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Boosting Your Instruments: Estimation with Overidentifying Inequality Moment Conditions

Author

Listed:
  • Hyungsik Roger Moon

    (Department of Economics, University of Southern California)

  • Frank Schorfheide

    (Department of Economics, University of Pennsylvania and CEPR)

Abstract

This paper derives limit distributions of empirical likelihood estimators for models in which inequality moment conditions provide overidentifying information. We show that the use of this information leads to a reduction of the asymptotic mean-squared estimation error and propose asymptotically valid con¯dence sets for the parameters of interest. While inequality moment conditions arise in many important economic models, we use a dynamic macroeconomic model as data generating process and il- lustrate our methods with instrumental variable estimators of monetary policy rules. The assumption that output does not fall in response to an expansionary monetary policy shock leads to an inequality moment condition that can substantially increase the precision with which the policy rule is estimated. The results obtained in this paper extend to conventional GMM estimators.

Suggested Citation

  • Hyungsik Roger Moon & Frank Schorfheide, 2006. "Boosting Your Instruments: Estimation with Overidentifying Inequality Moment Conditions," IEPR Working Papers 06.56, Institute of Economic Policy Research (IEPR).
    • Handle: RePEc:scp:wpaper:06-56
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    Cited by:

    1. Linton, Oliver & Song, Kyungchul & Whang, Yoon-Jae, 2010. "An improved bootstrap test of stochastic dominance," Journal of Econometrics, Elsevier, vol. 154(2), pages 186-202, February.
    2. Donald W. K. Andrews & Panle Jia Barwick, 2012. "Inference for Parameters Defined by Moment Inequalities: A Recommended Moment Selection Procedure," Econometrica, Econometric Society, vol. 80(6), pages 2805-2826, November.
    3. Donald W. K. Andrews & Xiaoxia Shi, 2013. "Inference Based on Conditional Moment Inequalities," Econometrica, Econometric Society, vol. 81(2), pages 609-666, March.
    4. Andrew Chesher, 2010. "Instrumental Variable Models for Discrete Outcomes," Econometrica, Econometric Society, vol. 78(2), pages 575-601, March.
    5. Rosen, Adam M., 2008. "Confidence sets for partially identified parameters that satisfy a finite number of moment inequalities," Journal of Econometrics, Elsevier, vol. 146(1), pages 107-117, September.
    6. Lu, Zhentong, 2022. "Estimating multinomial choice models with unobserved choice sets," Journal of Econometrics, Elsevier, vol. 226(2), pages 368-398.
    7. Moon, Hyungsik Roger & Schorfheide, Frank, 2009. "Estimation with overidentifying inequality moment conditions," Journal of Econometrics, Elsevier, vol. 153(2), pages 136-154, December.
    8. repec:cwl:cwldpp:1761rr is not listed on IDEAS

    More about this item

    Keywords

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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