We discuss techniques of estimation and inference for nonstationary nonlinear cohort panels with learning from experience, showing, inter alia, the consistency and asymptotic normality of the nonlinear least squares estimator used in empirical practice. Potential pitfalls for hypothesis testing are identified and solutions proposed. Monte Carlo simulations verify the properties of the estimator and corresponding test statistics in finite samples, while an application to a panel of survey expectations demonstrates the usefulness of the theory developed.

翻译：本文讨论了具有经验学习特征的非平稳非线性群体面板的估计与推断技术，特别论证了实证分析中使用的非线性最小二乘估计量的一致性和渐近正态性。我们识别了假设检验中潜在的问题，并提出了解决方案。蒙特卡洛模拟验证了该估计量及相关检验统计量在有限样本中的性质，而针对调查预期群体面板的应用案例则展示了所发展理论的有效性。