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Socioeconomic Driving Forces of International Migration

  • Dennis Wesselbaum EMAIL logo
Published/Copyright: May 18, 2018

Abstract

This paper makes a contribution to the literature on the driving forces of international migration. In contrast to the existing literature we consider the effect of socioeconomic variables (population dynamics, education and health, and openness) on migration flows. Especially the effects of openness of a society have not received much attention in the scientific debate.We use a panel data set of bilateral migration flows between 16 destination and 198 origin countries over the time span from 1980 to 2015. Most importantly, we find that our socioeconomic variables significantly affect the migration decision. Including socioeconomic variables does affect the size of the effects of the commonly used variables in the literature.Further, we find robust evidence that the socioeconomic variables at hand have non-linear effects on migration. For example, we find that the effect of human capital on migration follows an inverted U-shaped pattern.

JEL Classification: F22; I25; O15

Appendix

Table 7:

List of all countries in our sample, destination countries in bold.

AfghanistanBurundiEstoniaItalyMicronesiaRomaniaTanzania
AlbaniaCambodiaEthiopiaJamaicaMoldovaRussiaThailand
AlgeriaCameroonFijiJapanMonacoRwandaTogo
American SamoaCanadaFinlandJordanMongoliaSt. Kitts and NevisTonga
AndorraCape VerdeFranceKazakhstanMoroccoSt. LuciaTrinidad and Tobago
AngolaCentral African Rep.French GuianaKenyaMozambiqueSt. Vincent and the Gr.Tunisia
AnguillaChadFrench PolynesiaKiribatiMyanmarSamoaTurkey
Antigua and B.ChileGabonKoreaNamibiaSan MarinoTurkmenistan
ArgentinaChinaGambiaKuwaitNauruSao Tome and PrincipeTuvalu
ArmeniaColombiaGeorgiaKyrgyzstanNepalSaudi ArabiaUganda
AustraliaComorosGermanyLaosNetherlandsSenegalUkraine
AustriaCongoGhanaLatviaNew CaledoniaSerbiaUnited Arab Emirates
AzerbaijanCosta RicaGreeceLebanonNew ZealandSeychellesUnited Kingdom
BahamasCote d’IvoireGrenadaLesothoNicaraguaSingaporeUSA
BahrainCroatiaGuatemalaLiberiaNigerSlovakiaUruguay
BangladeshCubaGuineaLibyaNigeriaSloveniaUzbekistan
BarbadosCyprusGuinea-BissauLiechtensteinNorwaySolomon IslandsVanuatu
BelarusCzech RepublicGuyanaLithuaniaOmanSomaliaVenezuela
BelgiumDPR KoreaHaitiLuxembourgPakistanSouth AfricaViet Nam
BelizeDR CongoHondurasMacedoniaPalauSpainWestern Sahara
BeninDenmarkHong KongMadagascarPalestineSri LankaYemen
BhutanDjiboutiHungaryMalawiPanamaSudanZambia
BoliviaDominicaIcelandMalaysiaPapua New GuineaSurinameZimbabwe
Bosnia and Herz.Dominican Rep.IndiaMaldivesParaguaySwaziland
BotswanaEcuadorIndonesiaMaliPeruSweden
BrazilEgyptIranMaltaPhilippinesSwitzerland
BruneiEl SalvadorIraqMauritaniaPolandSyria
BulgariaEquatorial GuineaIrelandMauritiusPortugalTaiwan
Burkina FasoEritreaIsraelMexicoQatarTajikistan
Table 8:

Summary statistics.

VariableObsMeanStd. Dev.MinMax
Migration19,2341356.097363.450415,399.2
ln Distance24,7048.640.894.099.88
Border25,3440.020.1201
Language25,3440.140.3501
Colony25,3440.090.2801
ln GDPj25,34410.60.329.7711.41
ln GDPi21,9848.291.52511.89
ln Populationj25,34416.681.214.9719.59
ln Populationi24,73615.322.228.9521.02
Pop Densityj24,552123.53131.611.97502.82
Pop Densityi24,176271.581332.411.1519,153.5
Young Popj22,1760.210.030.150.28
Young Popi20,5440.260.030.150.36
lnAidji13,05914.062.477.622.33
Tradej23,562−7.25e91.09e11−6.55e112.69e11
Tradei19,7617.61e83.88e10−6.55e113.58e11
Tourismj12,8701.73e71.7e71,535,5006.7e7
Tourismi14,2404,779,9971.07e710008.45e7
Internetj15,84044.6333.140.0994.58
Interneti15,48815.6523.41095.83
Schoolj22,17610.521.497.0913.24
Schooli12,3207.113.070.2513.24
Tertiaryj22,17622.2710.852.855.6
Tertiaryi12,32010.3710.090.0163.1
Human Capj22,1762.890.422.033.76
Human Capi12,3202.140.681.038
Life Expj25,34478.332.6372.9783.49
Life Expi23,85666.999.9529.2784.28
Expj16,434165.8173.0330.26386.8
Expi21,344206.72324.041.018105.08
Impj21,344198.61189.865.351341.9
Impi16,434165.5167.8723.07331.43

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Published Online: 2018-5-18

©2017 Walter de Gruyter GmbH, Berlin/Boston

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