load BCProp.mat
per = 5500;
vars = 7;
trials = 10;
% Arrangement: (per+3) periods of simulated time series, 7 variables, (trials) of attempts
Temp = zeros(vars,trials);
StdArray = zeros(vars);
for i = 1:vars
    for j = 1:trials
        Temp(i,j)=std(SimData(501:per+3,i,j));
    end
    StdArray(i) = mean(Temp(i,:));
end

Temp = zeros(vars,trials);
Temp22 = zeros(2,2);
AutoCorrArray = zeros(vars);
for i = 1:vars
    for j = 1:trials
        Temp22 = corrcoef(SimData(501:per+3-1,i,j),SimData(502:per+3,i,j));
        Temp(i,j) = Temp22(1,2);
    end
    AutoCorrArray(i) = mean(Temp(i,:));
end

Temp = zeros(vars,vars,trials);
CorrArray = zeros(vars,vars);
for i = 1:trials
    Temp=corrcoef(SimData(501:per+3,:,i));
end
for i = 1:vars
    for j = 1:vars
        CorrArray(i,j)=mean(Temp(i,j,:));
    end
end


disp(['sig(GDP):    ', num2str(StdArray(1)*100)]);
disp('Standard deviations relative to GDP');
disp(['Consumption: ', num2str(StdArray(2)/StdArray(1))]);
disp(['Investment:  ', num2str(StdArray(3)/StdArray(1))]);
disp(['RER:         ', num2str(StdArray(4)/StdArray(1))]);
disp(['NER:         ', num2str(StdArray(5)/StdArray(1))]);
disp('Autocorrelations');
disp(['GDP:         ', num2str(AutoCorrArray(1))]);
disp(['Consumption: ', num2str(AutoCorrArray(2))]);
disp(['Investment:  ', num2str(AutoCorrArray(3))]);
disp(['RER:         ', num2str(AutoCorrArray(4))]);
disp(['NER:         ', num2str(AutoCorrArray(5))]);
disp('Cross-correlations');
disp(['Two GDPs:    ', num2str(CorrArray(1,6))]);
disp(['Two Cs:      ', num2str(CorrArray(2,7))]);
disp(['RER and GDP: ', num2str(CorrArray(1,4))]);