Sample Questions and Answers
In econometrics, “endogeneity” can arise from:
A) Simultaneous causality between the dependent and independent variables
B) The error term being normally distributed
C) The presence of multicollinearity
D) The use of random sampling
Answer: A
The “cointegration” test is useful when:
A) Both variables are non-stationary but share a common long-term trend
B) The error term exhibits autocorrelation
C) There is multicollinearity among the independent variables
D) The dependent variable is heteroscedastic
Answer: A
The “Lagrange Multiplier test” (LM test) is used to:
A) Test for heteroscedasticity
B) Test for autocorrelation in the residuals
C) Test for the presence of endogeneity
D) Test for the normality of the error terms
Answer: B
A “two-stage least squares” (2SLS) regression is used primarily to:
A) Estimate models with heteroscedastic errors
B) Address issues of endogeneity by using instrumental variables
C) Test for autocorrelation in panel data
D) Estimate models with time-series data
Answer: B
Which of the following tests is used to detect “heteroscedasticity” in a regression model?
A) Breusch-Pagan test
B) Jarque-Bera test
C) F-test
D) Durbin-Watson test
Answer: A
The “Chow test” is used to test:
A) Whether two or more regression models can be pooled together
B) The normality of residuals in a regression model
C) Whether the coefficients of a regression model are statistically significant
D) The presence of multicollinearity in the independent variables
Answer: A
“Granger causality” in time-series analysis is used to determine:
A) Whether a time-series is stationary
B) Whether one variable can predict another variable over time
C) Whether two time series are highly correlated
D) The presence of autocorrelation in the error terms
Answer: B
In the context of econometrics, “heteroscedasticity” refers to:
A) The presence of non-stationarity in the time series
B) The situation where the variance of the error term changes across observations
C) The correlation between two independent variables
D) The problem of endogeneity in the regression model
Answer: B
The “instrumental variable” (IV) method is used to:
A) Correct for heteroscedasticity in the model
B) Estimate the coefficients in the presence of endogeneity
C) Detect multicollinearity in the independent variables
D) Test the validity of the regression model
Answer: B
“Panel data” refers to:
A) Data collected at a single point in time across multiple entities
B) Data collected over multiple time periods for a single entity
C) Data collected across multiple time periods and entities
D) Data collected without any time dimension
Answer: C
A “stationary” time series is one where:
A) The mean and variance are constant over time
B) The values of the series are predictable
C) The time series exhibits autocorrelation
D) The variance of the error term increases over time
Answer: A
The “Akaike Information Criterion” (AIC) is used to:
A) Estimate the coefficients of the model
B) Test the validity of the regression model
C) Compare different models based on their likelihood and number of parameters
D) Test for heteroscedasticity
Answer: C
The “heteroscedasticity-robust standard errors” are used to:
A) Correct for heteroscedasticity when it is present in the error terms
B) Correct for autocorrelation in the residuals
C) Estimate the coefficients in the presence of endogeneity
D) Test for multicollinearity among the independent variables
Answer: A
The “Hansen J test” is used to:
A) Test the validity of the instrumental variables
B) Check for multicollinearity in the model
C) Test for normality in the residuals
D) Test for autocorrelation in the residuals
Answer: A
In the context of time-series data, “unit root” refers to:
A) A trend that makes a series predictable
B) A form of autocorrelation in the residuals
C) A property of a series that makes it non-stationary
D) A type of heteroscedasticity
Answer: C
The “Generalized Method of Moments” (GMM) is primarily used to:
A) Estimate coefficients in models with heteroscedastic errors
B) Estimate models with endogenous variables using instrumental variables
C) Correct for serial correlation in time-series data
D) Test for multicollinearity in panel data
Answer: B
In a regression model, the “error term” represents:
A) The relationship between the dependent and independent variables
B) The part of the dependent variable not explained by the independent variables
C) The degree of autocorrelation in the data
D) The effect of measurement errors in the variables
Answer: B
The “Durbin-Watson statistic” can take values between:
A) -1 and 1
B) 0 and 1
C) 0 and 4
D) -∞ and ∞
Answer: C
In econometrics, “heteroscedasticity” implies:
A) The residuals are not independent
B) The variance of the error terms is constant
C) The variance of the error terms varies across observations
D) The dependent variable is normally distributed
Answer: C
The “R-squared” in a regression model indicates:
A) The strength of the relationship between independent variables
B) The proportion of the variance in the dependent variable explained by the independent variables
C) The standard error of the regression
D) The significance of the model
Answer: B
The “normality assumption” in linear regression implies:
A) The dependent variable follows a normal distribution
B) The independent variables are normally distributed
C) The residuals of the regression model should be normally distributed
D) The error term should have a uniform distribution
Answer: C
The “simultaneous equations bias” occurs when:
A) The model has multicollinearity
B) The dependent variable is correlated with the error term
C) The residuals are heteroscedastic
D) The instrumental variables are weak
Answer: B
In the context of panel data, the “random effects” model assumes:
A) The individual effects are correlated with the independent variables
B) The individual effects are uncorrelated with the independent variables
C) The time periods are not related to the entities
D) There is no need to account for individual differences
Answer: B
The “heteroscedasticity-consistent” standard errors are useful for:
A) Correcting for autocorrelation
B) Correcting for heteroscedasticity when it is present in the model
C) Estimating coefficients in the presence of endogeneity
D) Estimating model parameters in the absence of multicollinearity
Answer: B
The “multicollinearity” problem is most severe when:
A) The variance of the residuals is constant
B) The independent variables are highly correlated with each other
C) The model includes too few independent variables
D) The dependent variable is binary
Answer: B
The “Granger causality test” helps determine:
A) Whether a relationship between two variables is statistically significant
B) Whether one time series can predict another
C) Whether the error terms in a regression model are independent
D) Whether a regression model is correctly specified
Answer: B
The “cross-sectional data” refers to:
A) Data collected from the same entities over multiple time periods
B) Data collected from multiple entities at a single point in time
C) Data collected over multiple time periods for a single entity
D) Data collected over time with a focus on the time dimension
Answer: B
The “Breusch-Pagan test” is used to detect:
A) Autocorrelation in the residuals
B) Multicollinearity in the independent variables
C) Heteroscedasticity in the regression model
D) Endogeneity in the independent variables
Answer: C
The “adjusted R-squared” is used to:
A) Adjust the R-squared for the number of predictors in the model
B) Adjust for the presence of multicollinearity
C) Adjust for the bias in the estimation of the coefficients
D) Adjust for the endogeneity of the independent variables
Answer: A
In time-series analysis, “cointegration” indicates:
A) A stable relationship between two variables over time
B) That the series are stationary
C) A form of autocorrelation in the residuals
D) The absence of multicollinearity between time-series variables
Answer: A
The “difference-in-differences” (DID) method is often used to:
A) Compare the means of two groups before and after a treatment or event
B) Test for heteroscedasticity in the error terms
C) Estimate the coefficients in the presence of multicollinearity
D) Estimate models with endogeneity using instrumental variables
Answer: A
In an instrumental variables (IV) estimation, the instrument must:
A) Be correlated with the dependent variable
B) Be correlated with the endogenous regressor but not the error term
C) Be uncorrelated with all independent variables
D) Be strongly correlated with the error term
Answer: B
The “Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test” is used to:
A) Test for the presence of cointegration
B) Test for unit roots in a time series
C) Test for heteroscedasticity in the regression model
D) Test for autocorrelation in the residuals
Answer: B
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