920 resultados para Sub-registry. Empirical bayesian estimator. General equation. Balancing adjustment factor
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The purpose of this study was to analyze emotions related to a child’s critical illness from the perspective of the family and discuss the link those emotions might form with value creation. High quality service is of paramount importance in hospital care, especially when a child is diagnosed with critical illness. Through the analysis of patient family emotions and their triggers, the study was aiming to deepen the understanding of value creation for customer. Therefore, the research sought to find answers to the following three sub-questions: 1. What are the emotions experienced? 2. What triggers them? 3. How are the emotions linked to amelioration or aggravation of value for patient and family? The theoretical background of this research is built on two core concepts: emotions and value creation. As both concepts are wide and multifaceted, the research concentrates on viewing emotions from the applicable cognitive angle, identifying and categorizing emotions in a general level. Value creation is studied from the service perspective, discussing the possible relations between emotions and value creation. Moreover, the suitability of views regarding customer value co-creation to health care encounters is analyzed. Qualitative approach was selected as the most appropriate methodology for conducting the empirical research. The empirical data was collected from public blogs, for which a total of 18 blogs were reviewed. Five blogs were selected for the analysis, which had the intent of identifying the emotions experienced by patient families and deepening the knowledge of their role in value creation during health care service encounters. The empirical study of this research discovered a wide range of positive and negative emotions, which denotes that a severe life situation does not prevent the feeling of positive emotions. Furthermore, by combining the empirical findings to the theoretical background, this study concludes that recognizing and treating the patient family as a partner and value creator is essential. The high quality technical aspect of care is vital, but it is not the sole attribute for service quality, as the interpersonal communication plays a large role in the customer’s overall assessment of the health care performance. The patients and their families largely evaluate the service encounter based on their perceptions, thus emotions play a significant role. Depending on the service experience, value maybe created or destructed. Hence, this study posits emotion at the core of the service encounter, indicating towards the importance of active assessment of customer perceptions and the recognition of the emotional states
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One of the most disputable matters in the theory of finance has been the theory of capital structure. The seminal contributions of Modigliani and Miller (1958, 1963) gave rise to a multitude of studies and debates. Since the initial spark, the financial literature has offered two competing theories of financing decision: the trade-off theory and the pecking order theory. The trade-off theory suggests that firms have an optimal capital structure balancing the benefits and costs of debt. The pecking order theory approaches the firm capital structure from information asymmetry perspective and assumes a hierarchy of financing, with firms using first internal funds, followed by debt and as a last resort equity. This thesis analyses the trade-off and pecking order theories and their predictions on a panel data consisting 78 Finnish firms listed on the OMX Helsinki stock exchange. Estimations are performed for the period 2003–2012. The data is collected from Datastream system and consists of financial statement data. A number of capital structure characteristics are identified: firm size, profitability, firm growth opportunities, risk, asset tangibility and taxes, speed of adjustment and financial deficit. A regression analysis is used to examine the effects of the firm characteristics on capitals structure. The regression models were formed based on the relevant theories. The general capital structure model is estimated with fixed effects estimator. Additionally, dynamic models play an important role in several areas of corporate finance, but with the combination of fixed effects and lagged dependent variables the model estimation is more complicated. A dynamic partial adjustment model is estimated using Arellano and Bond (1991) first-differencing generalized method of moments, the ordinary least squares and fixed effects estimators. The results for Finnish listed firms show support for the predictions of profitability, firm size and non-debt tax shields. However, no conclusive support for the pecking-order theory is found. However, the effect of pecking order cannot be fully ignored and it is concluded that instead of being substitutes the trade-off and pecking order theory appear to complement each other. For the partial adjustment model the results show that Finnish listed firms adjust towards their target capital structure with a speed of 29% a year using book debt ratio.
