Question 1

An equation in the simultaneous equations model satisfies the order condition for identification if:

Accepted Answer

A) the number of excluded endogenous variables from the equation is at most as large as the number of right-hand side exogenous variables. 
B) the number of excluded endogenous variables from the equation is at least as large as the number of right-hand side exogenous variables. 
C)  the number of excluded exogenous variables from the equation is at most as large as the number of right-hand side endogenous variables. 
D)  the number of excluded exogenous variables from the equation is at least as large as the number of right-hand side endogenous variables. 
A) the number of excluded endogenous variables from the equation is at most as large as the number of right-hand side exogenous variables. 
B) the number of excluded endogenous variables from the equation is at least as large as the number of right-hand side exogenous variables. 
C)  the number of excluded exogenous variables from the equation is at most as large as the number of right-hand side endogenous variables. 
D)  the number of excluded exogenous variables from the equation is at least as large as the number of right-hand side endogenous variables.

Question 2

A predetermined variable in a simultaneous equations model is:

Accepted Answer

A) a constant. 
B) the error term. 
C)  a lagged variable. 
D)  an omitted variable. 
A) a constant. 
B) the error term. 
C)  a lagged variable. 
D)  an omitted variable.

Question 3

The instrumental variables in the two stage least squares estimation method consists of endogenous variables appearing in either equation.

Accepted Answer

A) True 
 B)False

Question 4

Which of the following is a method which can be used for estimation in simultaneous equations models?

Accepted Answer

A) Feasible generalized least squares estimation 
B) Prais-Winsten transformation 
C)  Cochrane-Orcutt transformation 
D)  Two stage least squares estimation 
A) Feasible generalized least squares estimation 
B) Prais-Winsten transformation 
C)  Cochrane-Orcutt transformation 
D)  Two stage least squares estimation

Question 5

Which of the following correctly highlights a limitation of applying simultaneous equation models to time series data?

Accepted Answer

A) Most time series have variables with a unit root and 2SLS is complicated when applied to equations with such variables. 
B) 2SLS estimates are inefficient when applied to variables that are not in their levels but in first differences. 
C)  It is difficult to form simultaneous equations which satisfy the rank and order conditions using time series data. 
D)  The problem of serial correlation greatly limits the efficiency of simultaneous equation models and leads to inefficient estimations. 
A) Most time series have variables with a unit root and 2SLS is complicated when applied to equations with such variables. 
B) 2SLS estimates are inefficient when applied to variables that are not in their levels but in first differences. 
C)  It is difficult to form simultaneous equations which satisfy the rank and order conditions using time series data. 
D)  The problem of serial correlation greatly limits the efficiency of simultaneous equation models and leads to inefficient estimations.

An equation in the simultaneous equations model satisfies the order condition for identification if:

A predetermined variable in a simultaneous equations model is:

The instrumental variables in the two stage least squares estimation method consists of endogenous variables appearing in either equation.

Which of the following is a method which can be used for estimation in simultaneous equations models?

Which of the following correctly highlights a limitation of applying simultaneous equation models to time series data?

The Nature of Econometrics and Economic Data

The Simple Regression Model

Multiple Regression Analysis: Estimation

Multiple Regression Analysis: Inference

Multiple Regression Analysis: Ols Asymptotics

Multiple Regression Analysis: Further Issues

Multiple Regression Analysis With Qualitative Information: Binary or Dummy Variables

Heteroskedasticity

More on Specification and Data Problems

Basic Regression Analysis With Time Series Data

Further Issues in Using Ols With Time Series Data

Serial Correlation and Heteroskedasticity in Time Series Regressions

Pooling Cross Sections Across Time: Simple Panel Data Methods

Advanced Panel Data Methods

Instrumental Variables Estimation and Two Stage Least Squares

Limited Dependent Variable Models and Sample Selection Corrections

Advanced Time Series Topics

Carrying Out an Empirical Project

Filters

Exam 16: Simultaneous Equations Models

An equation in the simultaneous equations model satisfies the order condition for identification if:

A predetermined variable in a simultaneous equations model is:

The instrumental variables in the two stage least squares estimation method consists of endogenous variables appearing in either equation.

Which of the following is a method which can be used for estimation in simultaneous equations models?

Which of the following correctly highlights a limitation of applying simultaneous equation models to time series data?

The Nature of Econometrics and Economic Data

The Simple Regression Model

Multiple Regression Analysis: Estimation

Multiple Regression Analysis: Inference

Multiple Regression Analysis: Ols Asymptotics

Multiple Regression Analysis: Further Issues

Multiple Regression Analysis With Qualitative Information: Binary or Dummy Variables

Heteroskedasticity

More on Specification and Data Problems

Basic Regression Analysis With Time Series Data

Further Issues in Using Ols With Time Series Data

Serial Correlation and Heteroskedasticity in Time Series Regressions

Pooling Cross Sections Across Time: Simple Panel Data Methods

Advanced Panel Data Methods

Instrumental Variables Estimation and Two Stage Least Squares

Limited Dependent Variable Models and Sample Selection Corrections

Advanced Time Series Topics

Carrying Out an Empirical Project

Filters