Abstract
Studies of immigrants' destination language acquisition to date have focused on the individual. In contrast, this paper is concerned with the relationships among family members in the determinants of destination language proficiency among immigrants. A model of immigrant language proficiency is augmented to include dynamics among family members. It is tested using data on a sample of recent immigrants. Children are shown to have a negative effect on their mother's language proficiency, but no effect on their father's. There is a substantial positive correlation between the language skills of spouses. This is due to the correlation between spouses in both the measured and the unmeasured determinants of destination language skills, even when country of origin fixed effects are held constant.
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Notes
This approach has been used in empirical studies of English-language skills among immigrants in the United States (Chiswick and Miller 1992, 1998) and Australia (Chiswick and Miller 1995, 1996, 1999), Hebrew-language skills in Israel (Beenstock 1996; Chiswick 1998), French- and English-language skills among immigrants in Canada (Chiswick and Miller 1992, 1994a, 2001) and language skills among immigrants in Germany (Dustmann 1994). The model is highly robust across destination countries, time periods, countries of origin and legal status. See also, Espenshade and Fu 1997 and Stevens 1994 for sociological approaches to this issue.
The Principal Applicant is the person upon whom the approval to immigrate was based. Excluded from the survey are New Zealand citizens and those granted a visa while resident in Australia. Information on visa category is obtained from administrative records. The five main visa categories are Preferential Family, Concessional Family, Business Skills and Employer Nomination, Independent, and Humanitarian.
Variables that by construction of the data are common to both PAs and spouses are “visit of the PA to Australia prior to migration”, “reasons for choosing State”, “ethnic agencies contact”, and the family structure variables.
Using the same survey, but considering subsequent waves, Chiswick et al. 2005b show, however, that the influence of visa category on English-speaking skills diminishes with duration in the country.
Other the same measured variables, there is no gender difference in English-language proficiency within the Principal Applicant or the spouse category. When the data are pooled, the gender variable is significant (coefficient of −0.274, t of 3.85). This appears to reflect differences between MUSs and PAs. Controlling for MUS status reduces the gender variable to the margin of statistical significance.
Deleting the country-fixed effects has only a small impact on the equations' prediction success (percent):
Specification
Single equation
Bivariate probit
PA
MUS
Includes country-fixed effects (Table 2)
83.63
80.30
81.50
Excludes country-fixed effects
82.61
77.98
79.28
When the country-fixed effects are deleted from the equation, the correlation between the residuals increases to 0.467 (t=6.89). The linguistic distance measure remains negative but becomes statistically significant in the Principal Applicant equation but does not reach significance in the spouse equation.
The birthplace concentration data are from the 1991 Australian Census of Population and Housing (see Australian Bureau of Statistics 1993).
These data are from Fitzpatrick and Modlin's (1986) Direct Line Distances, International Edition.
Reference
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Acknowledgements
We appreciate the comments from Evelyn Lehrer and from the participants at presentations given to the Departments of Economics at the University of Illinois at Chicago and the Hebrew University of Jerusalem, the Department of Sociology at the University of Illinois at Chicago and the Annual Meeting of the North American Economics and Finance Association, January 2003, Washington, D.C., as well as those received from the referees. Chiswick acknowledges research support from the Institute of Government and Public Affairs, University of Illinois. Miller acknowledges financial assistance from the Australian Research Council. A fuller version of this paper with additional tables but with the same title is IZA Discussion Paper No. 460 (Chiswick et al. 2002).
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Appendix
Appendix
1.1 Definitions of variables
The study is based on the Longitudinal Survey of Immigrants to Australia (LSIA), a sample of Principal Applicant immigrants who arrived in Australia as offshore visaed immigrants in the 2-year period of September 1993 to August 1995. The data are from administrative records (for visa category only) and the wave one interviews conducted 5 to 6 months after immigration. Spouses who were granted approval to migrate to Australia as part of the PAs' migration application were also interviewed. The variables used in the statistical analysis are described below. For the statistical analyses, the relevant population is immigrants aged 15–64 years from the countries other than the developed English-speaking countries. These restrictions are applied to both the Principal Applicant and the Migrating Unit Spouse.
