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GMM estimation with noncausal instruments under rational expectations

  • Lof, Matthijs

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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File URL: http://mpra.ub.uni-muenchen.de/35536/1/MPRA_paper_35536.pdf
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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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  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. Lanne, Markku & Saikkonen, Pentti, 2010. "Noncausal autoregressions for economic time series," MPRA Paper 32943, University Library of Munich, Germany.
  3. Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2010. "Optimal Forecasting of Noncausal Autoregressive Time Series," MPRA Paper 23648, 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. Lanne, Markku & Saikkonen, Pentti, 2009. "Noncausal vector autoregression," Research Discussion Papers 18/2009, Bank of Finland.
  6. 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.
  7. Lanne, Markku & Saikkonen, Pentti, 2009. "GMM Estimation with Noncausal Instruments," MPRA Paper 23649, University Library of Munich, Germany.
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