Immigrant Unemployment: The Australian Experience

Immigrant Unemployment: The Australian Experience1

Paul W. Miller* and Leanne M. Neo*

ABSTRACT Between 1980 and 1996 both male and female immigrants experienced higher unemployment rates than Australia-born workers. In 1996, for example, the unemployment rate for the overseas-born was 9.8 per cent, compared with 8.1 per cent for the Australia-born. A multivariate analysis is used in this article to examine unemployment rate differentials between Australia-born and immigrants from English-speaking countries and immigrants from non-English-speaking countries. A feature of the analysis is decomposition of unemployment rate differences between birthplace groups into a component attributable to the different characteristics of the birthplace groups (e.g. different mean levels of education) and a part that is viewed as an impact associated simply with being foreign born. The analyses reveal that the principal factors that influence employment success in the Australian labour market are educational attainment, age, qualifications and, among the foreign-born, duration of residence in Australia and English language proficiency. Also, unemployment rate reductions associated with additional years of education are not as large for immigrants from non-English-speaking countries as they are for the Australia-born or for immigrants from English-speaking countries. The results suggest that if immigrants’ marketable characteristics were rewarded in the labour market in the same way that the Australia-born’s characteristics are rewarded, then immigrants would experience considerably lower unemployment rates than those of the Australia-born. The unemployment rate differentials actually observed in the labour market arise because this potential advantage is offset by “unjustified” factors. This suggests a role for skill adaptation courses, competency based skill standards and a strengthening of affirmative action programmes for ethnic minorities. * Department of Economics, The University of Western Australia. Published by Blackwell Publishers Ltd., 108 Cowley Road, Oxford OX4 1JF, UK, and 350 Main Street, Malden, MA 02148, USA.

© 1997 IOM International Migration Vol. 35 (2) 1997 ISSN 0020-7985

156

Miller and Neo The study also shows that recent immigrants are at a pronounced unemployment rate disadvantage, and that this disadvantage persists for a considerable period. This result differs from recent findings for the US labour market where duration of residence effects are short-lived. It is suggested that this difference may be associated with the Australian labour market being less flexible than the US labour market.

INTRODUCTION Immigration has been a major contributor to workforce growth in Australia. In 1991, twenty six per cent of the workforce were immigrants and a further thirteen per cent were the Australia-born children of immigrants. A large proportion of immigrants are of British and continental European origins, although among recent waves Asian immigrants are more important.2 This reflects changes in Australia’s immigration policy as well as supply and demand factors in the global economy.3 One important consideration in this regard is the potential for economic success in Australia. While the net influence of this in the migration decision depends on relative degrees of economic well-being in the country of origin and the country of destination, a first step to understanding its significance is to examine the economic wellbeing of immigrants in the country of destination. A prime determinant of economic well-being is whether the individual has a job. Immigrant employment outcomes are therefore the focus of this study. Immigrant employment outcomes in Australia were the subject of a series of studies based on data collected during the 1980s. These revealed that although immigrants experienced relatively high rates of unemployment during their first few years Australia, the disadvantage for most groups dissipated with increased duration of residence. Since these studies were conducted, the Australian labour market has deteriorated and the source of immigrants has continued to shift towards the Asia region. Establishing whether the findings from earlier research carry across to the labour market of the 1990s is therefore a research priority. In addition, advances in research methodology employed in previous studies are now possible, and a feature of the current study is that the unemployment rate differential between Australia-born and immigrant groups is decomposed into components which, on the basis of the model proposed, can be viewed as justified and unjustified.

IMMIGRANTS’ RELATIVE UNEMPLOYMENT EXPERIENCE Tables 1, 2 and 3 (pages 175-176) present data from The Labour Force (Australian Bureau of Statistics, selected years) on the unemployment situation of immigrants and the Australia-born. Table 1 shows the trend of

Immigrant unemployment: the Australian experience

157

unemployment experienced by both overseas-born and Australia-born from August 1980 to August 1996. These data indicate that the overseas-born have consistently had unemployment levels between 0.4 and 2.2 percentage points higher than the Australia-born throughout the period, with the gap rising to around 3 percentage points from 1991 and falling to 1.7 percentage points in 1996. Both male and female immigrants are characterized by an unemployment rate disadvantage and by a worsening of this disadvantage in recent years. Unemployment outcomes vary by characteristics such as age, educational attainment and country of origin. The relative unemployment rate disadvantage experienced by some groups of immigrants may depart considerably from the average portrayed in Table 1. Table 2, in which unemployment rates at August 1996 are cross-classified by birthplace and age, indicates that the overseas-born experience higher unemployment rates than the Australia-born for both males and females in each age group except teenagers. For example, among the 35-44 year age group the unemployment rate for Australia-born males is 5.7 per cent compared to 8.1 per cent for overseas-born males. For the same age group the unemployment rates of Australia-born and overseas-born females are 5.2 per cent and 8.0 per cent respectively. Table 3 shows that unemployment rates are lower for immigrants from Englishspeaking countries than for immigrants from non-English-speaking countries. Indeed, immigrants from English-speaking countries experience an unemployment rate marginally lower than the Australia-born (7.9 per cent versus 8.5 per cent for males and 6.6 per cent versus 7.5 per cent for females). The unemployment rate disadvantage experienced by immigrants has been examined in a number of studies based on the 1981 and 1986 censuses and survey data collected in 1983 and 1987. A number of techniques were employed in the studies (tabular, ordinary least squares, logit and probit), and there is considerable variation in the types of influences on labour market outcomes taken into account. For example, Miller (1986a) emphasizes the significant impact of pre-immigration knowledge about job opportunities in Australia on immigrant labour market outcomes. In comparison, Beggs and Chapman (1988) focus on post-immigration factors, such as investment in Australian qualifications and the accumulation of labour market experience in Australia, as determinants of immigrants’ relative labour market position. There is also considerable variation in the age groups studied. For example, Chapman and Miller (1985) and Inglis and Stromback (1986) focus on the labour market outcomes of 15-64 year old males and females, while Miller (1986b) and Wooden (1991) focus on the labour market success of 15-30 and 18-64 year old males and females respectively. Finally, the studies differ in terms of groups that are the primary focus of analysis. Jones (1992) analyses unemployment for four main ancestry groups, namely the Anglo-Celts, Dutch, Italian and Chi-

