Macroeconomic forecasts are frequently produced, widely published, intensively discussed and comprehensively used. The formal evaluation of such forecasts has a long research history. Recently, a new angle to the evaluation of forecasts has been addressed, and in this review we analyse some...

This paper estimates a long memory volatility model for 16 agricultural commodity futures returns from different futures markets, namely corn, oats, soybeans, soybean meal, soybean oil, wheat, live cattle, cattle feeder, pork, cocoa, coffee, cotton, orange juice, Kansas City wheat, rubber, and...

Macroeconomic forecasts are frequently produced, widely published, intensively discussed and comprehensively used. The formal evaluation of such forecasts has a long research history. Recently, a new angle to the evaluation of forecasts has been addressed, and in this review we analyse some...

Most multivariate variance or volatility models suffer from a common problem, the “curse of dimensionality”. For this reason, most are fitted under strong parametric restrictions that reduce the interpretation and flexibility of the models. Recently, the literature has focused on...

We propose a new procedure to detect unit roots based on subspace methods. It has three main original features. First, the same method can be applied to single or multiple time series. Second, it employs a flexible family of information criteria, which loss functions can be adapted to the...

In this paper we estimate the business telecommunications demands for local, intra-LATA and inter-LATA services, using US data from a Bill Harvesting R survey carried out during 1997. We model heterogeneity, which is present among firms due to a variety of different business telecommunication...

Peru is a South American country that is divided into two parts by the Andes Mountains. The rich historical, cultural and geographic diversity has led to the inclusion of ten Peruvian sites on UNESCO’s World Heritage List. For the potential negative impacts of mass tourism on the environment,...

Computing the gaussian likelihood for a nonstationary state-space model is a difficult problem which has been tackled by the literature using two main strategies: data transformation and diffuse likelihood. The data transformation approach is cumbersome, as it requires nonstandard filtering. On...

There has recently been growing interest in modeling and estimating alternative continuous time multivariate stochastic volatility models. We propose a continuous time fractionally integrated Wishart stochastic volatility (FIWSV) process. We derive the conditional Laplace transform of the FIWSV...

The paper proposes a general asymmetric multifactor Wishart stochastic volatility (AMWSV) diusion process which accommodates leverage, feedback efects and multifactor for the covariance process. The paper gives the closed-form solution for the conditional and unconditional Laplace transform of...