A0536
Title: Least squares estimation in nonlinear cohort panels with learning from experience
Authors: Alexander Mayer - Universita Ca\' Foscari (Italy) [presenting]
Michael Massmann - WHU - Otto Beisheim School of Management (Germany)
Abstract: Techniques of estimation and inference are discussed 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 prior paper. Potential pitfalls for hypothesis testing are identified and solutions are 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.