158

Miller and Neo

nese. Other studies generally define the group in focus by gender status. For instance, Beggs and Chapman (1988) focus on males only, while other studies (Brooks and Volker, 1985; Miller, 1986a; Inglis and Stromback, 1986; Chapman and Miller, 1985; Miller, 1986b; Wooden, 1991 and Chiswick and Miller, 1992) focus on both males and females. The summary in Table 4 (pages 177-179) shows that immigrants experience higher unemployment rates than comparable Australia-born persons, even when other determinants of unemployment (such as educational attainment, age and marital status) are held constant. This finding carries over to both males and females and to each age group. There appears to be four main reasons for this. First, human capital skills acquired overseas may not be fully transferable to the Australian labour market. Second, immigrants may have less information about job opportunities in the Australian labour market than the Australia-born. In addition, employers may face difficulty in assessing the productivity of the foreign born which will result in poorer employment prospects. Third, immigrants may have poor English language skills and, as a result, face inferior labour market prospects. Where this is a major contributor to the immigrants relatively high unemployment rate, the immigrant unemployment rate disadvantage should decline with duration of residence (Wooden, 1991). Fourth, immigrants may face discrimination from employers or fellow employees, a factor that will also increase the likelihood of unemployment (Chapman and Miller, 1985). The labour market disadvantage experienced by immigrants is expected to diminish with their increased duration of residence in Australia. The empirical evidence summarized in Table 4 is consistent with this expectation, although it should be noted that there is some disagreement over the nature of the unemployment rate-duration of residence relationship. For example, Miller’s (1986a) analysis of 1981 Census data indicates a U-shaped relationship between duration of residence and unemployment rates, while Brooks and Volker (1985) and Inglis and Stromback (1986) suggest that as period of residence increases, the unemployment probabilities of immigrants approach that of Australia-born persons in a monotonically decreasing form. A major feature reported in many studies is that unemployment rates for immigrants from English-speaking countries are lower than for those from nonEnglish-speaking countries, irrespective of gender. Among immigrants from non-English-speaking countries, those arriving under the humanitarian migration category and those from the Mediterranean region experience the highest unemployment rates (Miller, 1986a and 1986b; Wooden, 1991; Jones 1992; Chiswick and Miller, 1992). Another feature of the studies of immigrant labour market outcomes is that most report educational attainment being strongly associated with reduced

Immigrant unemployment: the Australian experience

159

unemployment rates. However, Miller’s analyses of 1981 Census data (1986a) and the First-Institute Manpower Program Survey data (1986b) show that additional years of education are associated with smaller unemployment rate reductions among immigrants, with the smallest reductions being experienced by immigrants from non-English-speaking countries (Jones, 1992). This suggests that human capital acquired in non-English-speaking countries is less internationally transferable than that acquired in English-speaking countries. The different links between educational attainment and unemployment rate reductions for the native-born and foreign-born result in additional years of education being associated with an increase in the relative unemployment rate among immigrants (Beggs and Chapman, 1988). This phenomenon emphasizes the difficulty faced by Australian employers in assessing the value of overseas education. Other studies have reported on unemployment rate effects associated with postarrival qualifications, though there is no agreement in this respect. Jones (1992) suggests that foreign qualifications provide weaker protection against unemployment than qualifications acquired after arrival, irrespective of ethnicity, whereas the study by Inglis and Stromback (1986), based on earlier data, indicates that the impact of a qualification acquired abroad on the unemployment rates does not differ from that of a qualification acquired in Australia. Some differences have been reported in findings relating to men and women. Of major importance in this regard is that most studies conclude that the human capital effect is not significant among female immigrants. For example, Chiswick and Miller (1992) report that qualifications only increase the labour force participation rate among female immigrants, whereas they tend to increase labour force participation and reduce the unemployment rates among male immigrants. Inglis and Stromback (1986) report that the impact of English language proficiency (another form of human capital) on the unemployment outcome is insignificant among female immigrants which contrasts to a negative and significant effect on the male immigrant predicted unemployment probability. In summary, the immigrant unemployment rate disadvantage varies by country of origin, and is particularly pronounced for immigrants from nonEnglish-speaking countries. Educational attainment, qualifications, duration of residence in Australia and English-language proficiency are shown to generally affect labour market outcomes in Australia, although the effects differ by country of origin and by gender. Disaggregation of statistical analyses by these characteristics is therefore an important lesson drawn from this overview. As noted in the Introduction, establishing whether the findings in Table 4 carry over to the 1990s, and refining the analysis to distinguish the “justified” and “unjustified” components of the immigrant unemployment rate differential, are the research priorities addressed in this study.

160

Miller and Neo

A MODEL OF UNEMPLOYMENT The first part of this section discusses the model of unemployment using the concept of “the tendency to be unemployed” which provides a framework that enables unemployment to be related to the individual characteristics believed to influence labour market performance. These individual characteristics and their relationships with the unemployment status of individuals are then discussed and the section concludes with a discussion of data source for the empirical analysis. An individual’s tendency to be unemployed is viewed as being influenced by personal characteristics. Hence we may write Ii* = Xi’β, where Ii* is the index of the tendency to be unemployed which is assumed to be a linear function of a vector of the characteristics of individual i, denoted by Xi. β is a vector of unknown weights of the vector X, which will be estimated. The relationship between the values of I* and the state of unemployment U is assumed to be monotonic. Whether or not an individual is unemployed therefore depends on a comparison of I*, which reflects an individual’s particular circumstances, with a critical value of the index I. The determination of employment/unemployment status is then given as: if I* > I , the individual is unemployed, otherwise the individual is employed.4 It is important to note that the tendency to be unemployed index I* is unobservable. All that we observe is a binary indicator variable U which takes the value of one if the individual is unemployed. Hence, the case where U takes the value of one corresponds to I* > I , and the case where U takes the value of zero corresponds to the employment outcome with I* ≤ I . To link the observable indicator of unemployment status (Ui) to the characteristics of the individual (Xi), we may write the conditional probability of being unemployed as: Prob(Ui/Xi) = Prob (Ii* > I ) = F(Xi’β)

(1)

where F denotes a cumulative distribution function. The dichotomous choice between employment and unemployment can be examined by several techniques, including linear probability, logit and probit methods of estimation. The logit model is employed in the analyses presented below. The vector of characteristics X expected to influence unemployment outcomes includes specific migrant variables (e.g. birthplace and period of residence in Australia) and other characteristics applicable to both the Australia-born and immigrants (e.g. age, sex, marital status, educational attainment, possession of

Immigrant unemployment: the Australian experience

161

qualifications, number of children, etc.). Some of the relationships expected between unemployment and the main explanatory variables are discussed briefly below: Birthplace is expected to influence unemployment status as it will capture elements of discrimination and aspects of the non-recognition of foreign qualifications that cannot be readily measured by other means. For example, if overseas educational qualifications, skills and experience are not fully recognized in Australia, and information on the country in which the particular skills were acquired is not available, these influences may be proxied by a variable for country of birth. A priori, it is expected that the foreign-born will have higher unemployment rates than the native born, and the extent of this disadvantage will vary with the economic and social distance of the country of origin from Australia. Period of residence is thought to be an important determinant of immigrant unemployment for the following reasons: First, as period of residence in Australia lengthens, immigrants can be expected to acquire Australian skills more suited to Australian employers’ requirements. Some of these skills may not be adequately measured by variables such as educational attainment and language proficiency and so may be indexed only by duration of residence. Second, immigrants who have resided in Australia for a reasonable period would have gained more information about Australian job opportunities. Third, employer or fellow employee discrimination faced by recent immigrants in the workforce is expected to diminish with increased duration of residence. In summary, because immigrants are expected to gradually adjust to the circumstances of the Australian labour market, there should be an inverse relationship between period of residence and unemployment. An inverse relationship between educational attainment and unemployment is expected because level of education may enhance an individual’s productivity, thereby making him/her more employable (Miller, 1989). Another reason is that employers may use education as a screening device to identify the ablest individuals in the pool of job applicants. Human capital, which includes general skills and specific human capital learned on the job, should be positively related to an individual’s age. Among young individuals, particularly teenagers, a low level of specific human capital may increase the probability of them being laid off and also increase their incentive to quit; since employers face low lay-off costs and young workers are less constrained by family commitments and financial responsibilities than prime-age workers. This suggests that the younger age group may be characterized by high turnover which is an important contributory factor to a relatively high unemployment rate. On the other hand, the prime age male group, who are

