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Queen's Economics Department Working Paper No. 784
Queen's University, Department of Economics, Kingston (Ontario)
This paper explores the determinants and labor market consequences for immigrants of proficiency in speaking the dominate language (English in the US, English or French in Canada). The statistical analysis is for adult men using the self-reported data, including data on language skills, available in the 1980 and 1981 censuses of the US and Canada, respectively. Fluency in the dominant language in the two countries is shown to vary systematically with the immigrant's skills, demographic characteristics, country of origin and economic incentive. That is, fluency is greater the younger the age at immigration, the greater the pre-immigration exposure to the dominant language, the longer the duration in the destination, the higher the level of schooling , and if the person immigrated unmarried, currently has children and lives in an area where few speak his native (non-dominant) language, among other variables. It is also shown that those who can expect to receive greater economic rewards from a higher level of language proficiency are more likely to make the investment and become more proficient. The determinants of earnings among immigrants are shown to be remarkably similar in the two countries; it is as if there is one earning determination process. Fluency in the dominant language has a large positive effect on earnings, independent of other personal characteristics and country of origin. The study shows the importance of explicitly incorporating dominate language fluency, and the determinates of dominant language fluency, in the criteria for allocating immigrant visas, if immigrant economic success is a policy objective. Canadian immigration policy has made more progress in this regards than U.S policy. Furthermore, this study shows that, because of the questions asked and the coding procedures, the data related to language in the U.S. census are superior to the data available in the Canadian census for both statistical and public policy analysis.
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