Africa

*** Linear Model ***

Call: lm(formula = LXfod ~ Lprfood + LGDPeu + LNTL, data = afrregreg, na.action =

na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.06335 -0.02102 -0.008746 0.0244 0.07167

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 4.2262 1.7580 2.4040 0.0472

Lprfood 0.3382 0.1230 2.7490 0.0285

LGDPeu 0.7183 0.0974 7.3767 0.0002

LNTL -0.1898 0.0685 -2.7700 0.0277

Residual standard error: 0.04331 on 7 degrees of freedom

Multiple R-Squared: 0.9543

F-statistic: 48.73 on 3 and 7 degrees of freedom, the p-value is 0.00004662

*** Linear Model ***

Call: lm(formula = LXfod ~ Lprfood + LNTL + LGDP.POP, data = afrregreg, na.action =

na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.07284 -0.02089 -0.006764 0.02577 0.06688

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 13.5276 0.9077 14.9025 0.0000

Lprfood 0.3214 0.1289 2.4925 0.0414

LNTL -0.1885 0.0714 -2.6415 0.0334

LGDP.POP 0.7598 0.1077 7.0550 0.0002

Residual standard error: 0.04505 on 7 degrees of freedom

Multiple R-Squared: 0.9506

F-statistic: 44.87 on 3 and 7 degrees of freedom, the p-value is 0.00006129

*** Linear Model ***

Call: lm(formula = LXar ~ LPRAGR, data = afrregreg, na.action = na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.4589 -0.08335 -0.01284 0.02165 0.8828

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 1.6123 5.3789 0.2998 0.7712

LPRAGR 2.9506 1.2128 2.4329 0.0378

Residual standard error: 0.3639 on 9 degrees of freedom

Multiple R-Squared: 0.3968

F-statistic: 5.919 on 1 and 9 degrees of freedom, the p-value is 0.0378

*** Linear Model ***

Call: lm(formula = LXar ~ LPRAGR, data = afrregreg, na.action = na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.4589 -0.08335 -0.01284 0.02165 0.8828

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 1.6123 5.3789 0.2998 0.7712

LPRAGR 2.9506 1.2128 2.4329 0.0378

Residual standard error: 0.3639 on 9 degrees of freedom

Multiple R-Squared: 0.3968

F-statistic: 5.919 on 1 and 9 degrees of freedom, the p-value is 0.0378

East

*** Linear Model ***

Call: lm(formula = LXfod ~ LGDPeu + LPOPeu, data = AfrESTregreg, na.action =

na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.06687 -0.0439 -0.02831 0.05091 0.08902

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 234.0653 42.2410 5.5412 0.0005

LGDPeu 1.1562 0.2145 5.3905 0.0007

LPOPeu -18.2746 3.4553 -5.2889 0.0007

Residual standard error: 0.06545 on 8 degrees of freedom

Multiple R-Squared: 0.797

F-statistic: 15.7 on 2 and 8 degrees of freedom, the p-value is 0.001698

*** Linear Model ***

Call: lm(formula = LXfod ~ Lprfood, data = AfrESTregreg, na.action = na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.1695 -0.058 -0.01621 0.03905 0.2027

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 11.5255 1.3173 8.7490 0.0000

Lprfood 0.6462 0.2775 2.3282 0.0449

Residual standard error: 0.1082 on 9 degrees of freedom

Multiple R-Squared: 0.3759

F-statistic: 5.42 on 1 and 9 degrees of freedom, the p-value is 0.04488

*** Linear Model ***

Call: lm(formula = LXar ~ LPRAGR + LPOPeu + LNTL, data = AfrESTregreg, na.action =

na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.1141 -0.02684 0.002583 0.03489 0.1108

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) -297.0069 33.3044 -8.9179 0.0000

LPRAGR 0.8166 0.2724 2.9975 0.0200

LPOPeu 23.3917 2.4830 9.4207 0.0000

LNTL 0.1729 0.1143 1.5133 0.1740

Residual standard error: 0.06988 on 7 degrees of freedom

Multiple R-Squared: 0.9322

F-statistic: 32.08 on 3 and 7 degrees of freedom, the p-value is 0.0001839

*** Linear Model ***

Call: lm(formula = LXar ~ LGDP.POP, data = AfrESTregreg, na.action = na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.1927 -0.04803 0.01425 0.07628 0.1215

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 8.8821 0.6658 13.3410 0.0000

LGDP.POP 1.2528 0.2168 5.7775 0.0003

Residual standard error: 0.1091 on 9 degrees of freedom

Multiple R-Squared: 0.7876

F-statistic: 33.38 on 1 and 9 degrees of freedom, the p-value is 0.0002669

MEADDLE

*** Linear Model ***

Call: lm(formula = LXfod ~ LGDPeu + LPOPeu + LNTL, data = afrMEADregreg, na.action

