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202 395 6974 P.21/37
dropouts tend to change jobs more often than graduates, so this effect may bias our results.
If the return to mobility is similar for low and medium skill workers, we may be overstating
the return to experience for low skill workers. In this section we examine this possibility.
The coefficients on these turnover variables are interesting in their own right and extend
the work on returns to mobility to include low wage workers.
In this section we use a somewhat different specification. Let Awit denote the change
in log wages from the beginning to the end of the year,
A
Since total weeks worked is the first difference of actual experience, this equation is just
a first differenced version of the regression above and can be thought of as another fixed
effects estimator. We do not instrument here for two reasons. First, job changes should be
considered to be endogenous to wages, so without instruments for job changes IV results
would be difficult to interpret. Second, instrumenting does not substantially change our
results. Our results in the previous section were robust to instrumenting, and the results
in this section are as well.6
In order to account for the effects of mobility on wage growth we control for the number
of job transitions. Let Trit denote the number of transitions made by individual i dur-
ing year t. To measure the effect of transitions on wage growth we can include it in the
regression,
T
Our goal is to examine the effect on Y₁ⱼ of including Trit in the regression.
When a worker changes jobs, the job match can end in two ways. One possibility is that
the worker may be let go without finding a new job first. A second possibility is that the
worker may terminate the job because he has a job prospect that is preferable. Typically we
may expect wage gains to be positive for the second type of worker since he left the original
job because his expected wage gain was large.⁷ However we would expect wage losses for
the first type of worker as a result of the loss in job-specific human capital and matching
'When we instrument for weeks worked but not turnover the coefficients are extremely close to those
presented here.
'Although they also lose experience so the net effect could be negative.
17
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"ocrText": "JUL-03-2000 12:20\nOMB DEP DIR MGMT\n202 395 6974 P.21/37\ndropouts tend to change jobs more often than graduates, so this effect may bias our results.\nIf the return to mobility is similar for low and medium skill workers, we may be overstating\nthe return to experience for low skill workers. In this section we examine this possibility.\nThe coefficients on these turnover variables are interesting in their own right and extend\nthe work on returns to mobility to include low wage workers.\nIn this section we use a somewhat different specification. Let Awit denote the change\nin log wages from the beginning to the end of the year,\nA\nSince total weeks worked is the first difference of actual experience, this equation is just\na first differenced version of the regression above and can be thought of as another fixed\neffects estimator. We do not instrument here for two reasons. First, job changes should be\nconsidered to be endogenous to wages, so without instruments for job changes IV results\nwould be difficult to interpret. Second, instrumenting does not substantially change our\nresults. Our results in the previous section were robust to instrumenting, and the results\nin this section are as well.6\nIn order to account for the effects of mobility on wage growth we control for the number\nof job transitions. Let Trit denote the number of transitions made by individual i dur-\ning year t. To measure the effect of transitions on wage growth we can include it in the\nregression,\nT\nOur goal is to examine the effect on Y₁ⱼ of including Trit in the regression.\nWhen a worker changes jobs, the job match can end in two ways. One possibility is that\nthe worker may be let go without finding a new job first. A second possibility is that the\nworker may terminate the job because he has a job prospect that is preferable. Typically we\nmay expect wage gains to be positive for the second type of worker since he left the original\njob because his expected wage gain was large.⁷ However we would expect wage losses for\nthe first type of worker as a result of the loss in job-specific human capital and matching\n'When we instrument for weeks worked but not turnover the coefficients are extremely close to those\npresented here.\n'Although they also lose experience so the net effect could be negative.\n17"
}