We analyze the relationship between website visits, magazine demand and the demand for advertising pages using Granger non-causality tests on the basis of an extensive and externally audited quarterly data set for the German magazine market spanning the period I/1998 to II/2004. We use traditional panel data estimators and an estimator suitable for heterogeneity across magazines. We find very r...

The few existing empirical studies of U.S.-Japan trade agreements have relied primarily on descriptive statistics or univariate time series methods. We conduct a more powerful test by evaluating agreements in the context of well-specified econometric models. Consistent with trade theory, import demand is modeled as a cointegrating relationship with income and relative price variables, where a t...

Synthetic peptides patterned on the amino acid sequences found in two exofacial regions of band 3 protein (residues 824-829 of loop 7 and residues 547-553 of loop 3) blocked, in a dose-dependent fashion, the in vitro adherence of Plasmodium falciparum-infected erythrocytes to C32 amelanotic melanoma cells. Intravenous infusion of these synthetic peptides into Aotus and Saimiri monkeys infected ...

We derive a de nition of linear cointegration for nonlinear stochastic processes using a martingale representation theorem. The result shows that stationary linear cointegrations can exhibit nonlinear dynamics, in contrast with the normal assumption of linearity. We propose a sequential nonparametric method to test rst for cointegration and second for nonlinear dynamics in the cointegrated syst...

This paper introduces quasi-maximum likelihood estimator for multivariate diffusions based on discrete observations. A numerical solution to the stochastic differential equation is obtained by higher order Wagner-Platen approximation and it is used to derive the first two conditional moments. Monte Carlo simulation shows that the proposed method has good finite sample property for both normal a...

In empirical work on multivariate financial time series, it is common to postulate a Multivariate GARCH model. We show that the popular Gaussian quasi-maximum likelihood estimator of MGARCH models is very sensitive to outliers in the data. We propose to use robust M-estimators and provide asymptotic theory for M-estimators of MGARCH models. The Monte Carlo study and empirical application docume...

We propose a new methodology for designing flexible proposal densities for the joint posterior density of parameters and states in a nonlinear, non-Gaussian state space model. We show that a highly efficient Bayesian procedure emerges when these proposal densities are used in an independent Metropolis-Hastings algorithm or in importance sampling. Our method provides a computationally more effic...

In this paper we consider the dynamics of spot and futures prices in the presence of arbitrage. We propose a partially linear error correction model where the adjustment coefficient is allowed to depend non-linearly on the lagged price difference. We estimate our model using data on the DAX index and the DAX futures contract. We find that the adjustment is indeed nonlinear. The linear alternati...

The paper develops a new and easy-to-use F test in a time series GMM framework that allows for general forms of serial dependence. The test is based on the Wald statistic with a multiplicative correction factor and employs critical values from a standard F distribution. The F critical values are high-order correct under the conventional asymptotics. Monte Carlo simulations show that the F test ...