1.2 Dependent variable
English-speaking skills
Five levels of English-speaking skills are distinguished. They are: (i) English best (or English only); Speaks a language other than English best and speaks English: (ii) Very well; (iii) Well; (iv) Not well; (v) Not at all. In this study the first three categories are denoted “proficient”, while the remaining categories are denoted “not proficient”.
1.3 Independent variables
Visa group
Five visa groups represented by dichotomous variables: (i) Preferential Family; (ii) Concessional Family; (iii) Business Skills and Employer Nomination; (iv) Independent; and (v) Humanitarian. The benchmark group in the regression analysis is Independent.
Age at migration
This is Age (15 to 64 years) since the immigrants have all been in Australia for 5 to 6 months.
Educational
The continuous “Years of Education” variable was created by assigning years of full-time equivalent education to each of the nine levels of education available. They are: (i) Higher degree (19.5 years); (ii) Postgraduate diploma (17.5 years); (iii) Bachelor degree (16.5 years); (iv) Technical/professional qualification (15 years); (v) Trade (13 years); (vi) 12 or more years of schooling (13 years); (vii) 10–11 years (10.5 years); (viii) 7–9 years (8 years); and (ix) 6 years or less (6 years).
Female
Dichotomous variable equal to unity if female.
Birthplace
Fourteen birthplace regions are identified, namely: (i) UK and Ireland; (ii) Southern Europe; (iii) Western Europe; (iv) Northern Europe; (v) Eastern Europe; (vi) The USSR and the Baltic States; (vii) The Middle East; (viii) North Africa; (ix) Southeast Asia; (x) Northeast Asia; (xi) Southern Asia; (xii) North America; (xiii) South and Central America, including Mexico; (xiv) Caribbean, Central and West Africa, and Southern and East Africa. Immigrants from English-speaking developed countries (i.e., UK and Ireland, North America, and South Africa) are excluded from the analysis. The region of Caribbean, Central and West Africa, and Southern and East Africa has been excluded from the analysis as an insufficient number of immigrants are represented to permit construction of some of the auxiliary regressors employed in the analysis. Note that immigrants from New Zealand are not included in the survey. An additional birthplace dichotomous variable is set equal to unity for birthplaces that are Former British colonies.
Culture/country contact
Dichotomous variable equal to unity if the immigrant had cross culture/country contact in their former home country.
PA visited Australia
Dichotomous variable equal to unity for those from migrating units where the PA visited Australia prior to migrating.
Reason for choice of state
Dichotomous variable equal to unity when family and friends were the main reason for choosing the initial State/Territory settled.
Contact with ethnic agencies
Dichotomous variable equal to unity when the recent arrival had post-immigrant contact with an ethnic organization, religious organization, or voluntary welfare agency.
Expect to leave
Dichotomous variable equal to unity for PAs who expect to return to their former home country or to emigrate to another country.
Birthplace concentration
The percentage of those in the immigrant's region of residence, measured at the postcode level, born in the same country or region as the immigrant.Footnote 10
Distance
The kilometers between the major city in the immigrant's country of origin and the capital city of the wave one Australian State/Territory of residence.Footnote 11
Language distance
This variable is constructed from a measure of the difficulty of learning a foreign language for English-speaking Americans. It is based on a set of language scores (LS) measuring achievements in speaking proficiency by English-speaking Americans at the U.S. Department of State, School of Language Studies, reported by Hart-Gonzalez and Lindemann (1993). For the same number of weeks of instruction, a lower score (LS) represents less language facility, and, it is assumed, greater linguistic distance between English and the specific foreign language. For example, Italian is scored at 2.5 (in a range from 1 to 3) and Arabic is scored at 1.5. This methodology assumes symmetry across languages, that is, if a language is difficult for English-speaking Americans to learn, it is equally difficult for native speakers of that language to learn English (see Chiswick and Miller 1998).
Family structure
There are three dichotomous variables relating to family structure. They are unity: (i) if there are children in the household (KIDS); (ii) if other relatives who gained approval to migrate to Australia as part of the PA's migration application are present in the household (MUR); and (iii) if other relatives are present in the household (OR).
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Chiswick, B.R., Lee, Y.L. & Miller, P.W. Family matters: the role of the family in immigrants' destination language acquisition. J Popul Econ 18, 631–647 (2005). https://doi.org/10.1007/s00148-005-0008-0
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DOI: https://doi.org/10.1007/s00148-005-0008-0