= na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.124 -0.04293 0.01295 0.04623 0.1285

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 370.6495 56.3297 6.5800 0.0003

LGDPeu 1.3383 0.3056 4.3795 0.0032

LPOPeu -28.7679 4.6302 -6.2131 0.0004

LNTL -0.5596 0.1384 -4.0439 0.0049

Residual standard error: 0.08688 on 7 degrees of freedom

Multiple R-Squared: 0.902

F-statistic: 21.48 on 3 and 7 degrees of freedom, the p-value is 0.0006585

*** Linear Model ***

Call: lm(formula = LXfod ~ LNTL, data = afrMEADregreg, na.action = na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.3164 -0.1088 -0.02726 0.1164 0.3296

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 17.8419 2.2192 8.0398 0.0000

LNTL -0.6162 0.2819 -2.1858 0.0566

Residual standard error: 0.1978 on 9 degrees of freedom

Multiple R-Squared: 0.3468

F-statistic: 4.778 on 1 and 9 degrees of freedom, the p-value is 0.05664

*** Linear Model ***

Call: lm(formula = LXar ~ LGDPeu + LPOPeu, data = afrMEADregreg, na.action =

na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.1405 -0.08184 -0.01028 0.07854 0.1676

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 190.9200 78.2338 2.4404 0.0405

LGDPeu 1.2916 0.3973 3.2512 0.0117

LPOPeu -15.2280 6.3994 -2.3796 0.0446

Residual standard error: 0.1212 on 8 degrees of freedom

Multiple R-Squared: 0.5745

F-statistic: 5.401 on 2 and 8 degrees of freedom, the p-value is 0.03277

*** Linear Model ***

Call: lm(formula = LXar ~ LGDP.POP, data = afrMEADregreg, na.action = na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.2424 -0.09636 -0.01888 0.0753 0.2166

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 11.5749 0.8979 12.8910 0.0000

LGDP.POP 0.5675 0.2925 1.9405 0.0842

Residual standard error: 0.1471 on 9 degrees of freedom

Multiple R-Squared: 0.295

F-statistic: 3.766 on 1 and 9 degrees of freedom, the p-value is 0.08424

NORD

*** Linear Model ***

Call: lm(formula = LXfod ~ LGDPeu, data = afrNORDregreg, na.action = na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.1118 -0.02785 0.009004 0.03326 0.07126

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) -5.8752 1.7990 -3.2658 0.0097

LGDPeu 1.2543 0.1118 11.2224 0.0000

Residual standard error: 0.05918 on 9 degrees of freedom

Multiple R-Squared: 0.9333

F-statistic: 125.9 on 1 and 9 degrees of freedom, the p-value is 1.36e-006

*** Linear Model ***

Call: lm(formula = LXfod ~ LNTL + LGDP.POP, data = afrNORDregreg, na.action =

na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.1029 -0.03522 0.01259 0.03423 0.05903

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 8.9457 0.9120 9.8085 0.0000

LNTL 0.1356 0.0872 1.5556 0.1584

LGDP.POP 1.4024 0.1216 11.5310 0.0000

Residual standard error: 0.05511 on 8 degrees of freedom

Multiple R-Squared: 0.9486

F-statistic: 73.81 on 2 and 8 degrees of freedom, the p-value is 6.986e-006

*** Linear Model ***

Call: lm(formula = LXar ~ LGDPeu, data = afrNORDregreg, na.action = na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.3515 -0.0407 -0.01841 0.0678 0.2647

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) -5.1034 4.8994 -1.0416 0.3248

LGDPeu 1.0961 0.3044 3.6008 0.0057

Residual standard error: 0.1612 on 9 degrees of freedom

Multiple R-Squared: 0.5903

F-statistic: 12.97 on 1 and 9 degrees of freedom, the p-value is 0.005741

*** Linear Model ***

Call: lm(formula = LXar ~ LGDP.POP, data = afrNORDregreg, na.action = na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.3612 -0.03978 -0.009312 0.06851 0.2533

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 9.0102 0.9882 9.1180 0.0000

LGDP.POP 1.1503 0.3219 3.5738 0.0060

Residual standard error: 0.1619 on 9 degrees of freedom

Multiple R-Squared: 0.5866

F-statistic: 12.77 on 1 and 9 degrees of freedom, the p-value is 0.005988

SUD

*** Linear Model ***

Call: lm(formula = LXfod ~ Lprfood + LGDPeu + LPOPeu, data = afrSUDregreg, na.action

= na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.07701 -0.01514 -0.008201 0.01644 0.06708

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) -285.9780 32.5271 -8.7920 0.0000