162

Miller and Neo

more likely to have acquired a high level of specific human capital and have strong family commitments, will generally have a lower turnover rate. A strong inverse relationship between age and the probability of unemployment should therefore be a characteristic of the data. The impact of marital status is likely to vary by gender. From the perspective of supply considerations, the greater family responsibilities of married males are expected to increase their incentive to work, while on the demand side, employers are more likely to employ married males because they are held to have greater work commitments, be more reliable and potentially more productive. Amongst females, the relationship between being married and the unemployment rate is difficult to determine a priori. On balance, married women’s lower degree of labour force attachment, relative to single women, may result in a lower measured unemployment rate. Ability to communicate in English will be necessary in the majority of jobs outside non-English linguistic enclaves. Immigrants with poor English skills will have access to fewer jobs and therefore are expected to have relatively high unemployment rates. However, immigrants who speak a language other than English at home, and who report that they are proficient in English, could be at an employment advantage compared with the Australia-born. This advantage could arise where immigrants have access to employment in firms where only English is spoken and also in firms where the immigrant’s mother tongue is spoken. As the latter market is expected to be small in Australia, any employment advantage to immigrants that arises from this source is likely to be small. A number of other variables will be included in the vector X, for example, the number of children in the family, the spouse’s employment status and locality. While their effects will not be considered in detail here, relevant comments will be provided in the discussion of empirical results. While other variables might influence employment status (e.g. whether the immigrant is a refugee and employment history), information on these was not collected at the Australian Census and it is therefore not possible to quantify their effects on the unemployment outcome. This restriction on the model specification should be kept in mind when interpreting the results. The empirical analyses presented below are based on data from the 1991 Australian Census of Population and Housing Sample File (Australian Bureau of Statistics, 1994), which is a one per cent sample of households in occupied private dwellings and a one per cent sample of persons in non-private dwellings. The sample comprises 39,810 males and 28,694 females5 aged between 15 and 64 years, in the labour force, residents of Australia, and not in school or at educational institutes at the time of the Census. A general description of the variables employed in the empirical work is given in the Data Appendix (pages 172-174).

Immigrant unemployment: the Australian experience

163

EMPIRICAL ANALYSIS OF THE LABOUR MARKET OUTCOMES OF THE AUSTRALIA-BORN AND IMMIGRANTS Tables 5 and 6 (pages 180-181) contain estimates from the logit models of unemployment for males and females respectively. Four equations are listed in each Table. The first is for the total sample (i.e., Australia-born and foreignborn), the second lists estimates obtained when the Australia-born are studied separately, and the third and fourth columns contain results for when the foreign-born from English-speaking countries and the foreign-born from nonEnglish-speaking countries are studied separately. The coefficients give the effect on the log-odds [ln U/(1-U)] of the variables listed in the left hand column. A positive coefficient indicates a higher probability of unemployment; a negative coefficient indicates a lower probability of unemployment. Most of the variables are shown to be statistically significant determinants of unemployment outcomes. Of particular relevance is the birthplace variables in the column (i) results. These show that unemployment rates are higher among immigrants from English-speaking countries than the Australia-born, and even higher among immigrants from non-English-speaking countries. As the models estimated hold constant the observable skills (e.g. education, qualifications, age, language etc.) of the labour force participants, these positive birthplace effects would reflect the presence of unobservable characteristics that are correlated with birthplace (e.g. motivation, ability), or discrimination in labour market outcomes on the basis of birthplace. The latter explanation is consistent with the usual definition of multivariate regression coefficients as the effect of the variable in question when all other factors in the model of unemployment are held constant. It is apparent from the column (i) results that, for males, regional factors are important only among the Australia-born, with residents of both non-metropolitan areas and ACT (Australian Capital Territory)/Tasmania having higher unemployment rates than residents of metropolitan areas. Such a finding might be expected where, upon arrival, migrants settle in regions of low unemployment for their set of observable and unobservable characteristics. Among females, the ACT/Tasmania variable is insignificant for all birthplace groups while the non-metropolitan variable is positive and significant (at the 10 per cent level or better) for all birthplace groups. The different results for males and females with respect to the location variable would be consistent with many female immigrants being tied movers. Years of education is an important factor leading to lower unemployment rates for all groups, though it is noted that the estimated coefficients are much smaller for immigrants from non-English-speaking countries. This finding is consistent with a major theme from studies reviewed in Table 4. Similarly, possession of

164

Miller and Neo

vocational qualifications is associated with unemployment rate reductions among males, though the impact in this regard is less among immigrants from non-English-speaking countries. Among females, however, it is only among the Australia-born that possession of qualifications is associated with lower unemployment. These findings are consistent with previous studies (Table 4). It would appear therefore that debate during the last decade in Australia about the non-recognition of skills acquired in non-English-speaking countries has done little to ease the problems faced by immigrants in this regard. Unemployment rates decrease with age up to around 50-55 years for Australiaborn males and females, and 40 years for male and female immigrants from non-English-speaking countries. Among immigrants from English-speaking countries, age effects peak at 40 years for males and 50 years for females. This U-shaped pattern most likely reflects the fact that many of the skills possessed by older cohorts are no longer relevant in the current labour market, a factor that would increase their likelihood of unemployment. This line of argument is also advanced in labour economics literature for the lower earnings among older employed individuals compared to those of middle age. Compared with the unmarried, those who are married and have a spouse who is not unemployed have lower unemployment rates. Where the spouse is unemployed, however, unemployment rates are much higher. Unemployment rates also tend to increase with the number of dependent children. As these models are estimated on a sample of labour force participants, this effect of children should be interpreted as deriving from limitations on the types of work that can be undertaken and from welfare system effects. While it is noted above that the ceteris paribus unemployment rates for foreignborn are higher than for the Australia-born, the unemployment rates of the foreign-born decrease at a decreasing rate with duration of residence in Australia. This result is consistent with the findings from studies reviewed in Table 4. The maximum reduction in this regard occurs after about 22 years of residence in Australia, which is slightly greater than the mean level of residency. The increases in unemployment beyond that level of residency presumably reflect cohort effects, with the groups that arrived in Australia during the 1960s having skills that are less relevant to the current Australian labour market than immigrants who arrived in the 1970s and 1980s. Finally, language skills are an important determinant of unemployment, but only among immigrants from non-English-speaking countries. This finding is consistent with Wooden’s (1991) conjecture concerning the source of the unemployment rate disadvantage experienced by refugees in Australia. The general patterns described above are quite robust across the specifications. However, while providing insights into the significance or otherwise of particular variables as determinants of unemployment, the estimates are not

