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Does Immigration Boost Per Capita Income?

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    WORKING PAPER 08-23

    Gabriel J. Felbermayr, Sanne Hiller and Davide Sala

    Does Immigration Boost Per Capita Income?

    Department of Economics

    ISBN 9788778823878 (print)

    ISBN 9788778823885 (online)

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    Does Immigration Boost Per Capita Income?

    Gabriel J. Felbermayr , Sanne Hiller , and Davide Sala

    October, 2008

    Abstract

    Using a cross-section of countries, we adapt Frankel and Romers (1999) IV strategy

    to international labor mobility. Controlling for institutional quality, trade, and nancial

    openness, we establish a robust and non-negative causal effect of immigration on real per-

    capita income.

    Keywords : Gravity model, international trade, international migration, cross-country in-

    come regression.JEL-Codes : F22, F12

    We thank Wilhelm Kohler and the participants at the Workshop Migration and Labor Market Integrationat T ubingen University for comments. The project was supported by grant no. 10.06.1.111 of the ThyssenFoundation. The Development Research Centre on Migration, Globalization and Poverty, at University of Sussexhas kindly provided us with the data. All remaining errors are ours. A replication archive is available onwww.asb.dk/staff/dsala

    [email protected]; Department of Economics, University of Stuttgart-Hohenheim, 70593Stuttgart, Germany.

    [email protected]; Department of Economics, Aarhus School of Business, University of Aarhus, Hermodsvej 22,8230 Aabyhj, Denmark

    Corresponding author: [email protected]; Department of Economics, Aarhus School of Business, University of Aarhus, Hermodsvej 22, 8230 Aabyhj, Denmark.

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    1 Motivation

    Advocates of liberal policies argue that immigration raises the income of native factor owners

    (Borjas, 1994). For this immigration surplus to materialize, the aggregate production function

    must display complementarity between inputs and the factor-content of the immigrant inow

    must have a different composition than the pre-existing stock of natives. 1 In contrast, per capita

    income - including immigrants- does not necessarily go up. If immigrants are on average poorer

    than natives, it trivially falls. 2 Besides being of intrinsic interest, the per capita income effect

    determines whether the winners of immigration can potentially compensate the losers without

    excluding the immigrants from the redistribution scheme.

    In the long-run, if immigrants assimilate perfectly (i.e. become indistinguishable from na-

    tives) and the capital stock adjusts, per capita income reverts to the initial level. However, even

    in the long-run, migrants may have different propensities to accumulate nancial and human

    capital than natives, which affects per capita income. Moreover, Ottaviano and Peri (2006)

    argue that the diversity-enhancing effect of immigration increases the value of aggregate out-

    put. Still, there may be an opposite effect, if immigration exacerbates ethnic tensions. These

    ambiguities call for an empirical assessment, the rst one - to our best knowledge - on a broad

    number of countries. 3

    We deal with the endogeneity of immigration to per capita income constructing the geograph-

    ical component of migration from cross-country data on bilateral migrant stocks and using it as

    an instrument - akin to Frankel and Romers (1999, henceforth F&R) for trade openness. Based

    on non-weak instruments, our analysis establishes a robust, non-negative effect of immigration

    on per capita income.

    1 Other conditions, such as the absence of distortions must hold too.2 Total GDP always increases if immigrants nd productive employment.3 Buch and Toubal (2008) account for labor market openness in their study of German states.

    2

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    2 Empirical strategy

    Income regression. Following a well established literature, we estimate the following cross-

    country income regression:

    ln yi = + M ln M i + T T i + F F i + i + I i + u i , (1)

    where i is the country index, yi is per capita GDP (constant dollar PPP, in 2000) and M i the

    stock of immigrants. The vector i contains population , land surface , a continuous measure

    of landlockedness - to capture domestic market size - and the malaria index - to control for

    geography (Rodrik et al., 2004). 4 I i proxies institutional quality (Glaeser et. al., 2004).

    Our focus is on M . Since we include population (native and foreign-born), M does not

    measure the pure size effect of immigration but rather its compositional effect, namely the one

    of an increase in the immigrant share.

    A countrys attitude towards migration is likely shaped by its history and culture. Unable to use

    xed effects in a cross-section, we account for unobserved heterogeneity by inclusion of T i - the

    ratio of exports and imports over GDP - and F i - an indicator of nancial market integration.

