Structural time series models and the Kalman filter: A concise review

The continued increase in availability of economic data in recent years and, more importantly, the possibility to construct larger frequency time series, have fostered the use (and development) of statistical and econometric techniques to treat them more accurately. This paper presents an exposition of structural time series models by which a time series can be decomposed as the sum of a trend, seasonal and irregular components. In addition to a detailled analysis of univariate speci fications we also address the SUTSE multivariate case and the issue of cointegration. Finally, the recursive estimation and smoothing by means of the Kalman filter algorithm is described taking into account its different stages, from initialisation to parameter s estimation.

Corporate finance in general equilibrium models with incomplete markets: A survey

A Masters Thesis, presented as part of the requirements for the award of a Research Masters Degree in Economics from NOVA – School of Business and Economics

Knowledge management framework based on brain models and human physiology

The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.

A systematic methodology to analyse the performance and design configurations of business interoperability in cooperative industrial networks

This thesis proposes a methodology for modelling business interoperability in a context of cooperative industrial networks. The purpose is to develop a methodology that enables the design of cooperative industrial network platforms that are able to deliver business interoperability and the analysis of its impact on the performance of these platforms. To achieve the proposed objective, two modelling tools have been employed: the Axiomatic Design Theory for the design of interoperable platforms; and Agent-Based Simulation for the analysis of the impact of business interoperability. The sequence of the application of the two modelling tools depends on the scenario under analysis, i.e. whether the cooperative industrial network platform exists or not. If the cooperative industrial network platform does not exist, the methodology suggests first the application of the Axiomatic Design Theory to design different configurations of interoperable cooperative industrial network platforms, and then the use of Agent-Based Simulation to analyse or predict the business interoperability and operational performance of the designed configurations. Otherwise, one should start by analysing the performance of the existing platform and based on the achieved results, decide whether it is necessary to redesign it or not. If the redesign is needed, simulation is once again used to predict the performance of the redesigned platform. To explain how those two modelling tools can be applied in practice, a theoretical modelling framework, a theoretical Axiomatic Design model and a theoretical Agent-Based Simulation model are proposed. To demonstrate the applicability of the proposed methodology and/or to validate the proposed theoretical models, a case study regarding a Portuguese Reverse Logistics cooperative network (Valorpneu network) and a case study regarding a Portuguese construction project (Dam Baixo Sabor network) are presented. The findings of the application of the proposed methodology to these two case studies suggest that indeed the Axiomatic Design Theory can effectively contribute in the design of interoperable cooperative industrial network platforms and that Agent-Based Simulation provides an effective set of tools for analysing the impact of business interoperability on the performance of those platforms. However, these conclusions cannot be generalised as only two case studies have been carried out. In terms of relevance to theory, this is the first time that the network effect is addressed in the analysis of the impact of business interoperability on the performance of networked companies and also the first time that a holistic approach is proposed to design interoperable cooperative industrial network platforms. Regarding the practical implications, the proposed methodology is intended to provide industrial managers a management tool that can guide them easily, and in practical and systematic way, in the design of configurations of interoperable cooperative industrial network platforms and/or in the analysis of the impact of business interoperability on the performance of their companies and the networks where their companies operate.

Understanding multi-asset factor models: Factor exposure interpretation

Field lab: Business project

Exploring the consumer decision journey and online shoping experience through an emotional prespective

Traditional consumer decision-making models have long used quantitative research to address a link between emotional and rational behavior. However, little qualitative research has been conducted in the area of online shopping as an end-to-end experience. This study aims to provide a detailed phenomenological account of consumers’ online shopping experience and extend Mckinsey & Companys’s consumer decision journey model from an emotional perspective. Six semi-structured interviews and a focus group of nine people are analyzed using Interpretive Phenomenology Analysis and five superordinate themes emerged from the results: emotional experience, empathy and encouragement, in relation to brand preference, emotional encounters in relation to consumer satisfaction and emotional exchange and relationship with a company or brand. A model interrelating these themes is then introduced to visually represent the emotional essence of a large online purchase. This study promises to be applicable as a descriptive, and perhaps, better predictive report for understanding the complex consumer decision-making process as it relates to online consumer behavior. Future research topics are also identified.

