Impact of excessive regulation on Economic development with fluctuations
Description
The provided Python code conducts a simulation to explore the impact of regulation on economic growth over time. Here's a description of the data and the simulation: Simulation Parameters: The code sets up parameters for the simulation, including the number of time periods (time_periods), the impact of regulation on the regulated sector (regulation_impact), and the degree of economic fluctuations (volatility). Initial Conditions: Arrays are initialized to store economic growth data for the regulated sector (regulated_sector_growth) and the less regulated sector (less_regulated_sector_growth) over the specified time periods. Simulation Loop: The simulation progresses over time periods, introducing randomness to simulate economic fluctuations. For each time period, a random factor is generated from a normal distribution with a mean of 0 and a specified volatility. The economic growth model incorporates the impact of regulation on the regulated sector, where growth is influenced by the previous period's growth, regulation impact, and fluctuations. The less regulated sector experiences growth more freely, with a constant growth factor of 1.05 and fluctuations. Plotting the Results: The simulation results are visualized using matplotlib. Two lines on the plot represent the economic growth of the regulated sector and the less regulated sector over time. Markers ('o') are used to highlight specific data points on the plot. Plot Labels and Title: The x-axis is labeled as 'Time Periods', and the y-axis is labeled as 'Economic Growth'. The plot is titled 'Impact of Excessive Regulation on Economic Development with Fluctuations'. A legend is included to differentiate between the regulated and less regulated sectors. Figure Size and Grid: The size of the plot figure is set to (10, 6) for better visualization. A grid is added to the plot for improved readability. In summary, the code creates a simulation to analyze the impact of excessive regulation on economic development, considering fluctuations in the economic environment. The resulting plot visually represents the growth trajectories of both the regulated and less regulated sectors over a specified number of time periods, providing insights into the potential consequences of regulatory policies on economic outcomes.
Files
Steps to reproduce
import numpy as np import matplotlib.pyplot as plt # Simulation parameters time_periods = 50 regulation_impact = 0.1 # Impact of regulation on the regulated sector volatility = 0.1 # Degree of fluctuations # Initial conditions time = np.arange(time_periods) regulated_sector_growth = np.ones(time_periods) less_regulated_sector_growth = np.ones(time_periods) # Simulate economic growth over time with fluctuations for t in range(1, time_periods): # Introduce randomness for fluctuations random_factor = 1 + np.random.normal(0, volatility) # Economic growth model with regulation impact and fluctuations regulated_sector_growth[t] = regulated_sector_growth[t - 1] * (1 - regulation_impact) * random_factor # Less regulated sector grows more freely with fluctuations less_regulated_sector_growth[t] = less_regulated_sector_growth[t - 1] * 1.05 * random_factor # Plotting the simulation results with fluctuations plt.figure(figsize=(10, 6)) plt.plot(time, regulated_sector_growth, label='Regulated Sector', marker='o') plt.plot(time, less_regulated_sector_growth, label='Less Regulated Sector', marker='o') plt.xlabel('Time Periods') plt.ylabel('Economic Growth') plt.title('Impact of Excessive Regulation on Economic Development with Fluctuations') plt.legend() plt.grid(True) plt.show()