We consider cross-validation strategies for the SNP nonparametric density estimator, which is a truncation (or sieve) estimator based upon a Hermite series expansion. Our main focus is on the use of SNP density estimators as an adjunct to EMM structural estimation. It is known that for this...

This paper proposes a new nonparametric estimator for general regression functions with multiple regressors. The method used here is motivated by a remarkable result derived by Kolmogorov (1957) and later tightened by Lorentz (1966). In short, they show that any continuous function of multiple...

We examine market volatility across an automated periodic auction mechanism and a continuous automated auction, using data on five futures contracts traded on the GLOBEX trading system. The analysis is supplemented by a comparison of the periodic market with floor trading. Our data permit...

In this paper, we consider expectations of the form E[log(y)|x] = a'log(x) as a good starting point for a more general analysis. We show why this naturally leads to the following flexible functional form E[y|x] = f(h(x)), where all functions are estimated by cubic splines. One of the main goals...

Almost all economic data sets are discretized or rounded to some extent. This paper proposes a regression and a density estimator that work especially well when the data is very discrete. The estimators are a weighted average of the data, and the weights are composed of cubic B-splines. Unlike...

We ask whether foreign equity ownership affects the stability of information signals that are absorbed into prices in an emerging economy. We address both the effect of ownership restrictions exogenously imposed on stock ownership and the impact of introducing or widening foreign ownership...

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...

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...