d. Dataon the price of a company’s share during a year.
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, 13. Which of the following is a difference between panel and pooled cross-sectional data?
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a. A panel data set consists of data on different cross-sectional units over a given period of time while a
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pooled data set consists of data on the same cross-sectional units over a given period of time.
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b. A panel data set consists of data on the same cross-sectional units over a given period of time while a
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pooled data set consists of data on different cross-sectional units over a given period of time
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c. A panel data consists of data on a single variable measured at a given point in time while a pooled data
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set consists of data on the same cross-sectional units over a given period of time.
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d. A panel data set consists of data on a single variable measured at a given point intime while a pooled data
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set consists of data on more than one variable at a given point in time.
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14. has a causal effect on v v v v v .
a. Income; unemployment v




b. Height; health v




c. Income;consumption v




d. Age; wage v




15. Which of the following is true? v v v v v




a. A variable has a causal effect on another variable if both variables increase or decrease
v v v v v v v v v v v v v v




simultaneously.
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b. Thenotion of ‘ceteris paribus’ plays animportant role incausal analysis.
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c. Difficultyin inferring causality disappears when studying data at fairly high levelsof aggregation.
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d. Theproblem of inferring causality arises if experimental data is used for analysis.
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16. Experimentaldata aresometimes called retrospective data. F v v v v v v v




17. An economic model consists of mathematical equations that describe various relationships between
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economic variables. T
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18. A cross-sectional data set consists ofobservations on a variable or severalvariables over time. F
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19. A time series data is also called a longitudinal data set. T
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20. The notion of ceteris paribus means “other factors being equal.” T
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Chapter 2 v




1. A dependent variable is also known as a(n)
v v v v v v v v .
a. explanatory variable v




b. control variable v




c. predictor variable v




d. response variable v
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