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~isPartOf:"Arbeitspapier / Institut für Volkswirtschaftslehre, Sozial- und Wirtschaftswissenschaftliche Fakultät, Johannes-Kepler-Universität, Linz,"
~isPartOf:"Boston College working papers in economics"
~isPartOf:"Cege discussion paper"
~isPartOf:"Discussion paper / Humboldt-Universität zu Berlin, Sonderforschungsbereich 373 Quantifikation und Simulation Ökonomischer Prozesse"
~isPartOf:"Discussion paper / Statistics Netherlands"
~isPartOf:"Discussion paper / Tinbergen Institute"
~isPartOf:"Discussion papers of interdisciplinary research project 373"
~isPartOf:"Working papers / Federal Reserve Bank of Boston"
~language:"eng"
~person:"Basu, Susanto"
~person:"Blasques, Francisco"
~person:"Daníelsson, Jón"
~person:"Dreher, Axel"
~person:"Gil-Alaña, Luis A."
~person:"Heckman, James J."
~person:"Herwartz, Helmut"
~person:"Koopman, Siem Jan"
~person:"Laan, Gerard van der"
~person:"Nijkamp, Peter"
~person:"Rietveld, Piet"
~person:"Weder, Mark"
~person:"Wijnbergen, Sweder van"
~subject:"EU-Staaten"
~subject:"Konjunktur"
~subject:"Konjunkturtheorie"
~subject:"Schätzung"
~subject:"State space model"
~subject:"USA"
~subject:"Welt"
~type_genre:"Collection of articles written by one author"
~type_genre:"Handbuch"
~type_genre:"Non-commercial literature"
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91
Low frequency and weighted likelihood solutions for mixed frequency dynamic factor models
Blasques, Francisco
;
Koopman, Siem Jan
;
Mallee, Max I. P.
-
2014
The multivariate analysis of a panel of economic and financial time series with mixed frequencies is a challenging problem. The standard solution is to analyze the mix of monthly and quarterly time series jointly by means of a multivariate dynamic model with a monthly time index: artificial...
Persistent link: https://www.econbiz.de/10010391543
Saved in:
92
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:
93
Models with time-varying mean and variance : a robust analysis of US industrial production
Bos, Charles S.
;
Koopman, Siem Jan
-
2010
Many seasonal macroeconomic time series are subject to changes in their means and variances over a long time horizon. In this paper we propose a general treatment for the modelling of time-varying features in economic time series. We show that time series models with mean and variance functions...
Persistent link: https://www.econbiz.de/10011379641
Saved in:
94
Modeling trigonometric seasonal components for monthly economic time series
Hindrayanto, Irma
;
Aston, John A.D.
;
Koopman, Siem Jan
; …
-
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/10011379642
Saved in:
95
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:
96
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:
97
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:
98
Network industries, economic stability and spatial integration
Button, Kenneth John
;
Nijkamp, Peter
-
1997
The evidence on the implications of transport for regionaleconomic and political integration is mixed. This is not surprisingsince transport is one element of a complex web of factors thatdetermine the extent to which spatial areas become integrated.There are also good reasons to expect the...
Persistent link: https://www.econbiz.de/10010336865
Saved in:
99
Innovation dynamics in space : local actors and local factors
Kangasharju, Aki
;
Nijkamp, Peter
-
1997
This paper addresses the issue of technogenesis and its geographical pattern. It aims to offer both a general analysis framework and a test on innovation data from several European cities. This framework is mainly built on the product life-cycle and the incubation approach. On the basis of this...
Persistent link: https://www.econbiz.de/10010337320
Saved in:
100
Multivariate volatility analysis of VW stock prices
Herwartz, Helmut
;
Lütkepohl, Helmut
-
1998
Persistent link: https://www.econbiz.de/10000992357
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