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.
Authors
Research Fellow Duke University
Adam is a Research Fellow associated with the Cemmap at the IFS and UCL and an Associate Professor of Economics at Duke University.
Working Paper details
- DOI
- 10.1920/wp.cem.2006.2506
- Publisher
- IFS
Suggested citation
Rosen, A. (2006). Confidence sets for partially identified parameters that satisfy a finite number of moment inequalities. London: IFS. Available at: https://ifs.org.uk/publications/confidence-sets-partially-identified-parameters-satisfy-finite-number-moment (accessed: 3 May 2024).
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