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This thesis is devoted to the models that are suitable for modelling spatial data. For this purpose, random fields with finite index set are used. Based on the neighbourhood relationship a spatial weight matrix is introduced which describes spatial dependencies. A recognition and testing of spatial dependence is mentioned and it is applied for macroeconomic indicators in the Czech Republic. Spatial models originated from generalization of usual time series models are subsequently combined with linear regression models. The parameter estimators are derived for selected models by three different methods. These methods are ordinary least squares, maximum likelihood and method of moments. Theoretical asymptotic results are supplemented by a simulation study that examines the performance of estimators for finite sample size. Finally, a short illustration on real data is demonstrated. Powered by TCPDF (www.tcpdf.org)

Spatial econometrics can bring a useful approach to macroeconomic analysis of regional data. This thesis delineates suitable cross-section data models regarding their geographical location. Neighbourhood relation is used for the analysis. The relation of neighbourhood among the regions is expressed using spatial weight matrix. We focus on spatial autocorrelation tests and introduce processes of finding a suitable spatial model. Further, we describe regression coefficients estimates and estimates of spatial dependence coefficients, especially method of maximum likelihood estimates. Besides illustrative examples we apply chosen basic spatial models on real macroeconomic data. We examine how they describe relation between household incomes, GDP and unemployment rate in western Europe. Results are compared with a linear regression model.

How to evaluate if a spatial model is well ajusted to a problem? How to know if it is the best model between the class of conditional autoregressive (CAR) and simultaneous autoregressive (SAR) models, including homoscedasticity and heteroscedasticity cases? To answer these questions inside Bayesian framework, we propose new ways to apply Bregman divergence, as well as recent information criteria as widely applicable information criterion (WAIC) and leave-one-out cross-validation (LOO). The functional Bregman divergence is a generalized form of the well known Kullback-Leiber (KL) divergence. There is many special cases of it which might be used to identify influential points. All the posterior distributions displayed in this text were estimate by Hamiltonian Monte Carlo (HMC), a optimized version of Metropolis-Hasting algorithm. All ideas showed here were evaluate by both: simulation and real data. / Como avaliar se um modelo espacial está bem ajustado? Como escolher o melhor modelo entre muitos da classe autorregressivo condicional (CAR) e autorregressivo simultâneo (SAR), homoscedásticos e heteroscedásticos? Para responder essas perguntas dentro do paradigma bayesiano, propomos novas formas de aplicar a divergência de Bregman, assim como critérios de informação bastante recentes na literatura, são eles o widely applicable information criterion (WAIC) e validação cruzada leave-one-out (LOO). O funcional de Bregman é uma generalização da famosa divergência de Kullback-Leiber (KL). Há diversos casos particulares dela que podem ser usados para identificar pontos influentes. Todas as distribuições a posteriori apresentadas nesta dissertação foram estimadas usando Monte Carlo Hamiltoniano (HMC), uma versão otimizada do algoritmo Metropolis-Hastings. Todas as ideias apresentadas neste texto foram submetidas a simulações e aplicadas em dados reais.

In the study a class of multisector network models, suitable for simulation of the interaction between production, demand, trade, and infrastructure, is presented. A characteristic feature of the class is a vintage model of the production system. Hence, the rigidities in existing capacities and the temporary monopolies obtainable from investments in new capacity at favourable locations are emphasized.As special cases, the class contains models in the modelling traditions of "interregional computable general equilibriunT, Hspatial price equilibrium**, "interregional input-output" and transportation networks.On the demand side, a multihousehold spatial linear expenditure system is introduced. This allows for an endogenous representation of income effects of skill-differentiated labour.The models are represented by a set of complementarity problems. This facilitates a comparison of model properties and the choice of an appropriate solution algorithm.The study is mainly devoted to single period models. Such equilibrium models are interpreted as adiabatic approximations of processes in continuous time. A separation by the time scale of the processes and an application of the slaving principle should thus govern the choice of endogenous variables in the equilibrium formulation. / digitalisering@umu

