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Tři eseje o finančním rozvoji / Three Essays on Financial DevelopmentMareš, Jan January 2020 (has links)
The dissertation is a compilation of three empirical papers on the effects of financial development. In the first paper, we examine finance's effect on long-term economic growth using Bayesian model averaging to address model uncertainty. Our global sample findings indicate that the efficiency of financial intermediation is robustly related to long-term growth. The second and third papers investigate the determinants of wealth and income inequality, capturing various economic, financial, political, institutional, and geographical factors. We reveal that finance plays a considerable role in shaping both distributions.
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Ekonomická nerovnost a percepce štěstí: Meta-analýza / Income Inequality and Happiness: A Meta-AnalysisKamenická, Lucie January 2021 (has links)
The relationship between income inequality and happiness is central to a host of welfare policies. If higher income inequality puts people down, advocating for income redistribution from the rich to the poor could make society happier. We show, however, that this popular consensus on the relationship's direction is rather absent in the academic literature. Based on the 868 observations col- lected from 53 studies and controlling for 62 aspects of study design, we use state-of-the-art meta-analysis techniques to identify several important drivers of the efect. Unless each study gets the same weight, the literature is driven by publication bias pushing the estimates against the popular consensus. While geographical diferences dominate among the systematic infuences of the re- lationship's magnitude, the relationship is also strongly afected by various methods and data the authors use in the primary studies. Most prominently, it matters if authors control for diferent individual's characteristics, such as perceived trust in people or their health status.
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A Comprehensive Approach to Posterior Jointness Analysis in Bayesian Model Averaging ApplicationsCrespo Cuaresma, Jesus, Grün, Bettina, Hofmarcher, Paul, Humer, Stefan, Moser, Mathias 03 1900 (has links) (PDF)
Posterior analysis in Bayesian model averaging (BMA) applications often includes the assessment of measures of jointness (joint inclusion) across covariates.
We link the discussion of jointness measures in the econometric literature to the literature on association rules in data mining exercises. We analyze a group of alternative jointness measures that include those proposed in the BMA literature and several others put forward in the field of data mining. The way these measures address the joint exclusion of covariates appears particularly important in terms of the conclusions that can be drawn from them. Using a dataset of economic growth determinants, we assess how the measurement of jointness in BMA can affect inference about the structure of bivariate inclusion patterns across covariates. (authors' abstract) / Series: Department of Economics Working Paper Series
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Validation des modèles statistiques tenant compte des variables dépendantes du temps en prévention primaire des maladies cérébrovasculairesKis, Loredana 07 1900 (has links)
L’intérêt principal de cette recherche porte sur la validation d’une méthode
statistique en pharmaco-épidémiologie. Plus précisément, nous allons comparer
les résultats d’une étude précédente réalisée avec un devis cas-témoins niché dans
la cohorte utilisé pour tenir compte de l’exposition moyenne au traitement :
– aux résultats obtenus dans un devis cohorte, en utilisant la variable exposition
variant dans le temps, sans faire d’ajustement pour le temps passé
depuis l’exposition ;
– aux résultats obtenus en utilisant l’exposition cumulative pondérée par le
passé récent ;
– aux résultats obtenus selon la méthode bayésienne.
Les covariables seront estimées par l’approche classique ainsi qu’en utilisant
l’approche non paramétrique bayésienne. Pour la deuxième le moyennage bayésien
des modèles sera utilisé pour modéliser l’incertitude face au choix des modèles.
La technique utilisée dans l’approche bayésienne a été proposée en 1997 mais
selon notre connaissance elle n’a pas été utilisée avec une variable dépendante du
temps. Afin de modéliser l’effet cumulatif de l’exposition variant dans le temps,
dans l’approche classique la fonction assignant les poids selon le passé récent sera
estimée en utilisant des splines de régression.
Afin de pouvoir comparer les résultats avec une étude précédemment réalisée,
une cohorte de personnes ayant un diagnostique d’hypertension sera construite
en utilisant les bases des données de la RAMQ et de Med-Echo.
