879 resultados para Panel Data Model
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Unemployment is related to economic, political and social aspects. One of the least analysed social aspects is the relationship between unemployment and the (individual) perceived levels of well-being, such as life satisfaction or happiness. This chapter complements previous work on the subject, using a panel-data econometrics methodology to analyze the relationship between unemployment and life satisfaction in a wide range of countries worldwide. The results confirm that unemployment has a negative effect, statistically significant, on life satisfaction, either for men or for women.
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Dissertação de Mestrado, Finanças Empresariais, Faculdade de Economia, Universidade do Algarve, 2015
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In this study, we examine the relationship between good corporate governance practices and the creation of value/performance of credit unions from 2010 to 2012. The objective was to create and validate a corporate governance index for credit unions, and to then analyse the relationship between good governance practices and the creation of value/performance. The problem question is: do good corporate governance practices provide value creation for credit unions? The research started by creating indices from factor analysis to identify latent dependent variables related to value creation and performance; next indices were created from the principal component analysis for the creation of independent latent variables related to corporate governance. Finally, based on panel data from regression models, the influence of the variables and indices related to corporate governance on the indices of value creation and performance was verified. Based on the research, it became evident that the Corporate Governance Index (IGC) is mainly impacted by Executive Management, with 40.31% of the IGC value, followed by the Representation and Participation dimension, with 34.07% of the IGC value. The contribution for academics was the creation of the Corporate Governance Index (IGC) applied for credit unions. As for the contribution to the system of credit unions, the highlight was the effectiveness of the mechanisms for economic-financial and asset management adopted by BACEN, credit unions and OCEMG.
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This dissertation comprised of three essays provides justification for the need to pursue research on multinationality and performance with a more fine-grained approach. Essay one is a conceptual response to an article written by Jean-Francois Hennart in 2011 which questions the need and approach toward future research in this domain. I argue that internalization theory does not render multinationality and performance research meaningless and identify key areas where methodological enhancements can be made to strengthen our research findings with regard to Hennart’s call for more content validity. Essay two responds to the need for more-fine grained research on the consequences of multinationality by introducing non-traditional measures of performance such as social and environmental performance and adopting a more theoretically relevant construct of regionalization to capture international diversification levels of the firm. Using data from the world’s largest 600 firms (based on sales) derived from Bloomberg and the Directory of Corporate Affiliates; I employ general estimating equation analysis to account for the auto-correlated nature of the panel data alongside multivariate regression techniques. Results indicate that regionalization has a positive relationship with economic performance while it has a negative relationship with environmental and social performance outcomes, often referred to as the “Triple Bottom-Line” performance. Essay three builds upon the work in the previous essays by linking the aforementioned performance variables and sample to corporate reputation which has been shown to be a beneficial strategic asset. Using Structural Equation Modeling I explore economic, environmental and social signals as mediators on relationship between regionalization and firm reputation. Results indicate that these variables partially mediate a positive relationship between regionalization and firm reputation. While regionalization positively affects the reputation building signal of economic performance, it aids in reputation building by reducing environmental and social disclosure effects which interestingly impact reputation negatively. In conclusion, the dissertation submits opportunities for future research and contributes to research by demonstrating that regionalization affects performance, but the effect varies in accordance with the performance criterion and context. In some cases, regional diversification may produce competing or conflicting outcomes among the potential strategic objectives of the firm.
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Este documento evidencia las posiciones hegemónicas que han llegado a ocupar las empresas más poderosas del país, basándose en el estudio de datos cuantitativos del conteo de las cien empresas con mejores ventas para los años 2013 y 2014, según la revista Gerente. Se usan cinco variables: ventas totales, activos, pasivos, patrimonio y utilidades netas. En la primera sección, se hace una revisión bibliográfica que conecta el origen de la hegemonía en un panorama económico con la influencia del neoliberalismo y la globalización en el actual tejido industrial colombiano. Posteriormente, se realiza una explicación sobre la metodología aplicada para el estudio de la base de datos; la cual es seguida por una exposición de los resultados obtenidos a partir de herramientas estadísticas como el análisis de correlación lineal, quintiles y variaciones porcentuales. Finalmente, se aborda el Programa de Transformación Productiva, esto con el objetivo de mostrar los puntos focales que necesitan especial atención para lograr catalizar el desarrollo económico de Colombia.
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¿Cuáles son los efectos de la guerra sobre el comportamiento político? Colombia es un caso interesante en el que el conflicto y las elecciones coexisten y los grupos armados ilegales intencionalmente afectan los resultados electorales. Sin embargo, los grupos usan diferentes estrategias para alterar estos resultados. Este artículo argumenta que los efectos diferenciales de la violencia sobre los resultados electorales son el resultado de estrategias deliberadas de los grupos ilegales, que a su turno, son consecuencia de las condiciones militares que difieren entre ellos. Usando datos panel de las elecciones al Senado de 1994 a 2006 y una aproximación por variables instrumentales para resolver posibles problemas de endogenidad, este artículo muestra que la violencia guerrillera disminuye la participación electoral, mientras que la violencia paramilitar no tiene ningún efecto sobre la participación pero reduce la competencia electoral y beneficia a nuevos partidos no-tradicionales. Esto es consistente con la hipótesis de que la estrategia de la guerrilla es sabotear las elecciones, mientras que los paramiltares establecen alianzas con ciertos candidatos.
