Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/309961 
Year of Publication: 
2024
Series/Report no.: 
cemmap working paper No. CWP26/24
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
Many economic panel and dynamic models, such as rational behavior and Euler equations, imply that the parameters of interest are identified by conditional moment restrictions. We introduce a novel inference method without any prior information about which conditioning instruments are weak or irrelevant. Building on Bierens (1990), we propose penalized maximum statistics and combine bootstrap inference with model selection. Our method optimizes asymptotic power by solving a data-dependent max-min problem for tuning parameter selection. Extensive Monte Carlo experiments, based on an empirical example, demonstrate the extent to which our inference procedure is superior to those available in the literature.
Subjects: 
conditional moment restrictions
conditional instruments
hypothesis testing
penalization
multiplier bootstrap
max-min
JEL: 
C12
C36
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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