Econ Chapters (1-3)

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9. Data on the income of law graduates collected at different times during the same year is_____. a. panel data b. experimental data c. time series data d. cross-sectional data

d

1. Econometrics is the branch of economics that _____. a. studies the behavior of individual economic agents in making economic decisions b. develops and uses statistical methods for estimating economic relationships c. deals with the performance, structure, behavior, and decision-making of an economy as a whole d. applies mathematical methods to represent economic theories and solve economic problems.

b

11. Suppose the variable x2 has been omitted from the following regression 1 is equation, y=β0+β1 x1+β2 x2+u . ~β1 is the estimator obtained when x2 is omitted is said to _____. from the equation. If E( ~β1 a. have an upward bias b. have a downward bias c. be unbiased d. be biased toward zero ) >β1, ~β1

a

13. The term _____ refers to the problem of small sample size. a. micronumerosity b. multicollinearity c. homoskedasticity d. heteroskedasticity

a

3. Which of the following is true of experimental data? a. Experimental data are collected in laboratory environments in the natural sciences. b. Experimental data cannot be collected in a controlled environment. c. Experimental data is sometimes called observational data. d. Experimental data is sometimes called retrospective data.

a

5. The term 'u' in an econometric model is usually referred to as the _____. a. error term b. parameter c. hypothesis d. dependent variable

a

6. If an independent variable in a multiple linear regression model is an exact linear combination of other independent variables, the model suffers from the problem of _____. a. perfect collinearity b. homoskedasticity c. heteroskedasticty d. omitted variable bias

a

8. A data set that consists of a sample of individuals, households, firms, cities, states, countries, or a variety of other units, taken at a given point in time, is called a(n) _____. a. cross-sectional data set b. longitudinal data set c. time series data set d. experimental data set

a

8. Exclusion of a relevant variable from a multiple linear regression model leads to the problem of _____.

a

12. Which of the following refers to panel data? a. Data on the unemployment rate in a country over a 5-year period b. Data on the birth rate, death rate and population growth rate in developing countries over a 10-year period. c. Data on the income of 5 members of a family on a particular year. d. Data on the price of a company's share during a year.

b

13. The error term in a regression equation is said to exhibit homoskedasticty if _____.

b

13. Which of the following is a difference between panel and pooled cross-sectional data? a. A panel data set consists of data on different cross-sectional units over a given period of time while a pooled data set consists of data on the same cross-sectional units over a given period of time. b. A panel data set consists of data on the same cross-sectional units over a given period of time while a pooled data set consists of data on different cross-sectional units over a given period of time c. A panel data consists of data on a single variable measured at a given point in time while a pooled data set consists of data on the same cross-sectional units over a given period of time. d. A panel data set consists of data on a single variable measured at a given point in time while a pooled data set consists of data on more than one variable at a given point in time.

b

14. Find the degrees of freedom in a regression model that has 10 observations and 7 independent variables. a. 17 b. 2 c. 3 d. 4

b

14. In the regression of y on x, the error term exhibits heteroskedasticity if _____. a. it has a constant variance b. Var(y|x) is a function of x c. x is a function of y d. y is a function of x

b

15. Which of the following is true? a. A variable has a causal effect on another variable if both variables increase or decrease simultaneously. b. The notion of 'ceteris paribus' plays an important role in causal analysis. c. Difficulty in inferring causality disappears when studying data at fairly high levels of aggregation. d. The problem of inferring causality arises if experimental data is used for analysis.

b

2. Nonexperimental data is called _____. a. cross-sectional data b. time series data c. observational data d. panel data

b

6. The parameters of an econometric model _____. a. include all unobserved factors affecting the variable being studied b. describe the strength of the relationship between the variable under study and the factors affecting it c. refer to the explanatory variables included in the model d. refer to the predictions that can be made using the model

b

9. If the total sum of squares (SST) in a regression equation is 81, and the residual sum of squares (SSR) is 25, what is the explained sum of squares (SSE)? a. 64 b. 56 c. 32 d. 18

b

1. In the equation, y=β0+β1 x1+β2 x2+u, β2 is a(n) _____. a. independent variable b. dependent variable c. slope parameter d. intercept parameter

c

10. A data set that consists of observations on a variable or several variables over time is called a _____ data set. a. binary b. cross-sectional c. time series d. experimental

c

10. If the residual sum of squares (SSR) in a regression analysis is 66 and the total sum of squares (SST) is equal to 90, what is the value of the coefficient of determination? a. 0.73 b. 0.55 c. 0.27 d. 1.2