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Requirement engineering is a key issue in the development of a software project. Like any other development activity it is not without risks. This work is about the empirical study of risks of requirements by applying machine learning techniques, specifically Bayesian networks classifiers. We have defined several models to predict the risk level for a given requirement using three dataset that collect metrics taken from the requirement specifications of different projects. The classification accuracy of the Bayesian models obtained is evaluated and compared using several classification performance measures. The results of the experiments show that the Bayesians networks allow obtaining valid predictors. Specifically, a tree augmented network structure shows a competitive experimental performance in all datasets. Besides, the relations established between the variables collected to determine the level of risk in a requirement, match with those set by requirement engineers. We show that Bayesian networks are valid tools for the automation of risks assessment in requirement engineering.
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In support of the achievement goal theory (AGT), empirical research has demonstrated psychosocial benefits of the mastery-oriented learning climate. In this study, we examined the effects of perceived coaching behaviors on various indicators of psychosocial well-being (competitive anxiety, self-esteem, perceived competence, enjoyment, and future intentions for participation), as mediated by perceptions of the coach-initiated motivational climate, achievement goal orientations and perceptions of sport-specific skills efficacy. Using a pre-post test design, 1,464 boys, ages 10-15 (M = 12.84 years, SD = 1.44), who participated in a series of 12 football skills clinics were surveyed from various locations across the United States. Using structural equation modeling (SEM) path analysis and hierarchical regression analysis, the cumulative direct and indirect effects of the perceived coaching behaviors on the psychosocial variables at post-test were parsed out to determine what types of coaching behaviors are more conducive to the positive psychosocial development of youth athletes. The study demonstrated that how coaching behaviors are perceived impacts the athletes’ perceptions of the motivational climate and achievement goal orientations, as well as self-efficacy beliefs. These effects in turn affect the athletes’ self-esteem, general competence, sport-specific competence, competitive anxiety, enjoyment, and intentions to remain involved in the sport. The findings also clarify how young boys internalize and interpret coaches’ messages through modification of achievement goal orientations and sport-specific efficacy beliefs.
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Small businesses form a significant share of all businesses and employ a large share of all employees. Therefore, governments are often interested in subsidizing them and especially employment in smaller firms. Nonemployer firms have received special interest, especially in Finland, due to their large share of all businesses. It has been argued that the government should encourage them to hire by subsidizing employment. However, there is no evidence on the effectiveness of such policies. In general, there is surprisingly little evidence on how small firms react to employment subsidies or of employment subsidies targeted according to firm characteristics. The subject of this thesis is the effects of subsidizing the first employee. While theoretical background suggests the subsidy might have efficiency gains, because there might be market inefficiencies that lead to too little employment in small firms. The focus of this research, however, is on the empirical evidence. There was a regional subsidy for hiring the first employee in Finland between 2007 and 2011. Nonemployer firms in the subsidy area were eligible for a wage subsidy for two years when they hired the first employee. The design of the subsidy enables studying the effects in a natural experiment framework that are nowadays popular in public economics. It can be shown that the area without the subsidy provides a good counterfactual to the area where the subsidy was available. Therefore, the effects of the subsidy can be estimated with difference-in-differences method. This method compares the change in the subsidy area to the change in the area without the subsidy. The data used is firm level data spanning from 2000 to 2013. The data is provided by the Finnish Tax Administration including tax declarations by all Finland based companies. The effects for hiring decisions are estimated by examining the effects for alternative variables such as employment, wage expenditure and turnover. According to the results, the subsidy did not have statistically significant effect on any of the variables of interest. Therefore, it can be concluded that the subsidy did not increase hires in nonemployer firms. This implies that the labour demand elasticity of nonemployer firms is very small. The results are in line with previous literature on the effectiveness of general employment subsidies in Scandinavia that suggest that labour demand elasticity is rather small resulting in small or no effects of employment subsidies. However, my research provides new evidence on labour demand of nonemployer firms especially that has not been studied before. The results are in line with the observation that most nonemployer firms are self-employed persons who are not interested in growing their business to employ others as well, but only provide for themselves. Because of this employment subsidies to the self-employed are not particularly well targeted. The theoretical grounds for the subsidy actually hold for other small firms as well, so it can be argued the subsidy would be more effective if it was extended for hiring the first few employees.
