Controlling for variables in pooled OLS estimation in EViews I am working on the Chinese economy and my topic of research is how external political instability can affect Chinese exports. So I want to estimate the Chinese export demand function for 1988-2011 with more than 130 countries. I want to estimate the regression equation given below.
$$
\begin{align}
\log(\mathrm{export})_{it} &= \beta_0+ \beta_1 \log(\mathrm{real gdp})_{it}+ \beta_2 \log(\mathrm{population})_{it} \\
&\quad+ \beta_3\mathrm{political stability}_{it}+ \beta_4\mathrm{realexchange rate}_{it}+ \varepsilon_{it}
\end{align}
$$
Where $\log(\mathrm{export})_{it}$ is the (log) of the export from china to other countries and $t=1988, \ldots, 2011$.
According to economic theory, the export of a country depends not only domestic GDP and  population but also on the GDP and population of other countries. In my research, I want to control for the effect of Chinese GDP and population on Chinese export in EViews in a pooled OLS estimation but I don't know how to do this. If i do not control these two variables I can run a pooled OLS estimation in EViews. Any help is greatly appreciated.
 A: Control variable is also an independent variable. So, it should be listed as independent variable in the model in Eviews. Then, you interpret the coefficient on rgdp of all other countries as the elasticity of exchange rate with respect to the rgdp of all other countries (if you put both in log form), other things remaining the same (i.e. controlling for all other factors). 
The model should be as follows:
$$
\begin{align}
\log(\mathrm{export})_{it} &= \beta_0+ \beta_1 \log(\mathrm{real gdp})_{it}+ \beta_2 \log(\mathrm{population})_{it} \\
&\quad+ \beta_3\mathrm{political stability}_{it}+ \beta_4\mathrm{realexchange rate}_{it}+ \beta_5\log(\mathrm{chinagdp})_{it}\\
&+\beta_6\log(\mathrm{chinapopn})_{it}+\varepsilon_{it}
\end{align}
$$
Where $\log(\mathrm{export})_{it}$ is the (log) of the export from china to other countries and $t=1988, \ldots, 2011$.
In Eviews, you have to import the data as panel data and run OLS (under estimate equation) with the following command (assuming that the variables have been log transformed, if necessary) with the variables appearing in the order as in the model (c stands for constant).
logexport c logrealgdp logpopulation politicalstability realexchangerate logchinagdp logchinapopn 

