两期OLG模型python代码示例

在Python中，OLG（Old-Lady-Growing）模型通常用于人口动态模拟，特别是描述人口老龄化过程。这是一个简化的模型，假设老年人口比例随着时间增长而增加。下面是一个简单的Python代码示例：

import numpy as np

class OLGModel:
    def __init__(self, initial_population, birth_rate, death_rate, retirement_age):
        self.population = initial_population
        self.birth_rate = birth_rate
        self.death_rate = death_rate
        self.retirement_age = retirement_age
        self.working_age_pop = self.population - self.get_retired_population()

    def get_retired_population(self):
        return int(self.population * (self.retirement_age / 100))

    def simulate_year(self):
        newborns = self.population * self.birth_rate
        deaths = self.population * self.death_rate
        working_age_increase = self.working_age_pop * (1 - self.birth_rate - self.death_rate)
        
        # 如果退休的人多于工作年龄人口增加，说明有新的退休人口
        new_retirees = min(working_age_increase, self.get_retired_population())
        self.working_age_pop -= new_retirees
        
        # 更新总人口
        self.population += newborns - deaths - new_retirees
        return self.population

# 使用示例
initial_population = 1000000
birth_rate = 0.025
death_rate = 0.015
retirement_age = 65
model = OLGModel(initial_population, birth_rate, death_rate, retirement_age)

for _ in range(50):  # 模拟50年
    model.simulate_year()
    print(f"第{_[0]}年的总人口: {model.population}")