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The definition for the notion of a "function" is not cast in stone, but depends upon what we adopt as types in our language. With partial equivalence relations (pers) as types in a relational language, we show that the functional relations are precisely those satisfying the simple equation f = f o fu o f, where "o" and "u" are respectively the composition and converse operators for relations. This article forms part of "A calculational theory of pers as types".
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Problem This dissertation presents a literature-based framework for communication in science (with the elements partners, purposes, message, and channel), which it then applies in and amends through an empirical study of how geoscientists use two social computing technologies (SCTs), blogging and Twitter (both general use and tweeting from conferences). How are these technologies used and what value do scientists derive from them? Method The empirical part used a two-pronged qualitative study, using (1) purposive samples of ~400 blog posts and ~1000 tweets and (2) a purposive sample of 8 geoscientist interviews. Blog posts, tweets, and interviews were coded using the framework, adding new codes as needed. The results were aggregated into 8 geoscientist case studies, and general patterns were derived through cross-case analysis. Results A detailed picture of how geoscientists use blogs and twitter emerged, including a number of new functions not served by traditional channels. Some highlights: Geoscientists use SCTs for communication among themselves as well as with the public. Blogs serve persuasion and personal knowledge management; Twitter often amplifies the signal of traditional communications such as journal articles. Blogs include tutorials for peers, reviews of basic science concepts, and book reviews. Twitter includes links to readings, requests for assistance, and discussions of politics and religion. Twitter at conferences provides live coverage of sessions. Conclusions Both blogs and Twitter are routine parts of scientists' communication toolbox, blogs for in-depth, well-prepared essays, Twitter for faster and broader interactions. Both have important roles in supporting community building, mentoring, and learning and teaching. The Framework of Communication in Science was a useful tool in studying these two SCTs in this domain. The results should encourage science administrators to facilitate SCT use of scientists in their organization and information providers to search SCT documents as an important source of information.
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This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed timevarying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible realtime term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.
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This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed time-varying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible real-time term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.
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Financial constraints influence corporate policies of firms, including both investment decisions and external financing policies. The relevance of this phenomenon has become more pronounced during and after the recent financial crisis in 2007/2008. In addition to raising costs of external financing, the effects of financial crisis limited the availability of external financing which had implications for employment, investment, sale of assets, and tech spending. This thesis provides a comprehensive analysis of the effects of financial constraints on share issuance and repurchases decisions. Financial constraints comprise both internal constraints reflecting the demand for external financing and external financial constraints that relate to the supply of external financing. The study also examines both operating performance and stock market reactions associated with equity issuance methods. The first empirical chapter explores the simultaneous effects of financial constraints and market timing on share issuance decisions. Internal financing constraints limit firms’ ability to issue overvalued equity. On the other hand, financial crisis and low market liquidity (external financial constraints) restrict availability of equity financing and consequently increase the costs of external financing. Therefore, the study explores the extent to which internal and external financing constraints limit market timing of equity issues. This study finds that financial constraints play a significant role in whether firms time their equity issues when the shares are overvalued. The conclusion is that financially constrained firms issue overvalued equity when the external equity market or the general economic conditions are favourable. During recessionary periods, costs of external finance increase such that financially constrained firms are less likely to issue overvalued equity. Only unconstrained firms are more likely to issue overvalued equity even during crisis. Similarly, small firms that need cash flows to finance growth projects are less likely to access external equity financing during period of significant economic recessions. Moreover, constrained firms have low average stock returns compared to unconstrained firms, especially when they issue overvalued equity. The second chapter examines the operating performance and stock returns associated with equity issuance methods. Firms in the UK can issue equity through rights issues, open offers, and private placement. This study argues that alternative equity issuance methods are associated with a different level of operating performance and long-term stock returns. Firms using private placement are associated with poor operating performance. However, rights issues are found empirically to be associated with higher operating performance and less negative long-term stock returns after issuance in comparison to counterpart firms that issue private placements and open offers. Thus, rights issuing firms perform better than open offers and private placement because the favourable operating performance at the time of issuance generates subsequent positive long-run stock price response. Right issuing firms are of better quality and outperform firms that adopt open offers and private placement. In the third empirical chapter, the study explores the levered share repurchase of internally financially unconstrained firms. Unconstrained firms are expected to repurchase their shares using internal funds rather than through external borrowings. However, evidence shows that levered share repurchases are common among unconstrained firms. These firms display this repurchase behaviour when they have bond ratings or investment grade ratings that allow them to obtain cheap external debt financing. It is found that internally financially unconstrained firms borrow to finance their share repurchase when they invest more. Levered repurchase firms are associated with less positive abnormal returns than unlevered repurchase firms. For the levered repurchase sample, high investing firms are associated with more positive long-run abnormal stock returns than low investing firms. It appears the market underreact to the levered repurchase in the short-run regardless of the level of investments. These findings indicate that market reactions reflect both undervaluation and signaling hypotheses of positive information associated with share repurchase. As the firms undertake capital investments, they generate future cash flows, limit the effects of leverage on financial distress and ultimately reduce the risk of the equity capital.
