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Confidence sets for partially identified parameters that satisfy a finite number of moment inequalities

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  • Adam Rosen

    (Institute for Fiscal Studies and Duke University)

Abstract

This paper proposes a new way to construct confidence sets for a parameter of interest in models comprised of finitely many moment inequalities. Building on results from the literature on multivariate one-sided tests, I show how to test the hypothesis that any particular parameter value is logically consistent with the maintained moment inequalities. The associated test statistic has an asymptotic chi-bar-square distribution, and can be inverted to construct an asymptotic confidence set for the parameter of interest, even if that parameter is only partially identified. The confidence sets are easily computed, and Monte Carlo simulations demonstrate good finite sample performance.

Suggested Citation

  • Adam Rosen, 2006. "Confidence sets for partially identified parameters that satisfy a finite number of moment inequalities," CeMMAP working papers CWP25/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:cemmap:25/06
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    References listed on IDEAS

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    More about this item

    Keywords

    Partial identification; inference; moment inequalities;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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