Essays on econometrics. Multivariate Markov chains

Tese de Doutoramento em Matemática aplicada à Economia e GestãoThis Dissertation is about Markov chains and their role in economics and in econometrics theory. Four essays on the Markov chain ap- proach are presented. We start by illustrating the analytical potential of multivariate Markov chains in the field of economic history, in particular with regard to a test of the Schumpeterian hypothesis of creative destruction. Then, we ilustrate the flexibility of Markov chains, and their per- tinence to situations that go beyond their traditional applicability: i) how can a Markov chain play the role of covariates; ii) how can a Markov chain representation be useful to compute expected hitting times. Finally, we present a new methodology for testing and detecting multiple structural breaks in multivariate Markov chains, where the dates at which the structural breaks occur are unknown.N/

Editorial Special Issue on Governance: International Journal of Film and Media Arts

In 2017, the Rome Declaration signaled the EU pledge to work towards a ‘Union where young people receive the best education and training and can study and find jobs across the continent. In that same year the Commission set out the vision of the European Education Area (EEA) as a genuine common space for quality education and lifelong learning across borders for all. Further acknowledgment of the key role higher education plays in the future of Europe occurred with the publication of the “Council Resolution on a strategic framework for European cooperation in education and training towards the European Education Area and beyond (2021-2030)” in February 2021 (2021/C 66/01). In order to attain this European Education Area and the related European Space for Higher Education, many actions have since then been designed and implemented, of which one of the most important is the “European Strategy for Universities” that aims to support the higher education sector in adapting to changing conditions and strengthen cooperation across borders. One of the key initiatives of this European Strategy for Universities is the “European Universities” initiative. Since 2020, this initiative has been supporting 44 Alliances of European Higher Education institutions (HEIs) in which approximately 340 HEIs take part, in reaching higher levels of cooperation and integration

Does habitat reachability affect the distribution of a range expanding species in a fragmented landscape?

A fragmentação da paisagem pode influenciar a capacidade de espécies em expansão de alcançarem habitat adequado ao impedir os seus movimentos de dispersão. Para estimar este efeito, avaliamos a acessibilidade de habitat para o esquilo-vermelho numa paisagem fragmentada utilizando modelos espacialmente explícitos. Prevemos que o esquilo não ocupe todas as parcelas de elevada qualidade e que a ocupação não é só mediada pela qualidade do habitat mas também pela sua acessibilidade . Para testar estas hipóteses comparámos um modelo de adequabilidade de habitat (HSM) baseado unicamente em variáveis ambientais, com outros HSM que integravam a permeabilidade da paisagem para diferentes distâncias máximas de dispersão (1000, 1500, 2000 metros). Observamos que o HSM que integra a permeabilidade de habitat com uma capacidade de dispersão até 1000m apresenta melhor ajustamento aos dados observados. Os nossos resultados apontam que a acessibilidade do habitat influência a distribuição do esquilo vermelho; Does habitat reachability affect the distribution of a range expanding species in a fragmented landscape? ABSTRACT: Landscape fragmentation may influence the ability of range expanding species to reach suitable habitat by impeding its dispersal movements. We used a spatially explicit modeling approach to access the influence of habitat reachability on the distribution of the red squirrel in a fragmented landscape. We hypothesize that the red squirrel does not occupy all suitable habitat patches, and patch occupancy is not only mediated by habitat suitability but also by its reachability. To test these hypothesis we compared a habitat suitability model (HSM) based only on environmental data to other three HSMs considering landscape permeability at different maximum dispersal distances (1000, 1500, 2000 meters). Our results show that the model that took in consideration a 1000m dispersal distance was better fitted to observed occupancy data. Our findings show that habitat reachability influences the distribution of red squirrel, since suitable habitat patches may not be reachable

Multivariate Markov Chains - estimation, inference and forecast. A new approach : what if we use them as stochastic covariates?

