past paper On Econometrics II For Revision
Econometrics II moves beyond the “BLUE” (Best Linear Unbiased Estimator) world of simple OLS into the reality of complex, non-ideal data. This course addresses what happens when the standard assumptions of Econometrics I fail—dealing with variables that are determined simultaneously, data that trends over time, and the unique challenges of following the same subjects over multiple years.
Below is the exam past paper download link
Above is the exam past paper download link
To succeed in this advanced module, you must demonstrate mathematical rigor in matrix algebra and a sharp eye for interpreting diagnostic tests. We have analyzed the most frequent “high-difficulty” modeling questions from recent examination papers to help focus your revision.
Econometrics II: Advanced Revision Q&A
Q1: What is “Endogeneity” and how do “Instrumental Variables” (IV) solve it?
A: Endogeneity occurs when an independent variable is correlated with the error term (due to omitted variables, measurement error, or simultaneity), making OLS estimates biased. The IV approach uses an external variable ($Z$) that is correlated with the problematic $X$ but uncorrelated with the error term. This is typically estimated via Two-Stage Least Squares (2SLS).
Q2: Explain the “Identification Problem” in Simultaneous Equation Models.
A: When variables like Supply and Demand are determined at the same time, we must determine if a unique solution for the parameters exists. We use the Order Condition (the number of excluded exogenous variables must be $\geq$ the number of endogenous variables in the equation minus one) to ensure the model is “Identified” and can be estimated.
Q3: What is “Stationarity” and why is it critical for Time-Series Analysis?
A: A time series is Stationary if its mean and variance are constant over time. Most economic data is “Non-Stationary” (contains a unit root). If you regress one non-stationary series on another, you get a Spurious Regression—where results look significant but are actually meaningless. The Augmented Dickey-Fuller (ADF) Test is used to check for this.
Q4: Differentiate between “Fixed Effects” (FE) and “Random Effects” (RE) in Panel Data.
A: Panel data follows the same entities (like countries or firms) over time.
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Fixed Effects: Controls for time-invariant characteristics (like geography) that might be correlated with your variables.
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Random Effects: Assumes those individual characteristics are random and uncorrelated with the regressors.
The Hausman Test is the standard exam tool used to decide which model is statistically appropriate.
Q5: What are “ARCH” and “GARCH” models used for in Finance?
A: Standard models assume constant variance (homoscedasticity). However, financial markets often show “Volatility Clustering” (periods of high swings followed by calm). ARCH/GARCH models allow the variance of the error term to change over time, making them essential for modeling risk and stock returns.
Why Practice with Econometrics II Past Papers?
Advanced Econometrics exams are famous for Matrix Derivations and Diagnostic Interpretation. You will likely be given a computer output (from Stata, EViews, or R) and asked to “Identify the presence of Multicollinearity” or “Critique the validity of the instruments used.”
By practicing with our past papers, you will:
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Master Matrix Algebra: Practice deriving the Generalized Least Squares (GLS) estimator using matrix notation.
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Refine Diagnostic Testing: Get fast at interpreting Durbin-Wu-Hausman, Sargan, and Johansen Cointegration tests.
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Link Math to Intuition: Learn to explain why a particular violation of OLS assumptions leads to specific types of bias in real-world policy analysis.
Access the Full Advanced Revision Archive
Ready to prove your coefficients are robust? We have organized a comprehensive PDF library containing five years of Econometrics II past papers, complete with full mathematical proofs, code snippets, and expert-level interpretation of regression output
