Question 1

Infeasible GLS

Accepted Answer

A) requires too much memory even for today's PCs. 
B) uses complicated interative techniques. 
C) cannot be calculated since it also uses quasi differences for Xt. 
D) assumes the parameters of the error autocorrelation process to be known. 
A) requires too much memory even for today's PCs. 
B) uses complicated interative techniques. 
C) cannot be calculated since it also uses quasi differences for Xt. 
D) assumes the parameters of the error autocorrelation process to be known.

Question 2

The distributed lag model relating orange juice prices to the Orlando weather reported in the text was of the form
%ChgPt = β0 + β1FDDt + β2FDDt-1 + β3FDDt-2 + ... + β19FDDt-18 + ut
(a)Suppose that an agricultural economist tells you that a freeze in December is more harmful than a freeze in the other months. How would you modify the regression to incorporate this effect? How would you test for this December effect?
(b)The same economist tells you that the damage caused by freezes is not well captured by the FDD variable. She says that a single day temperature with a temperature of 24° is more damaging than 8 days with a temperature of 31°. How would you modify the regression to incorporate this effect?

Accepted Answer

(a)A binary variable can be added to the

Question 3

Heteroskedasticity- and autocorrelation-consistent standard errors

Accepted Answer

A) result in the OLS estimator being BLUE. 
B) should be used when errors are autocorrelated. 
C) are calculated when using the Cochrane-Orcutt iterative procedure. 
D) have the same formula as the heteroskedasticity robust standard errors in cross-sections. 
A) result in the OLS estimator being BLUE. 
B) should be used when errors are autocorrelated. 
C) are calculated when using the Cochrane-Orcutt iterative procedure. 
D) have the same formula as the heteroskedasticity robust standard errors in cross-sections.

Question 4

In your intermediate macroeconomics course, government expenditures and the money supply were treated as exogenous, in the sense that the variables could be changed to conduct economic policy to influence target variables, but that these variables would not react to changes in the economy as a result of some fixed rule. The St. Louis Model, proposed by two researchers at the Federal Reserve in St. Louis, used this idea to test whether monetary policy or fiscal policy was more effective in influencing output behavior. Although there were various versions of this model, the basic specification was of the following type:
Δln(Yt)= β0 + β1Δln mt + ... + βpΔln mt-p-1 + βp+1Δln Gt + ... + βp+qΔln Gt-q-1 + ut
Assuming that money supply and government expenditures are exogenous, how would you estimate dynamic causal effects? Why do you think this type of model is no longer used by most to calculate fiscal and monetary multipliers?

Accepted Answer

If the money supply and government expen

Question 5

Consider the following distributed lag model $$Y _ { t } = \beta _ { 0 } + \beta _ { 1 } X _ { t } + \beta _ { 2 } X _ { t - 1 } + u _ { t } \text {, where } u _ { t } = \phi _ { 1 } u _ { t - 1 } + \tilde { u } _ { t } , \tilde { u } _ { t }$$ is serially uncorrelated, and X is strictly exogenous.
(a)How many parameters are there to be estimated between the two equations?
(b)Using the two equations of the model above, derive the ADL form of the model.
(c)There are five regressors in the ADL model, namely Yt-1, Xt, Xt-1, Xt-2 and the constant. Estimating the ADL model linearly will give you five coefficients. Can you derive the parameters of the original two equation model from these five estimates? Why or why not?
(d)What alternative method do you have to retrieve the parameters of the two equation model?

Accepted Answer

(a)There are four parameters to be estim

Question 6

The 95% confidence interval for the dynamic multipliers should be computed by using the estimated coefficient ±

Accepted Answer

A) 1.96 times the RMSFE. 
B) 1.96 times the HAC standard errors. 
C) 1.96, since the HAC errors are standardized. 
D) 1.64 times the HAC standard errors since the alternative hypothesis is one-sided. 
A) 1.96 times the RMSFE. 
B) 1.96 times the HAC standard errors. 
C) 1.96, since the HAC errors are standardized. 
D) 1.64 times the HAC standard errors since the alternative hypothesis is one-sided.

Question 7

In the distributed lag model, the dynamic causal effect

Accepted Answer

A) is the sequence of coefficients on the current and lagged values of X. 
B) is not the same as the dynamic multiplier. 
C) is generated by choosing different truncation points for the HAC standard errors. 
D) requires estimation of the model by Cochrane-Orcutt method. 
A) is the sequence of coefficients on the current and lagged values of X. 
B) is not the same as the dynamic multiplier. 
C) is generated by choosing different truncation points for the HAC standard errors. 
D) requires estimation of the model by Cochrane-Orcutt method.

