ECS4863 – Advanced Econometrics | January/February
2026 Supplementary Exam Memo (UNISA South Africa)
,Question 1:
What is the main assumption underlying Ordinary Least Squares (OLS) estimation?
A) Homoscedasticity
B) Independence
C) Linearity
D) All of the above
Correct Option: D) All of the above
Rationale: OLS estimation relies on multiple assumptions, including linearity,
independence of errors, and homoscedasticity. All are essential for the unbiased and
efficient estimation of the regression parameters.
Question 2:
Which of the following is a consequence of multicollinearity in a regression model?
A) Biased coefficients
B) Inflated standard errors
C) Difficulty in determining individual variable effects
D) Increased R-squared
Correct Option: C) Difficulty in determining individual variable effects
Rationale: Multicollinearity affects the estimation of regression coefficients, making it
hard to ascertain the individual contribution of each predictor variable. While it does not
bias coefficients, it inflates standard errors.
Question 3:
In time series analysis, what does the term 'stationarity' refer to?
A) Constant mean and variance over time
B) Predictability of the series
C) The absence of trends
D) A and C only
Correct Option: D) A and C only
Rationale: Stationarity implies that a time series has a constant mean and variance
over time and does not exhibit trends. Non-stationary data can lead to unreliable
statistical inference.
Question 4:
, Which test would you use to check for heteroscedasticity in a regression model?
A) Breusch-Pagan test
B) Durbin-Watson test
C) Dickey-Fuller test
D) Chow test
Correct Option: A) Breusch-Pagan test
Rationale: The Breusch-Pagan test is specifically designed to detect the presence of
heteroscedasticity in the residuals of a regression model.
Question 5:
Instrumental Variables (IV) estimation is primarily used to address which issue in
regression analysis?
A) Measurement error
B) Endogeneity
C) Model specification
D) Autocorrelation
Correct Option: B) Endogeneity
Rationale: IV estimation is employed when model predictors are correlated with the
error term, leading to endogeneity, which can bias results. Instruments help provide
consistent estimates.
Question 6:
Which of the following tests is used to determine whether a time series is
stationary?
A) Breusch-Pagan test
B) Granger causality test
C) Augmented Dickey-Fuller test
D) Chow test
Correct Option: C) Augmented Dickey-Fuller test
Rationale: The Augmented Dickey-Fuller (ADF) test is commonly used to test for the
presence of a unit root, which indicates non-stationarity in a time series.
Question 7:
In a multiple regression model, what does the term 'adjusted R-squared' account
for?
2026 Supplementary Exam Memo (UNISA South Africa)
,Question 1:
What is the main assumption underlying Ordinary Least Squares (OLS) estimation?
A) Homoscedasticity
B) Independence
C) Linearity
D) All of the above
Correct Option: D) All of the above
Rationale: OLS estimation relies on multiple assumptions, including linearity,
independence of errors, and homoscedasticity. All are essential for the unbiased and
efficient estimation of the regression parameters.
Question 2:
Which of the following is a consequence of multicollinearity in a regression model?
A) Biased coefficients
B) Inflated standard errors
C) Difficulty in determining individual variable effects
D) Increased R-squared
Correct Option: C) Difficulty in determining individual variable effects
Rationale: Multicollinearity affects the estimation of regression coefficients, making it
hard to ascertain the individual contribution of each predictor variable. While it does not
bias coefficients, it inflates standard errors.
Question 3:
In time series analysis, what does the term 'stationarity' refer to?
A) Constant mean and variance over time
B) Predictability of the series
C) The absence of trends
D) A and C only
Correct Option: D) A and C only
Rationale: Stationarity implies that a time series has a constant mean and variance
over time and does not exhibit trends. Non-stationary data can lead to unreliable
statistical inference.
Question 4:
, Which test would you use to check for heteroscedasticity in a regression model?
A) Breusch-Pagan test
B) Durbin-Watson test
C) Dickey-Fuller test
D) Chow test
Correct Option: A) Breusch-Pagan test
Rationale: The Breusch-Pagan test is specifically designed to detect the presence of
heteroscedasticity in the residuals of a regression model.
Question 5:
Instrumental Variables (IV) estimation is primarily used to address which issue in
regression analysis?
A) Measurement error
B) Endogeneity
C) Model specification
D) Autocorrelation
Correct Option: B) Endogeneity
Rationale: IV estimation is employed when model predictors are correlated with the
error term, leading to endogeneity, which can bias results. Instruments help provide
consistent estimates.
Question 6:
Which of the following tests is used to determine whether a time series is
stationary?
A) Breusch-Pagan test
B) Granger causality test
C) Augmented Dickey-Fuller test
D) Chow test
Correct Option: C) Augmented Dickey-Fuller test
Rationale: The Augmented Dickey-Fuller (ADF) test is commonly used to test for the
presence of a unit root, which indicates non-stationarity in a time series.
Question 7:
In a multiple regression model, what does the term 'adjusted R-squared' account
for?
