T=15;
>> N=285;
>> W=normw(W1);
>> y=A(:,[3]);
>> x=A(:,[4]);
>> xconstant=ones(N*T,1);
>> [nobs K]=size(x);
>> results=ols(y,[xconstant x]);
>> vnames=strvcat('logcit','intercept','yit-1');
>> prt_reg(results,vnames,1);

Ordinary Least-squares Estimates
Dependent Variable =        logcit   
R-squared      =    0.0106
Rbar-squared   =    0.0104
sigma^2        =    0.0064
Durbin-Watson  =    1.0545
Nobs, Nvars    =   4275,     2
***************************************************************
Variable       Coefficient      t-statistic    t-probability
intercept         0.035676         2.680379         0.007382
yit-1             0.009552         6.767010         0.000000

>> sige=results.sige*((nobs-K)/nobs);
>> loglikols=-nobs/2*log(2*pi*sige)- ...
1/(2*sige)*results.resid'*results.resid ...
LMsarsem_panel(results,W,y,[xconstant x]);
LMsarsem_panel(results,W,y,[xconstant x]);
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