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~isPartOf:"Discussion paper / Tinbergen Institute"
~isPartOf:"Discussion paper series / UCL Economics"
~isPartOf:"Estudos e documentos de trabalho"
~language:"eng"
~person:"Florax, Raymond J. G. M."
~person:"Gil-Alaña, Luis A."
~person:"Heckman, James J."
~person:"Koopman, Siem Jan"
~subject:"Kreditrisiko"
~subject:"Maximum-Likelihood-Schätzung"
~subject:"Meta-Analyse"
~subject:"Schätzung"
~subject:"USA"
~subject:"United States"
~subject:"Volatilität"
~type:"book"
~type_genre:"Collection of articles written by one author"
~type_genre:"Handbuch"
~type_genre:"Non-commercial literature"
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Florax, Raymond J. G. M.
Gil-Alaña, Luis A.
Heckman, James J.
Koopman, Siem Jan
Lucas, André
39
McAleer, Michael
18
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11
A general framework for observation driven time-varying parameter models
Creal, Drew
;
Koopman, Siem Jan
;
Lucas, André
-
2008
Persistent link: https://www.econbiz.de/10003787160
Saved in:
12
Likelihood functions for state space models with diffuse initial conditions
Francke, Marc K.
;
Koopman, Siem Jan
;
Vos, Aart F. de
-
2008
Persistent link: https://www.econbiz.de/10003706020
Saved in:
13
Dynamic factor analysis in the presence of missing data
Jungbacker, Borus
;
Koopman, Siem Jan
;
Wel, Michel van der
-
2009
Persistent link: https://www.econbiz.de/10003813787
Saved in:
14
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
Saved in:
15
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:
16
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
Saved in:
17
Macro, industry and frailty effects in defaults : the 2008 credit crisis in perspective
Koopman, Siem Jan
;
Lucas, André
;
Schwaab, Bernd
-
2010
We determine the magnitude and nature of systematic default risk using 1971{2009) default data from Moody's. We disentangle systematic risk factors due to business cycle effects, common default dynamics (frailty), and industry-specific dynamics (including contagion). To quantify the contribution...
Persistent link: https://www.econbiz.de/10011379607
Saved in:
18
A dynamic multivariate heavy-tailed model for time-varying volatilities and correlations
Creal, Drew
;
Koopman, Siem Jan
;
Lucas, André
-
2010
We propose a new class of observation-driven time-varying parameter models for dynamic volatilities and correlations to handle time series from heavy-tailed distributions. The model adopts generalized autoregressive score dynamics to obtain a time-varying covariance matrix of the multivariate...
Persistent link: https://www.econbiz.de/10011380135
Saved in:
19
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:
20
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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