One of the Most Frequently Estimated Equations in the Macroeconomics

One of the most frequently estimated equations in the macroeconomics growth literature
are so-called convergence regressions.In essence the average per capita income growth
rate is regressed on the beginning-of-period per capita income level to see if countries
that were further behind initially, grew faster.Some macroeconomic models make this
prediction, once other variables are controlled for.To investigate this matter, you collect
data from 104 countries for the sample period 1960-1990 and estimate the following
relationship (numbers in parentheses are for heteroskedasticity-robust standard errors): $$\begin{array} { l } \widehat { g 6090 } = 0.020 - 0.360 \times \text { gpop } + 0.004 \times \text { Educ } - 0.053 \times \operatorname { RelProd } _ { 60 } , R ^ { 2 } = 0.332 , \text { SER } = 0.013 \\\quad\quad\quad\quad( 0.009 ) ( 0.241 ) \quad \quad\quad\quad\quad (0.001 ) \quad \quad\quad\quad( 0.009 ) \\\end{array}$$ where g6090 is the growth rate of GDP per worker for the 1960-1990 sample period,
RelProd60 is the initial starting level of GDP per worker relative to the United States in
1960, gpop is the average population growth rate of the country, and Educ is educational
attainment in years for 1985.
(a)What is the effect of an increase of 5 years in educational attainment? What would
happen if a country could implement policies to cut population growth by one percent?
Are all coefficients significant at the 5% level? If one of the coefficients is not
significant, should you automatically eliminate its variable from the list of explanatory
variables?