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Possibly ill-behaved posteriors in econometric models
Hoogerheide, Lennart; Dijk, Herman K. van - 2008
Highly non-elliptical posterior distributions may occur in several econometric models, in particular, when the likelihood information is allowed to dominate and data information is weak. We explain the issue of highly non-elliptical posteriors in a model for the effect of education on income...
Persistent link: https://www.econbiz.de/10011374406
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Expected utility and catastrophic risk
Ikefuji, Masako; Laeven, Roger; Magnus, Jan R.; Muris, Chris - 2014
An expected utility based cost-benefit analysis is in general fragile to its distributional assumptions. We derive … necessary and sufficient conditions on the utility function of the expected utility model to avoid this. The conditions ensure … that expected (marginal) utility remains finite also under heavy-tailed distributional assumptions. Our results are context …
Persistent link: https://www.econbiz.de/10010412466
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The degree measure as utility function over positions in networks
Brink, René van den; Rusinowska, Agnieszka - 2017
In this paper, we connect the social network theory on centrality measures to the economic theory of preferences and … utility. Using the fact that networks form a special class of cooperative TU-games, we provide a foundation for the degree … measure as a von Neumann-Morgenstern expected utility function reflecting preferences over being in different positions in …
Persistent link: https://www.econbiz.de/10011688772
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Unobserved components with stochastic volatility in U.S. inflation : estimation and signal extraction
Li, Mengheng; Koopman, Siem Jan - 2018
We consider unobserved components time series models where the components are stochastically evolving over time and are subject to stochastic volatility. It enables the disentanglement of dynamic structures in both the mean and the variance of the observed time series. We develop a simulated...
Persistent link: https://www.econbiz.de/10011809984
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Estimating systematic continuous-time trends in recidivism using a non-Gaussian panel data model
Koopman, Siem Jan; Lucas, André; Ooms, Marius; … - 2007
We model panel data of crime careers of juveniles from a Dutch Judicial Juvenile Institution. The data are decomposed into a systematic and an individual-specific component, of which the systematic component reflects the general time-varying conditions including the criminological climate....
Persistent link: https://www.econbiz.de/10011372520
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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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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
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Inference for adaptive time series models : stochastic volatility and conditionally Gaussian state space form
Bos, Charles S.; Shephard, Neil G. - 2004
In this paper we replace the Gaussian errors in the standard Gaussian, linear state space model with stochastic volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algorithms for this type of model are ineffective, but that this problem can be removed by...
Persistent link: https://www.econbiz.de/10011334849
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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