    We presume that a liberal attitude towards labour ows comes along with a high degree of

    integration on goods and nancial markets.

    Instrumental Variables. M i , T i , are potentially endogenous. Following F&R, we exploit ge-

    ographical variation to instrument T i . We extend this strategy to M i , using a 226x226 matrix of

    international bilateral migrant stocks for the year 2000. Migrants are dened as foreign-born,

    so that our measure is unaffected by national naturalization policies. Let M ij denote the numberof individuals born in country j and residing in i. Then, M i = jJ M ij is the total immigrant

    stock.

    Let

    E (X ij |G ij ,ADJ ij ) = exp[ G ij X + ADJ ij X + ( G ij ADJ ij ) X ] (2)

    4

    The index of landlockedness is the share of land borders in total border length. Compare Sachs (2003).

    3

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    with X {M, T } . G ij is a vector containing geographical variables (landlockedness, ln pop-

    ulation in 1960, ln area for each i and j and ln bilateral distance) and ADJ ij an adjacency

    dummy.5

    We use Poisson Pseudo Maximum Likelihood (PPML) to estimate (2) for the year2000 (see Santos and Tenyreyro (2006)). Our instruments are computed as X i = j X ij ,

    X ij = G ij X + ADJ ij X + ( G ij ADJ ij ) X is the in-sample linear prediction.6

    Three remarks are in order. First, PPML estimation yields stronger instruments compared

    to OLS, since it accounts for cases with X ij = 0, representing a non-negligable share of country-

    pairs (6(3)% of M ij (T ij ) in the respective sample).

    Second, X i is a generated measure of multilateral remoteness determined exclusively by geogra-

    phy. Hence, no concerns about consistency of (2) as a gravity equation arise.

    Third, M i and T i prove to be collinear in our regression analysis, leading to weak-instruments

    when used simultaneously. On the presumption a countrys remoteness affects economic and

    psychological cost of migration, we shall use M i =1

    N 1 w Dwi as an alternative instrument for

    M i (N is the number of countries and D wi is bilateral distance).

    F i and I i may well be endogenous, but simultaneous instrumentation of many endogenousregressors exacerbates the concern for weak instruments. Since good bilateral data for nancial

    ows are rare, we abstain from instrumenting F i like X i , but rather proxy F i by the (ln) distance

    to the closest major nancial center (Rose and Spiegel, 2008). I i is constitutional review (La

    Porta et. al., 2004). Compared to alternative common measures (e.g. expropriation risk or

    government effectiveness ), it reects permanent constraints on the executive authority, rather

    than election outcomes or temporary policies (Glaeser et al., 2004). By denition, endogeneity

    concerns are attenuated.

    5 The specication is borrowed from F&R. Lewer and van den Berg (2008) show that bilateral migration owsare accurately predicted by geographical variables (along with income and population).

    6 Using only in-sample predictions increases precision, compare Noguer (2005).

    4

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    3 Results

    The elasticity of y with respect to the migrant stock is (signicantly) positive throughout all

    specication in Table 1. Most importantly, weakness of instruments is of no concern (see the

    minimum eigenvalue statistics - Stock and Motohiro (2002)).

    Effect of Immigration. (2) and (3) provide IV estimates based on M and M , respectively.

    The different performance in (2) relative to (3) is ascribed to the correlation of 0.52 between M

    and T (and, therefore with the residual), whereas M is free of this problem. Overall, OLS un-

    derestimates M . Several factors weigh upon this discrepancy. On the one hand, measurementerror in the migrant stock causes attenuation bias in OLS. On the other hand, unobserved het-

    erogeneity ( T, F ), would cause overestimation of OLS. Finally, the direction of the simultaneity

    bias(reverse causality of M and y) is ambiguous.

    Interestingly, throughout rst stage regressions, M is negatively correlated with immigration,

    but positively associated with trade openness.

    Trade Openness. In (5), we add trade openess. To avoid the multicollinearity between T and M when jointly used, we instrument M with M and T with T .7 The absence of such

    multicollinearity is essential to disentangle the effect of labour from goods market integration.

    Financial Openness. (6) and (7) additionally control for nancial openness. This undoes the

    statistical signicance of the immigration effect, but preserves its positive sign. A similar effect

    is produced by the direct inclusion among the regressors of the great circle distance, strongly

    correlated with Rose and Spiegels indicator ( = 0 .6059). Interestingly, the positive effect of

    trade openness remains.

