LabEC 2025/26

Laboratorio di Economia Computazionale
Università degli Studi di Firenze
Dipartimento di Scienze per l’Economia e l’Impresa

PROGRAMMA

Programma del Corso sul sito ufficiale dell’Università degli Studio di Firenze

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SCRIPT E NOTE

Alcune note su Python (link esterno)
Introduzione all’Economia Computazionale
Funzione Produzione Cobb-Douglas

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#!/usr/bin/env python3 """ @author: grarchive.net Cobb-Douglas Y= A L^alpha * K^(beta) """ import matplotlib.pyplot as plt import numpy as np fig=plt.figure() ax=plt.axes(projection="3d") #paramters A=1 alpha=0.33 beta=0.33 x=np.linspace(0,100,200) y=np.linspace(0,100,200) X,Y=np.meshgrid(x,y) Z = A*(X**alpha)*(Y**beta) plt.figure(1) ax.plot_surface(X,Y,Z) ax.set_xlabel("Labour") ax.set_ylabel("Kapital") ax.set_zlabel("Production") plt.figure(2) plt.contourf(X,Y,Z) plt.xlabel("Labour") plt.ylabel("Kapital")
Note sul Modello Reddito-Spesa (caso statico e caso dinamico)

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""" Dynamic Income–Expenditure model (Keynesian cross). Parameters: N = number of periods x0 = initial income A = autonomous expenditure epsilon = c(1-t)-q phi = speed of adjustment Returns: Array with the simulated income trajectory. """ import numpy as np import matplotlib.pyplot as plt def IE(N, x0, A, epsilon, phi): # Initialize vector of incomes with zeros x = np.zeros(N) # Set initial condition x[0] = x0 # Create grid for the static IE diagram Y = np.linspace(0, 50000, 11) Z = A + epsilon * Y # Plot expenditure line Z(Y) = A + epsilon*Y plt.plot(Y, Z, color="black", label=r"$Z(Y)$") # Plot the 45-degree line plt.plot(Y, Y, label="45° line") # Axes crossing at zero plt.axhline(color='black', lw=0.5) plt.axvline(color='black', lw=0.5) # Cobweb staircase: dynamic adjustment for t in range(N-1): # Update rule: Y_{t+1} = Y_t + phi*(Z(Y_t) - Y_t) x[t+1] = x[t] + phi*(A + epsilon*x[t] - x[t]) # Vertical segment: (Y_t, Y_t) -> (Y_t, Y_{t+1}) plt.plot([x[t], x[t]], [x[t], x[t+1]], color='blue') # Horizontal segment: (Y_t, Y_{t+1}) -> (Y_{t+1}, Y_{t+1}) plt.plot([x[t], x[t+1]], [x[t+1], x[t+1]], color='red') plt.title("Dynamic Income–Expenditure Model") plt.xlabel(r"$Y_t$") plt.ylabel(r"$Z(Y_t)$") plt.legend() plt.grid(True) plt.show() # Time series of income plt.plot(x, marker="o") plt.title("Income time series") plt.xlabel("t") plt.ylabel(r"$Y_t$") plt.grid(True) plt.show() return x # Example simulation x = IE(20, 10000, 15000, 0.53, 2.5)

SOFTWARE

Python distribuzone Anaconda

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LabEC 2025/26

Laboratorio di Economia Computazionale Università degli Studi di Firenze Dipartimento di Scienze per l’Economia e l’Impresa

PROGRAMMA

SCRIPT E NOTE

Script

Script

SOFTWARE

Laboratorio di Economia Computazionale
Università degli Studi di Firenze
Dipartimento di Scienze per l’Economia e l’Impresa