This paper develops an estimated hybrid model that combines the micro-founded DSGE model with the flexibility of the theoretical VAR model. The model is estimated via the maximum likelihood technique based on quarterly data on real Gross National Product (GNP), consumption, investment and hours worked, for the South African economy, over the period of 1970:1 to 2000:4. Based on a recursive esti...

The vector autoregressive (VAR) model is a powerful tool in learning complex time series and has been exploited in many fields. The VAR model poses some unique challenges to researchers: On one hand, the dimensionality, introduced by incorporating multiple numbers of time series and adding the order of the vector autoregression, is usually much higher than the time series length; On the other h...

A set of four-dimensional variational data assimilation (4D-Var) experiments were conducted using both a standard method and an incremental method in an identical twin framework. The full physics adjoint model of the Florida State University global spectral model (FSUGSM) was used in the standard 4D-Var, while the adjoint of only a few selected physical parameterizations was used in the increme...

Á unglingsárum takast einstaklingar á við ýmsar breytingar og áskoranir. Góð andleg líðan er forsenda velferðar fólks því vekur það áhyggjur að henni fer hrakandi hjá ungmennum Vesturlöndum. Áhyggjur beinast einnig vímuefnaneyslu ungmenna en sífellt koma fram nýjar áskoranir í efni. Markmið rannsóknarinnar var kortleggja andlega skoða samband þessara þátta gæði tengsla foreldra kyn. Einnig átti...

J. Milke”*, T. Antonib, W.D. Apela, F. Badea bt, K. Bekk”, A. Bercuciat, H. Bliimerab, H. Bozdog”, I.M. Branc&, C. Biittnerb, A. Chilingarian d, K. Daumillerb, P. Dolla, J. Englera, F. Fefilerb, H.J. Gils”, R. Glasstetterb, R. Haeuslerb, A. Haungsa, D. Hecka, J.R. Harandelb, A. Iwanbt, K.-H. Kampertba, H.O. Klagesa, G. Maiera, H.J. Mathesa, H.J. Mayera, M. Millera, R. Obenlanda, 3. OehlschlSger...

Four dimensional variational data assimilation, called 4D-Var in the atmospheric sciences literature, is a method for combining forecast, dynamical systems equations, prior information about properties of the atmosphere, and heterogeneous observations, to get an estimate of the evolving state of the atmosphere. Summary: We (abstractly) generalize thètoy' weak 4D-Var model in Gong, Wahba, Johnso...

Unrestricted reduced form vector autoregressive (VAR) models have become a dominant research strategy in empirical macroeconomics since Sims (1980) critique of traditional macroeconometric modeling. They are however subjected to the curse of dimensionality. In this paper we propose general-to-specific reductions of VAR models and consider computer-automated model selection algorithms embodied i...

This paper analyses the application of a switching volatility model to forecast the Ž . distribution of returns and to estimate the Value-at-Risk VaR of both single assets and portfolios. We calculate the VaR value for 10 Italian stocks and a number of portfolios based on these stocks. The calculated VaR values are also compared with the variance–coŽ . variance approach used by JP Morgan in Ris...

The prediction of visual field deterioration in patients who are suffering from normal tension glaucoma plays an important role in the management of the disease. The Vector Auto-Regressive (VAR) process appears to be an appropriate way of modelling the multivariate time series data from the visual fields. However, standard parameterisation techniques such as the Yule-Walker equations for buildi...