c

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

c

12. High (but not perfect) correlation between two or more independent variables is called _____. a. heteroskedasticty b. homoskedasticty c. multicollinearity d. micronumerosity

c

14. _____ has a causal effect on _____. a. Income; unemployment b. Height; health c. Income; consumption d. Age; wage

c

15. The Gauss-Markov theorem will not hold if _____. a. the error term has the same variance given any values of the explanatory variables b. the error term has an expected value of zero given any values of the independent variables c. the independent variables have exact linear relationships among them d. the regression model relies on the method of random sampling for collection of data

c

2. Consider the following regression equation: y=β1+β2 x1+β2 x2+u. What does β1 imply? a. β1 measures the ceteris paribus effect of x1 on x2 b. β1 measures the ceteris paribus effect of y on x1 c. β1 measures the ceteris paribus effect of x1 on y d. β1 measures the ceteris paribus effect of x1 on u

c

2. If a change in variable x causes a change in variable y, variable x is called the _____.

c

4. An empirical analysis relies on _____to test a theory. a. common sense b. ethical considerations c. data d. customs and conventions

c

5. In the equation c = β0 + β1 i + u, c denotes consumption and i denotes income. What is the residual for the 5th observation if c5 a. $975 b. $300 c. $25 d. $50

c

5. The value of R2 always _____. a. lies below 0 b. lies above 1 c. lies between 0 and 1 d. lies between 1 and 1.5

c

6. What does the equation ^y=β^0+^β1 x denote if the regression equation is y = β0 + β1x1 + u? a. The explained sum of squares b. The total sum of squares c. The sample regression function d. The population regression function

c

7. Which of the following is the first step in empirical economic analysis? a. Collection of data b. Statement of hypotheses c. Specification of an econometric model d. Testing of hypotheses

c

7. The assumption that there are no exact linear relationships among the independent variables in a multiple linear regression model fails if _____, where n is the sample size and k is the number of parameters. a. n>2 b. n=k+1 c. n>k d. n<k+1

d

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

d

12. Which of the following is assumed for establishing the unbiasedness of Ordinary Least Square (OLS) estimates? a. The error term has an expected value of 1 given any value of the explanatory variable. b. The regression equation is linear in the explained and explanatory variables. c. The sample outcomes on the explanatory variable are all the same value. d. The error term has the same variance given any value of the explanatory variable.

d

3. If the explained sum of squares is 35 and the total sum of squares is 49, what is the residual sum of squares? a. 10 b. 12 c. 18 d. 14

d

3. In the equation y = a. dependent variable b. independent variable c. slope parameter d. intercept parameter β0 + β1 x + u, β0 is the _____.

d

4. Which of the following is true of R2? a. R2 is also called the standard error of regression. b. A low R2 indicates that the Ordinary Least Squares line fits the data well. c. R2 usually decreases with an increase in the number of independent variables in a regression. d. R2 shows what percentage of the total variation in the dependent variable, Y, is explained by the explanatory variables.

d

7. Consider the following regression model: y = β0 + β1x1 + u. Which of the following is a property of Ordinary Least Square (OLS) estimates of this model and their associated statistics?

d

16. Experimental data are sometimes called retrospective data.

false

17. The key assumption for the general multiple regression model is that all factors in the unobserved error term be correlated with the explanatory variables.

false

17. The sample covariance between the regressors and the Ordinary Least Square (OLS) residuals is always positive.

false

18. A cross-sectional data set consists of observations on a variable or several variables over time.

false

18. The coefficient of determination (R2) decreases when an independent variable is added to a multiple regression model.

false

19. A time series data is also called a longitudinal data set.

false

19. An explanatory variable is said to be exogenous if it is correlated with the error term.

false

19. There are n-1 degrees of freedom in Ordinary Least Square residuals.

false

20. The variance of the slope estimator increases as the error variance decreases.

false

16. A natural measure of the association between two random variables is the correlation coefficient.

true

16. The term "linear" in a multiple linear regression model means that the equation is linear in parameters.

true

17. An economic model consists of mathematical equations that describe various relationships between economic variables.

true

18. R2 is the ratio of the explained variation compared to the total variation.

true

20. A larger error variance makes it difficult to estimate the partial effect of any of the independent variables on the dependent variable.

true

20. The notion of ceteris paribus means "other factors being equal."

true


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