#
#  PROTO, Maple version
#  PJW
#
#  Here are the equations of the model:
#

   eq1 :=           y = w*h + s   :
   eq2 :=   p*(1+t)*c = a*y       :
   eq3 :=         w*j = (1-a)*y   :
   eq4 :=         w*l = a*y - s   :
   eq6 :=           l = q/b       :
   eq7 :=           p = w/(b-1)   :
   eq8 :=       t*p*c = s         :
   eq9 :=         wal = q-(q/b)-c :

#
#  Here are the parameters:
#

   a := 0.285:
   b := 2.040:

#
#  Here are the base case variables:
#
   
   h := 100.0:
   t := 0.200:
   p := 1.000:

#
#  Now solve the model.  Fsolve finds a floating-point (numerical)
#  solution as opposed to a symbolic solution.
#

   fsolve({eq1,eq2,eq3,eq4,eq6,eq7,eq8,eq9},{y,w,s,c,l,j,q,wal});

#
#  Test the model's price and wage homogeneity by doubling p
#

   p := 2.000:
   fsolve({eq1,eq2,eq3,eq4,eq6,eq7,eq8,eq9},{y,w,s,c,l,j,q,wal});
   p := 1.000:

#
#  Test the model's quantity homogeneity by doubling h
#

   h := 200.0:
   fsolve({eq1,eq2,eq3,eq4,eq6,eq7,eq8,eq9},{y,w,s,c,l,j,q,wal});
   h := 100.0:

#
#  Here is a policy experiment: increase T to 0.3
#

   t := 0.300:
   fsolve({eq1,eq2,eq3,eq4,eq6,eq7,eq8,eq9},{y,w,s,c,l,j,q,wal});
   t := 0.200:

#
#  All done...
#

   quit: