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GMM estimation with noncausal instruments under rational expectations

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  • Lof, Matthijs

Abstract

There is hope for the generalized method of moments (GMM). Lanne and Saikkonen (2011) show that the GMM estimator is inconsistent, when the instruments are lags of noncausal variables. This paper argues that this inconsistency depends on distributional assumptions, that do not always hold. In particular under rational expectations, the GMM estimator is found to be consistent. This result is derived in a linear context and illustrated by simulation of a nonlinear asset pricing model.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 35536.

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Date of creation: 22 Dec 2011
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Handle: RePEc:pra:mprapa:35536

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Keywords: generalized method of moments; noncausal autoregression; rational expectations;

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  1. Jonathan H. Wright, 2000. "Detecting lack of identification in GMM," International Finance Discussion Papers 674, Board of Governors of the Federal Reserve System (U.S.).
  2. Motohiro Yogo, 2004. "Estimating the Elasticity of Intertemporal Substitution When Instruments Are Weak," The Review of Economics and Statistics, MIT Press, vol. 86(3), pages 797-810, August.
  3. Lanne, Markku & Saikkonen, Pentti, 2010. "Noncausal Vector Autoregression," MPRA Paper 23717, University Library of Munich, Germany.
  4. Tauchen, George & Hussey, Robert, 1991. "Quadrature-Based Methods for Obtaining Approximate Solutions to Nonlinear Asset Pricing Models," Econometrica, Econometric Society, vol. 59(2), pages 371-96, March.
  5. Markku Lanne & Pentti Saikkonen, 2011. "GMM Estimation with Nonā€causal Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(5), pages 581-592, October.
  6. Lanne Markku & Saikkonen Pentti, 2011. "Noncausal Autoregressions for Economic Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 3(3), pages 1-32, October.
  7. Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2010. "Optimal Forecasting of Noncausal Autoregressive Time Series," MPRA Paper 23648, University Library of Munich, Germany.
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