How to evaluate if a spatial model is well ajusted to a problem? How to know if it is the best model between the class of conditional autoregressive (CAR) and simultaneous autoregressive (SAR) models, including homoscedasticity and heteroscedasticity cases? To answer these questions inside Bayesian framework, we propose new ways to apply Bregman divergence, as well as recent information criteria as widely applicable information criterion (WAIC) and leave-one-out cross-validation (LOO). The functional Bregman divergence is a generalized form of the well known Kullback-Leiber (KL) divergence. There is many special cases of it which might be used to identify influential points. All the posterior distributions displayed in this text were estimate by Hamiltonian Monte Carlo (HMC), a optimized version of Metropolis-Hasting algorithm. All ideas showed here were evaluate by both: simulation and real data. / Como avaliar se um modelo espacial está bem ajustado? Como escolher o melhor modelo entre muitos da classe autorregressivo condicional (CAR) e autorregressivo simultâneo (SAR), homoscedásticos e heteroscedásticos? Para responder essas perguntas dentro do paradigma bayesiano, propomos novas formas de aplicar a divergência de Bregman, assim como critérios de informação bastante recentes na literatura, são eles o widely applicable information criterion (WAIC) e validação cruzada leave-one-out (LOO). O funcional de Bregman é uma generalização da famosa divergência de Kullback-Leiber (KL). Há diversos casos particulares dela que podem ser usados para identificar pontos influentes. Todas as distribuições a posteriori apresentadas nesta dissertação foram estimadas usando Monte Carlo Hamiltoniano (HMC), uma versão otimizada do algoritmo Metropolis-Hastings. Todas as ideias apresentadas neste texto foram submetidas a simulações e aplicadas em dados reais.

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<p>Human disease and the corresponding immune response occur in three-dimensional space and time. Many diseases are difficult to study, either <em>in vivo</em> or <em>in vitro</em>, due to the complexity of the system. Despite computational models that can address complexity, many do not capture the spatial  aspects  of  disease.  Agent-based  models  are  mechanistic,  spatiotemporal  computational models that can be integrated with other mathematical models to create multiscale models. Here I detail two models to examine spatiotemporal progression and possible treatment strategies for two diseases  with  low  treatment  success: <em>Mycobacterium  avium complex</em>  (MAC)  and  Alzheimer’s Disease.</p> <p>MAC  are  biofilm-forming  environmental  microbes  capable  of  residing  in  human  lung nodules,  causing  MAC  pulmonary  disease  (MAC-PD).  Clinical  drug  susceptibility  tests  and treatment  outcomes  are  poorly  correlated,  and  nodules  are  complex  and  difficult  to  monitor, leading to low MAC cure rates (45-65%)². I have developed an informative model of the initial infection  events  in  MAC-PD. This  model  has  been  used  to  probe  many  different  scenarios  of infection and to predict the effect of potential interventions.</p> <p>Alzheimer’s  Disease  (AD)  is  the  leading  cause  of  dementia,  with  no  disease-altering pharmacological  intervention.  Microglia  are  phagocytotic  neuroimmune  cells,  known  to  form barriers around plaques. There has been increased interest in leveraging microglia to slow the progression of neurodegeneration by manipulating these barriers. I present an agent-based model of microglia barriers at the single plaque level and use knock-out experiments to probe possible targets for immunotherapy and quantify their effects on plaque progression.</p>