Online strategies for offline business the case of Millennials and shopping centrs (Sonae Sierra)

The project, conducted within a direct research internship at Sonae Sierra, aims to propose innovative digital approaches for Shopping Centres (SC) to deal successfully with millennial consumer behavior concerning digital devices and online content in relation to shopping. An online survey followed by a focus group were conducted for this purpose. Results show a demand for specific digital services created by a SC and that their perception depends highly on gender of millennials. Moreover it´s a cohort seeking for personalized content, providing emotional or functional benefit. Consequently a SC must deliver services, as presented in this work satisfying those needs.

Conceptual-physical bridging – From BPMN models to physical implementations on kettle

Developing and implementing data-oriented workflows for data migration processes are complex tasks involving several problems related to the integration of data coming from different schemas. Usually, they involve very specific requirements - every process is almost unique. Having a way to abstract their representation will help us to better understand and validate them with business users, which is a crucial step for requirements validation. In this demo we present an approach that provides a way to enrich incrementally conceptual models in order to support an automatic way for producing their correspondent physical implementation. In this demo we will show how B2K (Business to Kettle) system works transforming BPMN 2.0 conceptual models into Kettle data-integration executable processes, approaching the most relevant aspects related to model design and enrichment, model to system transformation, and system execution.

The Good, the Bad and the Populist: A Model of Political Agency with Emotional Voters

This paper attempts to extend existing models of political agency to an environment in which voting may be divided between informed and instrumental, informed and ‘expressive’ (Brennan and Lomasky (1993)) and uninformed due to ‘rational irrationality’ (Caplan (2007)). It constructs a model where politicians may be good, bad or populist. Populists are more willing than good politicians to pander to voters who may choose inferior policies in a large-group electoral setting because their vote is insignificant compared with those that voters would choose were their vote decisive in determining the electoral outcome. Bad politicians would ideally like to extract tax revenue for their own ends. Initially we assume the existence of only good and populist politicians. The paper investigates the incentives for good politicians to pool with or separate from populists and focuses on three key issues – (1) how far the majority of voter’s preferences are from those held by the better informed incumbent politician (2) the extent to which the population exhibits rational irrationality and expressiveness (jointly labelled as emotional) and (3) the cost involved in persuading uninformed voters to change their views in terms of composing messages and spreading them. This paper goes on to consider how the inclusion of bad politicians may affect the behaviour of good politicians and suggests that a small amount of potential corruption may be socially useful. It is also argued that where bad politicians have an incentive to mimic the behaviour of good and populist politicians, the latter types of politician may have an incentive to separate from bad politicians by investing in costly public education signals. The paper also discusses the implications of the model for whether fiscal restraints should be soft or hard.

Asset Prices, Business Cycles, and Markov-Perfect Fiscal Policy when Agents are Risk-Sensitive

We study a business cycle model in which a benevolent fiscal authority must determine the optimal provision of government services, while lacking credibility, lump-sum taxes, and the ability to bond finance deficits. Households and the fiscal authority have risk sensitive preferences. We find that outcomes are affected importantly by the household's risk sensitivity, but not by the fiscal authority's. Further, while household risk-sensitivity induces a strong precautionary saving motive, which raises capital and lowers the return on assets, its effects on fluctuations and the business cycle are generally small, although more pronounced for negative shocks. Holding the stochastic steady state constant, increases in household risk-sensitivity lower the risk-free rate and raise the return on equity, increasing the equity premium. Finally, although risk-sensitivity has little effect on the provision of government services, it does cause the fiscal authority to lower the income tax rate. An additional contribution of this paper is to present a method for computing Markov-perfect equilibria in models where private agents and the government are risk-sensitive decisionmakers.

Family physician involvement in cancer care and lung cancer patient emotional distress and quality of life.

