Revisiting Quality of Governance, Financial Development, Globalisations on Foreign Direct Investment
Table 4: The effect of all independent variable towards FDI Inflows in both samples: Comprehensive Model (CM) approach
| Variables | Upper Middle-Income Countries | Lower Middle-Income Countries | ||||
| M1 | M2 | M3 | M1 | M2 | M3 | |
| CSD in SR | ||||||
| Error Correction | -0.502*** (0.0669) | -0.459*** (0.0763) | -0.557*** (0.0716) | -0.598*** (0.0747) | -0.566*** (0.0830) | -0.650*** (0.0901) |
| Δ QoG | 47.83(37.75) | 35.53(52.11) | 13.74(33.03) | 8.687(17.11) | -1.003(15.63) | 11.43(16.16) |
| Δ FD | 76.79** (34.51) | 51.34* (30.73) | 41.80(30.13) | -4.231(28.20) | -4.977(26.11) | 5.418(26.73) |
| Δ PGI | -16.53(36.15) | -4.422(20.35) | 12.07(26.19) | -47.66* (27.63) | -31.80(22.77) | -48.54* (28.71) |
| Δ SGI | 57.30(53.06) | 18.63(38.58) | 8.255(54.89) | 42.04** (17.96) | 24.70(19.72) | 36.38** (18.26) |
| Δ QoGFD | -11.48(9.556) | -8.201(13.21) | -2.575(8.395) | -1.732(4.485) | 0.559(4.171) | -2.830(4.279) |
| Δ PGIFD | 2.637(8.451) | -1.300(5.181) | -4.615(6.444) | 11.88(7.321) | 7.549(6.109) | 10.76(7.465) |
| Δ SGIFD | -14.61(13.17) | -5.028(9.430) | -2.133(13.46) | -11.03** (4.698) | -6.630(5.246) | -10.09** (4.890) |
| Δ CO2 | -0.637(0.521) | -0.0818(0.445) | -0.288(0.364) | -0.269(0.464) | -0.0248(0.482) | 0.118(0.436) |
| Δ INF | 0.00973(0.00779) | 0.00419(0.00542) | 0.00628(0.00610) | -0.00986(0.0125) | -0.0148(0.0147) | -0.00211(0.0151) |
| Δ LBF | -0.193(3.305) | -1.118(2.547) | -2.292(2.847) | -5.585(7.871) | -8.740(7.229) | -8.836(7.723) |
| CSD in LR | ||||||
| QoGt-1 | -4.604*** (1.050) | -2.063* (0.529) | -16.10*** (3.372) | 1.424*** (0.496) | 1.682*** (0.501) | 0.558(0.535) |
| FDt-1 | 4.825*** (0.745) | 4.798(3.987) | -1.447*** (0.406) | 7.172*** (1.816) | 19.54*** (4.100) | 18.13*** (3.692) |
| PGIt-1 | 5.936*** (0.330) | 7.992* (4.158) | 0.934** (0.449) | -2.068* (1.219) | 9.963*** (3.797) | 21.01*** (5.596) |
| SGIt-1 | 3.565*** (0.250) | -3.481(2.569) | 5.624*** (1.808) | -1.875*** (0.718) | -1.014(0.505) | -10.58*** (2.029) |
| QoGFDt-1 | 1.852*** (0.369) | 1.171*** (0.150) | 5.037*** (0.868) | 0.184(0.135) | -0.0132(0.133) | 0.443*** (0.152) |
| PGIFDt-1 | -1.671*** (0.0895) | -2.692** (1.110) | -0.432*** (0.130) | -0.249** (0.108) | -3.650*** (0.977) | -6.297*** (1.412) |
| SGIFDt-1 | -0.362*** (0.0206) | 1.076* (0.623) | -1.671*** (0.454) | 0.221(0.138) | 0.229** (0.102) | 2.890*** (0.585) |
| CO2t-1 | 0.887*** (0.123) | 0.591*** (0.194) | -0.203(0.166) | -0.000128(0.000111) | -0.453*** (0.107) | -0.562*** (0.119) |
| INFt-1 | 0.000319** (0.000146) | -6.74e-05(5.88e-05) | -7.23e-05 (0.000101) | -0.566*** (0.114) | 8.28e-05 (0.000121) | -9.95e-05(7.97e-05) |
| LBFt-1 | 1.551*** (0.381) | -1.449*** (0.374) | -1.346*** (0.406) | 1.638*** (0.285) | -1.100** (0.452) | -0.599(0.476) |
| Constant | -18.06*** (2.392) | -5.595*** (0.971) | -12.86*** (1.809) | -13.33*** (1.664) | ||
| Observation | 606 | 606 | 606 | 732 | 732 | 732 |
| Note: ***, **, * denotes significance at the 1 %, 5 %, and 10 % levels, respectively. We apply the cross-sectionally autoregressive distributive lag (CS-ARDL) methodology in Chudik et al. (2016) under the condition of short-run heterogeneity and long-run homogeneity by solving the problem of cross-sectional dependence in the short-run (SR) (M1), short-run and long run (Joint) (M2), and long-run (LR) (M3) | ||||||