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Objectives: Because there is scientific evidence that an appropriate intake of dietary fibre should be part of a healthy diet, given its importance in promoting health, the present study aimed to develop and validate an instrument to evaluate the knowledge of the general population about dietary fibres. Study design: The present study was a cross sectional study. Methods: The methodological study of psychometric validation was conducted with 6010 participants, residing in ten countries from 3 continents. The instrument is a questionnaire of self-response, aimed at collecting information on knowledge about food fibres. For exploratory factor analysis (EFA) was chosen the analysis of the main components using varimax orthogonal rotation and eigenvalues greater than 1. In confirmatory factor analysis by structural equation modelling (SEM) was considered the covariance matrix and adopted the Maximum Likelihood Estimation algorithm for parameter estimation. Results: Exploratory factor analysis retained two factors. The first was called Dietary Fibre and Promotion of Health (DFPH) and included 7 questions that explained 33.94 % of total variance ( = 0.852). The second was named Sources of Dietary Fibre (SDF) and included 4 questions that explained 22.46% of total variance ( = 0.786). The model was tested by SEM giving a final solution with four questions in each factor. This model showed a very good fit in practically all the indexes considered, except for the ratio 2/df. The values of average variance extracted (0.458 and 0.483) demonstrate the existence of convergent validity; the results also prove the existence of discriminant validity of the factors (r2 = 0.028) and finally good internal consistency was confirmed by the values of composite reliability (0.854 and 0.787). Conclusions: This study allowed validating the KADF scale, increasing the degree of confidence in the information obtained through this instrument in this and in future studies.
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A presente investigação empírica, desenvolvida na área da formação contínua, procura compreender como se processa a formação continua em contexto de trabalho dos enfermeiros de uma organização hospitalar, centrando-se na percepção e representações dos enfermeiros de cuidados gerais sobre a qualidade, autopercepção do impacte e importância da formação no desenvolvimento de competências e motivação para a participação na formação contínua, como forma de promover o desenvolvimento de competências. Considerando-se que a problemática do paradigma da formação, subsiste na falta de articulação entre os processos comunicacionais, motivadores, procedimentais e dos recursos à disposição dos usuários e gestores da formação, a nível micro dos serviços da organização e macro da tutela o que contribui para a inexistência de resultados quantificáveis, em termos de eficácia e eficiência da formação no desenvolvimento de competências dos colaboradores e crescimento da organização. Apesar da formação contínua, nas organizações, objectivar o desenvolvimento de competências, implicar a construção de um quadro de referência a partir de uma abordagem multidisciplinar, de forma a incluir a complexidade dos fenómenos, a investigação dos factores determinantes que concorrem para a performance dos enfermeiros, parece ser uma abordagem imprescindível para compreender e analisar a problemática na sua dimensão. O estudo empírico consistiu numa investigação exploratória/descritiva, partindo de uma amostragem não probabilística, optando-se por uma metodologia quantitativa, através da aplicação de questionários a 208 enfermeiros da prestação de cuidados, de uma organização hospitalar pública EPE, da Administração Regional de Saúde de Lisboa e Vale do Tejo. Esta investigação permitiu verificar que no geral, os enfermeiros têm uma percepção positiva sobre a qualidade da formação contínua desenvolvida no serviço onde desempenham funções. Maioritariamente consideram importante a formação contínua como