## Info

Source: Economic Report of the President, 1993. Data on Yfrom Table B-52, p. 407; data on X2 from Table 8-53, p. 408.

Source: Economic Report of the President, 1993. Data on Yfrom Table B-52, p. 407; data on X2 from Table 8-53, p. 408.

17.23. Use the data of exercise 17.22 but consider the following model:

Using the stock adjustment model (why?), estimate the short- and longrun elasticities of expenditure on new plant and equipment with respect to sales. Compare your results with those for exercise 17.22. Which model would you choose and why? Is there serial correlation in the data? How do you know?

17.24. Use the data of exercise 17.22 but assume that

Yt = a + 0 X* + ut where X* are the desired sales. Estimate the parameters of this model and compare the results with those obtained in exercise 17.22. How would you decide which is the appropriate model? On the basis of the h statistic, would you conclude there is serial correlation in the data?

17.25. Suppose someone convinces you that the relationship between business expenditure for new plant and equipment and sales is as follows:

Y* = a + 0 X* + ut where Y' is desired expenditure and X' is desired or expected sales. Use the data given in exercise 17.22 to estimate this model and comment on your results.

17.26. Using the data given in exercise 17.22, determine whether plant expenditure Granger-causes sales or sales Granger-causes plant expenditure. Use up to six lags and comment on your results. What important conclusion do you draw from this exercise?

Gujarati: Basic I III. Topics in Econometrics I 17. Dynamic Econometric I I © The McGraw-Hill

Econometrics, Fourth Models: Autoregressive Companies, 2004 Edition and Distributed-Lag

Models

CHAPTER SEVENTEEN: DYNAMIC ECONOMETRIC MODELS 711

17.27. Assume that sales in Exercise 17.22 has a distributed-lag effect on expenditure on plant and equipment. Fit a suitable Almon lag model to the data.

17.28. Reestimate Eq. (17.13.16) imposing (1) near-end restriction, (2) far-end restriction, and (3) both end restrictions and compare your results given in Eq. (17.13.16). What general conclusion do you draw?

17.29. Table 17.9 gives data on private fixed investment in information processing and equipment (Y, in billions of dollars), sales in total manufacturing and trade (X2, in millions of dollars), and interest rate (X3, Moody's triple A corporate bond rate, percent); data on Y and X2 are seasonally adjusted.

a. Test for bilateral causality between Y and X2, paying careful attention to the lag length.

b. Test for bilateral causality between Y and X3, again paying careful attention to the lag length.

c. To allow for the distributed lag effect of sales on investment, suppose you decide to use the Almon lag technique. Show the estimated model, after paying due attention to the length of the lag as well as the degree of the polynomial.

17.30. Table 17.10 gives data on indexes of real compensation per hour (Y) and output per hour (X2), with both indexes to base 1992 = 100, in the business sector of the U.S. economy for the period 1960-1999, as well as the civilian unemployment rate (X3) for the same period.

TABLE 17.9 INVESTMENTS, SALES, AND INTEREST RATE, UNITED STATES, 1960-1999

Observation

Investment

Sales

Interest

Observation

Investment

Sales

Interest