    Geography and Institutions. (1) to (7) draw on the largest possible sample, while (8) to

    (11) use a smaller sample for which institutional quality data is available. These 63 countries

    7 An F-test on the rst stage (regressing T on T and M ), reveals both instruments are jointly but not individ-ually signicant. In this case, weakness of instruments cannot be rejected. Multicollinearity persists even if (2) is

    not identically specied for M ij and T ij .

    5

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    tend to be richer, and presumably, have better data quality. Specications (8) and (9) control

    for a direct effect of geography - see Sachs (2003) - extending (6) and (7) with the inclusion of a

    malaria index. Adding institutional controls (coefficients not displayed) in (10) and (11) leavesthe coefficients on immigration, trade and nancial integration fairly unchanged. The IV and

    OLS estimates are considerably close. Finally, the inclusion of ethnic fragmentation (Alesina et

    al., 2003) leaves estimates qualitatively unchanged (not reported).

    4 Summary

    Using geography-based instruments and controlling for the sheer population size effect, we nd

    robust evidence for immigration to be non-negatively causally related to per capita income.

    Hence, immigration gives rise to a gain that can in principle be used to make the native

    population better off without excluding the immigrants from the redistribution scheme.

    Our preferred specication columns (10) and (11) in Table 1 imply that a 10% increase

    in the migrant stock leads to a per capita income gain of 2.2%. We also nd that trade and

    nancial integration positively affect per capita income.

    6

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    A Data Sources

    - Population, GDP per capita (2000 PPP USD)( yi ): World Development Indicators 2007.

    - Bilateral migration stocks ( M ij ): World Bank, Development Research Centre on Migra-tion, Globalisation and Poverty. 8

    - Bilateral trade data ( T ij = ( X ij + X ji ) /Y i ): Direction of Trade Statistics, IMF, Sept. 2006CD-ROM.

    - Trade openness ( T i ): Penn World Tables 6.2.

    - Adjacency ( ADJ ij ), Area, bilateral distance: CEPII, Paris. 9

    - Financial Openness ( F i ) proxy: negative of Rose (2008).

    - Constitutional Review ( I i ) : La Porta et al. (2004).

    - Landlockedness: CIA World Factbook 2008.

    - Malaria Index: Rodrick et al. (2004).

    References

    [1] Alesina, A., Devleeschauwer, A., Easterly, W., Kurlat, S. and Wacziarg, R. (2003). Frac-tionalization. Journal of Economic Growth 8(2): 155-194.

    [2] Borjas, G.J. (1994). The Economics of Immigration. Journal of Economic Literature 32(4):1667-1717.

    [3] Buch, C.M., Toubal, F. (2008). Openness and Growth: The Long Shadow of the BerlinWall. Journal of Macroeconomics , doi: 10.1016/j.jmacro.2008.07.004.

    [4] Frankel, J.A., and Romer, D. (1999). Does Trade Cause Growth? American EconomicReview 89(3): 379-399.

    [5] Glaeser, E. L., La Porta, R. F. L., and Shleifer, A. (2004). Do Institutions Cause Growth?.Journal of Economic Growth 9(4): 271-303.

    [6] La Porta , Rafael F. L., Lopez-de-Silanes, F., Pop-Eleches, C., Shleifer, A. (2004). Judicial

    Checks and Balances. Journal of Political Economy , 112(2): 445 - 470.[7] Lewer, J.J., and Van den Berg, H. (2008). A gravity model of immigration. Economics

    Letters 99(1): 164-167.

    [8] Noguer, M.,Siscart, M. (2005). Trade raises income: a precise and robust result. Journal of International Economics vol. 65(2): 447-460.

    [9] Ottaviano, G. and G. Peri (2006). Rethinking the Effects of Immigration on Wages. NBERWorking Paper (12496).

    8 http : //www.migrationdrc.org/research/typesofmigration/global migrant origin database.html9 www.cepii.fr/anglaisgraph/bdd/distances.htm

    7

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    [10] Rodrik, D., Subramanian A., and Trebbi F. (2004). Institutions rule: the primacy of in-stitutions over geography and integration in economic development. Journal of EconomicGrowth 9(2): 271-293.

    [11] Rose, A. K., and Spiegel, M. M. (2008). International Financial Remotness and Macroeco-nomic Volatility. Mimeo , University of California Berkeley.

