A.     Estimate the parameter ö by regression analysis.

B.     What are 95% confidence intervals for the value of ö?

C.    You initially believed that ö is 50%. Should you reject this assumption?

 

The time series course does not teach regression analysis. You are assumed to know how to run a regression analysis, and you must run regressions for the student project.

 

Use the Excel regression add-in. The 95% confidence interval is the estimated â ± the t-value × the standard error of â. The t-value depends on the number of observations. Excel has a built-in function giving the t-value for a sample of N observations.

 

 

 

We are able to use the regression feature of Excel with the model of y = a+bx. But the first-order case for AR(1) models is of the form

Y_t - mu = phi(T_{t-1} - mu) + e_t

How is mu being considered in the y = a +bx model? If b is phi, then what does a represent? Would e_t represent the RSS term?

Thanks.