Immigrant unemployment: the Australian experience

165

informative of the quantitative impact of the variable on unemployment. To this end one needs to compute partial effects. In the case of continuous variables (education, age, number of children, duration of residence) this is quite straightˆ (U)(1 - U), where βˆ is the forward, with the partial effect being ∂U/∂Xk = β k k estimated coefficient attached to a particular variable (Xk). For binary variables, however, the computation of partial derivatives is inappropriate, and it is conventional to base discussion of estimated impacts on differences between the predicted probabilities for different categories, for example, individuals residing in non-metropolitan areas and for the benchmark group of individuals from metropolitan areas.6 Relevant partial effects presented in Table 7 (page 182) show that an additional year of education results in a reduction in the predicted unemployment rate of over two percentage points for Australia-born males and for male immigrants from English-speaking countries. The comparable unemployment rate reductions among females are in the order of 1.6 to 1.8 percentage points. For both male and female immigrants from non-English-speaking countries, unemployment rate reductions associated with extra years of schooling are quite low: 0.6 of one year for males and 0.4 of one year for females. Unemployment rates decline with age, although unemployment rate reductions are only of the order of one-half a percentage point per year when evaluated at age of 30 years.7 A similar reduction in predicted unemployment rates results from increases in the period of residency in Australia, when evaluated at 10 years of residency in Australia. From an examination of the unemployment rate effects associated with the dichotomous variables, it is apparent that there are considerable ceteris paribus unemployment rate effects associated with birthplace. Hence, in the column (i) partial effects for the total sample, male immigrants from English-speaking countries are revealed as having predicted unemployment rates eight percentage points higher than their Australia-born counterparts, while male immigrants from non-English-speaking countries are shown to be at a nine percentage point unemployment rate disadvantage. In the female labour market, the respective unemployment rate disadvantages of the foreign-born are 11 and 17 percentage points for immigrants from English-speaking and nonEnglish-speaking countries respectively. English language deficiencies are also associated with higher rates of unemployment. Compared with monolingual English speakers, those who speak a language other than English at home and self-report their English-speaking skills as “good”, have unemployment rates two percentage points higher. Those who speak a language other than English at home and self-report their Englishspeaking skills as “poor”, have an unemployment rate disadvantage of 4.4 percentage points in the male labour market and 6.7 percentage points in the

Miller and Neo

166

female labour market. As expected, the unemployment rate effects associated with English-language deficiencies are evident only among immigrants from non-English-speaking countries. Moreover, when the analysis is restricted to this group (column (iv)), the unemployment rate effects are more pronounced than when the analysis is based on the total sample of immigrants (column (i)). Finally, Table 7 indicates that marital status and the employment status of the spouse exercise important influences on the unemployment outcome. Individuals who fall into the “married, spouse present” category have unemployment rates considerably lower than the other marital states provided that the spouse is not unemployed. Where the spouse is unemployed, however, the predicted unemployment rates are much higher: by over 30 percentage points in some cases.8 Some of the differences discussed above would be associated with immigrants having a higher incidence of unemployment than the Australia-born (e.g. the returns to education for immigrants from non-English-speaking countries) while others could be associated with immigrants having a lower incidence of unemployment (e.g. the locality effects). An overall assessment of the unemployment differences between birthplace groups can be obtained using the method proposed by Farber (1990). Under Farber’s method, the aim is to decompose the difference in the average predicted unemployment rates for two groups into a component that is attributable to the different characteristics of the birthplace groups (e.g. different mean levels of education), and a part that is to be viewed as an impact associated simply with being foreign born. For the purpose of this decomposition, the average predicted probability of unemployment is defined as: 1 P(X i' βˆ i ) = ni

ni

∑1/[1+ exp(−X j =1

ˆ

ij ' β i )

]

(2)

where i refers to the birthplace group (Australia-born, foreign-born from English-speaking countries, foreign-born from non-English-speaking countries) and j refers to the members of the specific group. Group i has a total of ni members. Using Farber’s methodology, the difference in average predicted probability between the Australia-born (a) and the foreign-born (f) can be categorized into two parts as follows: (3)

P(X' f βˆ f ) − P(X' a βˆ a ) = [P(X' f βˆ f ) − P(X' a βˆ f )] + [P(X' a βˆ f ) − P(X' a βˆ a )]

Immigrant unemployment: the Australian experience

167

The first term in square brackets on the right-hand side of this equation is the part of the unemployment rate differential that arises because of differences in the marketable characteristics of the two birthplace groups. For example, if the mean level of education of the Australia-born exceeds that of the foreign-born, then one would expect that this would result in the mean unemployment rate of the Australia-born being relatively low. Such an impact would be captured by this first term and it is the component of the unemployment rate differential that is conventionally labelled as “justified”. The second term in square brackets on the right-hand side of equation (3) is the component of the unemployment rate differential between the two groups that arises because the marketable endowments of the foreign-born are rewarded at rates different to those of the Australia-born in the labour market. This component of the unemployment rate differential is conventionally labelled “unexplained” or “unjustified” in the literature, and is often termed the “discriminatory” component of the unemployment rate differential. Where the “discrimination” terminology is adopted, the qualification that the effect could represent unmeasured factors that are correlated with birthplace should be noted. The results from this decomposition are presented in Table 8 (page 183).9 There are two key features of these results. First, for each comparison immigrants are shown to have endowments that should, ceteris paribus, lead to an unemployment rate lower than that of the Australia-born. In the case of males, the unemployment rate advantage would be 4.4 percentage points among immigrants from English-speaking countries, and three percentage points among immigrants from non-English-speaking countries. Among females the unemployment rate advantages of immigrants that should arise due to their favourable marketable characteristics are 5.9 and 7.3 percentage points for those from English-speaking and non-English-speaking countries respectively. These advantages derive from immigrants’ concentration in the relatively low unemployment metropolitan areas, a greater mean age and higher mean educational attainment. The second feature of the results is that each birthplace group’s labour market performance appears to be characterized by a substantial “unexplained” unemployment rate disadvantage. For immigrants from English-speaking countries, the unexplained unemployment rate component approximately offsets the advantage the immigrants would otherwise have gained from their favourable endowments. For immigrants from non-English-speaking countries, however, the unexplained component is sufficiently strong that it more than offsets the advantage associated with their favourable endowments. The unexplained component for immigrants from non-English-speaking countries is valued at almost seven percentage points in the case of males and almost 14 percentage points among females.

