The Bates (2006) Approximate Maximum Likelihood (AML) method is considered from a practical point of view. Application of the AML method is undertaken using FFT with splines for integration. Results are validated by both simulation and comparison to MCMC literature. The SVJ model is estimated...

We consider discrete default intensity based and logit type reduced form models for conditional default probabilities for corporate loans where we develop simple closed form approximations to the maximum likelihood estimator (MLE) when the underlying covariates follow a stationary Gaussian...

Following Wooldridge (2014), we discuss and implement in Stata an efficient maximum likelihood approach to the estimation of corrected standard errors of two-stage optimization models. Specifically, we compare the robustness and efficiency of this estimate using different non-linear routines...

The small sample performance of system Generalized Method of Moments (GMM) and an alternative Transformed Maximum Likelihood (TML) estimator is investigated in Monte Carlo simulations, implementing a data generating process that tracks important features inherent in dynamic panels used in...

This paper proposes a general computational framework for empirical estimation of financial agent-based models, for which criterion functions have unknown analytical form. For this purpose, we adapt a recently developed nonparametric simulated maximum likelihood estimation based on kernel...

Empirical likelihood is a popular nonparametric analog of the usual parametric likelihood, inheriting many of the large-sample properties of the latter construct. This article presents a review of the empirical likelihood approach from its introduction 30 years ago, up to recent theoretical...