Hi All,
You might find this questions quite easy but I need a help about finding the ' Correlations of variables with lead and lagged Y ' . For example: fprintf('%20s \t %3.2f\n','rho(y,w)',correlations(4))----This gives Contemporaneous correlation between wage and output.
How I can find the 2 leads and lags for these variables?
// HP-filter the non-stationary time series;
[ytrend,ycyclical]=sample_hp_filter([ly_nonstationary lcons_nonstationary lh_nonstationary linv_nonstationary lw_nonstationary ly_h_nonstationary],100);
//compute standard deviations
standard_devs=std(ycyclical);
//compute relative standard deviations
relative_standard_devs=standard_devs./standard_devs(1);
//compute autocorrelations
autocorrelations(1,1)=corr(ycyclical(2:end,1),ycyclical(1:end-1,1));
//compute correlations
correlations=corr(ycyclical(:,1),ycyclical(:,2:end));
//Display everything
fprintf('\n Table 1 - Moments\n');
fprintf('%20s \t %3.2f\n','sigma(y)',standard_devs(1,1));
fprintf('%20s \t %3.2f\n','sigma(c)/sigma(y)',relative_standard_devs(2));
fprintf('%20s \t %3.2f\n','sigma(h)/sigma(y)',relative_standard_devs(3));
fprintf('%20s \t %3.2f\n','sigma(i)/sigma(y)',relative_standard_devs(4));
fprintf('%20s \t %3.2f\n','sigma(w)/sigma(y)',relative_standard_devs(5));
fprintf('%20s \t %3.2f\n','sigma(y_h)/sigma(y)',relative_standard_devs(6));
fprintf('%20s \t %3.2f\n','rho(y)',autocorrelations(1,1));
fprintf('%20s \t %3.2f\n','rho(y,c)',correlations(1));
fprintf('%20s \t %3.2f\n','rho(y,h)',correlations(2));
fprintf('%20s \t %3.2f\n','rho(y,i)',correlations(3));
fprintf('%20s \t %3.2f\n','rho(y,w)',correlations(4));
fprintf('%20s \t %3.2f\n','rho(y,y_h)',correlations(5));
Thanks in advance.