    [12] Sachs, J. D. (2003) Institutions dont Rule: Direct Effects of Geography on per capitaIncome, NBER WP 9490.

    [13] Santos Silva, J.M.C. and Tenreyro, S. (2006). The log of gravity. Review of Economics and Statistics 88 (4): 641-658.

    [14] Stock, J., Motohiro, Y. (2002). Testing for Weak Instruments in Linear IV Regression.NBER Technical WP 0284.

    8

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    (1) (2) (3) (4) (5) (6)

    OLS IV IV OLS IV OLS

    Migration (M) 0.261*** 0.810*** 0.535*** 0.240*** 0.484** 0.210(0.0462) (0.153) (0.138) (0.0434) (0.228) (0.0426)

    Trade (T) 0.00565*** 0.0191*** 0.003(0.00191) (0.00724) (0.001

    Finance (F) 0.723(0.0

    Market Size yes yes yes yes yes yesGeography

    InstitutionAdj R2 / Wald Chi 0.343 66.20 79.10 0.387 68.09 0.542MES 27.86 18.03 5,506

    Variable instrumented: M for (2) M for (3) M for (5) T for (5) M for (7)

    1.500*** -2.881*** -1.763** 55.62 -2.242(0.279) (0.710) (0.861) (39.61) (0.921)

    0.0254*** 1.441** 0.04

    (0.00855) (0.584) (0.014Finance (F) -0.60

    (0.2

    Adj R2 0.556 0.531 0.549 0.375 0.565F-stat. on Excl. Instruments 28.82 16.49 15.94 3,996 12.73Robust standard errors in brackets. ***, **, * denote significance at the 1,5,10% levels, respectively. All regressions include a constant (not shown). Critical values for Minimum

    Table 1. Per capita income and im(A) Second-stage regress

    Large sample (N=162)

    Market Size Controls: ln Area, ln Population 1960, Landlockedness. Geography Controls: Malaria Index. Institutional Controls: Constitutional Review. All first stage regressio

    (B) First-stage regressi

    M

    T

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    WP 06-8 Valrie Smeets, Kathryn Ierulli and Michael Gibbs: Mergers of Equals & Unequals.ISBN 87-7882-165-7 (print); ISBN 87-7882-166-5 (online).

    WP 06-9 Valrie Smeets: Job Mobility and Wage Dynamics.ISBN 87-7882-167-3 (print); ISBN 87-7882-168-1 (online).

    WP 06-10 Valrie Smeets and Frdric Warzynski: Testing Models of Hierarchy: Span of Control, Compensation and CareerDynamics.ISBN 87-7882-187-8 (print); ISBN 87-7882-188-6 (online).

    WP 06-11 Sebastian Buhai and Marco van der Leij: A Social Network Analysis of Occupational Segregation.ISBN 87-7882-189-4 (print); ISBN 87-7882-190-8 (online).

    2007:

    WP 07-1 Christina Bjerg, Christian Bjrnskov and Anne Holm: Growth,Debt Burdens and Alleviating Effects of Foreign Aid in LeastDeveloped Countries.ISBN 87-7882-191-6 (print); ISBN 87-7882-192-4 (online).

    WP 07-2 Jeremy T. Fox and Valrie Smeets: Do Input Quality andStructural Productivity Estimates Drive Measured Differences inFirm Productivity?ISBN 87-7882-193-2 (print); ISBN 87-7882-194-0 (online).

    WP 07-3 Elisabetta Trevisan: Job Security and New RestrictivePermanent Contracts. Are Spanish Workers More Worried of Losing Their Job?ISBN 87-7882-195-9 (print); ISBN 87-7882-196-7 (online).

    WP 07-4 Tor Eriksson and Jaime Ortega: Performance Pay and the TimeSqueeze.ISBN 9788778822079 (print); ISBN 9788778822086 (online).

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    WP 08-2 Flora Bellone, Patrick Musso, Lionel Nesta et FrdricWarzynski: Leffet pro-concurrentiel de lintgration

    europenne : une analyse de lvolution des taux de marge dansles industries manufacturires franaisesISBN 9788778822857 (print); ISBN 9788778822864 (online).

