In this equation, _i_ represents a single individual, _e_ stands for the type of education and _c_ for the country of origin.<sup>13</sup> The specification is related to the econometric models previously used in the migration literature for estimating earnings assimilation as discussed earlier.<sup>14</sup> After equation (1) is estimated for each cohort (1970-9 and 1980-9 arrivals) for each census and OP measures, we construct synthetic individuals who are identical in terms of their personal characteristics and human capital endowments but differ in terms of their origin countries. We then predict the occupational placements, _O_ ˆ _P_  _e predicted_ (ln _OP_ ) , of these hypothetical migrants in each decade based on the estimation results. As a result, all the variation in the predicted levels of performance stems from the coefficients on country dummies, _β5_ , since these hypothetical individuals are identical in terms of their individual characteristics. Next, we ˆ ˆ ˆ calculate the predicted Occupational Placement Improvement  _OPc_ (, _t_  10)  _t_  _OPc_ , _t_  10  _OPc_ , _t_ as the predicted change in the level of professional achievement of hypothetical individual _i_ from country _c_ , between years t and t+10.

We construct two hypothetical individuals per country (Table 1), each with at least a Bachelor’s Degree (earned before migrating), and who were at 25 years old at the time of their arrival in the United States. The first person is assumed to arrive in 1975, and the second in 13 In accordance with most studies explaining earnings, the dependent variable is logged, which enables us to interpret the coefficient of each explanatory variable as the approximate percentage rather than unit change in the occupational placement index.

14As stated by Borjas (1995) and LaLonde and Topel (1990) there are three types of biases that can affect the accuracy of assimilation estimates measured in our case as _β3_ . These are cohort effects, period effects and the return migration effect. Cohort effects refer to unobservable changes in the quality of cohorts entering the US at different times. To account for the potential biases, we follow the progress of a group of individuals who arrive at a given time through several censuses, so that the errors due to unobserved differences cancel out. Period effects reflect modification of labor market conditions from one census to another. To eliminate them, studies focusing on earnings measure assimilation of migrants relative to a comparison group expected to have been influenced similarly by the changes in the economy. In our particular case, since the paper focuses on cross-country comparisons, period effects should be of no significant concern since it is assumed that changes in labor market conditions affect all immigrants. A third source of bias is the non-random cohort attrition related to either mortality or return migration. The bias introduces by the mortality rate, is dealt with by imposing upper limits on the ages of individuals. Later on in this paper, we attempt to address the concerns about return migration by identifying the countries with the highest rate of attrition and re-estimating our equations after excluding those countries from the sample.

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