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Generalized method of moments with latent variables

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  • Ron Gallant

    (Institute for Fiscal Studies and Duke University)

  • Raffaella Giacomini

    ()
    (Institute for Fiscal Studies and UCL)

  • Giuseppe Ragusa

Abstract

The contribution of generalized method of moments (Hansen and Singleton, 1982) was to allow frequentist inference regarding the parameters of a nonlinear structural model without having to solve the model, provided there were no latent variables. The contribution of this paper is the same with latent variables.

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Bibliographic Info

Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP50/13.

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Date of creation: Oct 2013
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Handle: RePEc:ifs:cemmap:50/13

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  1. Frank Schorfheide & Marco Del Negro, 2007. "Forming Priors for DSGE Models (and How It Affects the Assessment of Nominal Rigidities)," 2007 Meeting Papers 283, Society for Economic Dynamics.
  2. Fernández-Villaverde, Jesús & Rubio-Ramirez, Juan Francisco, 2006. "Estimating Macroeconomic Models: A Likelihood Approach," CEPR Discussion Papers 5513, C.E.P.R. Discussion Papers.
  3. Flury, Thomas & Shephard, Neil, 2011. "Bayesian Inference Based Only On Simulated Likelihood: Particle Filter Analysis Of Dynamic Economic Models," Econometric Theory, Cambridge University Press, vol. 27(05), pages 933-956, October.
  4. Gallant, A. Ronald & Tauchen, George, 1996. "Which Moments to Match?," Econometric Theory, Cambridge University Press, vol. 12(04), pages 657-681, October.
  5. Gallant, A. Ronald & McCulloch, Robert E., 2009. "On the Determination of General Scientific Models With Application to Asset Pricing," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 117-131.
  6. Duffie, Darrell & Singleton, Kenneth J, 1993. "Simulated Moments Estimation of Markov Models of Asset Prices," Econometrica, Econometric Society, vol. 61(4), pages 929-52, July.
  7. Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.
  8. Han Hong, 2007. "A Statistical Inquiry into the Plausibility of Recursive Utility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 5(4), pages 523-559, Fall.
  9. Christophe Andrieu & Arnaud Doucet & Roman Holenstein, 2010. "Particle Markov chain Monte Carlo methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(3), pages 269-342.
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