Skilled migration policy and the labour market performance of immigrants

This working paper examines whether migration policy, in addition to managing a country’s population size, is a suitable tool to influence immigrants’ labour market outcomes. It exploits a migration policy change that occurred in Australia in the late 1990s and data collected by the Longitudinal Survey of Immigrants to Australia. The statistical techniques employed in the empirical analysis consistently reveal that the policy change has no detectable impact on the employment rate, wages, over-education, occupational downgrading, and self-reported use of skills for male immigrants, who account for about 75 per cent of the sample, while they have a modest short-term positive impact on female immigrants. These results support the view that migration policy is an ineffective policy tool to influence migrants’ labour market outcomes. However, the economic relevance of making an effective use of migrants’ skills provides scope for close coordination between immigration and employment policy to ensure that efforts in attracting foreign talent are not dissipated by labour market frictions and other inefficiencies.

Australia has the world’s largest skilled migration program. The annual inflow of skilled foreign workers is about 1 per cent of Australia’s population, and an even higher proportion of its skilled labour force. Despite the potential competition with skilled natives, over the past three decades Australia has experienced wage growth and returns to higher education unparalleled in any other advanced economy.

Yet, the labour market outcomes for many foreign-educated migrants are substantially and stubbornly below those of comparably educated natives. The incidence of skill mismatch (over-education) among university-educated foreign workers in Australia is as high as 40–50 per cent versus 10–20 per cent among comparable domestic workers, placing Australia on equal footing with countries that do not implement selective immigration policies.[1] This evidence is counterintuitive, as selective policies are designed to admit only the most productive migrants. Skill mismatch is also inefficient: migrants’ economic under-achievement costs Australia potential income, spending for consumption and investment, and taxation revenue, and could compromise its ability to compete with other countries in attracting and effectively using the best foreign talent available.

Can migration policy be used as a tool to address immigrants’ education–occupation mismatch? This question is addressed by exploiting a migration policy change that occurred in Australia in the late 1990s and a detailed migrant survey that took place at the time. The survey is used to analyse the effect of the policy change on immigrants’ labour market outcomes using various quantitative techniques.

The migration policy change occurred between two cohorts of immigrants surveyed in detail by the Longitudinal Survey of Immigrants to Australia (LSIA). This makes this particular policy change unique as the available data can be used to identify changes due to time effects and other determinants of immigrants’ labour market outcomes.

This working paper focuses on five indicators of labour market performance: employment rate (the probability of finding employment); occupational downgrading; wages; whether the job carried out requires a lower level of education than the one held by the migrants (over-education); and a self-reported use of skills. The paper begins with a short review of the economics literature focusing on migration policy and the use of selective admission criteria. It then describes Australia’s immigration policy change in the late 1990s, and presents data from the LSIA and the results of the analysis of the effects of the policy change on labour market outcomes.

Economics-based studies tend to view migration as an individual decision, resulting from a rational cost-benefit analysis in which the net expected benefits that can be gained by staying in the home country are compared to those obtained by moving abroad. Migration occurs if the latter are greater than the former.[2] As individuals differ in innate and demographic characteristics and circumstances, migrating does not occur at random in the population, but characterises a subgroup of self-selected individuals.

The literature has exploited the notion of self-selection into migration to identify the type of migrants attracted to different countries.[3] Average differences in incomes between home and host countries play a critical role in determining who migrates where, as does the quality of the information set facing migrants. If information is complete and average incomes at home are below those of the host for each level of skill, then every home citizen will have an incentive to emigrate. However, if home and host countries place a similar value on skills, average incomes per capita will be similar, and the most skilled individuals will migrate to the country with the higher income inequality to increase the economic benefit they receive for their skills. Conversely, the least skilled will migrate to the country with a compressed income distribution to maximise the economic benefits for their skills. If the information is incomplete or imperfect then ‘irrational’ migration behaviours can occur.[4]

A selective immigration policy becomes relevant to the host country’s decision to impose restrictions about the type of migrant allowed to stay if the host country has a relatively high average income compared with the home country (most home citizens would want to emigrate), a compressed income distribution (low-skill home citizens want to emigrate), and a comprehensive welfare system for its low-income earners.[5] Keeping out low-skill immigrants in favour of skilled immigrants may not only ‘protect’ the host country’s welfare system and address its domestic employers’ needs, but may also stabilise income inequality trends between skilled native and unskilled native workers. This is because the earnings growth of skilled immigrants will be constrained (as there will be a large supply of them), whereas unskilled native workers will be in shorter supply and therefore will command higher wages.

