Inference based on Kotlarski's Identity
Kotlarski’s identity has been widely used in applied economic research. However, how to conduct inference based on this popular identification approach has been an open question for two decades. This paper addresses this open problem by constructing a novel confidence band for the density function of a latent variable in repeated measurement error model. The confidence band builds on our finding that we can rewrite Kotlarski’s identity as a system of linear moment restrictions. The confidence band controls the asymptotic size uniformly over a class of data generating processes, and it is consistent against all fixed alternatives. Simulation studies support our theoretical results.

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docs.google.com/spreadsheets/d/1B5eDfd-p_oFWK5FiVvLebyit0ZQTQ6lkjUzbAFYDhUw/edit#gid=0

Link to paper:
arxiv.org/pdf/1808.09375.pdf
Date: 17 May 2019, 14:15 (Friday, 3rd week, Trinity 2019)
Venue: Manor Road Building, Manor Road OX1 3UQ
Venue Details: Seminar Room C
Speaker: Yuya Sasaki (Vanderbilt University)
Organising department: Department of Economics
Part of: Nuffield Econometrics Seminar
Booking required?: Not required
Audience: Members of the University only
Editor: Melis Clark