Abstract
We examine the influence of corruption on migration for 111 countries between 1985 and 2000. Robust evidence indicates that corruption is among the push factors of migration, especially fuelling skilled migration. We argue that corruption tends to diminish the returns to education, which is particularly relevant to the better educated.
Notes
1 Note, however, that this assessment does not rule out that corruption may actually yield positive economic effects under specific circumstances (Dreher and Gassebner, Citation2013).
2 In addition to that, the increase of income inequality and poverty caused by corruption (Gupta et al., Citation2002) may foster the political demand for redistribution. As the better skilled are typically the typical net payers of (progressive) income taxes, this may further fuel skilled emigration.
3 The migration data is available only for three points in time (1990, 1995 and 2000). Therefore, we use 5-year averages of the explanatory variables (for the 1986–1990, 1991–1995 and 1996–2000 periods) to estimate their influence on migration.
4 We use the ICRG data because it is available since 1984, making a panel estimation approach to the corruption–migration nexus possible. Other corruption measures are available only for shorter time periods. Jain (Citation2001, p. 77) notes that the various corruption measures are usually highly correlated.
5Our findings are also robust to the inclusion of further controls for religious fractionalization, oil production, government size, further geographic and historic country characteristics (landlocked location, common language) and education (years of schooling).
6We also experimented with instrumental variable (IV) estimations, as reverse causation may be an issue. However, pooled and fixed-effects IV-estimations (where corruption is instrumented by the quality of judicial institutions and the degree of democratic participation) do not indicate that corruption is endogenous to migration. Also, Durbin–Wu–Hausman tests suggest that any endogeneity among the regressors does not bias our estimates.
7Note that all constant influencing factors (colonial ties, distance, etc.) are now subsumed under the fixed effects.