168

Miller and Neo

The estimates of the “unjustified” component of immigrants’ unemployment rate situation displayed in Table 8 are approximately three percentage points lower than estimates based on the more restrictive dummy variable approach in the unemployment rate model (see Table 7). These calculations were repeated using estimates of the unemployment rate model obtained using ordinary least squares. The basic patterns evident in Table 8 carry across to these alternative decompositions, indicating the major findings are not sensitive to choice of model. One aspect of the results in Table 8 which may be surprising is the size of the “unexplained/unjustified” component in the unemployment rate differential between the Australia-born and immigrants from English-speaking countries, particularly for males where it is comparable to the effect among immigrants from non-English-speaking countries. A number of studies have used the dummy variable approach to assess the ceteris paribus unemployment rate disadvantage of immigrants. Brooks and Volker (1985) distinguish immigrants from four birthplace regions in their study of the 1981 Census: Anglo-Saxon, Northern Europe, Southern Europe and Other. They report that the ranking of ceteris paribus unemployment rates (from lowest to highest) is Northern Europe, Southern Europe, Anglo-Saxon, Other for males and Southern Europe, Anglo-Saxon, Northern Europe and Other for females. Inglis and Stromback (1986) report similar ceteris paribus unemployment rates for immigrants from UK/Eire and Europe. These results are consistent with the finding in Table 8 of a sizeable “unjustified” component in the unemployment rate of immigrants from English-speaking countries.

CONCLUSION This study shows that between 1980 and 1996 both male and female immigrants were at an unemployment rate disadvantage compared with the Australiaborn, and that this disadvantage has worsened in recent years. Detailed study of the unemployment rate experience of birthplace groups based on the 1991 Census of Population and Housing reveals that the principal factors that influence employment success in the Australian labour market are educational attainment, age, qualifications and, among the foreign-born, duration of residence in Australia and English language proficiency. The returns to education, in terms of employment prospects, are not as large for immigrants from non-English-speaking countries as they are for the Australiaborn and for immigrants from English-speaking countries. Additionally, the employment enhancing effect of post-school qualifications is smaller among the foreign-born, particularly for females. The magnitudes of the period of residency effect on labour market performance are similar for male immigrants from both English-speaking and non-English-speaking countries, while in the

Immigrant unemployment: the Australian experience

169

female labour market the impact of duration of residence is much greater for immigrants from non-English-speaking countries. It has been shown that the unemployment rate differential between immigrants and the foreign-born can be decomposed into two components. The first of these is due to differences in the marketable characteristics of the foreign-born and the Australia-born. This is generally viewed as a “justified” component of the unemployment rate differential. The second component is due to differences in the way that the marketable characteristics of males and females translate into lower unemployment rates for the various birthplace groups. This component is unexplained by our model and is conventionally labelled as a “discriminatory” component of the unemployment rate differential. The decomposition presented shows that if immigrants’ marketable characteristics were rewarded in the labour market in the same way that the Australia-born’s characteristics are rewarded, then immigrants would experience unemployment rates considerably lower than those of the Australia-born. The unemployment rate differentials actually observed in the labour market appear to arise because this potential advantage is offset by a large unjustified unemployment rate disadvantage. As a result, the unemployment rates of immigrants from English-speaking countries are only slightly lower than those of the Australia-born, while the unemployment rates of immigrants from non-English-speaking countries are much greater than those of the Australiaborn. Many of the findings for the Australian labour market reported in this paper are similar to those reported by studies of other major immigrant-receiving countries. For example, Chiswick, Cohen and Zach (1997) report that educational attainment has a smaller negative effect on unemployment outcomes for immigrants than for the native born in the US. They also report that in the US labour market the ceteris paribus unemployment rate for immigrants from Europe and Canada is similar to that experienced by Asian immigrants. Contrary to the finding reported in this paper, however, Chiswick, Cohen and Zach report that the unemployment rate disadvantage experienced by recent immigrants is short-lived in the US, and the duration of residence effects are negligible after about five years. The duration of residence effects in the Australian labour market are more pronounced and persist for a longer period after arrival. This difference may be associated with the US labour market being more flexible.10 Reducing the unemployment rate disadvantage of immigrants may prove difficult in the short term. It is not simply a matter of improving language skills or levels of human capital. Rather, the crucial factors appear to be improving the transferability of overseas human capital skills and minimizing discriminatory practices in the workplace. With respect to the former problem, skill adaptation courses and competency based skill standards might be expected to

Miller and Neo

170

assist, although the heightened awareness of these issues in Australia in the past decade does not appear to have improved matters. A strengthening of affirmative action programmes for ethnic minorities may be required if the Australian labour market is still characterized by residual elements of discrimination.

NOTES 1. This research was supported by a grant from the Australian Research Council. We are grateful to two anonymous referees for a number of helpful comments. 2. According to the 1991 Australian Census data (ABS, 1991), immigrants from the main English-speaking countries and other European countries accounted for around 72 per cent of the overseas-born in 1991. However, there has been an increase in immigration from South East and North East Asia in the recent decade. 3. In 1973, a policy of non-discrimination on the grounds of race, colour or nationality in the selection of immigrants was adopted. 4. The employment/unemployment status is conditioned upon labour market entry. Some studies have analysed the distribution of the population across the states of employment, unemployment and non-participation. Study of the division between unemployment and employment among labour force participants offers more direct evidence on the effects of demand-side behaviour (see Brooks and Volker, 1985). 5. In arriving at this number of observations all records in the Census sample file with inadequately described information on variables included in the estimating equation are omitted from consideration. 6. The predicted probabilities are calculated as follows: Partition the regressors into two sets, the first relating to the J variables under immediate consideration (e.g., location) and the second relating to the K remaining variables. Then the predictions that form the basis of the discussion are calculated as: K

Uˆ j = 1/{1+ exp(∑ βˆ Xk + βˆ j )} , k=1

where X k denotes the mean of the kth regressor. The βˆ s are estimated coefficients and j denotes a particular element of the set of J variables under consideration (e.g. resident of a non-metropolitan area). 7. As a quadratic specification is used for the age variable, the partial effect of this variable will itself be a function of age. This function is evaluated at age 30 for the purposes of the discussion. A similar issue arises with regard to the period of residence variable. In this case the period of residence effects are evaluated at 10 years of residency in Australia. 8. It is possible that the unemployment status of the spouse is endogenous in this model. Consequently, the spouse’s unemployment rate variable was instrumented and the model re-estimated. This has a very minor impact on all coefficients other

Immigrant unemployment: the Australian experience

171

than that for the variable that was instrumented. The estimated partial effect of the spouse’s unemployment rate variable in this instrumental variable model was doubled in the male unemployment rate model and increased by 50 per cent in the model for female unemployment rates. However, given the small representation in the “spouse unemployed” category, the decompositions presented below are reasonably insensitive to choice of method of estimation. 9. The decomposition outlined in equation (3) evaluates the characteristics of the Australia-born (X a) using the migrant coefficients ( βˆ f). An alternative decomposition would be to evaluate the migrants’ characteristics (Xf) using the coefficients of the Australia-born ( βˆ a). To minimize the potential for bias, the average of the two decompositions is presented in Table 8. 10. In the study of wage determination in the US and Australia, strong duration of residence effects are usually reported for the US but duration of residence effects in Australia are quite modest (Chiswick and Miller, 1985). The links between this pattern of wage effects with duration of residence and the unemployment effects require further analysis.

