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What are reduced form equations in a system of equations?


A) the structural equations rewritten with endogenous variables as a function of exogenous variables
B) the structural equations without the endogenous regressors
C) the exogenous variables reworked as a function of the other exogenous variables
D) the equations remaining when the parameters of structural equations are reduced to generate additional degrees of freedom

E) B) and C)
F) A) and B)

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A

What estimation technique should be used to estimated parameters in an unidentified structural equation?


A) none-no techniques exist
B) OLS
C) 2SLS
D) GLS

E) A) and C)
F) C) and D)

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In a system of 4 simultaneous equations,how many endogenous variables must be excluded from an equation in the system for the parameters to be identified?


A) 1
B) 2
C) 3
D) 4

E) None of the above
F) C) and D)

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C

Why is it best to use specialized software to estimate 2SLS?


A) specialized t-values are needed for inference and hypothesis testing
B) the Ο„ \tau distribution is not widely available otherwise
C) it is algebraically difficult to find structural parameter estimates from reduced form estimates,so the software needs to use specialized algorithms when algebra does not work
D) it is too easy to make a data handling mistake when capturing predicted values to use as regressors in the second stage

E) B) and D)
F) C) and D)

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What is the first stage of 2SLS?


A) estimate parameters of reduced form equations and find predicted values
B) find a random sample large enough to divide into 2 separate samples for the two stages
C) estimate parameters of the structural equations using OLS
D) use reduced form parameter estimates as explanatory variables

E) All of the above
F) A) and D)

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When estimating the structural parameters of simultaneous equation models,how do least squares estimates,compare to the true value of Ξ²\beta ?


A) When estimating the structural parameters of simultaneous equation models,how do least squares estimates,compare to the true value of \beta ? A) B) C) D) The direction of the bias depends on the sample correlation.
B) When estimating the structural parameters of simultaneous equation models,how do least squares estimates,compare to the true value of \beta ? A) B) C) D) The direction of the bias depends on the sample correlation.
C) When estimating the structural parameters of simultaneous equation models,how do least squares estimates,compare to the true value of \beta ? A) B) C) D) The direction of the bias depends on the sample correlation.
D) The direction of the bias depends on the sample correlation.

E) A) and B)
F) B) and C)

Correct Answer

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What does 2SLS abbreviate?


A) twice squared linear series
B) second summed linear sample
C) second order stationary logical sequence
D) two stage least squares

E) A) and D)
F) B) and D)

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In a system of M simultaneous equations,at least M-1 variables must be excluded from each equation for the equation to be identified.What does it mean if the equation is not identified?


A) unique coefficient estimates for each variable cannot be identified using least squares
B) the economic value of the predicted value cannot be identified
C) the economic relationships are unclear and the equation should be dropped form the system
D) the exogenous variables have been incorrectly identified

E) C) and D)
F) B) and D)

Correct Answer

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How does the least squares estimator perform on a simultaneous equation model with an endogenous regressor?


A) unbiased and consistent in large samples
B) biased and inconsistent in all sample sizes
C) biased but consistent in large samples
D) unbiased but inconsistent unless collected through random sampling

E) C) and D)
F) None of the above

Correct Answer

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What does it mean for a structural equation to be unidentified?


A) too many endogenous variables are included in the equation to estimate a unique parameter value
B) the sample size is not large enough to rely on asymptotic estimator properties
C) the simultaneous nature of the equations makes random samples impossible to obtain
D) the sample size is not large enough to allow M*(M-1) degrees of freedom

E) A) and D)
F) A) and C)

Correct Answer

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How does the least squares estimator perform on a simultaneous equation model with an endogenous regressor?


A) unbiased and consistent in large samples
B) unbiased but inconsistent in all sample sizes
C) biased but consistent in large samples
D) biased and inconsistent for structural equations,but unbiased and consistent for reduced form equations

E) None of the above
F) B) and C)

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What are the implications for 2SLS estimators if reduced form parameter estimates are statistically insignificant?


A) still consistent in large samples,but no longer BLUE
B) there will be correlation in the structural equations,causing estimators to be inconsistent
C) there are no consequences,only structural parameters matter
D) small sample properties no longer hold,but asymptotic properties still apply

E) B) and D)
F) A) and B)

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What is the 2nd stage of 2SLS?


A) estimate parameters of reduced form equations and find predicted values
B) find a random sample large enough to divide into 2 separate samples for the two stages
C) estimate parameters of the structural equations using predicted values from reduced form equations
D) use reduced form parameter estimates as explanatory variables

E) All of the above
F) B) and C)

Correct Answer

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If a structural model has M simultaneous equations,what is the necessary condition for a unique parameter value to be consistently estimated for each variable in the equation?


A) The number of endogenous variables excluded from the equation must be at least as large as M-1
B) the number of endogenous variables excluded must be at least M/2
C) the number of exogenous variables in the equation must be greater than the number of endogenous variables in the equation
D) the sample size must be large enough to allow M * (M-1) degrees of freedom

E) None of the above
F) B) and C)

Correct Answer

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In a multi-equation model the jointly determined variables are referred to as____________.


A) exogenous
B) explanatory
C) regressors
D) endogenous

E) A) and D)
F) B) and C)

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D

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