We discuss techniques of estimation and inference for nonlinear cohort panels with learning from experience, showing, inter alia, the consistency and asymptotic normality of the nonlinear least squares estimator employed in the seminal paper by Malmendier and Nagel (2016). 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：我们讨论了具有经验学习特征的非线性队列面板的估计与推断技术，尤其证明了Malmendier和Nagel（2016）开创性论文中使用的非线性最小二乘估计量的一致性和渐近正态性。识别了假设检验中的潜在陷阱并提出了解决方案。蒙特卡洛模拟验证了该估计量及相应检验统计量在有限样本下的性质，而对调查预期面板数据的应用则证明了所发展理论的有用性。