The paper is concerned with a class of trend cycle filters, encompassing popular ones, such as the Hodrick-Prescott filter, that are derived using the Wiener-Kolmogorov signal extraction theory under maintained models that prove unrealistic in applied time series analysis. As the maintained...

The paper estimates an index of coincident economic indicators for the U.S. economy using time series with different frequencies of observation (monthly and quarterly, possibly with missing values). The model considered is the dynamic factor model proposed by Stock and Watson, specified in the...

We analyse the evolution of the business cycle in the accession countries, after a careful examination of the seasonal properties of the available series and the required modification of the cycle dating procedures. We then focus on the degree of cyclical concordance within the group of...

The article proposes an iterative algorithm for the estimation of fixed and random effects of a nonlinearly aggregated mixed model. The latter arises when an additive Gaussian model is formulated at the disaggregate level on a nonlinear transformation of the responses, but information is...

The paper illustrates and compares estimation methods alternative to maximum likelihood, among which multistep estimation and leave-one-out cross-validation, for the purposes of signal extraction, and in particular the separation of the trend from the cycle in economic time series, and...

The paper documents and illustrates state space methods that implement time series disaggregation by regression methods, with dynamics that depend on a single autoregressive parameter. The most popular techniques for the distribution of economic flow variables, such as Chow-Lin, Fernandez and...

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...