Question 8

(Requires some calculus)In the following, assume that Xt is strictly exogenous and that economic theory suggests that, in equilibrium, the following relationship holds between Y* and Xt, where the "*" indicates equilibrium.
Y* = kXt
An error term could be added here by assuming that even in equilibrium, random variations from strict proportionality might occur. Next let there be adjustment costs when changing Y, e.g. costs associated with changes in employment for firms. As a result, an entity might be faced with two types of costs: being out of equilibrium and the adjustment cost. Assume that these costs can be modeled by the following quadratic loss function:
L = λ1(Yt - Y*)2 + λ1(Yt - Yt-1)2
a. Minimize the loss function w.r.t. the only variable that is under the entity's control, Yt and solve for Yt.
b. Note that the two weights on Y* and Yt-1 add up to one. To simplify notation, let the first weight be θ and the second weight (1-θ). Substitute the original expression for Y* into this equation. In terms of the ADL(p,q)terminology, what are the values for p and q in this model?

Accepted Answer

a. Y_t = @#IMG-DLM&_TB5979_11_TB5979_11_TB

Question 9

Money supply is linked to the monetary base by the money multiplier. Macroeconomic textbooks tell you that the central bank cannot control the money supply, but it can control the monetary base. As a result, you decide to specify a distributed lag equation of the growth in the money supply on the growth in the monetary base. One of your peers tells you that this is not a good idea for modeling the relationship between the two variables. What does she mean?

Accepted Answer

Although the monetary base is one of the

Question 10

Ascertaining whether or not a regressor is strictly exogenous or exogenous ultimately requires all of the following with the exception of

Accepted Answer

A) economic theory. 
B) institutional knowledge. 
C) expert judgment. 
D) use of HAC standard errors. 
A) economic theory. 
B) institutional knowledge. 
C) expert judgment. 
D) use of HAC standard errors.

Question 11

Your textbook presents as an example of a distributed lag regression the effect of the weather on the price of orange juice. The authors mention U.S. income and Australian exports, oil prices and inflation, monetary policy and inflation, and the Phillips curve as other potential candidates for distributed lag regression. You are considering estimating the effect of minimum wages on teenage employment (employment population ratio)using a time series of U.S. data. Write a short essay on whether a distributed lag model would be a suitable tool to figure out dynamic causal effects in this case.

Accepted Answer

One of the first questions student must

Question 12

Consider the following model Yt = β0 + $X _ { t } ^ { e }$ + ut where the superscript "e" indicates expected values. This may represent an example where consumption depends on expected, or "permanent," income. Furthermore, let expected income be formed as follows: $X _ { t } ^ { e }$ = $x _ { t - 1 } ^ { e }$ + λ(Xt - $x _ { t - 1 } ^ { e }$ ); 0 st of December, if you had annual data. Give an intuitive explanation for this process.
(b)Rewrite the expectations equation in the following form: $X _ { t } ^ { e }$ = (1 - λ) 
  $x _ { t - 1 } ^ { e }$ + λXt
Next, following the method used in your textbook, lag both sides of the equation and replace $x _ { t - 1 } ^ { e }$ Repeat this process by repeatedly substituting expression for $x _ { t - 2 } ^ { e }$ , $x _ { t - 3 } ^ { e }$ , and so forth. Show that this results in the following equation: $X _ { t } ^ { e }$ = λXt + λ(1-λ)Xt-1 + λ(1- λ)2 Xt-2 + ... + λ(1- λ)n Xt-n + (1 - λ)n+1
  $X _ { t + 1 } ^ { e }$ Explain why it is reasonable to drop the last right hand side term as n becomes large.
(c)Substitute the above expression into the original model that related Y to $X _ { t } ^ { e }$ Although you now have right hand side variables that are all observable, what do you perceive as a potential problem here if you wanted to estimate this distributed lag model without further restrictions?
(d)Lag both sides of the equation, multiply through by (1- λ), and subtract this equation from the equation found in (c). This is called a "Koyck transformation." What does the resulting equation look like? What is the error process? What is the impact effect (zero-period dynamic multiplier)of a unit change in X, and how does it differ from long run cumulative dynamic multiplier?

Accepted Answer

(a)If the forecast error for the previou

Question 13

In time series, the definition of causal effects

Accepted Answer

A) says that one variable helps predict another variable. 
B) does not make much sense since there are not multiple subjects. 
C) assumes that the same subject is being given different treatments at different points in time. 
D) requires panel data. 
A) says that one variable helps predict another variable. 
B) does not make much sense since there are not multiple subjects. 
C) assumes that the same subject is being given different treatments at different points in time. 
D) requires panel data.

