Quantitative Methods for Economics Study Guide Questions
Course Introduction
Quantitative Methods for Economics introduces students to the essential mathematical and statistical tools required for economic analysis. The course covers topics such as linear algebra, calculus, probability theory, and statistical inference, focusing on their applications to economic modeling, estimation, and hypothesis testing. Students will learn to use quantitative techniques to interpret economic data, test economic theories, and solve optimization problems. Emphasis is placed on the use of real-world data sets and the application of software tools to perform econometric analysis, preparing students for advanced study and research in economics.
Recommended Textbook
Practical Econometrics data collection analysis and application 1st Edition by Christiana E. Hilmer
Available Study Resources on Quizplus
15 Chapters
507 Verified Questions
507 Flashcards
Source URL: https://quizplus.com/study-set/3155 Page 2
Chapter 1: An Introduction to Econometrics and Statistical
Inference
Available Study Resources on Quizplus for this Chatper
16 Verified Questions
16 Flashcards
Source URL: https://quizplus.com/quiz/62475
Sample Questions
Q1) What is a sampling distribution? How do you construct one? Why is it important to understand what a sampling distribution is? Explain.
Answer: A sampling distribution is the distribution of a sample statistic,such as the sample mean.It is constructed by drawing every possible sample of size n from the population of size N,calculating the value of a sample statistic for each sample,and placing all of those calculated values in order on a number line.It is important to understand this definition because statistics and hypothesis testing is based on principles learned from our knowledge of what sampling distributions look like.
Q2) A point estimate is
A)typically equal to the population parameter.
B)single valued statistic that is the best guess of a population parameter.
C)an interval that contains the population parameter.
D)computed from the population.
Answer: B
Q3) What is a statistic? A parameter? How are the two related? Explain.
Answer: A statistic is a function that is computed from the sample data.A parameter is a function that exists within the population.A sample statistic serves as a point estimate of the likely value of an unobserved parameter.
To view all questions and flashcards with answers, click on the resource link above. Page 3
Chapter 2: Collection and Management of Data
Available Study Resources on Quizplus for this Chatper
16 Verified Questions
16 Flashcards
Source URL: https://quizplus.com/quiz/62474
Sample Questions
Q1) Suppose you have identified a good question of interest but you cannot locate appropriate data on the internet.What could you do to collect appropriate data? Explain.
Answer: You could perform your own survey using an internet site such as surveymonkey.com.
Q2) Cross-sectional data is data collected
A)for a number of individuals,countries,firms,etc.over many different time periods.
B)for a given individual,country,firm,etc.over many different time periods.
C)for many different individuals,countries,firms,etc.in a given time-period.
D)with replacement.
Answer: B
Q3) Why do we recommend saving one master file while performing calculations in another file? Explain.
Answer: We recommend saving one master file so that if we make a mistake and overwrite or otherwise change our data,we can easily go back and reconstruct our correct data without having to start at square one with our internet search,data downloading,and so on.
To view all questions and flashcards with answers, click on the resource link above. Page 4
Chapter 3: Summary Statistics
Available Study Resources on Quizplus for this Chatper
29 Verified Questions
29 Flashcards
Source URL: https://quizplus.com/quiz/62473
Sample Questions
Q1) The correlation coefficient is generally preferred to the covariance because
A)the correlation coefficient is a unit free measure of linear association.
B)the covariance is bounded to fall between -1 and 1.
C)the correlation coefficient must be positive.
D)the covariance measures the quadratic relationship between two random variables.
Answer: A
Q2) A smaller standard deviation of a distribution indicates that
A)the observations in a data set are closer together.
B)the observations in a data set are farther apart.
C)a smaller mean.
D)the mean and median are closer together.
Answer: A
Q3) A scatter diagram is potentially valuable because it
A)visually depicts the relationship between two variables.
B)visually depicts the median of the sample.
C)visually depicts the standard deviation of the sample.
D)visually depicts the distribution of a variable.
Answer: A
To view all questions and flashcards with answers, click on the resource link above.
5
Chapter 4: Simple Linear Regression
Available Study Resources on Quizplus for this Chatper
44 Verified Questions
44 Flashcards
Source URL: https://quizplus.com/quiz/62472
Sample Questions
Q1) Suppose you determine the estimated sample regression function to be \(\hat { y } _ { i } = 1,016.82 + 473.65 \cdot x _ { i } \text {. }\)
You would conclude that
A)y<sub>i</sub> is estimated to equal 473.65 when x<sub>i</sub> = 0.
B)y<sub>i</sub> is estimated to increase by 473.65 for every one unit increase in x<sub>i</sub>.
C)y<sub>i</sub> is estimated to decrease by 473.65 for every one unit increase in x<sub>i</sub>.