REFERENCES Australian Bureau of Statistics 1991 1991 Census of Population and Housing: Australia in Profile, Cat. No. 2821.0, Australian Bureau of Statistics, Canberra. 1994 1991 Census of Population and Housing Sample File [computer file], Australian Bureau of Statistics, Canberra. “The labour force survey”, selected years and months, Cat. No.6203.0, Canberra. Beggs, J.J., and B.J. Chapman 1988 “The international transferability of human capital: immigrant labour market outcomes in Australia”, in P. Miller and L. Baker (Eds), The Economics of Immigration: Proceedings of a Conference, Australian Government Publishing Service, Canberra: 143-157. Brooks, C., and P.A. Volker 1985 “Labour market success and failure: an analysis of the factors leading to the workforce destinations of the Australian population”, in P.A. Volker (Ed.), The Structure and Duration of Unemployment in Australia, Australian Government Publishing Service, Canberra: 43-71. Chapman, B.J., and P.W. Miller 1985 “An appraisal of immigrants’ labour market performance in Australia”, in M.E. Poole, P.R. de Lacey and B.S. Randhawa (Eds), Australia in Transition: Culture and Life Possibilities, Harcourt Brace Jovanovich, Sydney: 300-310. Chiswick, B.R., and P.W. Miller 1985 “Immigrant generation and income in Australia”, Economic Record, 61(173): 540-553.

172

Miller and Neo

Chiswick, B.R., and P.W. Miller 1992 Post-Immigration Qualifications in Australia: Determinants and Consequences, Bureau of Immigration Research, Canberra. Chiswick, B.R., Y. Cohen and T. Zach 1997 “The labor market status of immigrants: effects of the unemployment rate at arrival and duration of residence”, Industrial and Labor Relations Review, 50(2): 289-303. Farber, H.S. 1990 “The decline of unionisation in the United States: what can be learned from recent experience”, Journal of Labor Economics, 8,1(2): S75-S105. Inglis, P.A., and T. Stromback 1986 “Migrants’ unemployment: the determinants of employment success”, Economic Record, 62(178): 310-324. Jones, F.L. 1992 Sex and Ethnicity in the Australian Labour Market: The Immigrant Experience, Australian Bureau of Statistics, Canberra. Miller, P.W. 1986a “Unemployment patterns in the youth labour market”, Australian Economic Papers, 25(47): 222-235. 1986b “Immigrant unemployment in the first year of Australian labour market activity”, Economic Record, 62(176): 82-87. 1989 “The structure of Aboriginal and Non-Aboriginal youth unemployment”, Australian Economic Papers, 28(52): 39-56. Veall, M.R., and K.F. Zimmermann 1996 “Pseudo-R2 measures for some common limited dependent variable models”, Journal of Economic Surveys: 241-260. Wooden, M. 1991 “The experience of refugees in the Australian labour market”, International Migration Review, 25(3): 514-535.

DATA APPENDIX The variables used in this study are defined below. The code of the Census variables used in the construction of each particular measure is given in parentheses prior to the description. Additional details on the primary data set can be found in Australian Bureau of Statistics (1994). Age (AGEP): This study is restricted to individuals between 15-64 years of age. The original data are measured in single years for those aged 15-24 and in five-year intervals for those between 25-64. A continuous measure of age is derived by assuming the midpoint age of each group. Birthplace (BPLP): The 1991 Census Household Sample File contains 38 birthplace classifications. These were regrouped according to whether the country of birth was English-speaking (ENGSP) or non-English-speaking (NENGSP) for each of those

Immigrant unemployment: the Australian experience

173

born overseas. The following countries are classified as English-speaking countries: UK and Ireland, New Zealand and US. All others are categorized as non-Englishspeaking countries. Individuals born in Australia constitute the benchmark group. Locality (GDHSF91): This is defined according to residence in the Australian Capital Territory or Tasmania (corresponds to “ACTAS” in the empirical work) or small urban areas (“NMETRO”) which includes: Hunter/Illawarra, Richmond/Tweed, Murrumbidgee, Mallee, Goulburn, Moreton, Far North Queensland and Remainder of Queensland, South Australia, Western Australia and Northern Territory (excluding capital cities). The omitted category comprises residents of capital cities (other than A.C.T. and Tasmania) and major urban areas; and they constitute the benchmark group in all regressions. Proficiency in English (ENGP): The Census language information has been regrouped to three levels: 1. speaks English only; 2. speaks a language other than English in the home and speaks English either very well or well (“ENGGOOD”); 3. speaks a language other than English in the home and either speaks English not well or not at all (“ENGPOOR”). The benchmark group is individuals who speak only English in the home. Educational attainment (ALSP, QLLP): This variable has been created from the Census “Age Left School” and “Qualifications” variables. The educational attainment variable “EDUC” corresponds to years of schooling which is calculated as “Age Left School – 5”. Individuals who did not go to school are assigned a value of zero for this variable while those who left school between ages 18 and 19 are assumed to have completed 13 years of schooling. In order to take into account higher education the following adjustments are made. Individuals with undergraduate or associate diplomas are assumed to have completed the equivalent of 15 years of full-time schooling, those with a bachelor degree the equivalent of 16.5 years of full-time schooling, those with a postgraduate diploma the equivalent of 17 years of full-time schooling and those with a higher degree the equivalent of 19 years of full-time schooling. Qualifications (QLLP): Qualifications is a dichotomous variable which takes the value of 1 if the individual holds a post-school qualification, otherwise it is set equal to zero. Marital Status (MSTP): Marital status is a dummy variable created from the Census data on marital status. It is set equal to one for those married and zero for all others. Number of Children (CDPF): The number of children is the number of dependent children in the family. Additional details can be found in 1991 Census Dictionary (ABS Catalogue No. 2901.0). Spouse’s unemployment status (LFSP): This is a binary variable which takes a value of one if the individual was married, the spouse was present at the time of the Census and also unemployed.

174

Miller and Neo

Period of Residence (YARP): The period of residence in Australia variable records the number of years a person has been resident in Australia. Australia-born respondents are assigned a value of zero. This variable is calculated as “1991 (the year of the Census) – Year of arrival”. The Census “Year of arrival” data are recorded in two-year intervals for those who arrived between 1986-1991 and five-year intervals for those who arrived between 1971-1985. In order to construct the period of residence variable, the midpoint year is used for each respondent. For those who arrived prior to 1971, their period of residence in Australia is assumed to be 30 years. Unemployment Status (LFSP): The unemployment status variable is the dependent variable, and it takes a value of one if the individual was unemployed and zero if employed at the time of the Census.

175

Immigrant unemployment: the Australian experience TABLE 1

UNEMPLOYMENT RATES OF AUSTRALIA-BORN AND OVERSEAS-BORN PERSONS AGED 15 AND OVER, AUGUST 1980 TO AUGUST 1996

Year

Males AustraliaOverseasborn born

Females AustraliaOverseasborn born

Australiaborn

Total Overseasborn

1980

4.8

5.5

7.4

7.5

5.8

6.2

1981

4.5

5.2

6.9

7.8

5.4

6.1

1982

6.1

7.0

7.1

8.6

6.4

7.6

1983

9.3

11.5

9.3

11.7

9.3

11.5

1984

8.1

10.2

7.9

9.7

8.0

10.0

1985

7.5

8.8

7.8

8.7

7.6

8.8

1986

7.5

8.3

8.2

9.0

7.8

8.6

1987

7.3

8.3

8.0

9.5

7.5

8.7

1988

6.4

7.0

7.0

8.1

6.7

7.4

1989

5.3

5.7

5.9

7.2

5.5

6.2

1990

6.7

7.4

6.8

8.1

6.7

7.7

1991

9.2

12.7

8.1

10.3

8.7

11.7

1992

10.7

13.1

8.9

11.6

9.9

12.5

1993

10.7

13.5

9.0

12.4

10.0

13.1

1994

8.7

11.5

8.1

11.4

8.5

11.4

1995

7.8

10.7

7.0

9.3

7.4

10.1

1996

8.5

10.0

7.5

9.5

8.1

9.8

Source: ABS, The Labour Force, 1980-1996 (August).

