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))