factor de desenvolvimento de competências, sentem-se motivados e participam activamente na formação. No entanto, não se conseguiu efectuar qualquer tipo de inferências ou correlações entre as variáveis de estudo constatando-se que os enfermeiros responderam frequentemente e Sempre, na grande maioria das questões, havendo heterogenia nas respostas a questões semelhantes. O estudo demonstrou que apesar da percepção positiva dos enfermeiros sobre a formação contínua desenvolvida no serviço, não se consegue ter a verdadeira percepção de como é conduzida a formação em serviço qual o seu impacte na melhoria do desempenho dos enfermeiros e se a organização evidencia uma cultura de formação voltada para uma estratégia de melhoria continua das qualificações dos enfermeiros. À luz dos resultados, foi desenvolvido um projecto de intervenção sócio-organizacional na área da gestão da formação, numa perspectiva de estratégia de desenvolvimento organizacional, melhoria das competências individuais e proposto um portfólio de descrição de funções do enfermeiro responsável pela formação. ABSTRACT: This study, based on the issues of continuous professional training in the hospital setting, as a factor to develop nurses competencies, intends to understand how the training program in the hospital milieu is conducted, focusing on perceptions and concepts of quality, impact, importance and motivation to participate in ongoing professional training, according to general care registered nurses point of view. The study main goal is to identify how is developed professional training in a medical institution from Sub-Região de Saúde de Lisboa and Vale do Tejo, and evaluate the impact of the training program. Considering that a problematic exists in the articulation between the communication processes, motivational drives, procedures and resources at the disposition of the participants and managers of the professional development program, at a micro level of services in the organization and at a macro level of the government policies and organizational strategies leaders; which contributed to the absence of quantifiable results and little evidence, in terms of efficiency of the professional development program to enhance the professional competencies of those participating in the study. The investigation of the factorial determinants related to nurse’s efficient performance enhanced by participating in continuous professional training, seems to be an imperative approach to understand and analyze the problematic in its own dimension. The empirical study consisted in an exploratory/descriptive investigation, departing from a random sample, by means of a quantitative methodology approach; through the use of questionnaires being administered to 208 nurses in general care, from a public medical organization. This study, allowed to verify that nurses have a positive perception of the professional development programs established in their workplace, and the competencies of those nurses in charge of delivering the program. The majority, considered the maintenance of a continuous professional development program, imperative to maintain good professional skills; they feel motivated and actively participate in professional development programs. However, it was not possible to make any correlations between the variables of the study, noticing that the nurses answered frequently and always, to the majority of the questions. The study demonstrated that even though nurses have a positive perception of professional development in terms of their workplace, it was inconclusive to ascertain the training quality programs delivered at medical facilities. ln conclusion, a plan of intervention centered on a socio-organizational model, was developed to create a uniform, procedural approach to developing high standards competencies for the registered nurses, by a professional training program, that include monitoring the process and assessing the results of the program. Management competencies according to a balanced scorecard it's another proposal of this study.