    WP 08-3 Erdal Yalcin: The Proximity-Concentration Trade-Off underGoods Price and Exchange Rate UncertaintyISBN 9788778822871 (print); ISBN 9788778822888 (online)

    WP 08-4 Elke J. Jahn and Herbert Brcker: Migration and the WageCurve: A Structural Approach to Measure the Wage andEmployment Effects of MigrationISBN 9788778822895 (print); ISBN 9788778822901 (online)

    WP 08-5 Sren Harck: A Phillips curve interpretation of error-correctionmodels of the wage and price dynamicsISBN 9788778822918 (print); ISBN 9788778822925 (online)

    WP 08-6 Elke J. Jahn and Thomas Wagner: Job Security as anEndogenous Job CharacteristicISBN 9788778823182 (print); ISBN 9788778823199 (online)

    WP 08-7 Jrgen Drud Hansen, Virmantas Kvedaras and Jrgen Ulff-Mller Nielsen: Monopolistic Competition, International Tradeand Firm Heterogeneity - a Life Cycle Perspective -ISBN 9788778823212 (print); ISBN 9788778823229 (online)

    WP 08-8 Dario Pozzoli: The Transition to Work for Italian UniversityGraduatesISBN 9788778823236 (print); ISBN 9788778823243 (online)

    WP 08-9 Annalisa Cristini and Dario Pozzoli: New Workplace Practicesand Firm Performance: a Comparative Study of Italy and Britain

    ISBN 9788778823250 (print); ISBN 9788778823267 (online)WP 08-10 Paolo Buonanno and Dario Pozzoli: Early Labour Market

    Returns to College SubjectsISBN 9788778823274 (print); ISBN 9788778823281 (online)

    WP 08-11 Iben Bolvig: Low wage after unemployment - the effect of changes in the UI systemISBN 9788778823441 (print); ISBN 9788778823458 (online)

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    WP 08-12 Nina Smith, Valdemar Smith and Mette Verner: Women in TopManagement and Firm Performance

    ISBN 9788778823465 (print); ISBN 9788778823472 (online)

    WP 08-13 Sebastian Buhai, Elena Cottini and Niels Westergrd-Nielsen:The impact of workplace conditions on firm performanceISBN 9788778823496 (print); ISBN 9788778823502 (online)

    WP 08-14 Michael Rosholm: Experimental Evidence on the Nature of theDanish Employment MiracleISBN 9788778823526 (print); ISBN 9788778823533 (online)

    WP 08-15 Christian Bjrnskov and Peter Kurrild-Klitgaard: EconomicGrowth and Institutional Reform in Modern Monarchies andRepublics: A Historical Cross-Country Perspective 1820-2000ISBN 9788778823540 (print); ISBN 9788778823557 (online)

    WP 08-16 Nabanita Datta Gupta, Nicolai Kristensen and Dario Pozzoli:The Validity of Vignettes in Cross-Country Health StudiesISBN 9788778823694 (print); ISBN 9788778823700 (online)

    WP 08-17 Anna Piil Damm and Marie Louise Schultz-Nielsen: TheConstruction of Neighbourhoods and its Relevance for theMeasurement of Social and Ethnic Segregation: Evidence fromDenmark ISBN 9788778823717 (print); ISBN 9788778823724 (online)

    WP 08-18 Jrgen Drud Hansen and Jrgen Ulff-Mller Nielsen: Price as anIndicator for Quality in International Trade?ISBN 9788778823731 (print); ISBN 9788778823748 (online)

    WP 08-19 Elke J. Jahn and John Wegner: Do Targeted Hiring Subsidiesand Profiling Techniques Reduce Unemployment?ISBN 9788778823755 (print); ISBN 9788778823762 (online)

    WP 08-20 Flora Bellone, Patrick Musso, Lionel Nesta and FredericWarzynski: Endogenous Markups, Firm Productivity andInternational Trade: Testing Some Micro-Level Implications of the Melitz-Ottaviano ModelISBN 9788778823779 (print); ISBN 9788778823786 (online)

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    WP 08-21 Linda Bell, Nina Smith, Valdemar Smith and Mette Verner:Gender differences in promotion into top-management jobs

    ISBN 9788778823830 (print); ISBN 9788778823847(online)

    WP 08-22 Jan Bentzen and Valdemar Smith: An empirical analysis of therelationship between the consumption of alcohol and livercirrhosis mortalityISBN 9788778823854 (print); ISBN 9788778823861(online)

    WP 08-23 Gabriel J. Felbermayr, Sanne Hiller and Davide Sala: DoesImmigration Boost Per Capita Income?ISBN 9788778823878 (print); ISBN 9788778823885(online)