This paper considers Lagrange Multiplier (LM) and Likelihood Ratio (LR) tests for determining the cointegrating rank of a vector autoregressive system. n order to deal with outliers and possible fat-tailedness of the error process, non-Gaussian likelihoods are used to carry out the estimation....

Regime-switching models, like the smooth transition autoregressive (STAR) model, are typically applied to time series of moderate length. Hence, the nonlinear features that these models intend to describe may be reflected in only a few observations. Conversely, neglected outliers in a linear...

Standard unit-root and cointegration tests are sensitive to atypical events such as outliers and structural breaks. In this article, the authors use outlier-robust estimation techniques to examine the impact of these events on cointegration analysis. Their outlier-robust cointegration test...

Using a limiting approach to portfolio credit risk, we obtain analytic expressions for the tail behavior of credit losses. To capture the co-movements in defaults over time, we assume that defaults are triggered by a general, possibly non-linear, factor model involving both systematic and...

We propose a new Markov switching model with time varying probabilities for the transitions. The novelty of our model is that the transition probabilities evolve over time by means of an observation driven model. The innovation of the time varying probability is generated by the score of the...

We propose a novel empirical framework to assess the likelihood of joint and conditional failure for Euro area sovereigns. Our model is based on a dynamic skewed-t copulawhich captures all the salient features of the data, including skewed and heavy-tailed changes in the price of CDS protection...

This discussion paper resulted in a publication in the <I>Journal of Econometrics</I> (2004). Volume 119, p. 45.<P> We study the optimal choice of quasi-likelihoods for nearly integrated,possibly non-normal, autoregressive models. It turns out that the two mostnatural candidate criteria, minimum Mean...</p></i>

Accepted for an article forthcoming in the <I>Review of Economics and Statics</I>. Volume 97, 2015.<P> We study whether and when parameter-driven time-varying parameter models lead to forecasting gains over observation-driven models. We consider dynamic count, intensity, duration, volatility and copula...</p></i>

We study the strong consistency and asymptotic normality of the maximum likelihood estimator for a class of time series models driven by the score function of the predictive likelihood. This class of nonlinear dynamic models includes both new and existing observation driven time series models....

A macro-prudential policy maker can manage risks to financial stability only if currentand future risks can be reliably assessed. We propose a novel framework to assessfinancial system risk. Using a dynamic factor framework based on state-space methods, we model latent macro-financial and credit...