Miller and Neo

176

TABLE 2 UNEMPLOYMENT RATES BY BIRTHPLACE, AGE AND SEX, AUGUST 1996

Age

Males AustraliaOverseasborn born

Females AustraliaOverseasborn born

Total AustraliaOverseasborn born

15 - 19

20.5

18.5

18.6

18.3

19.6

18.4

20 - 24

12.4

12.6

10.6

15.7

11.6

14.0

25 - 34

7.8

10.7

6.6

9.7

7.3

10.3

35 - 44

5.7

8.1

5.2

8.0

5.5

8.1

45 - 54

5.2

9.0

4.5

8.6

4.9

8.9

55 and over

6.3

12.1

2.9

6.7

5.1

10.6

15 - 64

8.6

10.1

7.6

9.5

8.2

9.8

Source: ABS, The Labour Force, August 1996.

TABLE 3 UNEMPLOYMENT RATES OF IMMIGRANTS AND THE AUSTRALIA-BORN AGED 15 AND OVER, AUGUST 1996 Birthplace

Males

Females

Total

Australia

8.5

7.5

8.1

ESB

7.9

6.6

7.4

NESB

11.5

11.7

11.6

Total Overseas-born

10.0

9.5

9.8

Note:

ESB = Born in main English-speaking countries NESB = Born in non-English-speaking countries Source: ABS, The Labour Force, August 1996.

Immigrant unemployment: the Australian experience

177

178

Miller and Neo

Immigrant unemployment: the Australian experience

179

Miller and Neo

180

TABLE 5 LOGIT ESTIMATES OF MODEL OF UNEMPLOYMENT, MALES AGED 15-64 Variable

Total Sample

Australiaborn

Constant

2.232 (14.39)

2.573 (13.50)

4.052 (7.17)

2.472 (5.24)

0.154 (4.44) 0.161 (2.03) -0.154 (21.44) -0.440 (11.15) -0.116 (14.26) 0.137 (13.00)

0.156 (4.01) 0.171 (1.93) -0.210 (20.46) -0.527 (11.16) -0.091 (9.48) 0.098 (7.72)

0.003 (0.03) -0.040 (0.15) -0.222 (8.73) -0.309 (2.91) -0.155 (5.95) 0.199 (6.23)

0.100 (0.86) 0.190 (0.79) -0.055 (4.45) -0.263 (2.61) -0.170 (7.32) 0.209 (7.46)

-1.104 (25.10) 2.283 (30.30) 0.106 (6.66)

-1.152 (21.34) 2.231 (21.46) 0.076 (3.94)

-0.944 (8.02) 2.046 (9.00) 0.123 (2.42)

-0.979 (9.55) 2.274 (17.47) 0.207 (5.85)

0.756 (7.54) 0.857 (7.95)

(a)

(a)

(a)

(a)

(a)

(a)

-0.063 (4.45) 0.142 (3.54)

(a)

-0.064 (2.77) 0.173 (2.66)

-0.046 (2.53) 0.081 (1.55)

0.224 (3.69) 0.425 (3.86)

(a)

-0.182 (0.52) -0.321 (0.20)

0.343 (3.39) 0.740 (5.25)

Sample Size

39,810

29,514

4516

5780

χ2

3041.7

2220.5

293.22

648.32

0.101

0.103

0.089

0.128

Locality (Metropolitan) Non-Metropolitan ACT/Tasmania Years of Education Qualifications Age 2

Age / 100 Married (not married) Spouse Present Spouse Unemployed Number of Children Birthplace (Australia) English-speaking Non-English-speaking Period of Residence 2

Period of Residence /100 Language Skills (English Only) Good Poor

c

2

M Fadden’s R Note:

(a)

(a)

Foreign-born ESB NESB

‘t’-statistics in parentheses; benchmark groups for categorical variables listed in c 2 parentheses; for information on M Fadden’s R see Veall and Zimmermann (1996). Source: 1991 Australian Census of Population and Housing.

181

Immigrant unemployment: the Australian experience TABLE 6

LOGIT ESTIMATES OF MODEL OF UNEMPLOYMENT, FEMALES AGED 15-64 Variable

Total Sample

Australiaborn

Constant

2.009 (9.67)

2.663 (10.55)

2.280 (2.93)

2.059 (3.27)

0.393 (8.68) 0.101 (0.96) -0.139 (14.94) -0.218 (3.08) -0.124 (10.51) 0.125 (7.67)

0.375 (7.47) 0.110 (0.96) -0.198 (15.18) -0.259 (3.11) -0.114 (8.29) 0.103 (5.25)

0.455 (3.12) -0.511 (1.07) -0.171 (5.08) -0.231 (1.09) -0.072 (1.77) 0.071 (1.32)

0.287 (1.81) 0.233 (0.74) -0.042 (2.58) -0.096 (0.54) -0.122 (3.77) 0.147 (3.52)

-1.296 (22.59) 2.810 (33.18) 0.109 (5.56)

-1.334 (18.99) 2.742 (24.03) 0.121 (5.33)

-1.281 (7.37) 2.672 (11.34) -0.010 (0.14)

-1.148 (9.29) 2.854 (18.42) 0.096 (2.02)

1.241 (10.17) 1.662 (12.71) -0.141 (7.93) 0.320 (6.16)

(a)

(a)

(a)

(a)

(a)

(a)

(a)

-0.091 (3.22) 0.204 (2.49)

-0.146 (6.31) 0.311 (4.57)

0.289 (3.76) 0.760 (5.56)

(a)

0.692 (1.70) -9.488 (0.05)

0.410 (2.94) 1.058 (5.80)

Sample Size

28,694

21,888

3132

3674

χ2

2915.8

1900.5

247.23

735.06

0.152

0.137

0.132

0.226

Locality (Metropolitan) Non-Metropolitan ACT/Tasmania Years of Education Qualifications Age Age2 / 100 Married (not married) Spouse Present Spouse Unemployed Number of Children Birthplace (Australia) English-speaking Non-English-speaking Period of Residence 2

Period of Residence /100 Language Skills (English Only) Good Poor

c

2

M Fadden’s R Note:

(a)

(a)

Foreign-born ESB NESB

‘t’-statistics in parentheses; benchmark groups for categorical variables listed in parentheses; for information on Mc Fadden’s R2 see Veall and Zimmermann (1996). Source: 1991 Australian Census of Population and Housing.