A new strand of literature argues that restricting migration could be efficient because it prevents migrants from low-income countries ‘transmitting’ low productivity to high-income countries. However, a recent study suggests that current restrictions to migration are still excessive for the ‘low productivity contagion hypothesis’ to be supported based on current migrant flows.[6]

In practice, countries such as Australia, Canada, and New Zealand limit the inflow of migrants using a point system.[7] This is typically based on level of education, language proficiency, and age. However, the effects of such restrictions are debatable,[8] especially regarding level of education and the influence of immigration policies on the self-selection process from both a theoretical and an empirical perspective.[9] Studies suggest that imposing minimum educational requirements raises the educational profile of immigrants, but this does not guarantee better labour market outcomes. For example, screening potential migrants on the basis of observable characteristics, in particular education, may reduce the quality of admitted migrants because education also influences migrants’ self-selection on variables that are not measured, such as ability and motivation.[10] An increase in selectivity based on education may lead to admitting less able and less motivated migrants.

This working paper adds to existing work that aims to draw general conclusions on the labour market effects of migration policy by studying the effect of a specific policy change in Australia. The policy change, which is well documented in the literature,[11] tightened entry conditions for applicants in the skilled independent and concessional family visa categories, but not in the preferential family, employer nomination, and humanitarian streams.[12] This differential treatment across visa categories offers a unique opportunity to identify the effect of the policy change on applicants and address the key question of this paper: is migration policy a suitable tool to influence not only a country’s population size (the main objective of migration policy) but also the labour market performance of its immigrants?

In 1996 the newly elected Howard government introduced a number of significant changes to Australia’s migration policy, affecting some visa categories in the skilled and family reunification streams but not the remaining migration channels.[13] The new policy:

• abolished the social security benefit to new immigrants in the first two years after their arrival, as well as access to the Adult Migrant English Program, whose costs were to be met by the immigrant, and labour market programs, whose costs were to be repaid after securing work
• allocated the highest points weighting to employability factors, namely skills, age, and English-language ability. Age-related points for applicants over the age of 45 were abolished while bonus points were awarded to those with relevant Australian or international professional work experience, a job offer, a spouse meeting the skill application criteria, an Australian sponsor who had agreed to provide a guarantee, and A$100,000 or more in capital
• introduced additional points for occupations in demand in addition to degree-level specific qualifications, and bonus points for qualifications obtained recently in Australia
• outsourced pre-migration qualification screening to professional bodies, which could disqualify non-English speaking background (NESB) applicants from eligibility for skill migration.

The effect of this policy change has been examined in detail by previous studies, which compare the outcomes of the first cohort of the LSIA, who arrived in Australia prior to the policy change between 1993 and 1995 (LSIA1), with those of the second cohort, who arrived after the change between 1999 and 2000 (LSIA2). These studies offer a mixed picture of the policy’s effects on migrants’ labour market outcomes. In line with the policy’s aims, the second cohort had better education levels compared to the first cohort (in particular higher university degrees at the time of arrival), higher workforce participation rates,[14] and lower durations to access their first job.[15] However, the job quality of the second cohort is markedly inferior to that of the first, with widespread occupational downgrade.[16] This is partly attributed to the worsening macroeconomic conditions faced by migrants surveyed in the second cohort.

Table 1: Unconditional means in the working sample

In order to provide a general test of whether immigration policy influences migrants’ labour market performance, the empirical analysis employs four different techniques widely used in the literature to detect causality in survey data (these are presented in some detail in Appendix A). It also makes use of two different data specifications: the cross-section capturing only the first wave of each cohort; and the panel dimension of the LSIA capturing the first two waves of each cohort.

This combination of data specification and technique generates several regressions, each using wage as a dependent variable and the following independent variables:

• individual characteristics:
  • education level (secondary schooling and below, vocational, tertiary)
  • age group (four categories: 25–34, 35–44, 45–49, and 50–65)
  • English-language proficiency based on whether the LSIA interview was conducted in English or in another language
  • main regions of origin (four categories: North Europe/North America, South and East Europe/Middle East and North Africa, Asia, and rest of the world)
  • state of residence after settlement (two categories: Tas/Vic and Other)
• control variables such as which cohort the migrant belongs to. This indicator also captures the economic conditions at the time the migrants settled in Australia.

