Question 1

Finite distributed lag models are most useful for

Accepted Answer

A) forecasting and economic policy analysis 
B) testing hypotheses and measuring economic dynamics 
C) measuring impacts and optimizing economic outcomes 
D) measuring autocorrelation and autoregressive dynamics 
A) forecasting and economic policy analysis 
B) testing hypotheses and measuring economic dynamics 
C) measuring impacts and optimizing economic outcomes 
D) measuring autocorrelation and autoregressive dynamics

Question 2

Which of the following is an AR(3)model?

Accepted Answer

A) yt = $\delta$+ $\theta$ 1yt-1+$\theta$ 2yt-2 +$\theta$ 3yt-3 + $\delta$0xt + $\delta$1xt-1+$\delta$2xt-2+ $\delta$3xt-3 + vt 
B) yt =$\delta$+ $\theta$ 1yt-1+ $\delta$0xt + $\delta$1xt-1+$\delta$2xt-2+ $\delta$3xt-3 + vt 
C) yt = $\delta$+ $\theta$ 1yt-1+$\theta$ 2yt-2 +$\theta$ 3yt-3 + $\delta$0xt + $\delta$1xt-1+ vt 
D) yt = $\delta$+ $\theta$ 1yt-1+$\theta$ 2yt-2 +$\theta$ 3yt-3 + vt 
A) yt = $\delta$+ $\theta$ 1yt-1+$\theta$ 2yt-2 +$\theta$ 3yt-3 + $\delta$0xt + $\delta$1xt-1+$\delta$2xt-2+ $\delta$3xt-3 + vt 
B) yt =$\delta$+ $\theta$ 1yt-1+ $\delta$0xt + $\delta$1xt-1+$\delta$2xt-2+ $\delta$3xt-3 + vt 
C) yt = $\delta$+ $\theta$ 1yt-1+$\theta$ 2yt-2 +$\theta$ 3yt-3 + $\delta$0xt + $\delta$1xt-1+ vt 
D) yt = $\delta$+ $\theta$ 1yt-1+$\theta$ 2yt-2 +$\theta$ 3yt-3 + vt

Question 3

When using the LM test for serial correlation,what is the null hypothesis?

Accepted Answer

A) it depends on the model specification 
B) no serial correlation is present 
C) statistically significant serial correlation with the first lag 
D) statistically significant serial correlation with unspecified lag 
A) it depends on the model specification 
B) no serial correlation is present 
C) statistically significant serial correlation with the first lag 
D) statistically significant serial correlation with unspecified lag

Question 4

Which model below has an autocorrelated error term?

Accepted Answer

A) yt = f(xt,xt-1,xt-2……. ) 
B) yt = f(yt-1,xt,xt-1,xt-2…) 
C) yt = f(xt,x2t,x3t) 
D) yt = f(xt)+ g(et-1) 
A) yt = f(xt,xt-1,xt-2……. ) 
B) yt = f(yt-1,xt,xt-1,xt-2…) 
C) yt = f(xt,x2t,x3t) 
D) yt = f(xt)+ g(et-1)

Finite distributed lag models are most useful for

Which of the following is an AR(3)model?

When using the LM test for serial correlation,what is the null hypothesis?

Which model below has an autocorrelated error term?

An Introduction to Econometrics

Pp : Prob, Probability Primer, Probability Primer

The Simple Linear Regression Model

Interval Estimation and Hypothesis Testing

Prediction, Goodness-Of-Fit and Modeling Issues

The Multiple Regression Model

Further Inference in the Multiple Regression Model

Using Indicator Variables

Heteroskedasticity

Random Regressors and Moment Based Estimation

Simultaneous Equations Models

Regression With Time Series Data: Nonstationary Variables

Vector Error Correction and Vector Autoregressive Models

Time-Varying Volatility and Arch Models

Panel Data Models

Qualitative and Limited Dependent Variable Models

Filters

Exam 10: Regression With Time Series Data: Stationary Variables

Finite distributed lag models are most useful for

Which of the following is an AR(3)model?

When using the LM test for serial correlation,what is the null hypothesis?

Which model below has an autocorrelated error term?

An Introduction to Econometrics

Pp : Prob, Probability Primer, Probability Primer

The Simple Linear Regression Model

Interval Estimation and Hypothesis Testing

Prediction, Goodness-Of-Fit and Modeling Issues

The Multiple Regression Model

Further Inference in the Multiple Regression Model

Using Indicator Variables

Heteroskedasticity

Random Regressors and Moment Based Estimation

Simultaneous Equations Models

Regression With Time Series Data: Nonstationary Variables

Vector Error Correction and Vector Autoregressive Models

Time-Varying Volatility and Arch Models

Panel Data Models

Qualitative and Limited Dependent Variable Models

Filters