Results of panel data models have been presented in Table 1.
From Table 1, it is evident that the results of the Wald test and F-test are significant at a
1% level of significance in all panel-data models. Therefore, we can conclude that we cannot
reject the null hypothesis that the explanatory variables do not explain (taken as a whole) GDP
per capita and hence, the determinants selected in this study can be considered to be enough
of an explanation of the economic growth determinant. Although this is true, in case of the
Hausman test, we reject the null hypothesis of correlation between countries’ unobservable
individual effects and economic growth determinants.
This implies that for our analysis, a random-effect model is more appropriate. However, if
we compare the sign and significance of coefficients associated with the respective variables,
we find that results reported in models 1 and 2 are the same (except the constant term that is
significant for the random-effect model, while insignificant for the fixed-effect model).
Both models, i.e. model 1 and model 2, show that FDI, exports and labour force have
positive and significant impact on the economic growth of the panel countries. However,
the coefficient of GFCF carries a negative sign but is highly insignificant. Further, when we
examine nonlinearity of FDI by incorporating the square value of FDI and we perform the
analysis based on random-effect and fixed-effect models, we find, from model 3 and 4, the
same results in terms of sign and significance of the coefficients associated with variables
in both cases (except the fixed-effect model labour force and constant term are significant,
while in the random-effect model we do not find the same). However, the Hausman test in this