GMM estimation with noncausal instruments under rational expectations
AbstractThere 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 InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 35536.
Date of creation: 22 Dec 2011
Date of revision:
generalized method of moments; noncausal autoregression; rational expectations;
Find related papers by JEL classification:
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
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- 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.).
- 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.
- Lanne, Markku & Saikkonen, Pentti, 2010.
"Noncausal Vector Autoregression,"
23717, University Library of Munich, Germany.
- 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.
- Markku Lanne & Pentti Saikkonen, 2011.
"GMM Estimation with Non‐causal Instruments,"
Oxford Bulletin of Economics and Statistics,
Department of Economics, University of Oxford, vol. 73(5), pages 581-592, October.
- 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.
- Lanne, Markku & Saikkonen, Pentti, 2010. "Noncausal autoregressions for economic time series," MPRA Paper 32943, University Library of Munich, Germany.
- Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2010.
"Optimal Forecasting of Noncausal Autoregressive Time Series,"
23648, University Library of Munich, Germany.
- Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2012. "Optimal forecasting of noncausal autoregressive time series," International Journal of Forecasting, Elsevier, vol. 28(3), pages 623-631.
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