(joint with Michael Massmann)

Abstract:

We discuss techniques of estimation and inference for nonlinear cohort pan-
els 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, QJE). Potential pitfalls
for hypothesis testing are identified and solutions proposed. Monte Carlo sim-
ulations verify the properties of the estimator and corresponding test statis-
tics in finite samples, while an application to a panel of survey expectations
demonstrates the usefulness of the theory developed.