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Barcelona GSE Roundtable on the Future of Europe: Migration


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Julian di Giovanni (UPF and Barcelona GSE)

Published in: Economy & Finance
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Barcelona GSE Roundtable on the Future of Europe: Migration

  1. 1. 14th Barcelona GSE Trobada “The Future of Europe”: Migration Julian di Giovanni Universitat Pompeu Fabra, Barcelona GSE, CREI, and CEPR October 14, 2016
  2. 2. Issues Driving Migration Debate Today 1. Economic concerns 2. Politics and policy 3. Cultural issues European context Intra-EU flows Refugee crisis
  3. 3. Current Headline Numbers Percentage of foreign-born/total population in 2014 Europe NA & Australasia France 12.4 Australia 28.1 Germany 13.2 Canada 20.1 Italy 9.6 New Zealand 11.8 Spain 13.2 United States 13.3 Sweden 16.6 United Kingdom 13.3 Source: OECD migration database
  4. 4. Current Headline Numbers Inflows of Asylum Seekers 05000001.0e+061.5e+06 Inflowofasylumseekers 2005 2010 2015 year EU Non-EU OECD Germany: 23.7%, France: 13.6%, Sweden: 12.4% Source: calculations based on OECD migration database
  5. 5. European Migration Over Time Post-WWII Source: de la Rica, Glitz, Ortega (2015)
  6. 6. Dynamics of the Main Recipient Countries Post-WWII Source: de la Rica, Glitz, Ortega (2015)
  7. 7. European Migration Over Time Post-EU Enlargement Source: de la Rica, Glitz, Ortega (2015)
  8. 8. Some Economic Effects Huge literature: Income and productivity Labor market impact (on natives): wages, employment, occupational specialization Firm creation and entrepreneurship Short-term fiscal costs & long-term reshaping of welfare state Space constraints: density, lack of housing, housing prices . . .
  9. 9. Cost-Benefit Analysis Will discuss a few major themes See Handbook of the Economics of International Migration, 2015, for recent reviews ⇒ “Immigration in Europe: Trends, Policies, and Empirical Evidence,” by Sara de la Rica, Albrecht Glitz, and Francesc Ortega of particular interest!
  10. 10. Aggregate Gains and Losses Early analysis with simple models Borjas (1995): what are gains in US from migration? Model shows tiny gains via immigration surplus ≈ 0.1% of GDP ⇒ Much lower than net fiscal costs arising from immigration ⇒ Corresponds to wealth transfer from native workers to capitalists Numbers improve depending on skill mix of immigrants
  11. 11. Aggregate Gains and Losses General equilibrium analysis More recent quantitative macro models generally find larger gains of immigration for natives and world economy as a whole Klein and Ventura (2007): labor reallocation in growth model di Giovanni, Levchenko and Ortega (2015): multicountry model that focuses on increased varieties and remittances (see also Iranzo and Peri, 2009; Aubrya, Burzy´nski, Docquier, 2016)
  12. 12. Gains from Elimination of Int’l Barriers (percent of world GDP) Table 1 Efficiency Gain from Elimination of International Barriers (percent of world GDP) All policy barriers to merchandise trade 1.8 Goldin, Knudsen, and van der Mensbrugghe (1993) 4.1 Dessus, Fukasaku, and Safadi (1999)a 0.9 Anderson, Francois, Hertel, Hoekman, and Martin (2000) 1.2 World Bank (2001) 2.8 World Bank (2001)a 0.7 Anderson and Martin (2005) 0.3 Hertel and Keeney (2006, table 2.9) All barriers to capital flows 1.7 Gourinchas and Jeanne (2006)b 0.1 Caselli and Feyrer (2007) All barriers to labor mobility 147.3 Hamilton and Whalley (1984, table 4, row 2)c 96.5 Moses and Letnes (2004, table 5, row 4)c 67 Iregui (2005, table 10.3)c,d 122 Klein and Ventura (2007, table 3)e a These studies assume a positive effect of trade on productivity; the other trade studies assume no effect. b Change in consumption rather than GDP. c Assumes two factors of production, immobile capital, and no differences in total factor productivity. Estimates from Hamilton and Whalley and from Moses and Letnes cited here assume no differences in inherent productivity Results from exercises point to much larger gains from international migration than other forms of globalization Source: Clemens (2011)
