alpha_h/(1-alpha_y)*100

import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline  

N = 200

alpha_y = 0.9
alpha_h = 0.5

C   = np.zeros(N) # consumption
Y   = np.zeros(N) # income
H_h = np.zeros(N) # private wealth

C[0] = 0
Y[0] = 0
H_h[0] = 100

for t in range(1, N):
    
    # calculate consumer spending
    C[t] = alpha_y*Y[t-1] + alpha_h*H_h[t-1] 
        
    # calculate total income (consumer spending plus constant government spending)
    Y[t]   = alpha_h/(1-alpha_y)*H_h[t-1] 
    
    H_h[t] = H_h[t-1] +(1-alpha_y)*Y[t] - alpha_h*H_h[t-1] 
   

fig = plt.figure(figsize=(12, 8))

consumption_plot = fig.add_subplot(131, xlim=(0, N), ylim=(0, np.max(C)*1.1))
consumption_plot.plot(range(N), C, lw=3)
consumption_plot.grid()
# label axes
plt.xlabel('time')
plt.ylabel('consumption')

income_plot = fig.add_subplot(132, xlim=(0, N), ylim=(0, np.max(Y)*1.1))
income_plot.plot(range(N), Y, lw=3)
income_plot.grid()
# label axes
plt.xlabel('time')
plt.ylabel('income')


debt_plot = fig.add_subplot(133, xlim=(0, N), ylim=(0,np.max(H_h)*1.5))
debt_plot.plot(range(N), H_h, lw=3)
debt_plot.grid()
# label axes
plt.xlabel('time')
plt.ylabel('government debt')

# space subplots neatly
plt.tight_layout()

N = 200

alpha_y = np.zeros(N)
alpha_y[0:(N/2)] =0.9
alpha_y[(N/2):-1] =0.85
alpha_h = 0.5

C   = np.zeros(N) # consumption
Y   = np.zeros(N) # income
H_h = np.zeros(N) # private wealth

C[0] = 0
Y[0] = 0
H_h[0] = 100

for t in range(1, N):
    
    # calculate consumer spending
    C[t] = alpha_y[t]*Y[t-1] + alpha_h*H_h[t-1] 
        
    # calculate total income (consumer spending plus constant government spending)
    Y[t]   = alpha_h/(1-alpha_y[t])*H_h[t-1] 
    
    H_h[t] = H_h[t-1] +(1-alpha_y[t])*Y[t] - alpha_h*H_h[t-1] 


alpha_y = np.zeros(N)
alpha_y[0:(N/2)] =0.9
alpha_y[(N/2):-1] =0.8 
alpha_y








N = 200

alpha_y = 0.9
alpha_h = 0.5

C   = np.zeros(N) # nominal consumption
c   = np.zeros(N) # real consumption
Y   = np.zeros(N) # nominal income
H_h = np.zeros(N) # private wealth

sigma_T = 0.5
chi     = 0.5
beta    = 0.5

y     = np.zeros(N) # real production
s_e   = np.zeros(N) # expected sales
s     = np.zeros(N) # realised real sales
inv   = np.zeros(N) # real value of inventories
inv_e = np.zeros(N) # expected inventories
inv_T = np.zeros(N) # targeted inventories

pr = 1           # productivity
E = np.zeros(N)  # employment
WB = np.zeros(N) # wage bill
UC = np.zeros(N) # unit cost

INV   = np.zeros(N) # nominal value of inventories
S     = np.zeros(N) # realised nominal sales
p     = np.zeros(N) # price level
NHUC  = np.zeros(N) # normal historical unit cost

C[0] = 0
Y[0] = 0
H_h[0] = 100

for t in range(1, N):
    
    # calculate consumer spending
    C[t] = alpha_y*Y[t-1] + alpha_h*H_h[t-1] 
        
    # calculate total income (consumer spending plus constant government spending)
    Y[t]   = alpha_h/(1-alpha_y)*H_h[t-1] 
    
    H_h[t] = H_h[t-1] +(1-alpha_y)*Y[t] - alpha_h*H_h[t-1]