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Title: Properties of an IV-estimator based on aggregated nonlinear moment conditions Authors:  Joachim Schnurbus - University of Passau (Germany) [presenting]
Andrew Adrian Yu Pua - Xiamen University (China)
Markus Fritsch - University of Passau (Germany)
Abstract: An instrumental variables (IV) estimator based on aggregated nonlinear moment conditions is proposed in order to estimate the autoregressive parameter in linear dynamic panel data models. As the IV-estimator may converge to two distinct solutions, we provide a weighting scheme to identify the correct solution. The derivation of the large sample properties of the proposed estimator is underlined by Monte Carlo results.