Showing 1 - 10 of 88
Publication in the 'Journal of Business & Economic Statistics' forthcoming.<A> 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...</a>
Persistent link: https://www.econbiz.de/10011255569
In this paper, we make use of state space models toinvestigate the presence of stochastic trends in economic time series. Amodel is specified where such a trend can enter either in the autoregressiverepresentation or in a separate state equation. Tests based on the formerare analogous to...
Persistent link: https://www.econbiz.de/10011255619
This discussion paper resulted in a publication IN the <a HREF="http://people.few.eur.nl/hkvandijk/PDF/Koop_and_Van_Dijk_2000_JoE_testing_for_integration.pdf">'Journal of Econometrics'</a>, 2000, 97(2), 261-291.<p> In this paper, we make use of state space models to investigate the presence of stochastic trends in economic time series. A model is specified where such a trend can enter either in the...</p>
Persistent link: https://www.econbiz.de/10011256048
Organizations with large-scale inventory systems typically have a large proportion of items for which demand is intermittent and low volume. We examine different approaches to forecasting for such products, paying particular attention to the need for inventory planning over a multi-period...
Persistent link: https://www.econbiz.de/10008861851
We introduce a new efficient importance sampler for nonlinear non-Gaussian state space models. By combining existing numerical and Monte Carlo integration methods, we obtain a general and efficient likelihood evaluation method for this class of models. Our approach is based on the idea that only...
Persistent link: https://www.econbiz.de/10008873337
We introduce a new method for drawing state variables in Gaussian state space models from their conditional distribution given parameters and observations. Unlike standard methods, our method does not involve Kalman filtering. We show that for some important cases, our method is computationally...
Persistent link: https://www.econbiz.de/10008617027
This paper considers the problem of estimating a linear univariate Time Series State Space model for which the shape of the distribution of the observation noise is not specified a priori. Although somewhat challenging computationally, the simultaneous estimation of the parameters of the model...
Persistent link: https://www.econbiz.de/10008684482
Purpose – The purpose of this paper is to propose and test empirically an inflation model containing permanent and transitory heteroskedastic components for the G7 countries. More specifically, recent evidences from the literature are gathered to construct a model with a heteroskedastic global...
Persistent link: https://www.econbiz.de/10010814565
A state space mixed models for binary time series where the inverse link function is modeled to be a cumulative distribution function of the scale mixture of normal (SMN) distributions. Specific inverse links examined include the normal, Student-t, slash and the variance gamma links. The...
Persistent link: https://www.econbiz.de/10010719688
This paper proves the Li (2009) [13] unawareness structure equivalent to the single-agent propositionally generated logic of awareness of Fagin and Halpern (1988) [4]. For any model of one type one can construct a model of the other type describing the same belief and awareness. Li starts from...
Persistent link: https://www.econbiz.de/10011042968