%
% real2.m is an example matlab program 
% to read in the solution to a simple real estate search model
% and compute reservation price for each type of house
% and simulate model
%

format bank

% ----- save output to file ----- %

clear all
diary real2.mout
diary off
delete real2.mout
diary real2.mout

% ----- display date and time of computation ----- %

%format short
date
time0 = clock;

% ----- set control vars ----- %

iters  = 700;

% ----- load data ----- %

X = load('real1.dat')

% ----- compute reservation prices ----- %

P11=min(X(X(:,9)==1 & X(:,2)==1 & X(:,3)==1,7))
P12=min(X(X(:,9)==1 & X(:,2)==1 & X(:,3)==2,7))
P13=min(X(X(:,9)==1 & X(:,2)==1 & X(:,3)==3,7))

P21=min(X(X(:,9)==1 & X(:,2)==2 & X(:,3)==1,7))
P22=min(X(X(:,9)==1 & X(:,2)==2 & X(:,3)==2,7))
P23=min(X(X(:,9)==1 & X(:,2)==2 & X(:,3)==3,7))

P31=min(X(X(:,9)==1 & X(:,2)==3 & X(:,3)==1,7))
P32=min(X(X(:,9)==1 & X(:,2)==3 & X(:,3)==2,7))
P33=min(X(X(:,9)==1 & X(:,2)==3 & X(:,3)==3,7))

P = [P11 P12 P13;
     P21 P22 P23;
     P31 P32 P33 ] ;
     
% ----- periods and people ----- %

t = 50
n = 300

% ----- set parameters ----- %

beta0 = 6;
beta1 = 1;
beta2 = 1;

% ----- for each person randomly draw housing hedonic values ----- %

omega = discreteinvrnd([.4,.4,.20],n,2) ;

% ----- for every person, draw a pricing shock 
%          and compute a price for each period 
%           till the reservation price is meet ----- %

[ep,eppr]=qnwnorm(3,0,.40);


for i = 1:n
 for j = 1:t
  ss           = ep(discreteinvrnd(eppr,1,1));
  price(i,1)   = exp(beta0 + beta1*omega(i,1) + beta2*omega(i,2) + ss ) ;
  exprice(i,1) = exp(beta0 + beta1*omega(i,1) + beta2*omega(i,2) ) ;
  timemkt(i,1) = j;
   if price(i,1) >= floor(P(omega(i,1),omega(i,2))), break, end
 end
end

% ----- plot time on the market histogram ----- %

figure(1)
hist(timemkt,20)
title('(A) Distribution of Time on the Market','fontsize',16,'fontname','times')
print -depsc2 -tiff -r300 -adobecset real2a

% ----- compute mean mean time on the market ----- %

mean(timemkt)

% ----- compute regression coefficient ----- %

inv([ones(n,1) omega]'*[ones(n,1) omega])*[ones(n,1) omega]'*log(price)



% ----- save data ----- %


X = [ log(price) omega(:,1:2) ] ;


save real2.dat X -ascii



comptime = etime(clock, time0)
diary off