  13. 13. Cross-Country EvidenceB) Gravity-predicted MSH and GDP per person ARE GAB T QAT .3 grants AFG AGO ALB ARE ARG ARM ATG AUS AUT AZE BDI BEL BEN BFABGD BGR BHR BHS BLR BLZ BMU BOL BRABRB BRN BTN BWA CAF CAN CHE CHL CHN CIV CMR COG COL COM CPV CRICUB CYPCZE DEU DJI DMA DNK DOM DZA ECU EGY ERI ESP EST ETH FIN FJI FRA FSM GAB GBR GEO GHAGIN GMB GNB GNQ GRC GRD GTM GUY HND HRV HTI HUN IDN IND IRL IRN IRQ ISL ISR ITA JAM JOR JPN KAZ KEN KGZ KHM KIR KNA KOR KWT LAO LBN LBY LCA LKA LSO LTU LUX LVA MAR MDA MDG MDV MEX MLI MLT MNG MOZ MRT MUS MWI MYS NAM NER NGA NIC NLD NOR NPL NZL OMN PAK PANPER PHL PNG POL PRIPRT PRY QAT ROU RUS RWA SAU SDN SEN SGP SLB SLE SLV SOMSTP SUR SVK SVN SWE SWZ SYC SYR TCD TGO THA TJK TKM TON TTO TUN TUR TWN TZAUGA UKR URY USA UZB VCT VEN VNM VUT WSM YEM ZAF ZAR ZMB ZWE -4-2024 -.05 0 .05 .1 predicted openness to migrants income per person and predicted openness to migrants Coefficient: 15.7, Standard Error: 3.9 nt: 6.5, Error: 1.2 In(GDPperperson) garithm of population and area. The predictor for immigration share used is the linear gravity predictor. country size. A: MSH and GDP per person. B: Gravity-predicted MSH and GDP per person. Note: The scatterplot The predictor for immigration share used is the linear gravity predictor. 239/ Journal of International Economics 92 (2014) 231–251 Results driven by TFP due to diversity effects: differentiated skill in labor force, increased innovation Source: Ortega and Peri (2014)
  14. 14. Labour Market Outcomes Natives vs. Migrants Table 24.3 Labor market outcomes Destination country Participation rate foreign- born (%) Participation gap (foreign- bornÀnative- born) (%) Unemployment rate foreign- born (%) Unemployment gap (foreign- bornÀnative- born) (%) Median wages foreign-born over median wages natives Share low education foreign- born (%) Gap share low education (foreign- bornÀnative- born) (%) (1) (2) (3) (4) (5) (6) (7) France 68.2 À3.2 15.8 6.7 0.90 49.6 3.8 Germany 74.0 À3.8 8.7 3.7 0.93 44.0 19.8 Italy 76.2 13.4 13.9 3.5 n.a. 50.4 À13.2 Spain 79.3 6.3 34.7 11.7 n.a. 45.5 À20.9 Sweden 74.9 À6.6 16.1 9.6 0.93 27.8 2.8 UK 73.5 À3.3 9.3 1.5 n.a. 28.0 À23.2 Data in columns 1–4 are taken from OECD International Migration Outlook 2013 and refer to the working-age population aged 15–64 in the year 2012. Data in column 5 are taken from International Migration Outlook 2008 (OECD, 2008), Chart I.13, and refer to unconditional relative median wages. Educational data in columns 6 and 7 are taken from the Database on Immigrants in OECD Countries (DIOC) of the OECD and refer to the year 2005/06. Low educational attainment means up to lower secondary education. Observations with unknown education level were excluded from the calculation of education shares. Education shares are calculated for the population aged 15 and older and are reported in percentages. In general, migrants More unemployed Paid less Education level: mixed across countries Source: de la Rica, Glitz, Ortega (2015)
  15. 15. Distributional Effects General Issues Given Borjas’s work, economists turned to studying labor market outcomes for both native and migrant workers Impact of entry of migrants can have impact on both wages and employment ⇒ Technology, labor force composition, institutional/country characteristics, how firms respond (output mix vs. factor intensity) impact on which margins migration may have largest impact Lots of work out there, and surely more to come
  16. 16. Distributional Effects Wage Impact on Natives Recent structural analysis with micro data provide mixed results Borjas (2003): Immigration is responsible for a substantial drop in unskilled wages in the US Ottaviano and Peri (2012): find opposite in a model that allows for imperfect substitution between immigrants and natives with equal education and potential experience (also see Manacorda et al. (2012) for similar results with UK data) Dustmann and Glitz (2015): firm-level analysis in Germany points to adjustments in relative factor intensities within firm + entry/exit Overall, results vary but arguably lower skilled native workers most likely to be negatively affected
  17. 17. Fiscal Effects & Politics of Migration Measuring net fiscal effects of migration is difficult How much spent on migrants? How much do migrants contribute to tax base? What is baseline viz. comparable natives’ contribution/cost? Dustmann and Frattini (2014) exploit micro data for UK over 1995–2011 ⇒ Punchline: “Immigration to the UK since 2000 has been of substantial net fiscal benefit” Longer-term issues: more immigrants may erode willingness to redistribute income, contribute to public education/healthcare/ pensions ⇒ Political economy of immigration
  18. 18. Migration Boom did not Occur in a Vacuum Other factors to consider “Great Recession” Growing inequality Austerity policies Increased international trade/outsourcing Technological change (skill biased?)
  19. 19. Going Forward A “longer view” Besides potential gains discussed, new migrants provide source of cheaper labor for Aging population services Facilitate continuing increase in female participation Greater use of policy tools such as “EU Blue Card Scheme” to attract better quality workers like Australia, Canada, US (not applicable to within EU)? Strains placed by migrants (economic or refugees) will require coordination across countries and more resources Institutional/social rigidity must be tackled (not just applicable to migration)