In order to assess the current stage of the business cycle at which the economy stands, real
time trend-cycle estimates are needed. The basic approach is that of assessing the real time …

Eric Ghysels and Denise R. Osborn provide a thorough and timely review of the recent
developments in the econometric analysis of seasonal economic time series, summarizing a …

TRAMO (" Time Series Regression with ARlMA Noise, Missing Observations, and Outliers")
is a program written in Fortran for mainframes and pes under MS-Dos. The program …

This article presents a new exact solution for the initialization of the Kalman filter for state
space models with diffuse initial conditions. For example, the regression model with …

lengths, that could not be captured with univariate linear filters. Exam ples of research in
both directions can be found in Sims (1977), Lahiri and Moore (1991), Stock and Watson …

Seasonal adjustment has a long and well-documented tradition; see, for example, Nerlove,
Grether and Carvalho (1979), Zellner (1978), Moore et al (1981), Den Butter and Fase …

This survey provides an overview with a broad coverage of the literature on methods for
temporal disaggregation and benchmarking. Dozens of methods, procedures and …

Optimal estimation of missing values in ARMA models is typically performed by using the
Kalman filter for likelihood evaluation,'skipping'in the computations the missing …

Forest transition (FT) has taken place in many developing countries in recent decades.
Analysis of developing countries FT is mostly based on case studies and exploring a limited …

A new clustering method for time series is proposed, based on the full probability density of
the forecasts. First, a resampling method combined with a nonparametric kernel estimator …