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~isPartOf:"Discussion paper / Tinbergen Institute"
~language:"eng"
~person:"Butter, Frank A. G. den"
~person:"Gil-Alaña, Luis A."
~person:"Heckman, James J."
~person:"Klaassen, Franc"
~person:"Koopman, Siem Jan"
~subject:"Kreditrisiko"
~subject:"Maximum-Likelihood-Schätzung"
~subject:"Schätzung"
~subject:"USA"
~subject:"United States"
~type:"book"
~type_genre:"Collection of articles written by one author"
~type_genre:"Handbuch"
~type_genre:"Non-commercial literature"
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Butter, Frank A. G. den
Gil-Alaña, Luis A.
Heckman, James J.
Klaassen, Franc
Koopman, Siem Jan
Lucas, André
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21
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
Saved in:
22
The stochastic volatility in mean model
Koopman, Siem Jan
;
Hol Uspensky, Eugenie
-
2000
In this paper we present an exact maximum likelihood treatment forthe estimation of a Stochastic Volatility in Mean(SVM) model based on Monte Carlo simulation methods. The SVM modelincorporates the unobserved volatility as anexplanatory variable in the mean equation. The same extension...
Persistent link: https://www.econbiz.de/10011303314
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23
Systemic risk diagnostics
Schwaab, Bernd
;
Lucas, André
;
Koopman, Siem Jan
-
2010
, and the rest of the
world
. Controlling for global,region-specific, and industry effects, we construct coincident measures …
Persistent link: https://www.econbiz.de/10011382067
Saved in:
24
Numerically accelerated importance sampling for nonlinear non-Gaussian state space models
Koopman, Siem Jan
;
Lucas, André
;
Scharth, Marcel
-
2012
We introduce a new efficient importance sampler for nonlinear non-Gaussian state space models. We propose a general and efficient likelihood evaluation method for this class of models via the combination of numerical and Monte Carlo integration methods. Our methodology explores the idea that...
Persistent link: https://www.econbiz.de/10011386179
Saved in:
25
Forecasting the US term structure of interest rates using a macroeconomic smooth dynamic factor model
Koopman, Siem Jan
;
Wel, Michel van der
-
2011
We extend the class of dynamic factor yield curve models for the inclusion of macro-economic factors. We benefit from recent developments in the dynamic factor literature for extracting the common factors from a large panel of macroeconomic series and for estimating the parameters in the model....
Persistent link: https://www.econbiz.de/10011386428
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26
Periodic unobserved cycles in seasonal time series with an application to US unemployment
Koopman, Siem Jan
;
Ooms, Marius
;
Hindrayanto, Irma
-
2006
This paper discusses identification, specification, estimation and forecasting for a general class of periodic unobserved components time series models with stochastic trend, seasonal and cycle components. Convenient state space formulations are introduced for exact maximum likelihood...
Persistent link: https://www.econbiz.de/10011350384
Saved in:
27
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
Saved in:
28
Long memory modelling of inflation with stochastic variance and structural breaks
Bos, Charles S.
;
Koopman, Siem Jan
;
Ooms, Marius
-
2007
We investigate changes in the time series characteristics of postwar U.S. inflation. In a model-based analysis the conditional mean of inflation is specified by a long memory autoregressive fractionally integrated moving average process and the conditional variance is modelled by a stochastic...
Persistent link: https://www.econbiz.de/10011373822
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29
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
In this paper we investigate whether the dynamic properties of the U.S. business cycle have changed in the last fifty years. For this purpose we develop a flexible business cycle indicator that is constructed from a moderate set of macroeconomic time series. The coincident economic indicator is...
Persistent link: https://www.econbiz.de/10011376640
Saved in:
30
Stock index volatility forecasting with high frequency data
Hol Uspensky, Eugenie
;
Koopman, Siem Jan
-
2002
The increasing availability of financial market data at intraday frequencies has not only led to the development of improved ex-post volatility measurements but has also inspired research into their potential value as an informa-tion source for longer horizon volatility forecasts. In this paper...
Persistent link: https://www.econbiz.de/10011326944
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