344
l
WIM NAUDÉ AND HENRI BEZUIDENHOUT
TABLE 28.3 Pooled OLS Regression Results dependent variable = log of remittances in dollars, no control variables Global financial crises Variable Constant
18.49 (71.6)*
Global financial crises
−1.25 (−4.37)*
Diagnostics R2
0.77
Time dummies
Yes
Country fixed effects
Yes
N
644
F
67.16
Source: Authors’ estimations. Note: Robust t-ratios are in parentheses. * = significance at 1 percent level.
TABLE 28.4 Pooled OLS Regression Results dependent variable = log of remittances in dollars, controls included Variable
Basic model
With global financial crises
Constant
−8.72 (−0.59)
−8.72 (−0.59)
−1.92 (−5.86)*
−1.92 (−5.86)*
Income host (SSA GDP per capita)
0.44 (2.10)***
0.44 (2.10)***
Credit private sector
0.61 (5.23)*
0.61 (5.23)*
Exchange rate
0.33 (4.52)*
0.33 (4.52)*
Aid from EU
0.02 (0.17)
0.02 (0.17)
Population
2.30 (2.56)**
2.29 (2.56)***
GNI home
Global financial crises
—
−0.90 (−1.32)
Diagnostics R2
0.85
0.86
Yes
Yes
Time dummies Country fixed effects N F
Yes 300 75.29*
Yes 300 75.29*
Source: Authors’ estimations. Note: Robust t-ratios are in parentheses. *, **, *** indicate significance at the 1, 5, and 10 percent levels, respectively. EU = European Union; — = not available.
absolute terms, larger migrant populations. To the extent that a country’s population is a proxy for its migrant stock, the finding is consistent with the proxy supposition. In a dynamic model, this would mean that lagged remittances ought to have a substantial and significant effect.