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A Simple Method for Uniform Subvector Inference of Linear Instrumental Variables Models

SSRN Electronic Journal
2015
  • 0
    Citations
  • 2,578
    Usage
  • 1
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Usage
    2,578
    • Abstract Views
      2,329
    • Downloads
      249
  • Captures
    1
  • Ratings
    • Download Rank
      246,272

Article Description

We propose a procedure for testing simple hypotheses on a subset of the structural parameters in linear instrumental variables models. Our test is valid uniformly over a large class of distributions allowing for identification failure and heteroskedasticity. The large-sample distribution of our test statistic is shown to depend on a key quantity that cannot be consistently estimated. Under our proposed procedure, we construct a confidence set for this key quantity and then maximize, over this confidence set, the appropriate quantile of the large-sample distribution of the test statistic. This maximum is used as the critical value and Bonferroni correction is used to control the overall size of the test. Monte Carlo simulations demonstrate the advantage of our test over the projection method in finite samples.

Bibliographic Details

Yinchu Zhu

Elsevier BV

weak instruments; uniform inference; subset inference; asymptotic size; linear IV model

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