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We explore the determinants of usage of six different types of health care services, using the Medical Expenditure Panel Survey data, years 1996-2000. We apply a number of models for univariate count data, including semiparametric, semi-nonparametric and finite mixture models. We find that the complexity of the model that is required to fit the data well depends upon the way in which the data is pooled across sexes and over time, and upon the characteristics of the usage measure. Pooling across time and sexes is almost always favored, but when more heterogeneous data is pooled it is often the case that a more complex statistical model is required.
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Background: Analyses of population structure and breed diversity have provided insight into the origin and evolution of cattle. Previously, these studies have used a low density of microsatellite markers, however, with the large number of single nucleotide polymorphism markers that are now available, it is possible to perform genome wide population genetic analyses in cattle. In this study, we used a high-density panel of SNP markers to examine population structure and diversity among eight cattle breeds sampled from Bos indicus and Bos taurus. Results: Two thousand six hundred and forty one single nucleotide polymorphisms ( SNPs) spanning all of the bovine autosomal genome were genotyped in Angus, Brahman, Charolais, Dutch Black and White Dairy, Holstein, Japanese Black, Limousin and Nelore cattle. Population structure was examined using the linkage model in the program STRUCTURE and Fst estimates were used to construct a neighbor-joining tree to represent the phylogenetic relationship among these breeds. Conclusion: The whole-genome SNP panel identified several levels of population substructure in the set of examined cattle breeds. The greatest level of genetic differentiation was detected between the Bos taurus and Bos indicus breeds. When the Bos indicus breeds were excluded from the analysis, genetic differences among beef versus dairy and European versus Asian breeds were detected among the Bos taurus breeds. Exploration of the number of SNP loci required to differentiate between breeds showed that for 100 SNP loci, individuals could only be correctly clustered into breeds 50% of the time, thus a large number of SNP markers are required to replace the 30 microsatellite markers that are currently commonly used in genetic diversity studies.
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Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.
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Objectives. In this study, we aimed to identify ancestry informative haplotypes and make interethnic admixture estimates using X-chromosome markers. Methods. A significant sample (461 individuals) of European, African, and Native American populations was analyzed, and four linkage groups were identified. The data obtained were used to describe the ancestral contribution of populations from four different geographical regions of Brazil (745 individuals). Results. The global interethnic admixture estimates of the four mixed populations under investigation were calculated applying all the 24 insertion/deletion (INDEL) markers. In the North region, a larger Native Americans ancestry was observed (42%). The Northeast and Southeast regions had smaller Native American contribution (27% in both of them). In the South region, there was a large European contribution (46%). Conclusions. The estimates obtained are compatible with expectations for a colonization model with biased admixture between European men (one X chromosome) and Native American and African women (two X chromosomes), so the 24 X-INDEL panel described here can be a useful to make admixture interethnic estimates in Brazilian populations. Am. J. Hum. Biol. 22:849-852,2010. (C) 2010 Wiley-Liss, Inc.
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Historically, the cure rate model has been used for modeling time-to-event data within which a significant proportion of patients are assumed to be cured of illnesses, including breast cancer, non-Hodgkin lymphoma, leukemia, prostate cancer, melanoma, and head and neck cancer. Perhaps the most popular type of cure rate model is the mixture model introduced by Berkson and Gage [1]. In this model, it is assumed that a certain proportion of the patients are cured, in the sense that they do not present the event of interest during a long period of time and can found to be immune to the cause of failure under study. In this paper, we propose a general hazard model which accommodates comprehensive families of cure rate models as particular cases, including the model proposed by Berkson and Gage. The maximum-likelihood-estimation procedure is discussed. A simulation study analyzes the coverage probabilities of the asymptotic confidence intervals for the parameters. A real data set on children exposed to HIV by vertical transmission illustrates the methodology.
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When the data consist of certain attributes measured on the same set of items in different situations, they would be described as a three-mode three-way array. A mixture likelihood approach can be implemented to cluster the items (i.e., one of the modes) on the basis of both of the other modes simultaneously (i.e,, the attributes measured in different situations). In this paper, it is shown that this approach can be extended to handle three-mode three-way arrays where some of the data values are missing at random in the sense of Little and Rubin (1987). The methodology is illustrated by clustering the genotypes in a three-way soybean data set where various attributes were measured on genotypes grown in several environments.
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In many occupational safety interventions, the objective is to reduce the injury incidence as well as the mean claims cost once injury has occurred. The claims cost data within a period typically contain a large proportion of zero observations (no claim). The distribution thus comprises a point mass at 0 mixed with a non-degenerate parametric component. Essentially, the likelihood function can be factorized into two orthogonal components. These two components relate respectively to the effect of covariates on the incidence of claims and the magnitude of claims, given that claims are made. Furthermore, the longitudinal nature of the intervention inherently imposes some correlation among the observations. This paper introduces a zero-augmented gamma random effects model for analysing longitudinal data with many zeros. Adopting the generalized linear mixed model (GLMM) approach reduces the original problem to the fitting of two independent GLMMs. The method is applied to evaluate the effectiveness of a workplace risk assessment teams program, trialled within the cleaning services of a Western Australian public hospital.