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...

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.

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...

Interest has been growing in testing for nonlinearity or chaos in economic data, but much controversy has arisen about the available results. This paper explores the reasons for these empirical difficulties. We designed and ran a single-blind controlled competition among five highly regarded...

SNP is a method of nonparametric time series analysis. The method employs a polynomial series expansion to approximate the conditional density of a multivariate process. An appealing feature of the expansion is that it directly nests familiar models such as a pure VAR, a pure ARCH, a nonlinear...

This Guide shows how to use the computer package EMM, whicih implements the estimator described in "Which Moments to Match" (Gallant and Tauchen, 1994). The term EMM refers to Efficient Method of Moments. The Guide provides an overview of the estimator, instructions on how to acquire the...

We describe an intuitive, simple, and systematic approach to generating moment conditions for GMM estimation of the parameters of a structural model. The idea is to use the score of a density that has an analytic expression to define the GMM criterion. The auxiliary model that generates the...

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...

We evaluate the statistical and economic differences between affine term-structure models. Despite the voluminous literature on this subject, we have a limited understanding of those structural features of the models that are important in practice. Given that the key distinguishing...