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1 The Labour Market Integration of Immigrants in OECD Countries on-going work for OECD's Working Party 1, EPC presented by Sébastien Jean (OECD) Workshop on the Economic Integration of Immigrants OECD, 29 May 2006
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2 Motivation Integration is a widely shared priority… But poor labour market outcomes of immigrants, compared to natives
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3 U immig = U natives U immig = 2 x U natives Unemployment is higher among immigrants than among natives….
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4 … even when computed for low skilled males only U immig = 2 x U natives U immig = U natives
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5 Motivation (2) Immigrants often fare worse than natives (in employment and/or wages), for comparable characteristics: imperfect labour market integration How does labour market integration compare across countries? –Are immigrants absorbed into employment? Higher risk of inactivity and/or unemployment? “Wage rebate“? How is integration linked to policy settings on product and labour markets? –How do structural policies interact with integration?
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6 Key points Sizeable cross-country differences in the degree and nature of labour market integration of immigrants Lesser wage gap tends to be associated with higher employment gap Employment gap more persistent (?) Integration can be related to product and labour market policies: –Some policy effects seem to be magnified for immigrants –Immigrants tend to suffer disproportionately from labour market dualism
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7 Outline The approach Data and implementation Results by country and across-countries Preliminary conclusions
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8 What can be learned from the literature? Mainly focused on wages in the US (Chiswick, 1978, Borjas, 1985, 1995), but also some evidence on employment in Europe (Zimmermann Constant eds., 2004, ongoing work in OECD-ELS, 2004-05) Is there a difference between immigrants and natives, once controlled for observable characteristics? Main findings: –Immigrants earn less than natives in the US (wage diff ~ 20% on average), but they catch up over time –In European countries, immigrants display higher risk of being unemployed Explanations: language, unobserved skills (self- selection), social capital, legal obstacles, imperfect skills transferability, discrimination
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9 Our approach Analyse differences across comparable immigrants and natives in activity rates / employment rates / wage rates Control for human capital and socioeconomic characteristics at the individual level Step 1- Carry out similar analysis, country by country Step 2- Jointly study all countries, and relate immigrants- natives differences to policies on the product and labour market
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10 Estimation Framework Step 1 (country by country): –separately for males and females –X: experience, squared experience, marital status, educational attainment –Immig: dummies for migration background (+ EU/nonEU if appl.), +/- 10 years since migration) Step 2 (across countries, with policy variables) –Pol: product and labour market policies
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11 The Data Individual data (longitudinal household surveys) comparable across countries EU15 Countries: ECHP data –standardised annual longitudinal survey, European Union, common questionnaire –7 waves (from 1994 to 2001). US: PSID, longitudinal household data (1997-2001) Australia: HILDA, longitudinal household data (2001- 2003) Canada: SLID, longitudinal household data (1996-2001, not in this presentation)
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12 Implementation Immigrants defined by country of birth –In EU countries, treat separately EU15/ non-EU 15 –In Australia, treat separately anglo-saxon countries –Use nationality for Germany Duration of stay in the country = key variable –But data limitations do not allow much inference about assimilation –Separate +/- 10 years since migration –Not possible in the US data Correct for non-random sample selection into activity and into employment based on observables and unobservables (Heckman, 1979)
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13 Limitations Conceptual –Impossible to control for all factors of cross-country differences: integration policies, immigration motive, immigrants unobserved skills (linked to migration policy, country income and inequality, geography, history!)… –Return-migration bias Statistical –Limited sample if immigrants: weak representativeness, clustered on a short period, cohort effects (although longitudinal), nb obs insufficient to use language and endogamy variables –Attrition bias + under-representation of recently-arrived immigrants
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14 Estimates by country: Employment gap versus wage gap among “recently arrived”, active immigrants
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15 Employment gap vs. wage gap at least 10 years after migration
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16 Cross-country integration differences and (product and) labour market policies Not the only explanation (integration policies etc.) But product and labour market policies may help explain how immigrants fare because –Different distribution of individual productivity –Different behaviour (reservation wage, location choices) –Less social capital –Discriminated against
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17 Cross-country differences and policies
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18 Illustrative evidence: precariousness and immigrants Holds in a regression context: higher risk of precarious contract among recently arrived immigrants (conditional on being employed, when individual observable characteristics are controlled for)
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19 Preliminary conclusions Work still in progress Immigrants = “fragile” population: need to limit perverse effects Think of integration in a dynamic setting: differences, but also rhythm of assimilation Role of integration policies, targeted policies
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