On the Determinants of Foreign Capital Flows - DAAD partnership ...

Dependent variable: LDFDI
Table 5.4 Summary results of Multiple Regression
Variables Coefficient Standard Errors T-Ratio P-Value Significant Beta Coeffs
LDGDP 1.265571 0.997528 2.01 0.049 8 Yes, Positive 0.6775634
LDOPEN 4.052001 0.663381 3.67 0.017 Yes, Positive 1.1815245
LDINV 1.895862 0.419843 3.43 0.028 Yes, Positive 0.8648651
LDPRO 2.335129 0.790041 3.54 0.023 Yes, Positive 0.9665672
LDRER -4.089821 0.064277 -3.87 0.006 Yes, Negative -1.5048924
Intercept 3.702278 0.035929 4.04 0.01 Yes -
Prob > F = 0.0000
R-squared = 0.8827
Adj R-squared = 0.8497
For the significance of the model, the p-value of the F-test is observed and with a p-value of
zero to four decimal places, the model is statistically significant. As per the tests for model
specification, the link test (_hat 0.017 and hat_sq: 0.283) and the Ovtest (Prob > F = 0.5844)
have both demonstrated significant results. Thus, one can say that the group of variables
LDRER, LDPRO, LGDP, LDINV and LDOPEN can be used to reliably predict LDFDI
(the dependent variable). The R-squared is 0.8827, when adjusted being about 0.8497
meaning that approximately 84% of the variability of LDFDI is accounted for by the
variables in the model as the adjusted R-squared attempts to yield a more honest value.
The “coeff” column indicates the amount of change one could expect in LDFDI given a
one-unit change in the value of that variable, given that all other variables in the model a
held constant. Expressed in terms of the variables used in this example, the regression
equation is:
LDFDI =3.702278 + 1.265571* LDGDP + 4.052001*LDOPEN + 1.895862*LDINV +
2.335129*LDPRO - 4.08982*LDRER + ut
8 Ldgdp with a p-value of 0.049 is taken as significant when reduced to 2 decimal places.
19
If less than or
equal to 5%,