Data Analysis and Economic Forecasting
|These questions are from the test bank. Some questions have multiple parts.|
1. You are forecasting future commodity prices, like gold and silver prices. Describe a good method to check the accuracy of your forecast.
2. What is autocorrelation in terms of a linear regression model?
How can you detect an AR(1) process?
3. If autocorrelation or heteroscedasticity is present, what can you say about the parameter estimates, standard errors, t-statistics, and F-test from a regular Linear Regression that does not correct these problems?
4. What is a polynomial trend regression?
When do you stop adding terms to a polynomial trend regression?
5. What is heteroscedasticity?
How do you detect heteroscedasticity?
6. What is the Durbin-Watson Statistic?
Does it have limitations?
7. What is Ridge Regression?
When do you use it?
8. What is a composite forecast?
If you have two time series, Xt and Yt, and their forecasts, how do you combine them together into one forecast?
9. How do econometricians define a stationary process?
Draw an example where a time series exhibits an I(0) process and its characteristic ACF plot.
10. You have a program that can only estimate ARMA models. However, you have data that is nonstationary of degree I(1). How could you estimate this ARIMA by using an ARMA?
11. You have the ARMA(1,0) process, (1 - f B) Xt = Zt. Please show the algebra to convert the AR process into an infinite series MA process
12. You have the ARIMA specification, (1 -
f B)(1 - B)1Xt = (1 + q B)Zt. Please write out the explicit
expression for Xt.
Note - these formulas will be given to you on the exam. You do not have to memorize them!
14. Please use a two-term Moving Average Forecast and a two-term
Exponential Smoothing Forecast for the data below: Round numbers
to the nearest tenth.
Choose Alpha to be a = 0.5
Note - I will give you these two formulas on the exam. You do not< have to memorize them!
15. Please calculate the Durbin-Watson statistic for the data below?
29.0 3.6 8.5 -0.7 -0.9
16. You estimated the following ARMA model, .Xt = 0.5 Xt-1 +Zt + 0.5 Zt-1. Please calculate its fit and forecasts below: