Luottolaitosten oman pääoman määrän muutos ja Basel II

Luottolaitosten pääoman valvonta on tärkeä osa talouden tasapainon säilyttämisessä. Tässä tutkielmassa tutkitaan miten luottolaitosten pääoman sääntelyn Basel II:n säännönmuutokset vuonna 2007 ovat vaikuttaneet luottolaitosten oman pääoman määrään. Muuttuneiden säännösten vaikutuksia selvitetään tutkimalla eurooppalaisten luottolaitosten omavaraisuusasteita ajalla 1999 – 2009 yleistetyllä lineaarisella regressiolla ja autoregressiivisellä aikasarjamallinnuksella. Talouden suhdanteiden ja vuonna 2007 alkaneen finanssikriisin vaikutukset pääoman määrään huomioidaan bruttokansantuotteen kasvun avulla analyysissa. Tuloksena todetaan, että oman pääoman määrä luottolaitoksissa on vähentynyt merkitsevästi Basel II:n voimaan astumisen jälkeen, mutta muutos on luultavasti aiheutunut talouden laskusuhdanteesta.

Acidic dissolution of iron oxides and regeneration of a ceramic filter medium

The dewatering of iron ore concentrates requires large capacity in addition to producing a cake with low moisture content. Such large processes are commonly energy intensive and means to lower the specific energy consumption are needed. Ceramic capillary action disc filters incorporate a novel filter medium enabling the harnessing of capillary action, which results in decreased energy consumption in comparison to traditional filtration technologies. As another benefit, the filter medium is mechanically and chemically more durable than, for example, filter cloths and can, thus, withstand harsh operating conditions and possible regeneration better than other types of filter media. In iron ore dewatering, the regeneration of the filter medium is done through a combination of several techniques: (1) backwashing, (2) ultrasonic cleaning, and (3) acid regeneration. Although it is commonly acknowledged that the filter medium is affected by slurry particles and extraneous compounds, published research, especially in the field of dewatering of mineral concentrates, is scarce. Whereas the regenerative effect of backwashing and ultrasound are more or less mechanical, regeneration with acids is based on chemistry. The chemistry behind the acid regeneration is, naturally, dissolution. The dissolution of iron oxide particles has been extensively studied over several decades but those studies may not necessarily be directly applicable in the regeneration of the filter medium which has undergone interactions with the slurry components. The aim of this thesis was to investigate if free particle dissolution indeed correlates with the regeneration of the filter medium. For this purpose, both free particle dissolution and dissolution of surface adhered particles were studied. The focus was on acidic dissolution of iron oxide particles and on the study of the ceramic filter medium used in the dewatering of iron ore concentrates. The free particle dissolution experiments show that the solubility of synthetic fine grained iron oxide particles in oxalic acid could be explained through linear models accounting for the effects of temperature and acid concentration, whereas the dissolution of a natural magnetite is not so easily explained by such models. In addition, the kinetic experiments performed both support and contradict the work of previous authors: the suitable kinetic model here supports previous research suggesting solid state reduction to be the reaction mechanism of hematite dissolution but the formation of a stable iron oxalate is not supported by the results of this research. Several other dissolution mechanisms have also been suggested for iron oxide dissolution in oxalic acid, indicating that the details of oxalate promoted reductive dissolution are not yet agreed and, in this respect, this research offers added value to the community. The results of the regeneration experiments with the ceramic filter media show that oxalic acid is highly effective in removing iron oxide particles from the surface of the filter medium. The dissolution of those particles did not, however, exhibit the expected behaviour, i.e. complete dissolution. The results of this thesis show that although the regeneration of the ceramic filter medium with acids incorporates the dissolution of slurry particles from the surface of the filter medium, the regeneration cannot be assessed purely based upon free particle dissolution. A steady state, dependent on temperature and on the acid concentration, was observed in the dissolution of particles from the surface even though the limit of solubility of free iron oxide particles had not been reached. Both the regeneration capacity and efficiency, with regards to the removal of iron oxide particles, was found to be temperature dependent, but was not affected by the acid concentration. This observation further suggests that the removal of the surface adhered particles does not follow the dissolution of free particles, which do exhibit a dependency on the acid concentration. In addition, changes in the permeability and in the pore structure of the filter medium were still observed after the bulk concentration of dissolved iron had reached a steady state. Consequently, the regeneration of the filter medium continued after the dissolution of particles from the surface had ceased. This observation suggests that internal changes take place at the final stages of regeneration. The regeneration process could, in theory, be divided into two, possibly overlapping, stages: (1) dissolution of surface-adhered particles, and (2) dissolution of extraneous compounds from within the pore structure. In addition to the fundamental knowledge generated during this thesis, tools to assess the effects of parameters on the regeneration of the ceramic filter medium are needed. It has become clear that the same tools used to estimate the dissolution of free particles cannot be used to estimate the regeneration of a filter medium unless only a robust characterisation of the order of regeneration efficiency is needed.

