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Author: Markus Wiener
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Description: Entrepreneurs, Chance, and the Deterministic Concentration of Wealth (Joseph E. Fargione, Clarence Lehman, Stephen Polasky)
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# Entrepreneurs, Chance, and the Deterministic Concentration of Wealth # Joseph E. Fargione, Clarence Lehman, Stephen Polasky # https://doi.org/10.1371/journal.pone.0020728 import numpy as np import scipy.stats as sts import matplotlib.pyplot as plt n, t = 100000, 200 dn, dt = n//1000, t//10 mu, sigma = 0.05, 0.3 R = np.random.normal(mu, sigma, (1000*dn, 10*dt)) X = R.cumsum(axis=1) Y = np.exp(X) S = np.ones((1000*dn, 1)) Z = np.concatenate((S, S*Y), axis=1) Z.sort(axis=0) W = Z[0*dn:1000*dn].sum(axis=0) Q0 = Z[0*dn:100*dn].sum(axis=0)/W Q1 = Z[100*dn:200*dn].sum(axis=0)/W Q2 = Z[200*dn:300*dn].sum(axis=0)/W Q3 = Z[300*dn:400*dn].sum(axis=0)/W Q4 = Z[400*dn:500*dn].sum(axis=0)/W Q5 = Z[500*dn:600*dn].sum(axis=0)/W Q6 = Z[600*dn:700*dn].sum(axis=0)/W Q7 = Z[700*dn:800*dn].sum(axis=0)/W Q8 = Z[800*dn:900*dn].sum(axis=0)/W Q9 = Z[900*dn:1000*dn].sum(axis=0)/W Q99 = Z[990*dn:1000*dn].sum(axis=0)/W Q999 = Z[999*dn:1000*dn].sum(axis=0)/W T = np.arange(0, 10*dt+1, 1) P9 = sts.norm.cdf(sigma*np.sqrt(T)-sts.norm.ppf(0.9)) P99 = sts.norm.cdf(sigma*np.sqrt(T)-sts.norm.ppf(0.99)) P999 = sts.norm.cdf(sigma*np.sqrt(T)-sts.norm.ppf(0.999)) fig, ax = plt.subplots(2, 3, sharey=True, figsize=(10.0, 5.0)) fig.suptitle('Distribution of wealth over time') I = ('0', '1', '2', '3', '4', '5', '6', '7', '8', '9') Q = np.stack((Q0, Q1, Q2, Q3, Q4, Q5, Q6, Q7, Q8, Q9)) ax[0, 0].bar(I, Q[0:10, 0*dt]) ax[0, 1].bar(I, Q[0:10, 1*dt]) ax[0, 2].bar(I, Q[0:10, 2*dt]) ax[1, 0].bar(I, Q[0:10, 3*dt]) ax[1, 1].bar(I, Q[0:10, 4*dt]) ax[1, 2].bar(I, Q[0:10, 5*dt]) fig, ax = plt.subplots(figsize=(10.0, 5.0)) fig.suptitle('Concentration of wealth over time') ax.plot(Q9, 'bo', T, P9, 'c', markersize=4.0, linewidth=2.0, label='Top 10%') ax.plot(Q99, 'bo', T, P99, 'c', markersize=2.0, linewidth=1.0, label='Top 1%') ax.plot(Q999, 'bo', T, P999, 'c', markersize=1.0, linewidth=0.5, label='Top 0.1%') ax.set(xlabel='Time (years)', ylabel='Proportion of total wealth') ax.set_xticks(np.arange(0, 10*dt+1, dt)) ax.legend(loc='lower right') ax.grid() plt.show()
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