Lprfood -0.2208 0.1429 -1.5452 0.1662

LGDPeu 0.5985 0.1816 3.2956 0.0132

LPOPeu 22.3679 2.6629 8.3999 0.0001

Residual standard error: 0.04455 on 7 degrees of freedom

Multiple R-Squared: 0.9862

F-statistic: 166.8 on 3 and 7 degrees of freedom, the p-value is 7.146e-007

*** Linear Model ***

Call: lm(formula = LXfod ~ Lprfood + LGDP.POP, data = afrSUDregreg, na.action =

na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.3281 -0.009917 0.04141 0.0693 0.1314

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 11.7715 1.8320 6.4255 0.0002

Lprfood -0.8155 0.4289 -1.9013 0.0938

LGDP.POP 1.9945 0.3324 6.0008 0.0003

Residual standard error: 0.1501 on 8 degrees of freedom

Multiple R-Squared: 0.821

F-statistic: 18.34 on 2 and 8 degrees of freedom, the p-value is 0.001027

*** Linear Model ***

Call: lm(formula = LXar ~ LPRAGR + LPOPeu, data = afrSUDregreg, na.action =

na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.1232 -0.05942 0.003525 0.04073 0.1561

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) -63.3556 38.5690 -1.6427 0.1391

LPRAGR 1.0554 0.3201 3.2971 0.0109

LPOPeu 5.4920 2.9220 1.8795 0.0970

Residual standard error: 0.09045 on 8 degrees of freedom

Multiple R-Squared: 0.5906

F-statistic: 5.77 on 2 and 8 degrees of freedom, the p-value is 0.0281

*** Linear Model ***

Call: lm(formula = LXar ~ LPRAGR + LGDP.POP, data = afrSUDregreg, na.action =

na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.1316 -0.05273 -0.007906 0.05161 0.1513

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 8.4258 1.3956 6.0375 0.0003

LPRAGR 0.7713 0.3070 2.5119 0.0363

LGDP.POP 0.3355 0.1832 1.8320 0.1043

Residual standard error: 0.09115 on 8 degrees of freedom

Multiple R-Squared: 0.5842

F-statistic: 5.621 on 2 and 8 degrees of freedom, the p-value is 0.02988

WEST

*** Linear Model ***

Call: lm(formula = LXfod ~ LGDPeu + LNTL, data = afrWESTregreg, na.action =

na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.2345 -0.05798 -0.009451 0.0939 0.1394

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 9.6175 5.3337 1.8032 0.1090

LGDPeu 0.5205 0.2749 1.8932 0.0950

LNTL -0.4058 0.2074 -1.9565 0.0861

Residual standard error: 0.1315 on 8 degrees of freedom

Multiple R-Squared: 0.6189

F-statistic: 6.496 on 2 and 8 degrees of freedom, the p-value is 0.02109

*** Linear Model ***

Call: lm(formula = LXfod ~ LNTL + LGDP.POP, data = afrWESTregreg, na.action =

na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.2273 -0.05676 -0.01276 0.09207 0.1358

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 16.2178 2.1505 7.5415 0.0001

LNTL -0.3994 0.2055 -1.9435 0.0879

LGDP.POP 0.5629 0.2868 1.9631 0.0853

Residual standard error: 0.1299 on 8 degrees of freedom

Multiple R-Squared: 0.6276

F-statistic: 6.74 on 2 and 8 degrees of freedom, the p-value is 0.01924

*** Linear Model ***

Call: lm(formula = LXar ~ LPRAGR + LGDPeu + LPOPeu, data = afrWESTregreg, na.action

= na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.232 -0.0667 -0.01399 0.08669 0.1403

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 202.4726 134.6402 1.5038 0.1763

LPRAGR 1.1808 0.6913 1.7080 0.1314

LGDPeu 1.0308 0.6402 1.6101 0.1514

LPOPeu -16.2097 10.8759 -1.4904 0.1797

Residual standard error: 0.135 on 7 degrees of freedom

Multiple R-Squared: 0.7601

F-statistic: 7.393 on 3 and 7 degrees of freedom, the p-value is 0.0142

*** Linear Model ***

Call: lm(formula = LXar ~ LPRAGR, data = afrWESTregreg, na.action = na.exclude)

Residuals:

Min 1Q Median 3Q Max

-0.2708 -0.07148 -0.004418 0.1043 0.1673

Coefficients:

Value Std. Error t value Pr(>|t|)

(Intercept) 4.2865 2.0606 2.0802 0.0672

LPRAGR 1.9914 0.4646 4.2863 0.0020

Residual standard error: 0.1394 on 9 degrees of freedom

Multiple R-Squared: 0.6712

F-statistic: 18.37 on 1 and 9 degrees of freedom, the p-value is 0.002031