78-83% of those who were overeducated in one of the years 1995-1997 were still overeducated five years later.<sup>37</sup>

# **_5.2. Determinants of overeducation_**

The results of the random effects logit model estimations are shown in Table 16. Note that the estimations are performed only for a sub-sample of individuals who have either a vocational education or a short, medium or long higher education. The reason for this is that the results concerning the incidence of overeducation in Section 5.1 revealed that the share of overeducated among those with no more than a primary or a secondary education is zero (see Table 13 and the comment regarding Table 9 in the text). As mentioned earlier, the mean sample values for this particular sub-sample are shown in Appendix Table A3.

Table 16 shows the results in terms of the estimated coefficients as well as their marginal effects. Coefficients in a logit model cannot be interpreted directly as marginal probabilities as they would in a linear regression and therefore their marginal effects have been calculated. Marginal effects show the change in the probability of being overeducated (in percentage points) caused by a one unit change in each of the explanatory variables evaluated at the mean values of all the explanatory variables.

In contrast with most other overeducation studies we are able to account directly for labor market experience in the host country, and therefore we have chosen to include all three variables: age, labor market experience, and years-since-migration (YSM) (and their squares)<sup>38</sup> in the equations.<sup>39</sup> This allows us to distinguish between labor-market relevant years spent in Denmark and years spent “just being here”. As a consequence, we generally find that age does not significantly affect the probability of being overeducated.<sup>40</sup> Danish labor market experience, on the other hand, has a strongly significant negative impact on the probability of being overeducated for both sub-groups of immigrants.

Since we can account directly for labor market experience acquired in Denmark, we find that YSM has a positive yet diminishing effect on the probability of being overeducated. This result is significant for immigrants with a foreign education, but not so for immigrants with a Danish

> 37 Analysing overeducation in Sweden, Böhlmark (2003) finds that more than 50% of workers found to be overeducated at the beginning of the study period are still poorly matched 10 years later (based on data for individuals observed in 1981 and 1991 and then for individuals observed in 1991 and 2000). Also, he finds that a considerable share of adequately matched workers that make transitions do so to poorer matches. See e.g. Rubb (2003b) for an analysis on the persistence of overeducation in the United States.

> 38 We start by describing the linear results separately and thereafter in combination with their squared counterparts. 39 Other studies which do not account explicitly for labour market experience capture this effect indirectly in the YSM variable, which therefore has a negative sign. In the study by Lindley and Lenton (2006), for example, this leads the authors to conclude that there is evidence of assimilation in overeducation. Although immigrants are more likely to be overeducated than natives upon arrival to (in this case) the UK, higher skilled immigrant workers tend to reduce this likelihood with duration in the UK. Our results are able to be more precise about the assimilation process by demonstrating that it is labour market attachment that reduces the likelihood of higher skilled immigrants being overeducated. Battu and Sloane (2004) include age rather than YSM or labour market experience (also for the case of Britain) and therefore their results are parallel to those of Lindley and Lenton (2006).

> 40 An exception is for immigrants with foreign-acquired educations, where age has a negative and diminishing impact.

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