Question 14

The Gallup Poll frequently surveys the electorate to quantify the public's opinion of the president. Since 1945, Gallup settled on the following wording of its presidential poll: "Do you approve or disapprove of the way (name)is handling his job as president?" Gallup has not changed its presidential question since then, and respondents can answer "approve," "disapprove," or "no opinion."
You want to see how this approval rating is related to the Michigan index of consumer sentiment (ICS). The monthly survey, conducted with a minimum sample of 500, asks people if they feel "better/worse off" with regard to current and future conditions.
(a)To estimate dynamic causal effects, you collect quarterly data from 1962:I - 1998:II for the United States. You allow a binary variable for each presidency to capture the intrinsic popularity of the President. Furthermore, you eliminate observations that include a change in party for the presidency by using a binary variable, which takes on the value of one during the first quarter of the year after the election. Finally, a friendly political scientist provides you with (i)an "events" variable, (ii)a "Vietnam" binary variable, and (iii)a "honeymoon" variable, which measures the effect of a higher popularity of a president immediately following the election. (The coefficients of these variables will not be reported here.)
Assuming that consumer sentiment is exogenous, you estimate the following two specifications (numbers in parenthesis are heteroskedasticity- and autocorrelation-consistent standard errors): $\widehat{\text { Approval }}_{t}$$\begin{aligned}
= & 26.08+0.178 \times I C S_{t}+0.232 \times I C S_{t-1} ; R^{2}=0.667, S E R=7.00 \
& (8.83)(0.120)\quad\quad\quad(0.135)
\end{aligned}$

$\widehat{\text { Approval }}_{t}$$\begin{array}{c}
=26.08+0.178 \times \Delta I C S_{t}+0.411+I C S_{t-1} ; R^{2}=0.667, S E R=7.00 \
\quad(8.17)(0.120) \quad(0.089)
\end{array}$
What is the difference between the two specifications? What is the advantage of estimating the second equation, if any?
(b)Assuming that the errors follow an AR(1)process, you also estimate the following alternative: $\widehat{\text { Approval }}_{t}$ $\begin{aligned}= & -4.61+0.300 \times I C S_{t}-0.070 \times I C S_{t-1}-0.054 \times I C S_{t-2}+0.776 \times \text { Approval }_{t-1} ; \
& (5.84)(0.083)
\end{aligned}$

$\begin{array} { l } 
R ^ { 2 } = 0.868 , S E R = 4.45 \
\end{array}$
How is this specification related to the previous ones? What implicit assumptions did you have to make to allow for desirable properties of the OLS estimator?
(c)You finally estimate the approval equation using the quasi-difference specification and the GLS estimator. $$\begin{array} { l } 
\widetilde {\text { Approvale } }= - 4.61 + 0.300 \times \widetilde { I C } S _ { t } - 0.070 \times \widetilde { I C } S _ { t - 1 } \
\quad\quad\quad\quad\quad\quad\quad\text { (5.84) }\quad ( 0.083 ) \quad\quad\quad ( 0.099 ) \
R ^ { 2 } = 0.868 , S E R = 4.45 \
\end{array}$$
$$R ^ { 2 } = 0.868 , S E R = 4.45$$
where $\tilde { Z } _ { t } = z _ { t } - \hat { \phi } _ { 1 } z _ { t - 1 }$ and $\hat { \phi } _ { 1 } = 0.896 ( 0.040 )$. How is this equation related to the ones in (a)and (b)? What are the properties of the GLS estimator here, under the assumption that ICS is strictly exogenous?
(d)Is it likely that the ICS is exogenous here? Strictly exogenous?

Accepted Answer

(a)If the regressor is exogenous, then t

Question 15

GLS

Accepted Answer

A) results in smaller variances of the estimator than OLS if the regressors are strictly exogenous. 
B) is the same as OLS using HAC standard errors. 
C) can be used even if the regressors are not strictly exogenous. 
D) can be used for time-series estimation, but not in cross-sectional data. 
A) results in smaller variances of the estimator than OLS if the regressors are strictly exogenous. 
B) is the same as OLS using HAC standard errors. 
C) can be used even if the regressors are not strictly exogenous. 
D) can be used for time-series estimation, but not in cross-sectional data.

Question 16

Your textbook presents as an example of a distributed lag regression the effect of the weather on the price of orange juice. The authors mention U.S. income and Australian exports, oil prices and inflation, monetary policy and inflation, and the Phillips curve as other candidates for distributed lag regression. Briefly discuss whether or not the exogeneity assumption is likely to hold in each of these cases. Explain why it is so hard to come up with good examples of distributed lag regressions in economics.