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Cette thèse développe des méthodes bootstrap pour les modèles à facteurs qui sont couram- ment utilisés pour générer des prévisions depuis l'article pionnier de Stock et Watson (2002) sur les indices de diffusion. Ces modèles tolèrent l'inclusion d'un grand nombre de variables macroéconomiques et financières comme prédicteurs, une caractéristique utile pour inclure di- verses informations disponibles aux agents économiques. Ma thèse propose donc des outils éco- nométriques qui améliorent l'inférence dans les modèles à facteurs utilisant des facteurs latents extraits d'un large panel de prédicteurs observés. Il est subdivisé en trois chapitres complémen- taires dont les deux premiers en collaboration avec Sílvia Gonçalves et Benoit Perron. Dans le premier article, nous étudions comment les méthodes bootstrap peuvent être utilisées pour faire de l'inférence dans les modèles de prévision pour un horizon de h périodes dans le futur. Pour ce faire, il examine l'inférence bootstrap dans un contexte de régression augmentée de facteurs où les erreurs pourraient être autocorrélées. Il généralise les résultats de Gonçalves et Perron (2014) et propose puis justifie deux approches basées sur les résidus : le block wild bootstrap et le dependent wild bootstrap. Nos simulations montrent une amélioration des taux de couverture des intervalles de confiance des coefficients estimés en utilisant ces approches comparativement à la théorie asymptotique et au wild bootstrap en présence de corrélation sérielle dans les erreurs de régression. Le deuxième chapitre propose des méthodes bootstrap pour la construction des intervalles de prévision permettant de relâcher l'hypothèse de normalité des innovations. Nous y propo- sons des intervalles de prédiction bootstrap pour une observation h périodes dans le futur et sa moyenne conditionnelle. Nous supposons que ces prévisions sont faites en utilisant un ensemble de facteurs extraits d'un large panel de variables. Parce que nous traitons ces facteurs comme latents, nos prévisions dépendent à la fois des facteurs estimés et les coefficients de régres- sion estimés. Sous des conditions de régularité, Bai et Ng (2006) ont proposé la construction d'intervalles asymptotiques sous l'hypothèse de Gaussianité des innovations. Le bootstrap nous permet de relâcher cette hypothèse et de construire des intervalles de prédiction valides sous des hypothèses plus générales. En outre, même en supposant la Gaussianité, le bootstrap conduit à des intervalles plus précis dans les cas où la dimension transversale est relativement faible car il prend en considération le biais de l'estimateur des moindres carrés ordinaires comme le montre une étude récente de Gonçalves et Perron (2014). Dans le troisième chapitre, nous suggérons des procédures de sélection convergentes pour les regressions augmentées de facteurs en échantillons finis. Nous démontrons premièrement que la méthode de validation croisée usuelle est non-convergente mais que sa généralisation, la validation croisée «leave-d-out» sélectionne le plus petit ensemble de facteurs estimés pour l'espace généré par les vraies facteurs. Le deuxième critère dont nous montrons également la validité généralise l'approximation bootstrap de Shao (1996) pour les regressions augmentées de facteurs. Les simulations montrent une amélioration de la probabilité de sélectionner par- cimonieusement les facteurs estimés comparativement aux méthodes de sélection disponibles. L'application empirique revisite la relation entre les facteurs macroéconomiques et financiers, et l'excès de rendement sur le marché boursier américain. Parmi les facteurs estimés à partir d'un large panel de données macroéconomiques et financières des États Unis, les facteurs fortement correlés aux écarts de taux d'intérêt et les facteurs de Fama-French ont un bon pouvoir prédictif pour les excès de rendement.
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Este trabajo tiene como objetivo la mejora en la validación de la simulación numérica del flujo bifásico característico del transporte de lecho fluido, mediante la formulación y desarrollo de un modelo numérico combinado Volúmenes Finitos - Elementos Finitos. Para ello se simula numéricamente el flujo de mezcla sólido-gas en una Cámara de Lecho Fluido, bajo implementación en código COMSOL, cuyos resultados son mejores comparativamente a un modelo basado en el método de Elementos Discretos implementado en código abierto MFIX. El problema fundamental de la modelización matemática del fenómeno de lecho fluido es la irregularidad del dominio, el acoplamiento de las variables en espacio y tiempo y, la no linealidad. En esta investigación se reformula apropiadamente las ecuaciones conservativas del fenómeno, tales que permitan obtener un problema variacional equivalente y solucionable numéricamente. Entonces; se define una ecuación de estado en función de la presión hidrodinámica y la fracción volumétrica de sólidos, quedando desacoplado el sistema en tres sub-problemas, garantizando así la existencia de solución del problema general. Una vez aproximados numéricamente ambos modelos, se comparan los resultados de donde se observa que el modelo materia del presente artículo, verifica de forma más eficaz las condiciones de mezcla óptima, reflejada en la calidad del burbujeo y velocidad de mezcla.