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In some cases non-citizens can be hired, if it can be demonstrated that no citizen is available and qualified for the job.
Bratsberg et al. (2002) had a sample of around 200,000 foreign-born individuals, while Chiswick (1978) used a sample of about 1,900.
For Canada, higher-status occupations include management, finance, administration, natural and applied science, and other professional occupations. In the United States, these include management, business, finance, and administrative occupations.
The log of weekly earnings provides a measure of the percentage difference between the earnings of citizens, and those of non-citizens. For example, in Table 1 for Canada, the log of weekly earnings for male immigrants who were not citizens is 6.60; for male immigrants who were citizens, the log of weekly earnings is 6.70. Hence there is a difference of 10 logs points, or roughly 10%, between the earnings of the two groups.
Except among immigrants from developed countries.
The absolute difference and the statistical significance of the difference observed between citizens and non-citizens in Table 1 are shown in the "Observed" line of Table 2.
The adjusted data control for differences in age at immigration, years since immigration, education, and source region between naturalized and non-citizen immigrants. For earnings, the controls include these variables, except that age rather than age at immigration is used, and the adjusted estimates also control for various work attributes, including whether the immigrant speaks an official language (English or French), geographic location, full-time/part-time job status, occupation, industry, and marital status.
Includes the United States, Canada, Europe, Australia, and New Zealand.
This higher value in the last case may be partially due to the inclusion of some unauthorized immigrants with lower earnings in the non-citizen category.
Chiswick and Miller (2009) found that variables describing individual characteristics increased the explanatory power of the model much more than those describing source region characteristics. For example, among males, omitting individual characteristics from the model reduced the R-squared from 0.250 to 0.080, while dropping the country-of-origin variables reduced it from 0.250 to 0.211. The results were similar for females.
They include immigrants of all ages, whereas the citizenship rates reported in this study relate to adult (over age 25) immigrants. Hence, the levels may be different, but the trends are similar.
To demonstrate this effect, ideally one would track cohorts of entering immigrants as they accumulate years in the host country and observe the change in citizenship rates. Comparable longitudinal data for both Canada and the U.S. are not available for such an analysis. The next-best approach is to construct "quasi-cohorts" based on census data. Five-year entry cohorts (e.g., immigrants entering in the 1966-to-1970 period, the 1971-to-1975 period, and so on) are observed every ten years in the U.S. Census and every five years in the Census of Canada. Data on the citizenship rates of these cohorts are presented in Table 7. Since only infrequent observations are available for each cohort, the average across all cohorts is calculated and shown at the bottom of the table.
Some permanent residents can become citizens before three years, such as those who were on temporary visas before becoming permanent residents.
Once again, these results could be affected by the inclusion of unauthorized immigrants in the United States, which would tend to reduce naturalization rates in that country compared to those in Canada. However, the results in Table 7 are shown for both Canadian and U.S. immigrants from developed countries, among whom unauthorized immigrants are not an issue, and the overall conclusions remain the same.
For this section, the analysis uses the 1971 Census of Canada 1/3 sample, and the 1981, 1991, 2001, and 2006 Census of Canada 20% sample microdata files to examine changes in citizenship rates among immigrants to Canada. For the United States, the analysis uses the following: the 1970 U.S. Census 1% sample; the 1980, 1990, and 2000 5% sample public use microdata files; and the combined 2005, 2006, and 2007 American Community Survey (ACS) (Ruggles et al. 2009). Only immigrants aged 25 years or over are included in the calculation of citizenship rates. The Canadian sample includes only landed immigrants, since non-permanent residents were not enumerated in the censuses before 1991. In the U.S. sample, immigrants include all foreign-born regardless of legal status, since information on legal status is not available in the data. Since authorized immigrants cannot be distinguished from unauthorized immigrants in the U.S. data, citizenship rates are calculated both with and without immigrants from Mexico (Mexico is probably the primary source of unauthorized immigrants to the United States).
Alternatively, logistic regression models were used. The results are very close to those obtained from linear probability models. The results from the linear probability models are presented, since it is more straightforward to interpret the coefficients and to conduct decomposition.
This is done following one variation of the Oaxaca decomposition method (Oaxaca and Ransom 1994). In this approach, the 'explained' component is calculated as the sum of the differences between group means and the means of the pooled sample of all groups; the differences are weighted by the model coefficients of the pooled sample.
Both the decline in the citizenship rate and the effect of compositional change on the decline in the rate will be overestimated in the analysis based on the first U.S. population as a result of the inclusion of a rising number of unauthorized immigrants, particularly for the period since 1990. The effect of compositional change on the decline in the rate may be overestimated because the increasing share of immigrants from Central and South America is overestimated when unauthorized immigration is rising and given that immigrants from these regions tend to have a low probability of becoming citizens. There may be changes to other compositional variables resulting from an increasing share of unauthorized immigrants which would affect the findings as well. However, as noted earlier, the number of unauthorized immigrants was not rising rapidly prior to the 1990s; consequently, the effect on the results will be less for the period from 1970 to 1990. The results based on the second population, excluding Central American and South American immigrants, will tend to underestimate the effect of compositional change on the decline. That is because excluding these immigrants would rule out the effect of the rising share of Mexican immigrants on the change in the rate, an effect which is negative given the very low tendency of eligible Mexican immigrants to become citizens.
Excluding the Caribbean, Central America and South America, the naturalization rate is seen to increase by 2.4 percentage points from 1991 to 2006 in the raw data, whereas there was no change when these countries were included. Other research suggests that the citizenship rate, when calculated on the basis of eligible immigrants, has risen in the U.S. since the mid-1990s (Fix, Passel, and Sucher 2003).
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