Miller and Neo

182

TABLE 7 ESTIMATED PARTIAL EFFECTS FROM UNEMPLOYMENT RATE MODELS Variable

Total Sample

Australiaborn

-1.68 -0.37

-2.30 -0.35

-2.43 -0.39

-0.60 -0.49

1.16 -0.38 1.40 1.47 7.81 9.22 2.14 4.40 -10.11

0.83 (a) 1.24 1.38 (a) (a) (a) (a) -9.36

1.35 -0.32 3 0.04 3 -0.46 (a) (a) -2.043 -3.433 -11.17

2.26 -0.33 3 1.36 3 2.61 (a) (a) 4.93 12.01 -13.01

Spouse unemployed if married

32.41

28.07

34.16

42.25

2. Females Education

1. Males Education Age1 Number of children 2 Duration of residence Non-metropolitan ACT/Tasmania English-speaking birthplace Non-English-speaking birthplace Good English Poor English Married

Foreign-born ESB NESB

-1.30

-1.85

-1.59

-0.39

Age Number of children 2 Duration of residence Non-metropolitan ACT/Tasmania English-speaking birthplace Non-English-speaking birthplace Good English Poor English

-0.46 1.02 -0.72 2.75 3 0.62 10.59 16.99 2.07 6.67

-0.49 1.13 (a) 2.24 3 0.58 (a) (a) (a) (a)

-0.27 3 -0.09 -0.47 4.71 3 -3.59 (a) (a) 9.29 -11.793

-0.32 0.89 -0.78 4.93 3 3.94 (a) (a) 7.43 22.02

Married Spouse unemployed if married

-8.58 35.14

-7.63 29.79

-12.16 40.91

-18.77 40.18

1

1. 2. 3. (a)

Evaluated at 30 years. Evaluated at 10 years. Estimated impact insignificant at 10% level. Variable not relevant.

183

Immigrant unemployment: the Australian experience TABLE 8 DECOMPOSITION OF UNEMPLOYMENT RATE DIFFERENTIAL BETWEEN THE AUSTRALIA-BORN AND IMMIGRANTS Comparison

Unemployment rate differential

Justified

Unjustified

-0.02

-4.4

4.38

3.83

-2.98

6.81

-0.84

-5.92

5.08

6.46

-7.32

13.78

Australia-born males and: •

male immigrants from English-speaking countries

•

male immigrants from non-English-speaking countries

Australia-born females and: •

female immigrants from English-speaking countries

•

female immigrants from non-English-speaking countries

184

Miller and Neo

CHOMAGE DES IMMIGRES : L’EXPERIENCE DE L’AUSTRALIE Entre 1980 et 1996, les immigrés des deux sexes ont connu un taux de chômage supérieur à celui des travailleurs nés en Australie. En 1996, par exemple, il était de 9.8 pour cent chez les immigrés et de 8.1 pour cent chez les autres. Cet article utilise l’analyse à variables multiples pour comparer les taux de chômage parmi les sujets nés en Australie et les immigrés nés dans des pays anglophones et non anglophones. L’analyse désagrège ensuite ces différences en deux composantes : celles attribuables aux différentes caractéristiques du lieu de naissance (comme le niveau moyen d’instruction) et celles qui sont la simple conséquence d’être né à l’étranger. L’analyse révèle que les principaux facteurs qui influencent la réussite professionnelle sur le marché du travail australien sont le niveau d’instruction, l’âge, les qualifications et, pour les immigrés, la durée de résidence en Australie et la maîtrise de l’anglais. Cependant, la diminution du taux de chômage liée à un allongement de la scolarité est moins nette pour les immigrants de pays non anglophones que pour les immigrants de pays anglophones et les personnes nées en Australie. Ces résultats suggèrent donc que si leurs aptitudes étaient récompensées comme celles des sujets nés en Australie, les immigrés auraient un taux de chômage très inférieur à celui des non-immigrés. Les différences constatées sur le marché du travail sont donc dues au fait que l’avantage potentiel des immigrés est compensé par des facteurs non fondés. C’est là que pourraient intervenir des cours de recyclage, le recours à des critères d’aptitude basés sur les compétences réelles et un renforcement des programmes de discrimination positive pour les minorités ethniques. Cette étude montre également que les immigrés récents sont nettement plus défavorisés en termes d’emploi et que cette situation persiste longtemps. Ces résultats diffèrent de ceux recueillis récemment sur le marché du travail américain où l’effet de la durée de résidence est éphémère. Ceci peut être attribué à une moindre souplesse du marché australien du travail.

Immigrant unemployment: the Australian experience

185

DESEMPLEO DE INMIGRANTES: LA EXPERIENCIA AUSTRALIANA Entre 1980 y 1996 los inmigrantes de ambos sexos han experimentado índices de desempleo más elevados que los correspondientes a los trabajadores nacidos en Australia. Así, por ejemplo, en 1996 el índice de desempleo de los nacidos en el extranjero era del 9,8 por ciento, en lugar del 8,1 por ciento en el caso de los nacidos en Australia. En este artículo se utiliza un análisis de multivariancia para examinar las diferencias en los índices de desempleo de los nacidos en Australia, los inmigrantes procedentes de paises de lengua inglesa y los inmigrantes de paises no anglófonos. Una caraterística del análisis es la descomposición de las diferencias en el índice de desempleo entre grupos por lugar de nacimiento en un componente atribuible a las diferentes características de los grupos por lugar de nacimiento (por ejemplo, diferencias en los niveles medios de escolaridad) y otra parte que se considera como consecuencias del simple hecho de haber nacido en el extranjero. El análisis revela que los principales factores e influencias en el éxito laboral obtenido en el mercado australiano de trabajo son el nivel de escolaridad, la edad, las calificaciones y, entre los nacidos en el extranjero, la duración de la residencia en Australia y los conocimientos del idioma inglés. Además, las reducciones en el índice de desempleo asociadas con el número de años de escolaridad no son tan importantes en el caso de los inmigrantes de países no anglófonos como en el de los nacidos en Australia o en el de los inmigrantes de países de lengua inglesa. Los resultados obtenidos indican que si las características comercializables de los inmigrantes se recompensaran en el mercado de trabajo de la misma forma que se recompensan las características de los nacidos en Australia, los inmigrantes presentarían índices de desempleo considerablemente más bajos que los de los nacidos en Australia. Las diferencias en los índices de desempleo realmente observadas en el mercado de trabajo se deben a que esta ventaja potencial queda compensada por factores “injustificados”. Esto indica que probablemente sería útil establecer cursos de adaptación de conocimientos, normas basadas en las aptitudes y programas de reforzamiento de la acción positiva en favor de las minorías étnicas. El estudio muestra además que los inmigrates recientes sufren una clara desventaja en sus índices de desempleo y que esta desventaja persiste durante un lapso de tiempo considerable. Estos resultados difieren de los hallazgos realizados recientemente en el mercado laboral de los Estados Unidos según los cuales los efectos de la duración de la residencia son de breve duración. Se sugiere la posibilidad de que esta diferencia se asocie al hecho de que el mercado laboral australiano es menos flexible que el de los Estados Unidos.