Autocorrelations adding seasonal lag of sales growth to interpret the coefficients in the model 3)Retail sales growing at a certain rate per month and involving the model to estimate a growt

Question 3:

We decide to use non-seasonally adjusted data on retail sales, adjusted for inflation. To begin with, we

estimate an AR(1) model with observations on the annualized monthly growth in real retail sales from

February 1972 to December 2000. We estimate the following equation:

Table 5 shows the results from this model:

A) What do the autocorrelations show and why?

B) Suppose we add the seasonal lag of sales growth (the 12th lag) to the AR(1) model to estimate the

equation:

Table 6 presents the results.

What do the autocorrelations show and why?

C) How can we interpret the coefficients in the model?

D) If retail sales grew at an annual rate of 5 percent last month and at an annual rate of 10 percent 12

months ago, the model predicts that retail sales will grow in the current month at an annual rate of?

Question 4:

A. Using the regression output in the above table, determine whether the estimates for b0 and b1 are

valid.

B. If this model is mis-specified, describe the steps we should take to determine the appropriate

autoregressive time-series model for these data.