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(i) In the wage equation in Example $14.4,$ explain why dummy variables for occupation might beimportant omitted variables for estimating the union wage premium.(ii) If every man in the sample stayed in the same occupation from 1981 through $1987,$ would youneed to include the occupation dummies in a fixed effects estimation? Explain.(iii) Using the data in WAGEPAN include eight of the occupation dummy variables in the equationand estimate the equation using fixed effects. Does the coefficient on union change by much?What about its statistical significance?

(i) (ii) (iii) See video

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Chapter 14

Advanced Panel Data Methods

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part one. We need occupation dummies because different occupations are unionized at different rates and wages also differ by occupation. So if we submit binary indicators for occupation, the union wage differential may simply be picking up wage differences across occupations. And we include these dummies specifically because people change occupation over the period. This also explain for Part two, if every man stays in the same occupation throughout the period, we won't need the occupation dummies. We would not have to deal with their admitted variable bias problem. In Part three. We will choose on of the occupational categories as the base group and the estimated union which differential is not affected by our choice. The fix effect estimate on union because we get is 0.804 with a standard error of poin 0194 There is no difference between this estimate and the one without occupational controls. Mhm, Mhm, yeah,

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