The equilibrium climate sensitivity is often estimated by the ordinary least squares applied to annual data of observed/calculated temperature and forcing series. One of the conditions under which the ordinary least squares estimator is consistent is the uncorrelatedness of the regressor and regression error. However, this condition can fail in a regression using historical data of temperature and forcing. Alternative estimators established in econometrics are shown to mitigate the impact of the correlated regressor and regression error and deliver a more reliable estimate of the equilibrium climate sensitivity.

中文翻译：

---

关于平衡气候敏感性的普通最小二乘估计的无效性

平衡气候敏感性通常通过应用于观测/计算温度和强迫序列的年度数据的普通最小二乘法来估计。普通最小二乘估计量一致的条件之一是回归量和回归误差的不相关性。然而，这种条件在使用温度和强迫的历史数据的回归中可能会失败。计量经济学中建立的替代估计量可以减轻相关回归量和回归误差的影响，并提供对平衡气候敏感性的更可靠估计。