Accepted Answer

There is some degree of simultaneity bet

Question 17

A distributed lag regression

Accepted Answer

A) is also called AR(p). 
B) can also be used with cross-sectional data. 
C) gives estimates of dynamic causal effects. 
D) is sometimes referred to as ADL. 
A) is also called AR(p). 
B) can also be used with cross-sectional data. 
C) gives estimates of dynamic causal effects. 
D) is sometimes referred to as ADL.

Question 18

The concepts of exogeneity, strict exogeneity, and predeterminedness

Accepted Answer

A) are defined in such a way that strict exogeneity implies exogeneity. 
B) can be used interchangeably. 
C) are defined in such a way that exogeneity implies strict exogeneity. 
D) correspond to endogeneity, strict endogeneity, and lagged endogenous variables. 
A) are defined in such a way that strict exogeneity implies exogeneity. 
B) can be used interchangeably. 
C) are defined in such a way that exogeneity implies strict exogeneity. 
D) correspond to endogeneity, strict endogeneity, and lagged endogenous variables.

Question 19

The distributed lag model assumptions include all of the following with the exception of:

Accepted Answer

A) There is no perfect multicollinearity. 
B) Xt is strictly exogenous. 
C) E(ut    | Xt, Xt-1, Xt-2)= 0 
D) The random variables Xt and Yt have a stationary distribution. 
A) There is no perfect multicollinearity. 
B) Xt is strictly exogenous. 
C) E(ut    | Xt, Xt-1, Xt-2)= 0 
D) The random variables Xt and Yt have a stationary distribution.

Question 20

In the distributed lag model, the coefficient on the contemporaneous value of the regressor is called the

Accepted Answer

A) dynamic effect. 
B) cumulative multiplier. 
C) autoregressive error. 
D) impact effect. 
A) dynamic effect. 
B) cumulative multiplier. 
C) autoregressive error. 
D) impact effect.

Infeasible GLS

Heteroskedasticity- and autocorrelation-consistent standard errors

The 95% confidence interval for the dynamic multipliers should be computed by using the estimated coefficient ±

In the distributed lag model, the dynamic causal effect

Ascertaining whether or not a regressor is strictly exogenous or exogenous ultimately requires all of the following with the exception of

In time series, the definition of causal effects

GLS

A distributed lag regression

The concepts of exogeneity, strict exogeneity, and predeterminedness

The distributed lag model assumptions include all of the following with the exception of:

In the distributed lag model, the coefficient on the contemporaneous value of the regressor is called the

Economic Questions and Data

Review of Probability

Review of Statistics

Linear Regression With One Regressor

Regression With a Single Regressor: Hypothesis Tests and Confidence Intervals

Linear Regression With Multiple Regressors

Hypothesis Tests and Confidence Intervals in Multiple Regression

Nonlinear Regression Functions

Assessing Studies Based on Multiple Regression

Regression With Panel Data

Regression With a Binary Dependent Variable

Instrumental Variables Regression

Experiments and Quasi-Experiments

Introduction to Time Series Regression and Forecasting

Additional Topics in Time Series Regression

The Theory of Linear Regression With One Regressor

The Theory of Multiple Regression

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Exam 15: Estimation of Dynamic Causal Effects

Infeasible GLS

Heteroskedasticity- and autocorrelation-consistent standard errors

The 95% confidence interval for the dynamic multipliers should be computed by using the estimated coefficient ±

In the distributed lag model, the dynamic causal effect

Ascertaining whether or not a regressor is strictly exogenous or exogenous ultimately requires all of the following with the exception of

In time series, the definition of causal effects

GLS

A distributed lag regression

The concepts of exogeneity, strict exogeneity, and predeterminedness

The distributed lag model assumptions include all of the following with the exception of:

In the distributed lag model, the coefficient on the contemporaneous value of the regressor is called the

Economic Questions and Data

Review of Probability

Review of Statistics

Linear Regression With One Regressor

Regression With a Single Regressor: Hypothesis Tests and Confidence Intervals

Linear Regression With Multiple Regressors

Hypothesis Tests and Confidence Intervals in Multiple Regression

Nonlinear Regression Functions

Assessing Studies Based on Multiple Regression

Regression With Panel Data

Regression With a Binary Dependent Variable

Instrumental Variables Regression

Experiments and Quasi-Experiments

Introduction to Time Series Regression and Forecasting

Additional Topics in Time Series Regression

The Theory of Linear Regression With One Regressor

The Theory of Multiple Regression

Filters