Q1: The amount of the State of Florida’s total revenue that is allocated to the education budget is believed to be dependent upon the total revenue for the year and the political party that controls the state legislature. Which of the following regression models is most appropriate for capturing the effect of the political party on the education budget? Assume Yt is the amount of the education budget for Florida in year t, X is Florida’s total revenue in year t, and Dt = {1 if the legislature has a Democratic majority in year t, 0 otherwise}. A) Yt = b0 + b1Dt + b2Xt + et. B) Yt = b0 + b1Dt + et. C) Yt = b1Dt + b2Xt + et. D) Yt = b0 + b2Xt + et.

q2: Jill Wentraub is an analyst with the retail industry. She is modeling a company’s sales over time and has noticed a quarterly seasonal pattern. If she includes dummy variables to represent the seasonality component of the sales she must use: A) four dummy variables. B) one dummy variables. C) two dummy variables. D) three dummy variables.

BB??

A?

A D

Q1. A Q2. D

didn’t see the second question, but will go with D.

A, D 4 quarters. So you need 4-1 dummy variable.

crap forgot the independent variable in the first ?

Lxwqh and Dinesh are correct. I wonder how come #1 C isn’t correct as there is no mention of a contant. Q3: When utilizing a proxy for one or more independent variables in a multiple regression model, which of the following errors is most likely to occur? A) Heteroskedasticity. B) Model misspecification. C) Multicollinearity. D) Serial correlation.

Q4: David Brice, CFA, has tried to use an AR(1) model to predict a given exchange rate. Brice has concluded the exchange rate follows a random walk without a drift. The current value of the exchange rate is 2.2. Under these conditions, which of the following would be least likely? A) The residuals of the forecasting model are autocorrelated. B) The forecast for next period is 2.2. C) The mean reverting level is undefined. D) The process is not covariance stationary.

B for question 3. think i’ve seen this one.

Q3. B Q4. A

C A

BB again…

- B 4. B?

Q5: Frank Batchelder and Miriam Yenkin are analysts for Bishop Econometrics. Batchelder and Yenkin are discussing the models they use to forecast changes in China’s GDP and how they can compare the forecasting accuracy of each model. Batchelder states, “The root mean squared error (RMSE) criterion is typically used to evaluate the in-sample forecast accuracy of autoregressive models.” Yenkin replies, “If we use the RMSE criterion, the model with the largest RMSE is the one we should judge as the most accurate.” With regard to their statements about using the RMSE criterion: A) Batchelder is correct; Yenkin is incorrect. B) Batchelder is incorrect; Yenkin is correct. C) Batchelder is incorrect; Yenkin is incorrect. D) Batchelder is correct; Yenkin is correct.

guys it’s **random walk without a drift** So next prediction would be 2.2. B is 100% correct. They need the FALSE answer

A

B, one of misspec. A.