The problem of dating the business cycle has recently received many contributions, with a lot of proposed statistical methodologies, parametric and non parametric. Despite of this, only a few countries produce an official dating of the business cycle. In this work we try to apply some procedures...

In this paper we propose a simple model to forecast industrial production in Italy. We show that the forecasts produced using the model outperform some popular forecasts as well as those stemming from a trading days- and outlier-robust ARIMA model used as a benchmark. We show that the use of...

A widely used filter to extract a signal in a time series, in particular in the business cycle analysis, is the Hodrick-Prescott filter. The model that underlies the filter considers the data series as the sum of two unobserved component (signal and non signal) and a smoothing parameter which...

The extraction of a common signal from a group of time series is generally obtained using variables recorded with the same frequency or transformed to have the same frequency (monthly, quarterly, etc.). The statistical literature has not paid a great deal of attention to this topic. In this...

In many real phenomena the behaviour of a certain variable, subjected to different regimes, depends on the state of other variables or the same variable observed in other subjects, so the knowledge of the state of the latter could be important to forecast the state of the former. In this paper a...

The financial time series are often characterized by similar volatility structures. The selection of series having a similar behavior could be important for the analysis of the transmission mechanisms of volatility and to forecast the time series, using the series with more similar structure. In...

The aims of this paper are estimate and forecast the Non-Accelerating Inflation Rate of Unemployment, or NAIRU, for Brazilian unemployment time series data. In doing so, we introduce a methodology for estimating mixed additive seasonal autoregressive (MASAR) models, by the Generalized Method of...

We consider the situation when there is a large number of series, $N$, each with $T$ observations, and each series has some predictive ability for the variable of interest, $y$. A methodology of growing interest is to first estimate common factors from the panel of data by the method of...

We examine the ability of the simple linear-quadratic model under rational expectations to explain dynamic behaviour of aggregate Canadian imports. In contrast to authors of previous studies who examine dynamic behaviour using the LQ model, we estimate the structural parameters using the Euler...

The use of subspace algorithms for the identification of non-stationary cointegrated stochastic systems is a promising technique that is currently under discussion. A revision of the literature provides two distinct algorithms: State Space Aoki Time Series (SSATS) identification algorithm (Aoki...