Le modèle de Cox incluant deux variables qui varient dans le temps sera
utilisé. Les variables qui varient dans le temps considérées dans ce mémoire sont
iv
la variable dépendante (premier évènement cérébrovasculaire) et une des variables
indépendantes, notamment l’exposition / The main interest of this research is the validation of a statistical method
in pharmacoepidemiology. Specifically, we will compare the results of a previous
study performed with a nested case-control which took into account the average
exposure to treatment to :
– results obtained in a cohort study, using the time-dependent exposure, with
no adjustment for time since exposure ;
– results obtained using the cumulative exposure weighted by the recent past ;
– results obtained using the Bayesian model averaging.
Covariates are estimated by the classical approach and by using a nonparametric
Bayesian approach. In the later, the Bayesian model averaging will be used to
model the uncertainty in the choice of models. To model the cumulative effect of
exposure which varies over time, in the classical approach the function assigning
weights according to recency will be estimated using regression splines.
In order to compare the results with previous studies, a cohort of people diagnosed
with hypertension will be constructed using the databases of the RAMQ
and Med-Echo.
The Cox model including two variables which vary in time will be used. The
time-dependent variables considered in this paper are the dependent variable (first
stroke event) and one of the independent variables, namely the exposure.
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Bayesian and Frequentist Approaches for the Analysis of Multiple Endpoints Data Resulting from Exposure to Multiple Health Stressors.Nyirabahizi, Epiphanie 08 March 2010 (has links)
In risk analysis, Benchmark dose (BMD)methodology is used to quantify the risk associated with exposure to stressors such as environmental chemicals. It consists of fitting a mathematical model to the exposure data and the BMD is the dose expected to result in a pre-specified response or benchmark response (BMR). Most available exposure data are from single chemical exposure, but living objects are exposed to multiple sources of hazards. Furthermore, in some studies, researchers may observe multiple endpoints on one subject. Statistical approaches to address multiple endpoints problem can be partitioned into a dimension reduction group and a dimension preservative group. Composite scores using desirability function is used, as a dimension reduction method, to evaluate neurotoxicity effects of a mixture of five organophosphate pesticides (OP) at a fixed mixing ratio ray, and five endpoints were observed. Then, a Bayesian hierarchical model approach, as a single unifying dimension preservative method is introduced to evaluate the risk associated with the exposure to mixtures chemicals. At a pre-specied vector of BMR of interest, the method estimates a tolerable area referred to as benchmark dose tolerable area (BMDTA) in multidimensional Euclidean plan. Endpoints defining the BMDTA are determined and model uncertainty and model selection problems are addressed by using the Bayesian Model Averaging (BMA) method.
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Důchodová elasticita poptávky po vodě: Meta-analýza / Income Elasticity of Water Demand: A Meta-AnalysisVlach, Tomáš January 2016 (has links)
If policymakers address water scarcity with the demand-oriented approach, the income elasticity of water demand is of pivotal importance. Its estimates, however, differ considerably. We collect 307 estimates of the income elasticity of water demand reported in 62 studies, codify 31 variables describing the estimation design, and employ Bayesian model averaging to address model uncertainty inherent to any meta-analysis. The studies were published between 1972 and 2015, which means that this meta-analysis covers a longer period of time than two previous meta-analyses on this topic combined. Our results suggest that income elasticity estimates for developed countries do not significantly differ from income elasticity estimates for developing countries and that different estimation techniques do not systematically produce different values of the income elasticity of water demand. We find evidence of publication selection bias in the literature on the income elasticity of water demand with the use of both graphical and regression analysis. We correct the estimates for publication selection bias and estimate the true effect beyond bias, which reaches approximately 0.2. 1
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Ohodnocování a predikce systémového rizika: Systém včasného varovaní navržený pro Českou republiku / Systemic Risks Assessment and Systemic Events Prediction: Early Warning System Design for the Czech RepublicŽigraiová, Diana January 2013 (has links)
This thesis develops an early warning system framework for assessing systemic risks and for predicting systemic events, i.e. periods of extreme financial instability with potential real costs, over the short horizon of six quarters and the long horizon of twelve quarters on the panel of 14 countries both advanced and developing. Firstly, Financial Stress Index is built aggregating indicators from equity, foreign exchange, security and money markets in order to identify starting dates of systemic financial crises for each country in the panel. Secondly, the selection of early warning indicators for assessment and prediction of systemic risks is undertaken in a two- step approach; relevant prediction horizons for each indicator are found by means of a univariate logit model followed by the application of Bayesian model averaging method to identify the most useful indicators. Next, logit models containing useful indicators only are estimated on the panel while their in-sample and out-of-sample performance is assessed by a variety of measures. Finally, having applied the constructed EWS for both horizons to the Czech Republic it was found that even though models for both horizons perform very well in-sample, i.e. both predict 100% of crises, only the long model attains the maximum utility of 0,5 as...
