def compute_stats_list(state_list, state_names):
mean = np.empty(len(state_list))
variance = np.empty(len(state_list))
sd = np.empty(len(state_list))
gini_stat = np.empty(len(state_list))
for i, state in enumerate(state_list):
mean[i] = np.mean(state)
variance[i] = np.var(state)
sd[i] = np.sqrt(np.var(state))
gini_stat[i] = gini(state)
data = {
'state': state_names,
'mean': mean,
'Variance': variance,
'Sd': sd,
'Gini': gini_stat
}
df = pd.DataFrame.from_dict(data)
return df
plt.ylabel("Density")
plt.legend()
plt.show()
mean_m1t = mean_m1[T-1]
var_m1t = np.var(m1_state)
sd_m1t = np.sqrt(var_m1t)
mean_m2t = mean_m2[T-1]
var_m2t = np.var(m2_state)
sd_m2t = np.sqrt(var_m2t)
gini_input1s = gini(m1_state)
gini_m2 = gini(m2_state)
input1s_stats = [mean_m1t, sd_m1t, gini_input1s]
input2_stats = [mean_m2t, sd_m2t, gini_m2]
print(input1s_stats)
print(input2_stats)
#%% Assets
fig, ax = plt.subplots()
ax.plot(range(0,T), mean_a, label='Average_asset')
ax.legend()
ax.set_xlabel('Time')
plt.plot(ages, cage[:, 1])
plt.xlabel('age')
plt.ylabel('hours per week')
plt.title('Labor Supply Intesive Margin Life-Cycle (20-65 years)')
### Inequality - Gini
# the greater (close to 1), more inequality
# Full sample
g = data_labor[["hh_work", "hh_hour", "age"]]
g = g.fillna(0)
w_array = np.array(g['hh_work'])
gini_work = gini(w_array)
h_array = np.array(g['hh_hour'])
gini_hour = gini(h_array)
print(gini_work, gini_hour)
del gini_work, gini_hour
# By Ages
gw = np.zeros((46, 1))
gh = np.zeros((46, 1))
j = list(range(0, 46))
for i in range(20, 66):
plt.legend('CIW ')
plt.xlabel('age')
plt.ylabel('log')
plt.title('CIW over the Life-Cycle')
plt.show()
### Inequality - Gini
# the greater (close to 1), more inequality
# Full sample
g = data[["ctotal", "inctotal", "wtotal", "age"]]
g = g.fillna(0)
c_array = np.array(g['ctotal'])
gini_c = gini(c_array)
inc_array = np.array(g['inctotal'])
gini_inc = gini(inc_array)
w_array = np.array(g['wtotal'])
gini_w = gini(w_array)
del g
print(gini_c, gini_inc, gini_w)
# By Ages
gc = np.zeros((46, 1))
gi = np.zeros((46, 1))