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...

We discuss here a method for identifying relationships between high-frequency and lowfrequency data based on a dynamic regression technique. This allows users to estimate a quarterly analogue to an underlying monthly regression equation. The resulting equation which may be non-linear in 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, Fernandez and...

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...

This paper proposes a reduced rank regression framework for constructing coincident and leading indexes. Based on a formal definition that requires that the first differences of the leading index are the best linear predictor of the first differences of the coincident index, it is shown that the...