Table 2.
Descriptive statistics.
| LNGDP | LNENG | LNTRA | LNCAP | LNLAB | LNFDI | LNHCI | |
|---|---|---|---|---|---|---|---|
| Mean | 9.680 | 7.878 | 8.915 | 8.290 | 17.412 | 5.134 | 1.005 |
| Median | 10.205 | 8.158 | 9.323 | 8.659 | 17.180 | 5.431 | 1.067 |
| Maximum | 11.275 | 9.147 | 11.508 | 9.889 | 20.484 | 10.712 | 1.324 |
| Minimum | 5.850 | 5.657 | 3.764 | 4.380 | 15.154 | -4.423 | 0.251 |
| Std. Dev. | 1.233 | 0.822 | 1.500 | 1.104 | 1.273 | 2.081 | 0.254 |
| Skewness | -1.210 | -0.805 | -1.047 | -1.376 | 0.543 | -0.800 | -0.751 |
| Kurtosis | 3.732 | 2.765 | 4.130 | 4.878 | 3.015 | 4.434 | 2.593 |
| Jarque-Bera | 207.655 | 85.963 | 184.064 | 360.839 | 38.309 | 150.121 | 78.658 |
| Probability | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| Observations | 780 | 780 | 780 | 780 | 780 | 780 | 780 |
Note: All the variables are transformed into the natural logarithm form. The Jarque-Bera test is used to see whether a series is normally distributed or not. The null hypothesis of this test is a series is normally distributed.