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Table 4 2SLS estimations. Baseline model, eq. (1)

From: Illicit financial flows and the provision of child and maternal health services in low- and middle-income countries

Independent variables Dependent variable
Family planning
(1)
Antenatal care
(2)
DTP3
(3)
Measles
(4)
Tuberculosis
(5)
Sanitation
(6)
ln Beds
(7)
ln Physic
(8)
Lag (IFFT) −0.299 (0.157) −0.340a (0.089) − 0.611c (0.007) − 0.426b (0.021) 0.106 (0.350) − 0.254 (0.389) − 0.001 (0.934) −0.020 (0.278)
ln GDPpc 7.40c (0.000) 10.96c (0.000) 10.95c (0.000) 10.66c (0.000) 6.05c (0.000) 7.81c (0.000) 0.07c (0.000) −0.04 (0.287)
RESET test (p-value) 4.76 (0.033) 1.54 (0.219) 3.87 (0.053) 4.16 (0.045) 2.00 (0.163) 56.62 (0.000) 14.03 (0.000) 7.20 (0.009)
K-P rk LM (p-value) 46.70 (0.000) 11.08 (0.004) 12.30 (0.002) 12.30 (0.002) 36.65 (0.000) 14.18 (0.001) 11.90 (0.003) 12.08 (0.002)
K-P rk F (S-Y 10% max. IV size) 88,671.96 (19.93) 9.68 (13.43) 16.48 (19.93) 16.48 (19.93) 79,885.44 (19.93) 81.77 (19.93) 48.94 (13.43) 87.86 (19.93)
J statistic (p-value) 1.11 (0.291) 0.09 (0.764) 0.03 (0.850) 0.04 (0.835) 0.32 (0.569) 0.26 (0.608) 0.17 (0.685) 0.05 (0.817)
# Countries 72 64 72 72 59 72 63 66
  1. Estimated coefficients and statistics, p-values in brackets. a Denotes coefficient statistically significant at the 10% level, b at the 5% level, and c at the 1% level. Standard errors and covariance are heteroscedasticity-consistent. RESET is the regression equation specification error (heteroscedastic-robust) test designed to test for missing (excluded) regressors. It also has great power to detect non-linearities in the model. Thus, rejection of the null hypothesis could be due to either a nonlinearity or an omitted explanatory variable. The model is identified if the heteroscedasticity-robust Kleinbergen-Paap rk LM statistic for underidentification test (K-P rk LM) rejects the null hypothesis. If the robust Kleinbergen-Paap rk Wald F statistic for weak identification test (K-P rk F) is greater than the Stock and Yogo [60] critical value (S-Y 10% max. IV relative size), then the null hypothesis of weak instruments can be rejected. The null hypothesis of the robust Hansen’s J statistic is that the instruments are uncorrelated with the error term and that excluded instruments are correctly excluded from the estimated equation. The excluded instruments used in the estimations for the instrumented variables are as follows (lagged values of variables (lag) refer to averages of variables for the period 2002–2007):
  2. - Column (1). Instrumented: ln GDPpc. Excluded instruments: lag (Urban), lag (ln GDPpc)
  3. - Column (2): Instrumented: lag (IFFT), ln GDPpc. Excluded instruments: lag (CPI), lag (IFF/Population), lag (ln GDPpc)
  4. - Column (3): Instrumented: lag (IFFT). Excluded instruments: lag (CPI), lag (IFF/Population)
  5. - Column (4): Instrumented: lag (IFFT). Excluded instruments: lag (CPI), lag (IFF/Population)
  6. - Column (5): Instrumented: ln GDPpc. Excluded instruments: Literacy, lag (ln GDPpc)
  7. - Column (6): Instrumented: lag (IFFT). Excluded instruments: lag (CPI), lag (IFF/GDP)
  8. - Column (7): Instrumented: lag (IFFT), ln GDPpc. Excluded instruments: lag (CPI), lag (IFF/GDP), lag (ln GDPpc).
  9. - Column (8): Instrumented: lag (IFFT). Excluded instruments: lag (CPI), lag (IFF/GDP)