35 resultados para Models, Theoretical


Relevância:

30.00% 30.00%

Publicador:

Resumo:

Although financial theory rests heavily upon the assumption that asset returns are normally distributed, value indices of commercial real estate display significant departures from normality. In this paper, we apply and compare the properties of two recently proposed regime switching models for value indices of commercial real estate in the US and the UK, both of which relax the assumption that observations are drawn from a single distribution with constant mean and variance. Statistical tests of the models' specification indicate that the Markov switching model is better able to capture the non-stationary features of the data than the threshold autoregressive model, although both represent superior descriptions of the data than the models that allow for only one state. Our results have several implications for theoretical models and empirical research in finance.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

The research network Basic Concepts for Convection Parameterization in Weather Forecast and Climate Models was organized with European funding (COST Action ES0905) for the period of 20102014. Its extensive brainstorming suggests how the subgrid-scale parameterization problem in atmospheric modeling, especially for convection, can be examined and developed from the point of view of a robust theoretical basis. Our main cautions are current emphasis on massive observational data analyses and process studies. The closure and the entrainmentdetrainment problems are identified as the two highest priorities for convection parameterization under the massflux formulation. The need for a drastic change of the current European research culture as concerns policies and funding in order not to further deplete the visions of the European researchers focusing on those basic issues is emphasized.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

We propose a geoadditive negative binomial model (Geo-NB-GAM) for regional count data that allows us to address simultaneously some important methodological issues, such as spatial clustering, nonlinearities, and overdispersion. This model is applied to the study of location determinants of inward greenfield investments that occurred during 20032007 in 249 European regions. After presenting the data set and showing the presence of overdispersion and spatial clustering, we review the theoretical framework that motivates the choice of the location determinants included in the empirical model, and we highlight some reasons why the relationship between some of the covariates and the dependent variable might be nonlinear. The subsequent section first describes the solutions proposed by previous literature to tackle spatial clustering, nonlinearities, and overdispersion, and then presents the Geo-NB-GAM. The empirical analysis shows the good performance of Geo-NB-GAM. Notably, the inclusion of a geoadditive component (a smooth spatial trend surface) permits us to control for spatial unobserved heterogeneity that induces spatial clustering. Allowing for nonlinearities reveals, in keeping with theoretical predictions, that the positive effect of agglomeration economies fades as the density of economic activities reaches some threshold value. However, no matter how dense the economic activity becomes, our results suggest that congestion costs never overcome positive agglomeration externalities.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Individual-based models (IBMs) can simulate the actions of individual animals as they interact with one another and the landscape in which they live. When used in spatially-explicit landscapes IBMs can show how populations change over time in response to management actions. For instance, IBMs are being used to design strategies of conservation and of the exploitation of fisheries, and for assessing the effects on populations of major construction projects and of novel agricultural chemicals. In such real world contexts, it becomes especially important to build IBMs in a principled fashion, and to approach calibration and evaluation systematically. We argue that insights from physiological and behavioural ecology offer a recipe for building realistic models, and that Approximate Bayesian Computation (ABC) is a promising technique for the calibration and evaluation of IBMs. IBMs are constructed primarily from knowledge about individuals. In ecological applications the relevant knowledge is found in physiological and behavioural ecology, and we approach these from an evolutionary perspective by taking into account how physiological and behavioural processes contribute to life histories, and how those life histories evolve. Evolutionary life history theory shows that, other things being equal, organisms should grow to sexual maturity as fast as possible, and then reproduce as fast as possible, while minimising per capita death rate. Physiological and behavioural ecology are largely built on these principles together with the laws of conservation of matter and energy. To complete construction of an IBM information is also needed on the effects of competitors, conspecifics and food scarcity; the maximum rates of ingestion, growth and reproduction, and life-history parameters. Using this knowledge about physiological and behavioural processes provides a principled way to build IBMs, but model parameters vary between species and are often difficult to measure. A common solution is to manually compare model outputs with observations from real landscapes and so to obtain parameters which produce acceptable fits of model to data. However, this procedure can be convoluted and lead to over-calibrated and thus inflexible models. Many formal statistical techniques are unsuitable for use with IBMs, but we argue that ABC offers a potential way forward. It can be used to calibrate and compare complex stochastic models and to assess the uncertainty in their predictions. We describe methods used to implement ABC in an accessible way and illustrate them with examples and discussion of recent studies. Although much progress has been made, theoretical issues remain, and some of these are outlined and discussed.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Abstract. Three influential theoretical models of OCD focus upon the cognitive factors of inflated responsibility (Salkovskis, 1985), thought-action fusion (Rachman, 1993) and meta-cognitive beliefs (Wells and Matthews, 1994). Little is known about the relevance of these models in adolescents or about the nature of any direct or mediating relationships between these variables and OCD symptoms. This was a cross-sectional correlational design with 223 non-clinical adolescents aged 13 to 16 years. All participants completed questionnaires measuring inflated responsibility, thought-action fusion, meta-cognitive beliefs and obsessive-compulsive symptoms. Inflated responsibility, thought-action fusion and metacognitive beliefs were significantly associated with higher levels of obsessive-compulsive symptoms. These variables accounted for 35% of the variance in obsessive-compulsive symptoms, with inflated responsibility and meta-cognitive beliefs both emerging as significant independent predictors. Inflated responsibility completely mediated the effect of thoughtaction fusion and partially mediated the effect of meta-cognitive beliefs. Support for the downward extension of cognitive models to understanding OCD in a younger population was shown. Findings suggest that inflated responsibility and meta-cognitive beliefs may be particularly important cognitive concepts in OCD. Methodological limitations must be borne in mind and future research is needed to replicate and extend findings in clinical samples. Keywords: Obsessive compulsive disorder, adolescents, cognitive models.