D)y<sub>i</sub> is estimated to increase by 1,016.82 for every one unit increase in x<sub>i</sub>.
Q2) What is the goal of linear regression analysis? Explain.
Q3) In simple linear regression analysis,the independent variable is
A)the variable that changes in response to changes in an independent variable. B)the variable whose changes affect the dependent variable.
C)the left-hand side variable.
D)can be either variable.
Q4) Why is an error term included in the estimated sample regression function? What factors does this term include? Explain.
Q5) Why does Ordinary Least Squares (OLS)produce the "best-fit" line? Explain.
To view all questions and flashcards with answers, click on the resource link above. Page 6
Chapter 5: Hypothesis Testing in Linear Regression Analysis
Available Study Resources on Quizplus for this Chatper
34 Verified Questions
34 Flashcards
Source URL: https://quizplus.com/quiz/62471
Sample Questions
Q1) What is the intuition behind the confidence interval method of hypothesis testing? Explain.
Q2) The <i>t</i>-statistic for the individual significance of the estimated slope coefficient\(\hat { \beta } _ { 1 }\)Is
A)the standard error of the estimated slope coefficient.
B)the estimated slope coefficient.
C)the ratio of the estimated slope coefficient to the standard error of the estimated slope coefficient.
D)the ratio of the estimated slope coefficient to the variance of the estimated slope coefficient.
Q3) A standard error is
A)the variance of the sampling distribution.
B)the standard deviation of the population distribution.
C)the standard deviation of the sampling distribution.
D)the variance of the population distribution.
Q4) Why is hypothesis testing is necessary? Explain.
Q5) Why are each of the individual simple linear regression model assumptions important? Explain.
Q6) What is a sampling distribution? Why is it important? Explain.
Page 7
To view all questions and flashcards with answers, click on the resource link above.
Chapter 6: Multiple Linear Regression Analysis
Available Study Resources on Quizplus for this Chatper
44 Verified Questions
44 Flashcards
Source URL: https://quizplus.com/quiz/62470
Sample Questions
Q1) Chow tests are used to determine whether
A)an estimated slope coefficient is different for different subsamples of the data.
B)a subset of independent variables is jointly significant.
C)estimated sample regression functions are different for two different subsamples of the data.
D)a subset of estimated slope coefficients is jointly significant for two different subsamples of the data.
Q2) How do you perform a test of the joint significance of a subset of slope coefficients? What are the null and alternative hypothesis for this test? What is the rejection rule? What is the intuition for why the test works? Explain.
Q3) Based on the estimates in Figure 6.2,you should conclude that,holding all other independent variables constant,each additional family member is estimated to be associated with
A)a statistically significant decrease of 0.093 cigarettes smoked per day.
B)a statistically insignificant decrease of 0.093 cigarettes smoked per day.
C)a statistically significant increase of 0.093 cigarettes smoked per day.
D)a statistically insignificant increase of 0.093 cigarettes smoked per day.
Q4) Why is multiple linear regression analysis such a valuable tool? Explain.
To view all questions and flashcards with answers, click on the resource link above.
Page 8
Chapter 7: Qualitative Variables and Non-Linearities in
Multiple Linear Regression Analysis
Available Study Resources on Quizplus for this Chatper
40 Verified Questions
40 Flashcards
Source URL: https://quizplus.com/quiz/62469
Sample Questions
Q1) Suppose you estimate the sample regression function \[\log ( \text { Solar } \widehat {Syst}em \text { Sales} ) = 108,632.47 - 3.78 \cdot \log ( \text { Solar System Tax Rate } )\]
You should conclude that a A)$1 increase in the solar system tax rate is associated with 3.78 fewer solar system sales.
B)1 percent increase in the solar system tax rate is associated with a 3.78 percent decrease in solar system sales.
C)1 percent increase in the solar system tax rate is associated with 3.78 fewer solar system sales.
D)$1 increase in the solar system tax rate is associated with a 3.78 percent decrease in solar system sales.
Q2) Suppose you estimate the sample multiple linear regression function \(\hat { y } _ { i } = \hat { \beta } _ { 0 } + \hat { \beta } _ { 1 } x _ { 1 i } + \hat { \beta } _ { 2 } x _ { 2 i } + \hat { \beta } _ { 3 } x _ { 1 i } \cdot x _ { 2 i }\) . What is the estimated marginal effect of x<sub>1</sub>? x<sub>2</sub>? Explain.
