The regression results from the from 9 sets of regressions using feasible GLS estimation with cross-country weights are reported in Table 6. Regression models referred in column (1) to (6) uses time-invariant GDP per capita (GDPPC) or the Barro effect, The results reported for regression models in columns ((7) to (9) are based on cross-country specific fixed effects model. The standard errors have been estimated using heteroscedasticity White’ s covariance estimates that are robust to general heteroscedasticity. The regression models estimated with the time-invariant initial conditions (or Barro-effect) do not provide efficient estimators. But the regression models for cross-country specific effect models provide efficient estimators and therefore we focus mainly on these results for analyzing the TFP spillover effects due to FDI inward and outward stocks. Regression equation (7) includes inward FDI (FDII) but excludes the outward FDI (FDIO), while equation (8) includes FDIO but excludes FDII. Equation (9) includes both inward and outward FDI stocks. The regression coefficients for FDII and FDIO have positive and significant impacts on the TFP growth variable. The results from equation (9) are undermined by the multicollineaity between growth rates of FDII and FDIO. The value for the growth of FDII is 0.01 implying that 1% increase in growth of FDI inward stock results in growth of TFP by 0.01 percent. The coefficient of FDIO or growth of outward stock of FDI is also around 0.01 and is significant. Besides, R&D (GERD), capital formation (CAPF) also have positive effects on growth TFP as expected. The control variables relating to policy proxied by government expenditure (GOVX) , inflation (INFL) and business cycle effects due to unemployment ( 1-1/EMP) all have negative effects on TFP growth as expected. The interaction term is not statistically significant and the regression results fail the residual test. Given that the sample of countries have attained the same threshold level of absorptive capacity )
The regression results from the from 9 sets of regressions using feasible GLS estimation with cross-country weights are reported in Table 6. Regression models referred in column (1) to (6) uses time-invariant GDP per capita (GDPPC) or the Barro effect, The results reported for regression models in columns ((7) to (9) are based on cross-country specific fixed effects model. The standard errors have been estimated using White’ s heteroscedasticity covariance estimates that are robust to general heteroscedasticity. The regression models estimated with the time-invariant initial conditions (or Barro-effect) do not provide efficient estimators. But the regression models for cross-country specific effect models provide efficient estimators and therefore we focus mainly on these results for analyzing the TFP spillover effects due to FDI inward and outward stocks. Regression equation (7) includes inward FDI (FDII) but excludes the outward FDI (FDIO), while equation (8) includes FDIO but excludes FDII. Equation (9) includes both inward and outward FDI stocks. The regression coefficients for FDII and FDIO have positive and significant impacts on the TFP growth variable. The results from equation (9) are undermined by the multicollineaity between growth rates of FDII and FDIO. The value for the growth of FDII is 0.01 implying that 1% increase in growth of FDI inward stock results in growth of TFP by 0.01 percent. The coefficient of FDIO or growth of outward stock of FDI is also around 0.01 and is significant. Besides, R&D (GERD), capital formation (CAPF) also have positive effects on growth TFP as expected. The control variables relating to policy proxied by government expenditure (GOVX) , inflation (INFL) and business cycle effects due to unemployment ( 1-1/EMP) all have negative effects on TFP growth as expected. The interaction term is not statistically significant and the regression results fail the residual test. Given that the sample of countries have attained the same threshold level of absorptive capacity )
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