The importance of consumer confidence in stimulating economic activity is a disputed issue in macroeconomics. Do changes in confidence represent autonomous fluctuations in optimism, independent of information on economic fundamentals, or are they a reflection of economic news? I study this question by using high-frequency microdata on spending and consumer confidence, and I find that consumer c...

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...

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...

Often we are interested in the largest root of an autoregressive process. Available methods rely on inverting t-tests to obtain confidence intervals. However, for large autoregressive roots, t-tests do not approximate asymptotically uniformly most powerful tests and do not have optimality properties when inverted for confidence intervals. We exploit the relationship between the power of tests a...

Using a time series framework, the paper studies the interactions of the annual real per capita GDP data of the G7 countries. We find evidence of six common nonstationary processes behind the international output dynamics. In addition, there is evidence for the existence of a common business cycle among these countries. The trend and cycle components of each output series are obtained with a pr...

Recently, there has been a renewed interest in modeling economic time series by vector autoregressive moving-average models. However, this class of models has been unpopular in practice because of estimation problems and the complexity of the identification stage. These disadvantages could have led to the dominant use of vector autoregressive models in macroeconomic research. In this paper, sev...

This paper concerns the effects of macroeconomic announcements on the covariance structure of US government bond returns for six different maturities; the study shows that the conditional variances, covariances, and correlation coefficients are significantly greater on announcement days. On non-announcement days, the correlation coefficients are relatively large and are greater the closer the b...