The SNP estimator is the most convenient nonparametric method for simultaneously estimating the parameters of a nonlinear model and the density of a latent process by maximum likelihood. To determine if this convenience comes at a price, we assess the qualitative behavior of SNP in finite...

Efficient Method of Moments (EMM) is used to fit the standard stochastic volatility model and various extensions to several daily financial time series. EMM matches to the score of a model determined by data analysis called the score generator. Discrepancies reveal characteristics of data that...

This paper summarizes comments at the Panel Discussion on Calibration at the Seventh World Congress of the Econometric Society, Keio University, Tokyo, Japan, 22-29 August 1995.

We describe a computationally intensive methodology for the estimation and analysis of partially observable nonlinear systems. An example from epidemiology is the SEIR model, which is a system of differential equations with random coefficients that describe a population in terms of four state...

This paper evaluates the role of various volatility specifications, such as multiple stochastic volatility (SV) factors and jump components, in appropriate modeling of equity return distributions. We use estimation technology that facilitates non-nested model comparisons and use a long data set...

The paper describes the use of the Gallant-Tauchen efficient method of moments (EMM) technique for diagnostic checking of stochastic differential equations (SDEs) estimated from financial market data. The EMM technique is a simulation-based method that uses the score function of an auxiliary...

We propose a minimum chi-square estimator for the parameters of an ergodic system of stochastic differential equations with partially observed state. We prove that the efficiency of the estimator approaches that of maximum likelihood as the number of moment functions entering the chi-square...

The paper uses and extends the Efficient Method of Moments (EMM) technique to estimate and test continuous time diffusion models for stock returns and interest rates. The EMM technique, developed in previous papers by Gallatn and Tauchen along with various collaborators, is a simulation-based...