An MLE of the unknown parameters of co integrating vectors is presented for systems in which some variables exhibit higher orders of integration, in which there might be deterministic components, and in which the co integrating vector itself might involve variables of differing orders of...

Do studies of time use interfere too much in the lives of the subjects? As a result are those who agree to participate a biased sample of the population? We examine the characteristics of the Experience Sampling Method (ESM) adolescent sample from the Alfred P. Sloan Study of Youth and Social...

Because of non-normality of stock returns nonparametric rank tests are gaining incremental popularity over parametric tests in financial economics event studies. In rank tests financial assets' multiple day cumulative abnormal returns (CARs) are replaced by cumulated ranks. This paper proposes...

We consider extreme value analysis in a semi-supervised setting, where we observe, next to the n data on the target variable, n +m data on one or more covariates. This is called the semi-supervised model with n labeled and m unlabeled data. By exploiting the tail dependence between the target...

We develop a uniform test for detecting and dating the integrated or mildly explosive behaviour of a strictly stationary generalized autoregressive conditional heteroskedasticity (GARCH) process. Namely, we test the null hypothesis of a globally stable GARCH process with constant parameters...

We provide a framework for evaluating and improving multivariate density forecasts. Among other things, the multivariate framework lets us evaluate the adequacy of density forecasts involving cross-variable interactions, such as time-varying conditional correlations. We also provide conditions...

We consider the implications of a specific alternative to the classical measurement error model, in which the data are optimal predictions based on some information set. One motivation for this model is that if respondents are aware of their ignorance they may interpret the question what is the...

The linear Gaussian state space model, also known as dynamic linear model in the Bayesian literature, has become one of the standard parametric modeling forms with parameters changing over time in the time series analysis. It provides a unified and flexible framework for describing, modeling and...

Meijer, Rohwedder, and Wansbeek (MRW, Journal of Business & Economic Statistics, 2012) develop methods for prediction of a single earnings figure per worker from mixture factor models fitted using earnings data from multiple linked data sources. MRW apply their method using parameter estimates...