La crisi finanziaria esplosa nel 2008 è degenerata in un’aspra e duratura ondata recessiva, che ha colpito l’economia reale a livello internazionale. La presente tesi si propone di contribuire alla letteratura econometrica sull’ultima crisi focalizzandosi su due temi ampiamente dibattuti: vincoli finanziari e produttività totale dei fattori. Il manifatturiero italiano si presenta come scenario preferenziale per condurre l’analisi, tenuto conto della struttura produttiva frammentata e della dipendenza delle imprese dal debito bancario. Si cercherà dapprima di analizzare l’impatto dei vincoli finanziari sulle dinamiche manifatturiere durante la crisi, per poi passare a trattare i temi della rigidità finanziaria e degli effetti di contagio che si sono verificati tra le imprese attraverso il canale del credito commerciale, quali determinanti della probabilità di insolvenza. Infine, il tema delle agglomerazioni tra imprese, di tipo geografico e settoriale, sarà analizzato quale fattore cruciale per la formazione di spillover di produttività, insieme alla capacità innovativa del territorio. I risultati confermano il carattere di pervasività dell’ultima recessione, che alterando le dinamiche manifatturiere ha contribuito ad esacerbare gli episodi di insolvenza. Il possedere una base produttiva clusterizzata ed eterogenea può tuttavia rappresentare ancora un punto di forza, persino all’interno di un contesto operativo plasmato dalla crisi. / The financial crisis that erupted in 2008 translated into harsh recessionary effects at an international level, that were passed on to the real economy. A solid recovery is still lagging behind. The dissertation contributes to the econometric literature on the great recession by focusing attention on two debated topics: financing constraints and total factor productivity (TFP). The fragmented and strongly bank-dependent Italian production base is a preferred environment to conduct the analysis. The role played by financing constraints as amplifiers of manufacturing dynamics is firstly investigated. As a second step, financial rigidity of firms and contagion effects that occurred via trade credit interconnections are considered, and jointly modelled as core determinants of distress likelihoods by resorting to spatial econometric techniques. In the last section, geographical and sectoral clustering phenomena are spatially analyzed in order to investigate knowledge spillovers at the micro level. Results highlight the pervasive nature of the last crisis. The harshness of the recessionary effects fostered a change in manufacturing equilibria and caused the proliferation of distress episodes. Nevertheless, a clustered production base still represents a driver for the formation of positive externalities.

O presente estudo agrega os dados geoespaciais livres, cedidos pela prefeitura de São Paulo, IBGE, CNAE, RAIS, entre outros e particulares, cedidos pela empresa Maplink, com os recursos dos Sistemas de Informações Geográficas - SIG, para planejamento de Transportes. A megacidade de São Paulo com mais de dez milhões de habitantes tem milhares de estabelecimentos comerciais para atender a demanda dessa população, que precisa ser abastecidos. Os veículos de carga que abastecem, além de afetarem o trânsito e mobilidade urbana, emitem poluentes. O objetivo é hierarquizar as áreas da megacidade de São Paulo (Brasil) com características potenciais para alta concentração de poluentes decorrentes da circulação dos veículos de carga para abastecer os estabelecimentos comerciais. A metodologia correlaciona espacialmente os dois conjuntos de dados (localização de estabelecimentos comerciais e a circulação de veículos de transporte de cargas) utilizando ferramentas de análises espaciais, baseada em Kernel Density Estimator - KDE, a análise de multicritério, como a Analytic Hierarchy Process - AHP para avaliar como estes duas variáveis estão relacionadas, e também a lógica Fuzzy para calcular esses dados. Os resultados obtidos demonstra que as avenidas e rodovias do município de São Paulo possuem alta concentração de poluentes, sendo utilizadas como rotas para os veículos de carga que tanto fazem do município sua origem e/ou destino, as regiões que possuem alta concentração de poluentes atmosféricos são: Cerqueira César, Parque Dom Pedro II e Ibirapuera, com destaque também na Marginal Tietê e Marginal Pinheiros, além da zona leste (Itaquera e Itaim Paulista). / This study adds free geospatial data, granted by the city of São Paulo, IBGE, CNAE, RAIS, among others and individuals assigned by Maplink company with the capabilities of Geographic Information Systems - GIS for Transportation planning. The megacity of São Paulo with more than ten million inhabitants has thousands of shops to meet the needs of this population, which must be supplied. The cargo vehicles that supply, as well as affect the traffic and urban mobility, emit pollutants. The goal is to prioritize areas of the megacity of São Paulo (Brazil) with potential characteristics for high concentration of pollutants resulting from the movement of cargo vehicles to supply shops. The methodology spatially correlate the two sets of data (location of commercial establishments and the movement of cargo transport vehicles) using tools of spatial analysis based on Kernel Density Estimator - KDE, the multi-criteria analysis, as the Analytic Hierarchy Process - AHP to evaluate how these two variables are related, and also fuzzy logic to calculate this data. The results show that the avenues and highways of São Paulo have a high concentration of pollutants, being used as routes for freight vehicles that both make the city their origin and / or destination, the regions with high concentration of air pollutants they are: Cerqueira Cesar, Parque Dom Pedro II and Ibirapuera, highlighting also the Marginal Tiete and Pinheiros, besides the east side (Itaquera and Itaim Paulista).