Use and misuse of unobserved components in economic forecasting [PDF]
AbstractThe paper deals with unobserved components in economic time series within a general model‐based approach. The component, its final estimator, and the preliminary one (which also includes the forecast) are seen to follow different ARIMA models, which can be expressed in terms of the series innovations.
Agustin Maravall
exaly +4 more sources
Unobserved components in ARCH models: An application to seasonal adjustment [PDF]
The article is a published version of EUI ECO WP; 1994 ...
Gabriele Fiorentini, Agustin Maravall
exaly +5 more sources
Granger-Causality Inference of the Existence of Unobserved Important Components in Network Analysis
Detecting causal interrelationships in multivariate systems, in terms of the Granger-causality concept, is of major interest for applications in many fields. Analyzing all the relevant components of a system is almost impossible, which contrasts with the
Heba Elsegai
doaj +1 more source
Modeling COVID-19 Infection Rates by Regime-Switching Unobserved Components Models
The COVID-19 pandemic is characterized by a recurring sequence of peaks and troughs. This article proposes a regime-switching unobserved components (UC) approach to model the trend of COVID-19 infections as a function of this ebb and flow pattern ...
Paul Haimerl, Tobias Hartl
doaj +1 more source
A simple analytical approach to deal with unobserved feeding in lifetime measurements using a plunger method [PDF]
Determination of lifetime of low-lying states using a plunger method could be a subject of systematic uncertainty if, among else, correction of unobserved feeding is not properly taken into account. In this paper, a simple analytical approach is
Milanović Tamara J. +1 more
doaj +1 more source
On the Automatic Identification of Unobserved Components Models [PDF]
Automatic identi cation of time series models is a necessity once the big data era has come and is staying among us. This has become obvious for many companies and public entities that has passed from a crafted analysis of each individual problem to handle a tsunami of information that has to be processed e ciently, online and in record time ...
Diego J. Pedregal, Juan R. Trapero
openaire +2 more sources
Automatic Identification and Forecasting of Structural Unobserved Components Models with UComp
UComp is a powerful library for building unobserved components models, useful for forecasting and other important operations, such us de-trending, cycle analysis, seasonal adjustment, signal extraction, etc.
Diego J. Pedregal
doaj +1 more source
Remittances in Mexico and their unobserved components [PDF]
The present study aims to determine the common trends and the permanent and transitory components of remittances received by Mexican households. This is done by estimating a small Dynamic Factor Model (DFM), using the approach first proposed by Gonzalo and Granger (1995), determining the number of common trends subject to the cointegration results. The
Corona, Francisco, Orraca, Pedro
openaire +2 more sources
COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models
With the aim of mitigating the damage caused by the coronavirus disease 2019 (COVID-19) pandemic, it is important to use models that allow forecasting possible new infections accurately in order to face the pandemic in specific sociocultural contexts in ...
Sergio Contreras-Espinoza +4 more
doaj +1 more source
A comparative analysis of alternative univariate time series models in forecasting Turkish inflation
This paper analyses inflation forecasting power of artificial neural networks with alternative univariate time series models for Turkey. The forecasting accuracy of the models is compared in terms of both static and dynamic forecasts for the period ...
A. Nazif Çatık, Mehmet Karaçuka
doaj +1 more source

