Hierarchical linear model (HLM) for exports for LAC (2010, 2012, 2014, 2016, 2018)
| Year | Model | R2 | F(df) | P | R2 change | F(df) change | P |
|---|---|---|---|---|---|---|---|
| 2010 | 1 | 0.901 | 34.229(4,15) | 0.000 | |||
| 2 | 0.906 | 26.870(5,14) | 0.000 | 0.004 | 0.648(1,14) | 0.433 | |
| 3 | 0.919 | 24.665(6,13) | 0.000 | 0.014 | 2.193(1,13) | 0.161 | |
| 4 | 0.938 | 25.966(7,12) | 0.000 | 0.019 | 3.646(1,12) | 0.079* | |
| 5 | 0.939 | 21.124(8,11) | 0.000 | 0.001 | 0.147(1,11) | 0.708 | |
| 6 | 0.940 | 17.418(9,10) | 0.000 | 0.001 | 0.192(1,10) | 0.670 | |
| GDP (3.418)***, TRFR (32.42)***, infra (−7.212)**, QLS (3.051)*, N = 20 | |||||||
| 2012 | 1 | 0.906 | 36.319(4,15) | 0.000 | |||
| 2 | 0.908 | 27.518(5,14) | 0.000 | 0.001 | 0.187(1,14) | 0.672 | |
| 3 | 0.912 | 22.524(6,13) | 0.000 | 0.005 | 0.682(1,13) | 0.423 | |
| 4 | 0.914 | 18.212(7,12) | 0.000 | 0.002 | 0.240(1,12) | 0.632 | |
| 5 | 0.914 | 14.645(8,11) | 0.000 | 0.000 | 0.026(1,11) | 0.875 | |
| 6 | 0.916 | 12.102(9,10) | 0.000 | 0.002 | 0.206(1,10) | 0.659 | |
| GDP (3.404)***, TRFR (30.79)***, FDI (−1.886)*, N = 20 | |||||||
| 2014 | 1 | 0.757 | 11.674(4,15) | 0.000 | |||
| 2 | 0.772 | 9.494(5,14) | 0.000 | 0.015 | 0.945(1,14) | 0.346 | |
| 3 | 0.773 | 7.382(6,13) | 0.001 | 0.001 | 0.048(1,13) | 0.829 | |
| 4 | 0.786 | 6.297(7,12) | 0.003 | 0.013 | 0.725(1,12) | 0.410 | |
| 5 | 0.857 | 8.210(8,11) | 0.001 | 0.071 | 5.409(1,11) | 0.038** | |
| 6 | 0.908 | 11.028 | 0.000 | 0.052 | 5.672(1,10) | 0.036** | |
| TRFR (27.79)***, QLS (−6.960)**, LPTT (6.872)**, LPTL (−3.653)**, N = 20 | |||||||
| 2016 | 1 | 0.627 | 6.298(4,15) | 0.004 | |||
| 2 | 0.728 | 7.476(5,14) | 0.001 | 0.101 | 5.176(1,14) | 0.038** | |
| 3 | 0.735 | 6.006(6,13) | 0.003 | 0.007 | 0.360(1,13) | 0.558 | |
| 4 | 0.775 | 5.893(7,12) | 0.004 | 0.040 | 2.118(1,12) | 0.169 | |
| 5 | 0.781 | 4.899(8,11) | 0.009 | 0.006 | 0.311(1,11) | 0.588 | |
| 6 | 0.783 | 4.014 | 0.021 | 0.002 | 0.109(1,10) | 0.748 | |
| IND (11.669)**, LPCUST (−2.206)**, N = 20 | |||||||
| 2018 | 1 | 0.718 | 9.564(4,15) | 0.000 | |||
| 2 | 0.788 | 10.436(5,14) | 0.000 | 0.070 | 4.640(1,14) | 0.048** | |
| 3 | 0.820 | 9.895(6,13) | 0.000 | 0.032 | 2.310(1,13) | 0.151 | |
| 4 | 0.835 | 8.705(7,12) | 0.001 | 0.015 | 1.102(1,12) | 0.313 | |
| 5 | 0.837 | 7.056(8,11) | 0.002 | 0.001 | 0.098(1,10) | 0.760 | |
| 6 | 0.845 | 6.060(9,10) | 0.005 | 0.008 | 0.526(1,10) | 0.484 | |
| Year | Model | ||||||
|---|---|---|---|---|---|---|---|
| 2010 | |||||||
| 2012 | |||||||
| 2014 | |||||||
| 2016 | |||||||
| 2018 | |||||||
Note(s): TRFR (14.91)**, IND (10.41)**, LPCUST (−2.56)**, N = 20, ***p < 0.01, **p < 0.05, *p < 0.1. Model 1 uses the general OLPI index (overall); model 2 uses the LPI customs index; model 3 uses the LPI infrastructure; model 4 uses the LPI quality of logistics services index; model 5 uses the LPI tracking and tracing index; model 6 uses the LPI timeliness. Coefficients are based on log-transformed variables and therefore reflect scaled associations rather than standardized beta coefficients. QLS = Quality of logistics services and IND = Industry or industrial sector indicator
Sharing content requires targeting cookies to be enabled. Please update your cookie preferences to use this feature.