Mestrado em Econometria Aplicada e PrevisãoThis dissertation proposes a new concept: the usage of Multivariate Markov Chains (MMC) as covariates. Our innovative approach is based on the observation that we can treat possible categorical regressors as a MMC in order to improve the forecast error of a certain dependent variable,provided it is caused, in the Granger sense, by the MMC. We conduct a Monte Carlo simulation study to assess the performance of our model and we archive excellent results in terms of forecast. An empirical illustration, that widely supports the results obtained in the Monte Carlo study, is also provided. Furthermore, the results of our empirical illustration suggest that the sovereign bond markets in peripherical European countries, namely Portugal, are ine cient. The conclusions drawn include implications for policy. We also discuss the ideas behind several methods to estimate MMC, tackling issues with regard to the statistical inference topic. We provide a general framework to allow us to obtain the MMC h-step-ahead forecast closed formulas.Esta dissertação propõe um novo conceito: a utilização de Cadeias de Markov Multivariadas enquanto regressores. A nossa abordagem inovadora baseia-se na observação de que é possível fazer uso de CMM enquanto variáveis explicativas com o intuito de se reduzirem os erros de previsão de uma determinada variável dependente, desde que essa variável dependente seja causada, a la Granger, pela CMM. Com o objectivo de perceber a performance do nosso modelo em termos de previsão operacionalizamos um estudo de simulação de Monte Carlo no qual obtemos excelentes resultados. Também recorremos a uma ilustração empírica que sustenta fortemente os resultados obtidos no estudo de simulação de Monte Carlo. Para além disso, os resultados da ilustração empírica apontam para a circunstância de que os mercados das obrigações das dívidas soberanas dos países da periferia europeia, nomeadamente Portugal, são ine cientes. Podem retirar-se das conclusões obtidas algumas implicações em termos de orientação de política económica. Discutimos ainda algumas ideias subjacentes às diversas metodologias de estimação de CMM, sublinhando as questões relativas ao tópico da inferência estatística. Providenciamos uma utensilagem teórica do seio da qual se obtêm as expressões da previsão a h-passos com CMM

Combining a regression model with a multivariate Markov chain in a forecasting problem

This paper proposes a new concept: the usage of Multivariate Markov Chains (MMC) as covariates. Our approach is based on the observation that we can treat possible categorical (or discrete) regressors, whose values are unknown in the forecast period, as an MMC in order to improve the forecast error of a certain dependent variable. Hence, we take advantage of the information about the past state interactions between the MMC categories to forecast the categorical (or discrete) regressors and improve the forecast of the actual dependent variable.info:eu-repo/semantics/publishedVersio

Self-service business intelligence data analytics

Information systems bring competitive advantages to companies when they know how to use them to their full potential. Business intelligence systems can garner large volumes of data and convert it into information but have the disadvantage of having associated high implementation costs both structurally and qualified people. Then comes Self Service Business Intelligence which provides companies with much lower costs of extracting information from their systems. This work arises from Tecmic’s need to extract information in the form of reports and dashboards from the incident system it has currently implemented. This system has limited information extraction and handling capabilities to help company managers make informed decisions about customer reported incidents. In order to address this problem, it was proposed to implement the Self-Service Business Intelligence software from Microsoft, Power BI. This work details all the preparatory steps to import the data into Power BI as well as an analysis of the results obtained. Additionally, through reports created in Power BI, it is explored what inefficiencies can be tackled in order to improve company performance and drive down the number of services created.Os sistemas de informação trazem vantagens competitivas para as empresas que retiram máximo proveito deles. Os sistemas de business intelligence podem reunir grandes volumes de dados e convertê-los em informação, mas têm a desvantagem de ter elevados custos associados, estruturalmente e de trabalhadores qualificados. Surge então o Self Service Business Intelligence, que possibilita às empresas custos muito mais baixos de extrair informação de seus sistemas de informação. Este trabalho surge da necessidade da Tecmic de extrair informação sob forma de relatórios e dashboards do sistema de incidentes que tem atualmente implementado. Este sistema tem capacidades limitadas no que diz respeito à extração e tratamento de informação o que dificulta os gestores da empresa de tomar decisões informadas sobre incidentes relatados pelos clientes. Para resolver esse problema, foi proposto implementar o software de Self-Service Business Intelligence da Microsoft, o Power BI. Este trabalho detalha todas as etapas preparatórias para importar os dados para o Power BI, bem como uma análise sobre os resultados obtidos. Adicionalmente, por meio de relatórios criados no Power BI, são exploradas as ineficiências que podem ser enfrentadas para melhorar o desempenho da empresa e diminuir o número de serviços criados