For analyses based on panel data, two additional indicators are included:

• a variable that controls for the particular wave in which data was collected
• a dummy variable for each individual surveyed, which controls for unobserved but time-invariant individual characteristics.

Table 2 shows the estimated link between a change in immigration policy and migrants’ labour market outcomes controlling for all the observed covariates above. It summarises 60 separate regressions — one for each labour market outcome, by gender,[22] and across various techniques. Only the key relationship of interest is analysed: namely whether migration policy affects migrants’ subsequent labour market outcomes.

Table 2: Regression results

Notes: Source first and second waves of LSIA1 and LSIA2
***, **, and * indicate whether the estimate is statistically significantly different from zero at the 1%, 5%, and 10% level of significance
n.m. = not meaningful

Models (1) to (6) are as follows: (1) ordinary least squares (OLS); (2) propensity score matching (unrestricted scores); (3) propensity score matching (central scores only); (4) pooled OLS; (5) random effects; (6) random effects with Mundlak correction. See Appendix A for a description of each model.

A few general observations linking the results to the findings of the previous literature are worth noting before discussing the overall picture that emerges from Table 2. First, the increase in employment rate documented by previous studies[23] is partly confirmed when policy-evaluation specific techniques are applied, but it arises only for males and in models 1 and 4 applying a low significance level (10 per cent). No detectable effect on employment rate emerges when the effect of the policy change is estimated using estimators that better control for individual heterogeneity (models 2, 3, 5, and 6). In the case of females, the only notable effect on employment arises using model 3. These outcomes imply a very modest effect, if any, of the policy change on the short-term employment prospects of the immigrants of the second cohort.

Second, in contrast to employment rate, the policy change seems to have had mixed effects on occupational downgrading:[24] there is no effect in the case of men, where the estimate is positive (implying that the occupation after migration is lower in the occupation scale than what was held before migrating) but statistically equivalent to zero.

The effect of the policy change on occupational downgrading is negative and significant in the case of females but only in model 2. This result implies that after migrating, women take up jobs that are on a substantially lower level of the occupational scale relative to what they were performing in their countries of origin. However, part of this result may be attributed to the characteristics of the migrants rather than the effect of the policy change due to a composition effect of the groups analysed by model 2. Furthermore, the effect of migration policy on occupational downgrading for women appears mixed across estimation techniques, suggesting additional caution in interpreting the result as conclusive that the policy change was principally responsible for the negative outcome observed.

Third, in relation to wages, over-education, and use of skills, the policy change has affected immigrant men and women differently. In particular, the policy had no detectable statistical effect on the three indicators in the case of immigrant men in all models reported in Table 2. The small effect observed in the use of skills in models 5 and 6 indicates better matches between education and occupation, but it could arise from changing job or employer rather than being the effect of the policy change.

In contrast, the policy change seems to have significantly raised the wage and the use of skills, and lowered the degree of over-education among immigrant women, although only at the time of the first wave. This outcome likely reflects the higher proportion of unmarried women of working age in the second cohort (49 per cent vs 27 per cent in the first cohort), which could be the result of concurrent circumstances characterising immigrant trends in addition to the policy change examined. None of these results holds in the panel data analysis, where the estimation controls for unobserved individual characteristics that do not change over time. This suggests that results attributable to the effect of the policy change in models 1 to 3 may be caused by unobserved variables that affect migrants’ quality rather than the policy change (e.g. higher volume of international students qualifying for a permanent visa at the time of the second cohort).

Overall, the estimates of the effects of the immigration policy change on migrants’ labour market outcomes in Table 2 are remarkably consistent, with most results statistically no different from zero, and only a handful of exceptions in the case of females. In the case of males, the policy change appears to have had no detectable effect on the five indicators of labour market performance regardless of whether using cross-sections or panel data techniques. The modest increase in the self-reported use of skills is confined to models 5 and 6, which cover a longer period of time during which migrants had the opportunity to gain labour market experience and complete additional educational and professional qualifications in Australia. With reference to the other indicators of performance, the policy change has no statistical effect on salaries, over-education (where the sign points to worsening conditions relative to those occurring before the policy change), and skills usage.

In the case of females, the improvement across indicators of labour market performance only in the first wave of both cohorts may be caused by unobserved variables that affect migrants’ quality but are unrelated to the policy change, such as an increase in the number of female international students completing their degrees in Australia and applying for permanent migration. Alternatively, this may reflect aspects of the policy change that are only corollary to immigration policy, such as the deferred access to welfare and/or heightened skill shortages in Australia, particularly in scientific and engineering jobs.[25] These changes may have prompted women to find a better education–occupation match in the labour market.

