Why are migrants paid more? Alex Bryson NIESR and CEP Rob Simmons Lancaster University Institute of Education 5th October 2011 National Institute of Economic and Social Research Research Issue • In efficient labour markets for very highly paid workers one expects wage differentials between migrant and domestic workers to reflect differences in labour productivity. • Yet, using panel linked employer-employee data for a single industry, we find a persistent wage penalty for domestic workers having conditioned on individual time-varying labour productivity and firm fixed effects. • Why? Contribution • Examines role of migration in generating within-occupation wage differentials • Is migrant wage premium a superstar effect? – Will explore two definitions of superstar: • Higher output • More popular or charisma • If so does migration affect team fortunes? • Or do natives face employer monopsony power in wage setting resulting in wages below marginal product? • Able to account for time-varying individual labour productivity and team FE Empirical strategy • Individual wage equations containing nationality and locality indicators • OLS and quantile regression – superstars in the upper tail – returns to talent should be magnified at the top • Wage decomposition – with and without individual labour productivity – Oaxaca/Blinder and Machado/Mata for quintiles • Match attendance and team points models – change in nationality shares on change in team attendance controlling for team FE – If migrants > productive should show up in wins – if migrants > popular should show up in attendance Theory: migration effects and wages • Migrant wage penalty: - unable to pursue previous career in new host country - assimilation (qualification accreditation, language) - employer discrimination (tastes) • Offsetting effects – Working harder/longer – „Better‟: drawn from different part of ability distribution -> more productive – Bargaining power of highly skilled with good outside options • Employer competition for their scarce skills • Broader labour market impacts: – Increase in labour supply lowering ambient wages – Ability to substitute for natives -> unemployment? • Lump of labour fallacy Migration empirical evidence US literature • Migrant wage penalty but convergence with assimilation (Lazear 1999; Hu, 2000) • Effects on native workers hotly disputed – Borjas (2006): significant negative impact on native wages – Card (1990): little/no impact of Mariel boatlift on Miami unemployment rates UK literature: • Manacorda et al. (2011) GHS and LFS, 1973-2007 – NS effect on native wages due to imperfect substitution – Sizeable negative effect on existing immigrants‟ wages • US v UK – Higher degree of substitution of migrants for natives in US than UK? (Ottaviano and Peri, 2011) Evidence on Skilled Migration Effects Some evidence that highly skilled immigrants: - Have lower probability than natives of similar education levels to obtain highly skilled jobs - Get lower wages than natives (see Clark & Drinkwater, 2008, UK using LFS; Friedberg, 1996, Israel) - Penalty could be due to misallocation/skills mismatch or discrimination - Possible assimilation but mixed evidence on wage convergence - Can reduce native and migrant returns to higher qualifications but size of migrant cohorts too small to have big effects - But problems with survey data - education and occupation are just proxies for ability, don‟t observe individual productivity, unobserved heterogeneity at individual and industry levels Superstars • Superstardom: “relatively small numbers of people earn enormous amounts of money and dominate the activities in which they engage” (Rosen) • Rosen (1981) versus Adler (1985) on superstar formation • Rosen‟s (1981) superstars are individuals who are slightly better than their peers – lower talent=imperfect substitute for higher talent – convex relationship between talent distribution and distribution of rewards “small differences in talent become magnified in large earnings differences” – scale economies of joint consumption allow relatively few sellers to service a large market (“one‟s personal market scale”) • Adler (1985): A reputation arising through popularity – Underpinning = Stigler/Becker consumption capital – “Stardom is a market device to economise on learning costs in activities where the more you know the more you enjoy. Thus stardom may be independent of the existence of a hierarchy of talent”. Implications of Rosen V Adler • Both agree on need for economies of scale – Football industry is good example • Rosen: labour productivity should capture superstar effects – Search for convex relationship between productivity and rewards – If fully capture productivity should be no role for residuals nor for talent-based migrant effects on