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Modeling Trigonometric Seasonal Components for Monthly Economic Time Series

Hindrayanto, Irma; Aston, John A.D.; Koopman, Siem Jan; … - Tinbergen Instituut - 2010

This discussion paper led to an article in Applied Economics (2013). Vol. 45, pages 3024-3034. The basic structural time series model has been designed for the modelling and forecasting of seasonal economic time series. In this paper we explore a generalisation of the basic structural time...

Persistent link: https://www.econbiz.de/10011255517

Testing for Parameter Instability in Competing Modeling Frameworks

Calvori, Francesco; Creal, Drew; Koopman, Siem Jan; … - Tinbergen Instituut - 2014

We develop a new parameter stability test against the alternative of observation driven generalized autoregressive score dynamics. The new test generalizes the ARCH-LM test of Engle (1982) to settings beyond time-varying volatility and exploits any autocorrelation in the likelihood scores under...

Persistent link: https://www.econbiz.de/10011255854

Modeling Trigonometric Seasonal Components for Monthly Economic Time Series

Hindrayanto, Irma; Aston, John A.D.; Koopman, Siem Jan; … - Tinbergen Institute - 2010

The basic structural time series model has been designed for the modelling and forecasting of seasonal economic time series. In this paper we explore a generalisation of the basic structural time series model in which the time-varying trigonometric terms associated with different seasonal...

Persistent link: https://www.econbiz.de/10008838551

Model-Based Measurement of Latent Risk in Time Series with Applications

Bijleveld, Frits - 2006

we introduce a general multivariate framework for the time series analysis of risk that is modeled as a latent process … present a general model for the analysis of risk and discuss its statistical treatment based on linear state space methods … the general methodology can be effectively used in the assessment of risk …

Persistent link: https://www.econbiz.de/10012734846

A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk

Koopman, Siem Jan - 2005

decomposed into a systematic and firm-specific risk component, where the systematic component reflects the general economic …

Persistent link: https://www.econbiz.de/10012736328

Analyzing the Term Structure of Interest Rates Using the Dynamic Nelson-Siegel Model with Time-Varying Parameters

Koopman, Siem Jan - 2011

In this paper we introduce time-varying parameters in the dynamic Nelson-Siegel yield curve model for the simultaneous analysis and forecasting of interest rates of different maturities, known as the term structure. The Nelson-Siegel model has been recently reformulated as a dynamic factor model...

Persistent link: https://www.econbiz.de/10012714319

Economic Trends and Cycles in Crime: A Study for England and Wales

Vujic, Suncica; Koopman, Siem Jan; Commandeur, Jacques J. F. - In: Journal of Economics and Statistics (Jahrbuecher fuer … 232 (2012) 6, pp. 652-677

This paper models cyclical behaviour in property crime series (burglary and theft) in relation to the macroeconomic activity indicators in England andWales in the period from 1955 to 2001. Using unobserved components (UC) time series models, univariate time series analysis suggests that recorded...

Persistent link: https://www.econbiz.de/10010907921

Measuring Synchronisation and Convergence of Business Cycles

Koopman, Siem Jan; Azevedo, Joao Valle e - Tinbergen Instituut - 2003

This discussion paper resulted in an article in the Oxford Bulletin of Economics and Statistics (2008). Vol. 70 issue 1, pages 23-51. This paper investigates business cycle relations among different economies in theEuro area. Cyclical dynamics are explicitly modelled as part of a time series...

Persistent link: https://www.econbiz.de/10011255482

On Importance Sampling for State Space Models

Jungbacker, Borus; Koopman, Siem Jan - Tinbergen Instituut - 2005

We consider likelihood inference and state estimation by means of importance sampling for state space models with a nonlinear non-Gaussian observation y ~ p(y|alpha) and a linear Gaussian state alpha ~ p(alpha). The importance density is chosen to be the Laplace approximation of the smoothing...

Persistent link: https://www.econbiz.de/10011255603

A General Framework for Observation Driven Time-Varying Parameter Models

Creal, Drew; Koopman, Siem Jan; Lucas, André - Tinbergen Instituut - 2008

We propose a new class of observation driven time series models referred to as Generalized Autoregressive Score (GAS) models. The driving mechanism of the GAS model is the scaled score of the likelihood function. This approach provides a unified and consistent framework for introducing...

Persistent link: https://www.econbiz.de/10011255643