Government statistical agencies are required to seasonally adjust non-stationary time series resulting from an aggregate of a number of cross-sectional time series. Traditionally, this has been achieved using the X-11 or X12-ARIMA process by us- ing either direct or indirect seasonal adjustment....

Both temporal disaggregation techniques and bridge models are tools to analyse the GDP dynamics in the very short run (the current quarter), though their methodological approaches differ on how to exploit the available monthly information. The aim of this paper is to propose a way to merge the...

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, Fern´andez and...

This work presents a comparison of different techniques for disaggregating annual flow time series by a quarterly related indicator, based on a Monte Carlo experiment. A first goal of the study is related to the estimation of the autoregressive parameter implied by the solution proposed by Chow...

Discrete values of flow variables can be regarded as the integrals of unobserved flow functions. The estimated flows are defined as the product of two functions. One is predetermined and selected to eliminate or reduce trend in mean and variance. The other is approximately stationary, selected...

The paper discusses the main issues arising in the construction of quarterly national accounts estimates, adjusted for seasonality and calendar effects, obtained by disaggregating the original annual actual measurements using related monthly indicators. It proposes and implements an approach...

In this paper we present a program designed to perform temporal disaggregation of economic time series using a variety of techniques: univariate methods without indicators (Boot-Feibes-Lisman, Stram-Wei), univariate methods with indicators (Denton, Chow-Lin, Fernandez, Litterman, Santos-Cardoso,...