Efficient GMM Estimation Using the Empirical Characteristic Function

By M. Carrasco, Jean-Pierre Florens. 2002

74 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/72b6319330262c0546349a67dc62a872bc292796

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Citations in the corpus

Estimation of Stable Distributions by Indirect Inference (2011, unknown): “1810−6 is the same value that Carrasco and Florens (2002) chose for their Monte Carlo study with the α-stable distribution.”
Efficient estimation of general dynamic models with a continuum of moment conditions (2007, methodology): “This is the approach taken in Carrasco and Florens (2002) in an iid context and may be very 9 Let θ = (θ1, ..., θq) ′.”
The Method of Simulated Quantiles (2013, unknown): “…optimization (both time and computationally wise) and, ii) when the grid becomes sufficiently thin, it would not be possible to estimate efficiently since the quantiles become collinear when the number as τ ’s goes to infinity (this was pointed out by Carrasco and Florens (2002) in a GMM set up).”
Simulation-Based Method of Moments and Efficiency (2002, methodology): “Moments based on the characteristic function also have this property (see Carrasco and Florens 2000b; Carrasco, Chernov, Florens, and Ghysels 2001).”
Maximum likelihood estimation of stochastic frontier models by the Fourier transform (2012, methodology): “Madan and Seneta (1982) suggest using a 7 the efficient GMM technique of Carrasco and Florens (2002) who use a continuum of moment conditions.”
Empirical Characteristic Function Estimation and Its Applications (2004, unknown): “Based on the results obtained in Carrasco and Florens (2000), Carrasco and Florens (2002) provide a solution to this dilemma which also avoids the singularity problem discussed in the discrete case.”