蒙特卡洛模拟：OLS无偏性

import numpy as np

def solve():
    np.random.seed(____)
    n, n_sim = ____, ____
    beta0_true, beta1_true = ____, ____
    beta1_ests = []
    for _ in range(____):
        x = np.random.randn(____)
        eps = np.random.randn(____)
        y = beta0_true + beta1_true * x + eps
        X = np.column_stack([np.ones(____), x])
        b = np.linalg.inv(____) @ X.T @ y
        beta1_ests.append(____)
    print(____)