The results in Table 2 show that the immigration policy change of the late 1990s had no real impact on the labour market performance of affected immigrants. Indeed, this is the key message of the analysis, notwithstanding that the results are obtained from an imperfect database covering only the very short term.

This conclusion raises the question of what set of policy tools could be used to influence migrants’ labour market outcomes. One answer is labour market policy, which broadly ensures the proper functioning of the labour market. In the case of migrants, employment departments guarantee the respect of legislation and established practices, ensuring, for example, that migrants’ employment reflects the laws of the country, and that they have access to the same rights and responsibilities enjoyed by native workers. Employment departments are therefore the obvious regulatory body to oversee whether the skills brought by immigrants, especially highly educated migrants, are efficiently used, and whether policy intervention is necessary.

Such responsibilities are markedly different from those of immigration departments. Broadly speaking, immigration departments administer the orderly management of population inflows, but in countries that operate a selective immigration policy, such as Australia, Canada, and New Zealand, they also carry out the immigration selection mechanism, deciding whether applicants meet stated selection criteria. Immigration departments ultimately determine migrants’ skill composition, which they regularly review using research covering economic and other aspects of integration. This has limited effect on outcomes once immigrants enter the host country’s labour market, as shown by the results reported in Table 2.

This consideration raises another question: namely, to what extent is it desirable for immigration and employment policies to coordinate their aims and policy tools, at least with respect to migrants undergoing a selection process? The division of policy responsibility between immigration departments attracting foreign talent and employment departments ensuring its efficient usage in the labour market can generate discrepancies if carried out independently from each another. This presents a cost for the migrants, who may spend additional time working in jobs for which they are overqualified before their skills are properly utilised and rewarded. It also presents a cost for the host country due to the inefficient valuation of its immigrants’ skills once they join the workforce.

The results of the analysis in this paper suggest that immigration and employment policymakers could benefit from working together to address issues around recruiting foreign talent and ensuring the subsequent utilisation of that talent in the labour market. Examples of collaborative work could include the development of accreditation programs to ease the path into licensing for foreign-trained professionals, English-language support, or access to finance for new start-ups. Coordination between immigration and employment policies is important as the costs of going it alone are not only borne by immigrants and their families, but also by the host society at large, which does not benefit from the skills and talent that were selected (at some) cost and had been made available for use in the host country.

While issues related to the efficiency of the labour market do not appear to be at the forefront of migration policies, including in Australia, at times of sluggish economic growth even a small forward step in improving efficiency in migrants’ skill utilisation can make a substantial positive contribution to a country’s economy.

where the dependent variable is the labour market outcome of interest for an individual surveyed at a given time. The five outcomes considered are: the employment rate (the probability of finding employment); wages (derived from the ANU-4 scale of occupational prestige[37]); the probability of being over-educated for the job according to the job analysis method;[38] the subjective perception of skill usage; and occupational downgrading, defined as a reduction in the occupational prestige (as measured by occupational codes at 4-digits) between the last job performed before migrating and the job carried out after settlement at the time of the survey.

Labour market outcomes

Figure 1: Employment rate

Source: First wave, LSIA1 and LSIA2

Figure 2: Incidence of education-occupation mismatch by visa class

Source: First wave, LSIA1 and LSIA2

Figure 3: Weekly wage – based on ANU job score

Source: First wave, LSIA1 and LSIA2

Figure 4: Use of qualifications (self-assessed)

Source: First wave, LSIA1 and LSIA2

Figure 5: Occupational downgrading

Source: First wave, LSIA1 and LSIA2

Figure 6: Common support – Males

Source: First wave, LSIA1 and LSIA2

Figure 7: Common support – Females

Source: First wave, LSIA1 and LSIA2

This working paper series is part of the Lowy Institute’s Migration and Border Policy Project, which aims to produce independent research and analysis on the challenges and opportunities raised by the movement of people and goods across Australia’s borders. The Project is supported by the Australian Government’s Department of Immigration and Border Protection. The views expressed in this working paper are entirely the author’s own and not those of the Lowy Institute for International Policy or the Department of Immigration and Border Protection.

Massimiliano Tani is Professor of Finance in the School of Business at the University of New South Wales, Canberra, and a Research Fellow at the IZA Institute of Labor Economics, Bonn.