Introductory Econometrics: A Modern Approach 6th Edition by Jeffrey M Wooldridge

Exercise 3

In Example, define the growth in hourly wage and output per hour as the change in the natural log: ghrwage = ?log(hrwage) and goutphr = ? log(outphr). Consider a simple extension of the model estimated in:

ghrwaget = ?0 + ?1goutphrt +?2goutphrt - 1 + ut.

This allows an increase in productivity growth to have both a current and lagged effect on wage growth.

(i) Estimate the equation using the data in EARNS.RAW and report the results in standard form. Is the lagged value of goutphr statistically significant?

(ii) If ?1 + ?2 = 1, a permanent increase in productivity growth is fully passed on in higher wage growth after one year. Test H0: ?1 + ?2 = 1 against the twosided alternative. Remember, one way to do this is to write the equation so that ? = ?1 + ?2 appears directly in the model, as in Example 10.4 from Chapter 10.

(iii) Does goutphrt-2 need to be in the model? Explain.

Step 1 of 4

(i)

Estimating the regression equation:

The result is as follows:

The standard form of the regression model is:

The coefficient of the lagged is 0.457635, with the p-value 0.009 which is less than critical p-value of 0.05 at 5% level of significance. Hence, it is concluded that lagged, which is given by is statistically significant. It shall be noted that GOUTPH_1=.