Question 1

What does VEC abbreviate?&#10;A)vector error correction&#10;B)variable error correction&#10;C)vector economic cointegration&#10;D)variable econometric condition

Accepted Answer

VEC stands for vector error correction, which is a statistical model used to analyze and forecast time series data. It is commonly used in econometrics to study the long-term relationships between variables and correct any errors in the short-term.

Question 2

Impulse response funcitons can be difficult to identify as a result of&#10;A)interdependent dynamics and unobserved data&#10;B)violations of the ceteris paribus assumption&#10;C)unobserved data and violations of the ceteris paribus assumption&#10;D)interdependent dynamics and innovation

Accepted Answer

A

Question 3

What type of model shows how series react dynamically to shocks?&#10;A)a VAR model&#10;B)an impulse response function&#10;C)variance decomposition&#10;D)an ARDL model

Accepted Answer

An impulse response function shows how series react dynamically to shocks.

Question 4

What type of model provides information about sources of volatility?&#10;A)a VAR model&#10;B)an impulse response function&#10;C)variance decomposition&#10;D)an ARDL model

Accepted Answer

Variance decomposition breaks down the variance of the error term of the forecast into proportions attributable to different sources, including various shocks or innovations, thus providing information about sources of volatility.

Question 5

When estimating a VEC model using a two step least squares process,what is the second step?&#10;A)use least squares to estimate the cointegrating relationship&#10;B)use least squares to estimate first differences as a function of estimated residuals&#10;C)use least squares to estimated residuals as a function of first differences&#10;D)use least squares to estimate first differences as a function of lagged differences

Accepted Answer

The second step in estimating a Vector Error Correction (VEC) model using a two-step least squares process involves using least squares to estimate first differences as a function of the estimated residuals from the cointegrating relationship. This step incorporates the error correction term, which represents the short-term adjustments needed to return to the long-term equilibrium path.

Question 6

Functions that show how variables adjust to shocks over time are known as&#10;A)adjustment functions&#10;B)system dynamic functions&#10;C)impulse response functions&#10;D)expansion paths

Accepted Answer

The correct term for describing how variables adjust to shocks over time is impulse response functions. Option A is too general and does not capture the specific term used in economics. Option B is not an accurate or commonly used term in this context. Option D refers to a different concept in economics and does not capture the specific term used for this question.

Question 7

What type of model tells you whether two series are significantly related to each other?&#10;A)a VAR model&#10;B)an impulse response function&#10;C)variance decomposition&#10;D)an ARDL model

Accepted Answer

A VAR model (vector autoregression) is specifically designed to analyze the relationship between multiple time series variables. It can tell you whether two series are significantly related to each other by estimating the parameters of the model and examining the significance of the coefficients.

Question 8

In which case should a VAR model be used rather than a VEC model?&#10;A)the series are I(1)&#10;B)all series are stationary&#10;C)the series are not cointegrated&#10;D)you have more than 2 series

Accepted Answer

VAR models are suitable for modeling series that are not cointegrated, while VEC models should be used when the series are cointegrated. Therefore, if the series are not cointegrated, a VAR model would be more appropriate.

Question 9

What is the difference between a VEC and a VAR?&#10;A)The VAR model is for only 2 series and VEC models accommodate 3 or more variables.&#10;B)The VAR model is a special form of the VEC model and should be used for nonstationary series.&#10;C)The VEC model is a special form of the VAR and should be used with cointegrated series.&#10;D)The VAR model deals with stationary series while the VEC allows for dynamic series.

Accepted Answer

The VEC model is a special form of the VAR model that should be used when the variables under analysis are cointegrated, implying a long-run relationship between them. The VEC model uses the error correction term to adjust for any deviations from this long-run equilibrium, while the VAR model does not incorporate any such mechanism. Therefore, the VEC model is more appropriate when dealing with nonstationary time series that are related and cointegrated.

Question 10

When estimating a VEC model using a two step least squares process,what is the first step?&#10;A)use least squares to estimate the cointegrating relationship&#10;B)use least squares to estimate first differences as a function of estimated residuals&#10;C)use least squares to estimated residuals as a function of first differences&#10;D)use least squares to estimate first differences as a function of lagged differences

Accepted Answer

The first step in estimating a VEC model using a two-step least squares process is to use least squares to estimate the cointegrating relationship. This involves regressing the non-stationary variables on each other to find a linear combination of the variables that is stationary, which represents a long-run equilibrium relationship. This cointegrating vector is then used in the second step to estimate the short-run dynamics of the system. The other options (B, C, and D) do not accurately reflect the first step in the process.

Question 11

What does VAR abbreviate?&#10;A)variance auto reduction&#10;B)vector autoregressive&#10;C)variance active regression&#10;D)vector alpha reduction

Accepted Answer

The answer of What does VAR abbreviate?&#10;A)variance auto reduction&#10;B)vector autoregressive&#10;C)variance...

Deck 14: Vector Error Correction and Vector Autoregressive Models