PURPOSE: This study aims to describe emotional distress and quality of life (QoL) of patients at different phases of their lung cancer and the association with their family physician (FP) involvement. METHODS: A prospective study on patients with lung cancer was conducted in three regions of Quebec, Canada. Patients completed, at baseline, several validated questionnaires regarding their psychosocial characteristics and their perceived level of FP involvement. Emotional distress [profile of mood states (POMS)] and QoL [European Organization for Research and Treatment of Cancer Quality of Life Core 30 (EORTC QLQ-C30)] were reassessed every 3-6 months, whether patients had metastasis or not, up to 18 months. Results were regrouped according to cancer phase. Mixed models with repeated measurements were performed to identify variation in distress and QoL. RESULTS: In this cohort of 395 patients, distress was low at diagnosis (0.79 ± 0.7 on a 0-4 scale), raising to 1.36 ± 0.8 at the advance phase (p < 0.0001). Patient's global QoL scores significantly decreased from the diagnosis to the advance phase (from 66 to 45 on a 0-100 scale; p < 0.0001). At all phases of cancer, FP involvement was significantly associated with patients' distress (p = 0.0004) and their global perception of QoL (p = 0.0080). These associations remained statistically significant even after controlling for age, gender, and presence of metastases. CONCLUSIONS: This study provides new knowledge on patients' emotional distress and QoL with cancer evolution and, particularly, their association with FP involvement. Other studies should be conducted to further explore FP role in cancer supportive care.

Emotional intelligence: On definitions, neuroscience, and marshmallows

In his timely article, Cherniss offers his vision for the future of "Emotional Intelligence" (EI). However, his goal of clarifying the concept by distinguishing definitions from models and his support for "Emotional and Social Competence" (ESC) models will, in our opinion, not make the field advance. To be upfront, we agree that emotions are important for effective decision-making, leadership, performance and the like; however, at this time, EI and ESC have not yet demonstrated incremental validity over and above IQ and personality tests in meta-analyses (Harms & Credé, 2009; Van Rooy & Viswesvaran, 2004). If there is a future for EI, we see it in the ability model of Mayer, Salovey and associates (e.g, Mayer, Caruso, & Salovey, 2000), which detractors and supporters agree holds the most promise (Antonakis, Ashkanasy, & Dasborough, 2009; Zeidner, Roberts, & Matthews, 2008). With their use of quasi-objective scoring measures, the ability model grounds EI in existing frameworks of intelligence, thus differentiating itself from ESC models and their self-rated trait inventories. In fact, we do not see the value of ESC models: They overlap too much with current personality models to offer anything new for science and practice (Zeidner, et al., 2008). In this commentary we raise three concerns we have with Cherniss's suggestions for ESC models: (1) there are important conceptual problems in both the definition of ESC and the distinction of ESC from EI; (2) Cherniss's interpretation of neuroscience findings as supporting the constructs of EI and ESC is outdated, and (3) his interpretation of the famous marshmallow experiment as indicating the existence of ESCs is flawed. Building on the promise of ability models, we conclude by providing suggestions to improve research in EI.

Macroeconomic shocks and the business cycle: evidence from a structural factor model

We use a dynamic factor model to provide a semi-structural representation for 101 quarterly US macroeconomic series. We find that (i) the US economy is well described by a number of structural shocks between two and six. Focusing on the four-shock specification, we identify, using sign restrictions, two non-policy shocks, demand and supply, and two policy shocks, monetary and fiscal. We obtain the following results. (ii) Both supply and demand shocks are important sources of fluctuations; supply prevails for GDP, while demand prevails for employment and inflation. (ii) Policy matters, Both monetary and fiscal policy shocks have sizeable effects on output and prices, with little evidence of crowding out; both monetary and fiscal authorities implement important systematic countercyclical policies reacting to demand shocks. (iii) Negative demand shocks have a large long-run positive effect on productivity, consistently with the Schumpeterian "cleansing" view of recessions.

