# # 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: