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p.rm0 = p.rm;
p.rm1 = (1 + 0.015)^(1/4) - 1;
p.P0 = 1;
p.P1 = 1;
p.mbar0 = p.rm0/(1 - (1 + p.rm0)^(-p.D)); % minimum payment required per 1 of initial debt
p.mbar1 = p.rm1/(1 - (1 + p.rm1)^(-p.D)); % minimum payment required per 1 of initial debt
p.rm = [];
p.mbar = [];
p.rmgrid = [p.rm0; p.rm1];
p.Pgrid = [p.P0; p.P1];
p.rgrid = [1; 2]; % index for whether mortgage is old o rnew
p.nr = 2; % number of possible mortgage contracts
fprintf('\n');
fprintf('PV of savings from rate refi (discounted at old rm) = %9.2f\n', (p.mbar0 - p.mbar1)*(1 - (1 + p.rm0)^(-p.D))/p.rm0*p.thetam*p.hbar);
fprintf('\n');
% Construct grids:
sv = gridmake(sv, [1; 2]);
sw = gridmake(sw, [1; 2]);
svbar = gridmake(svbar, [1; 2]);
cmax = bisect('savings', 1e-13, 1e5, p.lgrid, p, amin); % c that implies a' = amin
cmin = bisect('savings', 1e-13, 1e5, p.lgrid, p, amax); % c that implies a' = amax
cmax = repmat(cmax, p.nt*p.nr, 1);
cmin = repmat(cmin, p.nt*p.nr, 1);
Vbar = repmat(Vbar, p.nr, 1);
for iter = 1 : 5
Vbarold = Vbar;
EV = griddedInterpolant({p.agrid, p.tgrid, p.rgrid}, reshape(Vbar, p.na, p.nt, p.nr), intmeth, 'linear');
% solve consumption-savings choice
c = solve_golden('wfunc_new', cmin, cmax, sw, EV, p);
[~, aprime] = savings(c, sw, p);
W = wfunc_new(c, sw, EV, p);
Winterp = griddedInterpolant({p.lgrid, p.tgrid, p.rgrid}, reshape(W, p.nl, p.nt, p.nr), intmeth, 'linear');
% Solve discrete choice problem
V = solveh_new(sv, Winterp, p);
% Interpolate V(w, theta)
Vinterp = griddedInterpolant({p.wgrid, p.tgrid, p.rgrid}, reshape(V, p.nw, p.nt, p.nr), intmeth, 'linear');
% Compute expected value and update vbar
Vbar = zeros(p.na*p.nt*p.nr, 1);
for i = 1 : p.ny
Vbar = Vbar + wy(i)*Vinterp((1 + p.rl)*svbar(:,1) + y(i), svbar(:,2), svbar(:,3));
end
fprintf('%4i %6.2e \n', [iter, norm(Vbar - Vbarold)/norm(Vbar)]);
end
for iter = 1 : 5000
Vbarold = Vbar;
EV = griddedInterpolant({p.agrid, p.tgrid, p.rgrid}, reshape(Vbar, p.na, p.nt, p.nr), intmeth, 'linear');
% solve consumption-savings choice
if mod(iter, 50) == 0
c = solve_golden('wfunc_new', cmin, cmax, sw, EV, p);
end
[~, aprime] = savings(c, sw, p);
W = wfunc_new(c, sw, EV, p);
Winterp = griddedInterpolant({p.lgrid, p.tgrid, p.rgrid}, reshape(W, p.nl, p.nt, p.nr), intmeth, 'linear');
% Solve discrete choice problem
V = solveh_new(sv, Winterp, p);
% Interpolate V(w, theta)
Vinterp = griddedInterpolant({p.wgrid, p.tgrid, p.rgrid}, reshape(V, p.nw, p.nt, p.nr), intmeth, 'linear');
% Compute expected value and update vbar
Vbar = zeros(p.na*p.nt*p.nr, 1);
for i = 1 : p.ny
Vbar = Vbar + wy(i)*Vinterp((1 + p.rl)*svbar(:,1) + y(i), svbar(:,2), svbar(:,3));
end
if mod(iter, 50) == 0
fprintf('%4i %6.2e \n', [iter/50, norm(Vbar - Vbarold)/norm(Vbar)]);
if norm(Vbar - Vbarold)/norm(Vbar) < 1e-7, break, end
end
end
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