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Obchodovaný objem a očekávané výnosy akcií: metaanalýza / Trading volume and expected stock returns: a meta-analysisBajzík, Josef January 2019 (has links)
I investigate the relationship between expected stock returns and trading volume. I collect together 522 estimates from 46 studies and conduct the first meta-analysis in this field. Use of Bayesian model averaging and Frequentist model averaging help me to discover the most influential factors that affect the return-volume relationship, since I control for more than 50 differences among primary articles such as midyear and type of data, length of the primary dataset, size of market, or model employed. In the end, I find out that the relation between expected stock returns and trading volume is rather negligible. On the other hand, the contemporaneous relation between returns and volume is positive. These two findings cut the mixed results from previously written studies. Moreover, the investigated relationship is influenced by the size of country of interest and the level of its development. Besides the primary studies that employ higher data frequency provide substantially larger estimates than the studies with data from longer time periods. On the contrary, there is no difference among different estimation methodologies used. Finally, I employ classical and modern techniques such as stem-based methodology for publication bias detection, and I find evidence for it in this field. 1
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Ponderação bayesiana de modelos utilizando diferentes séries de precipitação aplicada à simulação chuva-vazão na Bacia do Ribeirão da Onça / Ponderação bayesiana de modelos utilizando diferentes séries de precipitação aplicada à simulação chuva-vazão na Bacia do Ribeirão da OnçaMeira Neto, Antônio Alves 11 July 2013 (has links)
Neste trabalho foi proposta uma estratégia de modelagem hidrológica para a transformação chuva vazão da Bacia do Ribeirão da Onça (B.R.O) utilizando-se técnicas de auto calibração com análise de incertezas e de ponderação de modelos. Foi utilizado o modelo hidrológico Soil and Water Assessment Tool (SWAT), por ser um modelo que possui uma descrição física e de maneira distribuída dos processos hidrológicos da bacia. Foram propostas cinco diferentes séries de precipitação e esquemas de interpolação espacial a serem utilizados como dados de entrada para o modelo SWAT. Em seguida, utilizou-se o método semiautomático Sequential Uncertainty Fitting ver.-2 (SUFI-2) para a auto calibração e análise de incertezas dos parâmetros do modelo e produção de respostas com intervalos de incerteza para cada uma das séries de precipitação utilizadas. Por fim, foi utilizado o método de ponderação bayesiana de modelos (BMA) para o pós-processamento estocástico das respostas. Os resultados da análise de incerteza dos parâmetros do modelo SWAT indicam uma não adequação do método Soil Conservation Service (SCS) para simulação da geração do escoamento superficial, juntamente com uma necessidade de maior investigação das propriedades físicas do solo da bacia. A análise da precisão e acurácia dos resultados das séries de precipitação em comparação com a resposta combinada pelo método BMA sugerem a última como a mais adequada para a simulação chuva-vazão na B.R.O. / This study proposed an approach to the hydrological modeling of the Ribeirão da Onças Basin (B.R.O) based on automatic calibration and uncertainty analysis methods, together with model averaging. The Soil and Water Assessment Tool (SWAT) was used due to its distributed nature and physical description of hydrologic processes. An ensemble, composed by five different precipitation schemes, based on different sources and spatial interpolation methods was used. The Sequential Uncertainty Fitting ver-2 (SUFI-2) procedure was used for automatic calibration and uncertainty analysis of the SWAT model parameters, together with generation of streamflow simulations with uncertainty intervals. Following, the Bayesian Model Averaging (BMA) was used to merge the different responses into a single probabilistic forecast. The results of the uncertainty analysis for the SWAT parameters show that the Soil Conservation Service (SCS) model for surface runoff prediction may not be suitable for the B.R.O, and that more investigations about the soil physical properties at the Basin are recommended. An analysis of the accuracy and precision of the simulations produced by the precipitation ensemble members against the BMA simulation supports the use of the latter as a suitable framework for streamflow simulations at the B.R.O.
