An Alternative View of the US Price-Dividend Ratio Dynamics

As a necessary condition for the validity of the present value model, the price-dividend ratio must be stationary. However, significant market episodes seem to provide evidence of prices significantly drifting apart from dividends while other episodes show prices anchoring back to dividends. This paper investigates the stationarity of this ratio in the context of a Markov- switching model à la Hamilton (1989) where an asymmetric speed of adjustment towards a unique attractor is introduced. A three-regime model displays the best regime identification and reveals that the first part of the 90’s boom (1985-1995) and the post-war period are characterized by a stationary state featuring a slow reverting process to a relatively high attractor. Interestingly, the latter part of the 90’s boom (1996-2000), characterized by a growing price-dividend ratio, is entirely attributed to a stationary regime featuring a highly reverting process to the attractor. Finally, the post-Lehman Brothers episode of the subprime crisis can be classified into a temporary nonstationary regime.

Optimal Investment in Energy Efficiency under Uncertainty

41 p.

Optimal Abandonment of Coal-Fired Stations in the EU

36 p.

On the optimal usage of labelled examples in semi-supervised multi-class classification problems

In recent years, the performance of semi-supervised learning has been theoretically investigated. However, most of this theoretical development has focussed on binary classification problems. In this paper, we take it a step further by extending the work of Castelli and Cover [1] [2] to the multi-class paradigm. Particularly, we consider the key problem in semi-supervised learning of classifying an unseen instance x into one of K different classes, using a training dataset sampled from a mixture density distribution and composed of l labelled records and u unlabelled examples. Even under the assumption of identifiability of the mixture and having infinite unlabelled examples, labelled records are needed to determine the K decision regions. Therefore, in this paper, we first investigate the minimum number of labelled examples needed to accomplish that task. Then, we propose an optimal multi-class learning algorithm which is a generalisation of the optimal procedure proposed in the literature for binary problems. Finally, we make use of this generalisation to study the probability of error when the binary class constraint is relaxed.

Gipuzkoako udalen finantza kaudimenaren rankinga ratio aipagarrienen analisiaren arabera

[EU]Lan honen helburu nagusia,Gipuzkoako udalen finantza kaudimena aztertzeaz gain, beraien arteko konparaketa bat egin ahal izatea zen. Beste modu batera esanda,egoera hobeagoan dauden udalak nortzuk diren identifikatu ahal izatea. Hasi aurretik bagenekien, ordea, udal baten finantza kaudimena ez dagoela faktore bat edo biren arabera soilik, eta gauza asko subjektiboak direla ere bai. Gainera, eragina duten baldintza guztiak kontuan hartzea ere zaila da. Kasu honetan, 9-10 adierazle aukeratu dira, ondoren udal bakoitzak besteekin konparatuz adierazle horretan lortutako zenbatekoa 1etik 10erako puntuazio batekin baloratu da, eta azkenik, udaletxe guztien ranking bat osatu da. Ondorengo lerroetan ikus daiteke ranking honen testuingurua,erabilitako metodologia eta egindako kalkuluen ondorio nagusiak ere.

Optimal Taxation and Indeterminacy in the Uzawa-Lucas Model with Sector-specific Externalities

Documento de trabajo

Gipuzkoako udalen finantza kaudimenaren rankinga ratio aipagarrienen analisiaren arabera

Gipuzkoako udalen finantza kaudimenari buruzko analisi bat burutu ondoren, hauen rankinga burutzea da GrAL honen helburu nagusia.