Technology, growth, and causality

I've run some Granger causality tests on various technological measures and other variables across different countries. Granger causality examines whether a change in something precedes a change in something else. So we might want to test whether b is not zero in the following model
technological change in year t =
constant + a.techno change in year t-1 + b.techno gap in year t-1 + an error term

VAR models like this produce coefficients which are specific to the country, and since they may not be stable across countries, one has to find a way to produce combined statistics for the significance of b across countries. I took simple averages of the significance level of the t-statistic on b, and frequency counts of significance at the five percent level.

Results vary across measures, and the measures of the variables are imperfect, but broadly speaking:
gaps in technology granger-cause technology transfers, with a frequency of 60 percent
technology gaps g-cause technology change, 65 percent
transfers g-cause change, 55 percent
income levels g-cause transfers, 55 percent
income levels g-cause change, 35 percent
transfers g-cause growth, 35 percent
change g-causes growth, 35 percent
national savings g-cause transfers, 40 percent
government expenditure g-cause transfers, 45 percent
national savings g-cause change, 35 percent
government expenditure g-cause change, 50 percent