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The effect of the great moderation on the US business cycle in a time-varying multivariate trend-cycle model

Creal, Drew; Koopman, Siem Jan; Zivot, Eric - 2008

accounts for time variation in macroeconomic volatility, known as the great moderation. In particular, we consider an … volatility processes and mixture distributions for the irregular components and the common cycle disturbances enable us to … that time-varying volatility is only present in the a selection of idiosyncratic components while the coefficients driving …

Persistent link: https://www.econbiz.de/10011376640

Tracking growth and the business cycle : a stochastic common cycle model for the Euro area

Azevedo, João Valle e; Koopman, Siem Jan; Rua, António - 2003

This paper proposes a new model-based method to obtain a coincident indicator for the business cycle. A dynamic factor model with trend components and a common cycle component is considered which can be estimated using standard maximum likelihood methods. The multivariate unobserved components...

Persistent link: https://www.econbiz.de/10011334364

Likelihood-based analysis for dynamic factor models

Jungbacker, Borus; Koopman, Siem Jan - 2008

We present new results for the likelihood-based analysis of the dynamic factor model that possibly includes intercepts and explanatory variables. The latent factors are modelled by stochastic processes. The idiosyncratic disturbances are specified as autoregressive processes with mutually...

Persistent link: https://www.econbiz.de/10011373811

Dynamic factor analysis in the presence of missing data

Jungbacker, Borus; Koopman, Siem Jan; Wel, Michel van der - 2011

This paper concerns estimating parameters in a high-dimensional dynamic factormodel by the method of maximum likelihood. To accommodate missing data in theanalysis, we propose a new model representation for the dynamic factor model. Itallows the Kalman filter and related smoothing methods to...

Persistent link: https://www.econbiz.de/10011377572

Empirical Bayes methods for dynamic factor models

Koopman, Siem Jan; Mesters, Geert - 2014

We consider the dynamic factor model where the loading matrix, the dynamic factors and the disturbances are treated as latent stochastic processes. We present empirical Bayes methods that enable the efficient shrinkage-based estimation of the loadings and the factors. We show that our estimates...

Persistent link: https://www.econbiz.de/10010357912

Analyzing the term structure of interest rates using the dynamic Nelson-Siegel model with time-varying parameters

Koopman, Siem Jan; Mallee, Max I. P.; Wel, Michel van der - 2007

factor. Second, we specify the overall volatility as a generalized autoregressive conditional heteroscedasticity (GARCH …

Persistent link: https://www.econbiz.de/10011373825

Intraday stock price dependence using dynamic discrete copula distributions

Koopman, Siem Jan; Lit, Rutger; Lucas, André - 2015

Persistent link: https://www.econbiz.de/10010494787

Model-based measurement of latent risk in time series with applications

Bijleveld, Frits; Commandeur, Jacques Jean François; … - 2005

Risk is at the center of many policy decisions in companies, governments and other institutions. The risk of road fatalities concerns local governments in planning counter- measures, the risk and severity of counterparty default concerns bank risk managers on a daily basis and the risk of...

Persistent link: https://www.econbiz.de/10011348356

Measuring asymmetric stochastic cycle components in US macroeconomic time series

Koopman, Siem Jan; Lee, Kai Ming - 2005

To gain insights in the current status of the economy, macroeconomic time series are often decomposed into trend, cycle and irregular components. This can be done by nonparametric band-pass filtering methods in the frequency domain or by model-based decompositions based on autoregressive moving...

Persistent link: https://www.econbiz.de/10011346480

Model-based business cycle and financial cycle decomposition for Europe and the U.S.

Koopman, Siem Jan; Lit, Rutger; Lucas, André - 2016

We develop a multivariate unobserved components model to extract business cycle and financial cycle indicators from a panel of economic and financial time series of four large developed economies. Our model is flexible and allows for the inclusion of cycle components in different selections of...

Persistent link: https://www.econbiz.de/10011520505

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