A NONPARAMETRIC SIMULATED MAXIMUM LIKELIHOOD ESTIMATION METHOD

By Jean-David Fermanian, Bernard Salanié. Econometric Theory, 2004

73 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/1706427f679a75a1ecbeade5a1f8322c3d931e07

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Citations in the corpus

Estimating Macroeconomic Models: A Likelihood Approach (2007, unknown): “Thus, a second order approximation to the policy function for capital is given by: log e Kt+1 = Ψk1e st + 1 2 e s0tΨk2e st (18)”
Minimizing Sensitivity to Model Misspecification (2018, methodology): “Applying the same formula as in (31), but now only considering the deviations v = θ0 − θ(η) along the j-th component θj , we obtain e ωj = ω · (Heθ(bη))(j,j), the j-th diagonal element of Hθ(bη) multiplied by some constant ω (which can be chosen equal to one without loss of generality).”
Simulation-Based Method of Moments and Efficiency (2002, methodology): “Fermanian and Salanié (2001) proposed a nonparametric SML estimator based on a kernel estimation of the likelihood and showed that this method delivers an ef cient estimator in the static case.”
Estimating functions in indirect inference (2004, background): “Fermanian and Salanié (2001) proved asymptotic efficiency as the bandwidth goes to 0.”
UNIFORM CONVERGENCE RATES OF KERNEL ESTIMATORS WITH HETEROGENEOUS DEPENDENT DATA (2009, unknown): “…application can be found in the recent literature on nonparametric simulated maximumlikelihood and generalized method of moments (GMM) estimation (Altissimo and Mele, 2008; Brownlees, Kristensen, and Shin, 2009; Creel and Kristensen, 2009; Fermanian and Salanié, 2004; Kristensen and Shin, 2008).”
Efficient estimation of general dynamic models with a continuum of moment conditions (2007, methodology): “This approach can be thought as a simple alternative to the Indirect Inference proposed by Gouriéroux, Monfort and Renault (1993), the Efficient Method of Moments (EMM) suggested by Gallant and Tauchen (1996), and the nonparametric simulated maximum likelihood method (Fermanian and Salanie, 2004).”
Semi-Parametric Comparison of Stochastic Volatility Models using Realized Measures (2006, methodology): “Recently, Fermanian and Salanié (2004) have suggested a simulated maximum likelihood estimator obtained by using a kernel density estimator of the simulated data; Altissimo and Mele (2005) have proposed a new estimator based on the minimization of the weighted distance between a kernel estimator of…”