No news in business cycles

This paper uses a structural, large dimensional factor model to evaluate the role of 'news' shocks (shocks with a delayed effect on productivity) in generating the business cycle. We find that (i) existing small-scale VECM models are affected by 'non-fundamentalness' and therefore fail to recover the correct shock and impulse response functions; (ii) news shocks have a limited role in explaining the business cycle; (iii) their effects are in line with what predicted by standard neoclassical theory; (iv) the bulk of business cycle fluctuations are explained by shocks unrelated to technology.

Entrevistant infants pre-escolars víctimes d’abús sexual i/o maltractament familiar : Eficàcia dels models d’entrevista forense

Entrevistant infants pre-escolars víctimes d’abús sexual i/o maltractament familiar: eficàcia dels models d’entrevista forense Entrevistar infants en edat preescolar que han viscut una situació traumàtica és una tasca complexa que dins l’avaluació psicològica forense necessita d’un protocol perfectament delimitat, clar i temporalitzat. Per això, s’han seleccionat 3 protocols d’entrevista: el Protocol de Menors (PM) de Bull i Birch, el model del National Institute for Children Development (NICHD) de Michel Lamb, a partir del qual es va desenvolupar l’EASI (Evaluación del Abuso Sexual Infantojuvenil) i l’Entrevista Cognitiva (EC) de Fisher i Geiselman. La hipòtesi de partida vol comprovar si els anteriors models permeten obtenir volums informatius diferents en infants preescolars. Conseqüentment, els objectius han estat determinar quin dels models d’entrevista permet obtenir un volum informatiu amb més precisions i menys errors, dissenyar un model d’entrevista propi i consensuar aquest model. En el treball s’afegeixen esquemes pràctics que facilitin l’obertura, desenvolupament i tancament de l’entrevista forense. La metodologia ha reproduït el binomi infant - esdeveniment traumàtic, mitjançant la visualització i l’explicació d’un fet emocionalment significatiu amb facilitat per identificar-se: l’accident en bicicleta d’un infant que cau, es fa mal, sagna i el seu pare el cura. A partir d’aquí, hem entrevistat 135 infants de P3, P4 i P5, mitjançant els 3 models d’entrevista referits, enfrontant-los a una demanda específica: recordar i narrar aquest esdeveniment. S’ha conclòs que el nivell de record correcte, quan s’utilitza un model d’entrevista adequat amb els infants en edat preescolar, oscil•la entre el 70-90%, fet que permet defensar la confiança en els records dels infants. Es constata que el percentatge d’emissions incorrectes dels infants en edat preescolar és mínim, al voltant d’un 5-6%. L’estudi remarca la necessitat d’establir perfectament les regles de l’entrevista i, per últim, en destaca la ineficàcia de les tècniques de memòria de l’entrevista cognitiva en els infants de P3 i P4. En els de P5 es comencen a veure beneficis gràcies a la tècnica de la reinstauració contextual (RC), estant les altres tècniques fora de la comprensió i utilització dels infants d’aquestes edats. Interviewing preschoolers victims of sexual abuse and/or domestic abuse: Effectiveness of forensic interviews models 135 preschool children were interviewed with 3 different interview models in order to remember a significant emotional event. Authors conclude that the correct recall of children ranging from 70-90% and the percentage of error messages is 5-6%. It is necessary to fully establish the rules of the interview. The present research highlights the effectiveness of the cognitive interview techniques in children from P3 and P4. Entrevistando niños preescolares víctimas de abuso sexual y/o maltrato familiar: eficacia de los modelos de entrevista forense Se han entrevistado 135 niños preescolares con 3 modelos de entrevista diferentes para recordar un hecho emocionalmente significativo. Se concluye que el recuerdo correcto de los niños oscila entre el 70-90% y el porcentaje de errores de mensajes es del 5-6%. El estudio remarca la necesidad de establecer perfectamente las reglas de la entrevista y se destaca la ineficacia de las técnicas de la entrevista cognitiva en los niños de P3 y P4.