team fortunes • Adler: superstardom also requires popularity – Players can increase wages by investing in on-field talent or popularity – Popularity may be unobservable even when have all on-field performance • Own thoughts: an unobserved dimension of “effort” – Distinction between „what you do‟ and „the way that you do it‟ – Not all goals scored are the same - role for charisma? • Is this equivalent to „popularity‟ or more like effort being multi- tasked? • What you do v how you do it or on-field versus off-field activities? • Might expect important role for residuals in team outcomes even having controlled for time-varying individual labour productivity Literature on superstars • Andersson et al. (2009) superstar wages in software design – programmers are rewarded highly for their potential to deliver high (but unknown) returns i.e. a successful computer game • Football (soccer) papers – Lucifora and Simmons (2003) mid-1990s, one superstar (Roberto Baggio) – Brandes et al. (2008) on superstars in German football - apparently Bayern Munich had 6 superstars in 2002/03 (too many?) – Franck & Nüesch (2008), German football, evidence in favour of Adler but Franck & Nüesch, Econ Inquiry forthcoming find support for Adler and Rosen (better data) • These authors don‟t look at migration • Only one paper looks at migration and superstars – Kleven et al (2010): top rate taxation affects location of superstar professional footballers in Europe Institutional setting: (1) The footballers‟ labour market • In principle, football labour market is highly competitive - players are globally mobile. • No barriers to entry across EU post-Bosman, no unions, observable performance, so pay = MRP, should not observe any discrimination. • OK but performance is multi-dimensional, questions of productivity spillovers, peer effects. • And restrictions remain: immigration controls (visas, work permits) and quotas for non-EU players. • And players have preferences e.g. few English players outside England – Preference to remain gives employer some monopsony power in wage setting where few credible outside options – Compensating differential for amenity of remaining local Institutional setting for our paper (2) Italian football • Our sample period is 2000-2008, just after boom period • High dependence on sale of broadcast rights • In our sample period rights were sold individually by clubs. • And gate attendances and receipts fell during this period. – Role of hooliganism: teams who were forced to play behind closed doors – Calciopoli corruption effects. • So negative shocks to revenues, in contrast to England, France, Germany and Spain. • Quotas imposed on club hiring of non EU players but incremental and not very apparent on the ground – Teams able to trade quotas – % non-EU migrants in sample constant over time (21-23%) • Most famous clubs are most reliant on migrants – Inter Milan: 30% Italian; 56% non-EU Italians in Italy • % Italian (domestic) players is between 69-74% over sample period, somewhat higher than native shares in other European leagues (Frick, 2007) • Other evidence that Italians have strong preference for remaining in Italy and for remaining „local‟ • Boeri and van Ours (2008): intra-regional mobility dominated by net migration of foreign workers • Manacorda and Moretti (2006): lack of mobility among native Italians partly reflects parental preferences to have children co-resident • 19% of Italian players in our sample are „local‟ (playing for a team <=200km from birth place) Why football data can contribute • Able to pin down within-occupation wage differentials • Good data on migration – Where born – Assimilation: years playing professionally in Italy • Very complete time-varying measures of on- field worker performance • Good data on team revenues • Worker and employer panels – Take out FE‟s Wage equation Log real salary = f(age, age squared, experience, team characteristics, player productivity, playing for national team, team fixed effects, nationality dummies). • Nationality = Italian (base), non-Italian EU, non-EU. • This is our most complete model. • But we‟ll estimate in stages to see how nationality coefficients vary. • Raw, then demographics, then productivity, then team time-varying covariates and finally with team FE • Also check on productivity squared (Rosen) Data • Unbalanced panel N=2,601 player-year observations – 914 footballers, 38 clubs in Serie A and B. Estimation sample 906 players at 34 clubs: 2488 player-year observations • Wages: basic contractual net salary excluding bonuses and endorsements, image rights etc. • These are actual salaries reported in Italian newspapers and annuals: Corriere dello Sport Stadio (2001), Il Messaggero (2002), La Pagelle di Paolo Ziliani (2003-06), Gazzetta dello Sport