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Validation des modèles statistiques tenant compte des variables dépendantes du temps en prévention primaire des maladies cérébrovasculairesKis, Loredana 07 1900 (has links)
L’intérêt principal de cette recherche porte sur la validation d’une méthode
statistique en pharmaco-épidémiologie. Plus précisément, nous allons comparer
les résultats d’une étude précédente réalisée avec un devis cas-témoins niché dans
la cohorte utilisé pour tenir compte de l’exposition moyenne au traitement :
– aux résultats obtenus dans un devis cohorte, en utilisant la variable exposition
variant dans le temps, sans faire d’ajustement pour le temps passé
depuis l’exposition ;
– aux résultats obtenus en utilisant l’exposition cumulative pondérée par le
passé récent ;
– aux résultats obtenus selon la méthode bayésienne.
Les covariables seront estimées par l’approche classique ainsi qu’en utilisant
l’approche non paramétrique bayésienne. Pour la deuxième le moyennage bayésien
des modèles sera utilisé pour modéliser l’incertitude face au choix des modèles.
La technique utilisée dans l’approche bayésienne a été proposée en 1997 mais
selon notre connaissance elle n’a pas été utilisée avec une variable dépendante du
temps. Afin de modéliser l’effet cumulatif de l’exposition variant dans le temps,
dans l’approche classique la fonction assignant les poids selon le passé récent sera
estimée en utilisant des splines de régression.
Afin de pouvoir comparer les résultats avec une étude précédemment réalisée,
une cohorte de personnes ayant un diagnostique d’hypertension sera construite
en utilisant les bases des données de la RAMQ et de Med-Echo.
Le modèle de Cox incluant deux variables qui varient dans le temps sera
utilisé. Les variables qui varient dans le temps considérées dans ce mémoire sont
iv
la variable dépendante (premier évènement cérébrovasculaire) et une des variables
indépendantes, notamment l’exposition / The main interest of this research is the validation of a statistical method
in pharmacoepidemiology. Specifically, we will compare the results of a previous
study performed with a nested case-control which took into account the average
exposure to treatment to :
– results obtained in a cohort study, using the time-dependent exposure, with
no adjustment for time since exposure ;
– results obtained using the cumulative exposure weighted by the recent past ;
– results obtained using the Bayesian model averaging.
Covariates are estimated by the classical approach and by using a nonparametric
Bayesian approach. In the later, the Bayesian model averaging will be used to
model the uncertainty in the choice of models. To model the cumulative effect of
exposure which varies over time, in the classical approach the function assigning
weights according to recency will be estimated using regression splines.
In order to compare the results with previous studies, a cohort of people diagnosed
with hypertension will be constructed using the databases of the RAMQ
and Med-Echo.
The Cox model including two variables which vary in time will be used. The
time-dependent variables considered in this paper are the dependent variable (first
stroke event) and one of the independent variables, namely the exposure.
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