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~isPartOf:"Discussion paper / Tinbergen Institute"
~isPartOf:"Discussion paper series / UCL Economics"
~language:"eng"
~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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Gil-Alaña, Luis A.
Heckman, James J.
Klaassen, Franc
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21
Spillover dynamics for systemic risk measurement using spatial financial time series models
Blasques, Francisco
;
Koopman, Siem Jan
;
Lucas, André
; …
-
2014
We introduce a new model for time-varying spatial dependence. The model extends the well-known static spatial lag model. All parameters can be estimated conveniently by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimator for the...
Persistent link: https://www.econbiz.de/10010391531
Saved in:
22
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
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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
Observation driven mixed-measurement dynamic factor models with an application to credit risk
Creal, Drew
;
Schwaab, Bernd
;
Koopman, Siem Jan
;
Lucas, …
-
2011
This paper has been accepted for publication in the 'Review of Economics and Statistics'.We propose a dynamic factor model for mixed-measurement and mixed-frequency panel data. In this framework time series observations may come from a range of families of parametric distributions, may be...
Persistent link: https://www.econbiz.de/10011383248
Saved in:
25
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:
26
The stochastic volatility on mean model : empirical evidence from international stock markets
Koopman, Siem Jan
;
Uspensky, Eugenie Hol
-
2000
Persistent link: https://www.econbiz.de/10001472890
Saved in:
27
Business and default cycles for credit risk
Koopman, Siem Jan
;
Lucas, André
-
2003
Persistent link: https://www.econbiz.de/10001792714
Saved in:
28
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
Persistent link: https://www.econbiz.de/10001792789
Saved in:
29
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:
30
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
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