/* works out numbers for constantinides - duffie example */

library pgraph;
output file=constant.out reset;
convt = 0;

/* table of s(dc) vs risk aversion */

gam = seqa(1,1,20);
rho = 0.05;
Elnr = 0.09;
slnr = 0.17;

sdc =  (1.0./(gam.*(gam+1)))^2.0.*slnr^2;
sdc = sdc^0.5;

"gamma, second term of sdev Dc";
gam~(100*sdc);


/* cross-sectional dispersion */

gam = 1|2|5|10|25;
edca = 0.01;
lnrm = seqb(-0.25,0.25,0.005);
y = 2./(gam.*(1+gam)).*(rho-lnrm'+gam*edca);

y = y .* (y.>=0);
y = y^0.5;

/* make table */
format /RD 6,2;
"r on rows, gam on cols, cross sec sd of dc growth" ;
0~gam';
lnrm~y';

graphjc;
fonts("simplex simgrma");

_pcolor = 15;
title("Cross-sectional standard deviation of consumption growth\L"$+
       "in Constantinides-Duffie Model");
xlabel("Market return, %");
ylabel("Standard deviation, %");

px = (100*lnrm);
py = 100*y';

_pmsgstr = "\202g\201 = 1\000\202g\201 = 2\000\202g\201 = 5"$+
           "\000\202g\201 = 10\000\202g\201 = 25";
_pmsgctl = (px[1]*ones(cols(py),1))~(py[1,.]'+1)~
            ( ones(cols(py),1)*(0.15~0~1~15~0)  ) ;
xtics(-25,25,5,0);

"Cross-sectional standard deviation of consumption growth";
"in Constantinides-Duffie Model";
format /RD 10,6;
"x data";
px;
"y data" ;
py;
xy(px,py);
if convt;
    dos pqgrun graphic.tkf -CF=dufc.pic -C=2;
endif;
output off;


/*

/*artificial dc, r data */

nI = 10; /* number of people */
nT = 10;  /* number of time periods (for aggregate c) */

Dc = 1.01;
gam = 2;

t = 1;
do while t <= nT;
    lnr = elnr+slnr*rndn(1,1);
    i = 1;
    do while i <= ni;
        y2 = 2/(gam*(gam+1))*(rho-lnr+gam*dc)

*/