To view all questions and flashcards with answers, click on the resource link above. Page 9
Chapter 8: Model Selection in Multiple Linear Regression Analysis
Available Study Resources on Quizplus for this Chatper
31 Verified Questions
31 Flashcards
Source URL: https://quizplus.com/quiz/62468
Sample Questions
Q1) Suppose that you estimate the regression function \(\text { Stock Price } _ { i } = \beta _ { 0 } + \beta _ { 1 } \text { Wealth } _ { i } + \beta _ { 2 } \text { Earnings } _ { i } + \beta _ { 3 } \text { Rainfall } _ { i } + \varepsilon _ { i }\)
You might be concerned that \(\hat { \beta } _ { 2 }\)
May have a large standard error because
A)investor wealth is likely an irrelevant independent variable.
B)the amount of rainfall is likely an irrelevant independent variable.
C)investor wealth is likely measured with error.
D)the first letter in the firm's name is likely an omitted variable.
Q2) One can deal with missing data by
A)dropping observations with missing data if the missing data is random and therefore will not affect the resulting coefficient estimates.
B)making up values for missing data.
C)ignoring the potential impact of the missing data in the analysis.
D)running a regression with the number 6 put in lieu of the missing data.
Q3) What is omitted variable bias? Why is it a problem? How do you try to prevent it? Explain.
To view all questions and flashcards with answers, click on the resource link above.
Page 10
Chapter 9: Heteroskedasticity
Available Study Resources on Quizplus for this Chatper
39 Verified Questions
39 Flashcards
Source URL: https://quizplus.com/quiz/62467
Sample Questions
Q1) Weighted Least Squares is performed by
A)re-weighting the estimated standard errors from the OLS regression.
B)re-weighting the estimated slope coefficients from the OLS regression.
C)including the command ",robust" in the estimation.
D)re-weighting the original data so that OLS provides estimated standard errors with minimum variance.
Q2) The second step in the Breusch-Pagan test is to regress the
A)residuals on the independent variables from the original OLS regression.
B)squared residuals on the residuals from the original OLS regression.
C)squared residuals on the independent variables from the original OLS regression.
D)residuals on the squared residuals from the original OLS regression.
Q3) Why are White's heteroskedastic consistent standard errors the preferred method for dealing with potential heteroskedasticity? Explain.
Q4) The null hypothesis for the Goldfeld-Quandt test is
A) \(H _ { 0 } : U S S _ { 2 } / U S S _ { 1 } = 0\)
B) \(H _ { 0 } : U S S _ { 2 } / U S S _ { 1 } \neq 0\)
C) \(H _ { 0 } : U S S _ { 2 } / U S S _ { 1 } = 1\)
D) \(H _ { 0 } : U S S _ { 2 } / U S S _ { 1 } \neq 1\)
Q5) How do you perform Weighted Least Squares? Why should it work? Explain.
To view all questions and flashcards with answers, click on the resource link above. Page 11
Chapter 10: Time Series Analysis
Available Study Resources on Quizplus for this Chatper
38 Verified Questions
38 Flashcards
Source URL: https://quizplus.com/quiz/62466
Sample Questions
Q1) You can control for quarterly seasonality in your data by
A)de-trending your time-series data.
B)including a time-trend in your regression.
C)including binary dummy variables for all four quarters in your regression.
D)including binary dummy variables for three of the four quarters in your regression.
Q2) A weakly dependent time series is one for which
A)the observations for a given variable become more closely related over time.
B)the probability of distribution of the dependent variable changes over time.
C)the probability of distribution of the dependent variable does not changes over time.
D)the observations for a given variable become less closely related over time.
Q3) What does it mean to de-trend your data? How can you do so? Explain.
Q4) You can control for a potential time-trend in your data by
A)not including spuriously correlated variables in your regression.
B)including dummy variables for three of the four quarters in your regression.
C)de-trending the data before performing OLS.
D)performing weighted least squares by diving the initial data by the estimate coefficient on the time-trend variable.
To view all questions and flashcards with answers, click on the resource link above.
12
Chapter 11: Auto-Correlation
Available Study Resources on Quizplus for this Chatper
50 Verified Questions
50 Flashcards
Source URL: https://quizplus.com/quiz/62465
Sample Questions
Q1) A simple method for determining whether autocorrelation is present in a given data set is to
A)construct a histogram.
B)calculate the variance of the sample.
C)examine the residual plot.
D)plot the data points from smallest to largest.
Q2) Iterations in the Cochrane-Orcutt method for AR(1)should be continued until
A) \(\hat { \rho } = 0 .\)
B) \(\hat { \rho } = \rho .\)
C) \(\hat { \rho }\) changes by .05 between iterations.
D) \(\hat { \rho }\) is stable between iterations.
Q3) What is the intuition behind the Regression test for AR(1)? Explain.
Q4) The second iteration of the Cochrane-Orcutt method for AR(1)involves
A)repeating the process in the first iteration for the data adjusted by \(\hat { \rho } _ { 1 }\) and \(\hat { \rho } _ { 2 }\) .
