Week 6

Which of the following statements is true about non-stationary time series data?

• Non-stationary time series data always yield reliable regression results.

• Non-stationarity can lead to spurious regression results, where variables appear related when they are not.

• A stationary series does not have a constant mean and variance.

• The Augmented Dickey-Fuller (ADF) and KPSS tests are not useful for testing stationarity.

Which of the following best describes the difference between endogenous and exogenous relationships in econometrics?

• Endogenous variables are determined outside the model, while exogenous variables are determined within the model.

• Exogenous variables are influenced by other variables in the model, while endogenous variables remain unaffected by the model.

• Endogenous variables are those whose values are influenced by other variables in the model, while exogenous variables are determined outside the model and are not affected by other variables within it.

• There is no difference between endogenous and exogenous variables; they can be used interchangeably in regression analysis.

Why is applying Ordinary Least Squares (OLS) to structural equations in a simultaneous system problematic?

• OLS will produce unbiased and consistent estimates in a simultaneous equation system.

• OLS leads to biased coefficient estimates, but the estimator remains consistent.

• OLS leads to biased and inconsistent coefficient estimates, making it invalid for estimating structural equations.

• OLS can only be used if there are no endogenous variables in the structural equations.

Which of the following best describes the Two-Stage Least Squares (2SLS) method?

• 2SLS is only applicable for exactly identified systems and cannot be used for over-identified systems.

• In the first stage, the structural equations are estimated directly using OLS.

• 2SLS involves first estimating the reduced-form equations using OLS and then replacing endogenous variables in the structural equation with their fitted values.

• 2SLS does not require using reduced-form equations and directly estimates the structural equations.

Why are instruments used in econometric modeling?

• Instruments replace all endogenous variables in a model to ensure unbiased estimation.

• Instruments are variables that are highly correlated with endogenous variables but uncorrelated with the error term, helping to address endogeneity issues.

• Instruments are used to increase the number of independent variables in a regression to improve model accuracy.

• Instruments directly replace endogenous variables in the structural equation without any further transformation.

Which of the following best describes a Vector Autoregression (VAR) model?

• A VAR model is a single-equation regression model where only one dependent variable is used.

• A VAR model is a system of regression equations where multiple dependent variables are modeled simultaneously.

• A VAR model does not account for the relationships between multiple time series variables.

• A VAR model assumes that all variables are strictly exogenous and do not influence each other.

What is the purpose of impulse response analysis in VAR models?

• To determine the best lag length for the VAR model.

• To trace out the responsiveness of dependent variables to shocks in the error terms.

• To estimate the structural parameters of the VAR model directly.

• To ensure that all variables in the VAR model are stationary.