Table 4.
Cointegrating long-run estimations by using the Vector Autoregression (VAR) model.
| Panel A: Variables | Model 1 | Model 2 | |||||
|---|---|---|---|---|---|---|---|
| LY | 1.03 (0.05) | – | |||||
| LRP | −0.22 (0.05) | −0.87 (0.12) | |||||
| LR | −0.008 (0.002) | – | |||||
| LX | – | 0.39 (0.22) | |||||
| LFCG | – | 0.77 (0.17) | |||||
| LI | – | 0.75 (0.14) | |||||
| C |
−3.21 |
−6.79 |
|||||
|
Panel B: Cointegration test | |||||||
|
Null |
Alternative |
Eigenvalue |
Trace Statistics |
Max-Eigen Statistics |
Eigenvalue |
Trace Statistics |
Max-Eigen Statistics |
| r = 0 r ≤ 1 r ≤ 2 r ≤ 3 r ≤ 4 |
r = 1 r = 2 r = 3 r = 4 r = 5 |
0.65 0.34 0.31 0.07 |
68.58* (55.25) 31.07 (35.01) 15.98 (18.40) 2.72 (3.84) |
37.51* (30.82) 15.09 (24.25) 13.27 (17.15) 2.72 (3.84) |
0.81 0.78 0.49 0.12 0.05 |
142.91* (79.34) 83.94* (55.25) 30.34 (35.01) 6.63 (18.40) 1.95 (3.48) |
58.96* (37.16) 53.60* (30.82) 23.71 (24.25) 4.67 (17.15) 1.95 (3.84) |
| Diagnostic tests | Observations = 39 (adjusted) R2 = 0.63 SEE = 0.03 Portmanteau = X2 64.50 (p. 0.0001) Normality = X2 3.23 (p. 0.91) LM = F 0.52 (p. 0.91) Hetero. = X2 255.07 (p. 0.39) |
Observations = 39 (adjusted) R2 = 0.98 SEE = 0.03 Portmanteau = X2 179.70 (p. 0.000) Normality = X2 2.57 (p. 0.98) LM = F 1.76 (p. 0.054) Hetero. = X2 468.43 (p. 0.45) |
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Notes: In panel A: standard errors in parentheses, ***p < 0.01, **p < 0.05, *p < 0.1. In panel B: r denotes the number of cointegrating vectors. Critical values are provided in the parentheses, which are taken from MacKinnon, Haug and Michelis (1999).