B)repeating the process in the first iteration for the data adjusted by \(\hat { \rho }\) .
C)re-estimating \(\hat { \rho }\) following the process in the first iteration.
D)re-estimating \(\hat { \rho }\) using the data lagged one period.
Q5) What is a unit root? Why is it problematic? Explain.
To view all questions and flashcards with answers, click on the resource link above. Page 13
Chapter 12: Limited Dependent Variables
Available Study Resources on Quizplus for this Chatper
40 Verified Questions
40 Flashcards
Source URL: https://quizplus.com/quiz/62464
Sample Questions
Q1) What do the coefficient estimates from the multinomial logit model represent? What do you need to do to determine true estimated marginal effects? Explain.
Q2) What is a categorical dependent variable? Why does it present a challenge to estimating the population multiple linear regression model by OLS? Explain.
Q3) The assumption required for the multinomial logit to be the most-preferred estimator for categorical dependent variables is referred to as
A)multinomial logit theorem.
B)independence of relevant alternatives.
C)independence of irrelevant alternatives.
D)dependence of irrelevant alternatives.
Q4) When using the logit model,estimated marginal effects are obtained by
A)estimating the model by the logit function.
B)estimating the model by OLS.
C)taking the derivative of the estimated coefficients.
D)converting the estimated coefficients into marginal effects by taking the derivative of the logit function with respect to the indepdendent variable.
Q5) What is a multinomial logit model? Why is it more appropriate than OLS? Explain.
To view all questions and flashcards with answers, click on the resource link above.
Page 14
Chapter 13: Panel Data
Available Study Resources on Quizplus for this Chatper
31 Verified Questions
31 Flashcards
Source URL: https://quizplus.com/quiz/62463
Sample Questions
Q1) Random-effects models are more appropriate than fixed-effects models when
A)the time invariant component of the error term is not correlated with one or more the independent variables.
B)dealing with panel data.
C)the error term is random.
D)the intercept is not constant.
Q2) Treating each data point in panel data as an individual observation and not accounting for the fact that individuals are observed over many time periods is referred to as estimating a ____ model.
A)static time-series
B)heteroskedastic consistent
C)pooled cross-section
D)fixed-effects
Q3) Fixed-effects models are more appropriate than random-effects models when A)the error terms are autocorrelated.
B)the independent variables are constant over time.
C)the time invariant component of the error term is correlated with any of the independent variables.
D)the error term is not constant.
To view all questions and flashcards with answers, click on the resource link above.
Page 15
Chapter 14: Instrumental Variables for Simultaneous
Equations, Endogenous Independent Variables, and
Measurement Error
Available Study Resources on Quizplus for this Chatper
26 Verified Questions
26 Flashcards
Source URL: https://quizplus.com/quiz/62462
Sample Questions
Q1) Simultaneous equations present a challenge because OLS estimates
A)do not properly weight the data for the undue influence of outliers.
B)do not account for the autoregressive structure of the error term.
C)treat the dependent variable as a continuous variable.
D)are biased because one or more right hand side variables from each equation are correlated with the error term due to the equations being jointly determined.
Q2) Endogeneity of an independent variable occurs when
A)an independent variable is correlated with the dependent variable.
B)an independent variable is correlated with the error term.
C)the dependent variable is correlated with the error term.
D)the dependent variable is correlated with an independent variable.
Q3) Two-stage least squares can be used to
A)control for heteroskedasticity.
B)control for measurement error in an independent variable.
C)deal with limited dependent variables.
D)account for the time-invariant component of the error term.
Q4) What are endogenous independent variables? How can instrumental variables be used to control for endogenous independent variables? Why? Explain.
To view all questions and flashcards with answers, click on the resource link above. Page 16
Chapter 15: Quantile Regression, Count Data, Sample
Selection Bias, and Quasi-Experimental Methods
Available Study Resources on Quizplus for this Chatper
29 Verified Questions
29 Flashcards
Source URL: https://quizplus.com/quiz/62461
Sample Questions
Q1) Sample-selection bias occurs when
A)the researcher selects a bad sample.
B)the sample contains an independent variable that is correlated with the error term.
C)individuals randomly select the sample to which they belong.
D)individuals non-randomly select themselves into a given outcome of the dependent variable.
Q2) You can choose between the Poisson and the Negative Binomial models by performing a A)test of over-dispersion.
B)Poisson choice test.
C)Negative Binomial test.
D)test of overall significance of the Poisson model.
Q3) Non-negative count data presents a challenge because OLS estimates
A)are biased.
B)cannot be calculated.
C)are heteroskedastic.
D)are the BLUE.
Q4) What is quantile regression? When might it be preferred to OLS? Explain.
Page 17
To view all questions and flashcards with answers, click on the resource link above.