We investigate autoregressive approximations of multiple frequency I(1) processes, of which I(1) processes are a special class. The underlying data generating process is assumed to allow for an infinite order autoregressive representation where the coefficients of the Wold representation of the...

A fresh interpretaion is provided of the influential finding that the markup of prices over marginal costs is counter-cyclical. Using Rotemberg and Woodford's data set we argue that the markup is best modelled as a variable that is integrated of order one. A consequence of this finding is that...

The estimation of large Vector Autoregressions with stochastic volatility using standard methods is computationally very demanding. In this paper we propose to model conditional volatilities as driven by a single common unobserved factor. This is justified by the observation that the pattern of...

The paper studies large-dimention factor models with nonstationary factors and allows for deterministic trends and factors integrated of order higher then one.We follow the model speci.cation of Bai (2004) and derive the convergence rates and the limiting distributions of estimated factors,...

This paper develops an asymptotic estimation theory for nonlinear autoregressive models with conditionally heteroskedastic errors. We consider a functional coefficient autoregression of order p (AR(p)) with the conditional variance specified as a general nonlinear first order generalized...

We show how to a derive exact distribution-free nonparametric results for minimax risk when underlying random variables have known finite bounds and means are the only parameters of interest. Transform the data with a randomized mean preserving transformation into binary data and then apply the...

In structural vector autoregressive (SVAR) analysis a Markov regime switching (MS) property can be exploited to identify shocks if the reduced form error covariance matrix varies across regimes. Unfortunately, these shocks may not have a meaningful structural economic interpretation. It is...

Many contemporaneously aggregated variables have stochasticaggregation weights. We compare different forecasts for such variables including univariate forecasts of the aggregate, a multivariate forecast of the aggregate that uses information from the disaggregate components, a forecast which...

This paper relies on wavelet multiresolution analysis to capture the dependence structure of currency markets and reveal the complex dynamics across different timescales. It investigates the nature and direction of causal relationships among the most widely traded currencies denoted relative to...

Recent economic developments have shown the importance of spillover and contagion effects in financial markets. Such effects are not limited to relations between the levels of financial variables but also impact on their volatility. I investigate Granger causality in conditional mean and...