Table 3

Determinants of migration flow by educational level: OLS and Heckman regressions

(1)(2)(3)(4)(5)(6)(7)
Ln(flow ijt)Ln(flow ijt)Ln(flow ijt)Ln(flow-iprim ijt)Ln(flow-prim ijt)Ln(flow-sec ijt)Ln(flow-ter ijt)
Low-skilledHigh-skilled
MethodOLSOLSHeckmanHeckmanHeckmanHeckmanHeckman
Ln migrant networks ij(t-1)0.74***0.76***0.75***0.94***0.76***0.66***0.38***
(0.02)(0.02)(0.02)(0.02)(0.02)(0.02)(0.02)
Ln distance ij−0.20***−0.25***−0.20***0.04−0.05−0.23***−0.51***
(0.04)(0.05)(0.04)(0.05)(0.04)(0.03)(0.04)
Ln pcGDP i(t-1)−0.67***−0.59**−0.63***−0.09−0.14−1.46***−0.40
(0.23)(0.30)(0.23)(0.29)(0.32)(0.28)(0.31)
Ln pcGDP j(t-1)0.010.240.03−0.080.330.34−0.23
(0.22)(0.29)(0.22)(0.28)(0.31)(0.28)(0.32)
FE i  YesYesYesYesYes
FE j  YesYesYesYesYes
FE t  YesYesYesYesYes
Cluster ij  YesYesYesYesYes
Rho  0.20***0.30***0.40***0.31 ***0.46***
  (0 .03)(0.04)(0.04)(0.03)(0.03)
Mills Inverse - VIF  2.073.174.443.644.12
R20.870.84     
Uncensored Observations  6.5665.7594.9425.7945.091
Observations6.5667.0207.0207.0207.0207.0207.020

Note(s): Robust standard errors in parentheses

***p < 0.01, **p < 0.05, *p < 0.1

Selection equation: pbf_educ_tot = Ln migrant networks ij(t-1) Ln distance ij Ln pcGDP i(t-1) Ln pcGDP j(t-1) i.year i.J

Source(s): Table created by authors

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