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Inference for parameters identified by conditional moment restrictions using a generalized Bierens maximum statistic

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  • Xiaohong Chen
  • Sokbae Lee
  • Myung Hwan Seo
  • Myunghyun Song

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.

Suggested Citation

  • Xiaohong Chen & Sokbae Lee & Myung Hwan Seo & Myunghyun Song, 2020. "Inference for parameters identified by conditional moment restrictions using a generalized Bierens maximum statistic," Papers 2008.11140, arXiv.org, revised Oct 2024.
    • Handle: RePEc:arx:papers:2008.11140
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    References listed on IDEAS

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