Fatigue and quality of life in breast cancer survivors: a comparative study

PURPOSE: To assess fatigue and quality of life in disease-free breast cancer survivors in relation to a sample of age-matched women with no cancer history and to explore the relationship between fatigue and quality of life.METHODS: A cross-sectional study was conducted in a sample of 202 consecutive disease-free Brazilian breast cancer survivors, all of whom had completed treatment, treated at 2 large hospitals. The patients were compared to age-matched women with no cancer history attending a primary health care center. The Piper Fatigue Scale-Revised and the World Health Organization Quality of Life Instrument (WHOQOL-BREF) were used to measure the fatigue and quality of life, respectively. Socio-demographic and clinical variables were also obtained. The χ2 test, generalized linear model, and Spearman correlation coefficient were used for statistical purposes. The adopted level of significance was 5%.RESULTS: Breast cancer survivors experienced significantly greater total and subscale fatigue scores than comparison group (all p-values<0.05). In addition, survivors reported a poorer quality of life in physical (p=0.002), psychological (p=0.03), and social relationships (p=0.03) domains than comparison group. No difference was found for the environmental domain (p=0.08) for both groups. For survivors of breast cancer and for comparison group, the total and subscale fatigue scores were related to lower quality of life (all p-values<0.01).CONCLUSION: The findings of this study highlight the importance of assessing fatigue and quality of life in breast cancer survivors.

Air pollution and cardiovascular hospital admissions in a medium-sized city in São Paulo State, Brazil

The objective of the present study was to estimate the contribution of environmental pollutants to hospital admissions for cardiovascular disease. A time series ecological study was conducted on subjects aged over 60 years and living in São José dos Campos, Brazil, with a population near 700,000 inhabitants. Hospital admission data of public health patients (SUS) were obtained from DATASUS for the period between January 1, 2004 and December 31, 2006, according to the ICD-10 diagnoses I20 to I22 and I24. Particulate matter with less than 10 µm in aerodynamic diameter, sulfur dioxide and ozone were the pollutants examined, and the control variables were mean temperature and relative humidity. Data on pollutants were obtained from the São Paulo State Sanitary Agency. The generalized linear model Poisson regression with lags of up to 5 days was used. There were 1303 hospital admissions during the period. Exposure to particulate matter was significantly associated with hospitalization for cardiovascular disease 3 days after exposure (RR = 1.006; 95%CI = 1.000 to 1.010) and an increase of 16 µg/m³ was associated with a 10% increase in risk of hospitalization; other pollutants were not associated with hospitalization. Thus, it was possible to identify the role of exposure to particulate matter as an environmental pollutant in hospitalization for cardiovascular disease in a medium-sized city inSoutheastern Brazil.

Instrumental color and sensory acceptance of soy-based emulsions: a response surface approach

Response Surface Methodology (RSM) was applied to evaluate the chromatic features and sensory acceptance of emulsions that combine Soy Protein (SP) and red Guava Juice (GJ). The parameters analyzed were: instrumental color based on the coordinates a* (redness), b* (yellowness), L* (lightness), C* (chromaticity), h* (hue angle), visual color, acceptance, and appearance. The analyses of the results showed that GJ was responsible for the high measured values of red color, hue angle, chromaticity, acceptance, and visual color, whereas SP was the variable that increased the yellowness intensity of the assays. The redness (R²adj = 74.86%, p < 0.01) and hue angle (R²adj = 80.96%, p < 0.01) were related to the independent variables by linear models, while the sensory data (color and acceptance) could not be modeled due to a high variability. The models of yellowness, lightness, and chromaticity did not present lack of fit but presented adjusted determination coefficients bellow 70%. Notwithstanding, the linear correlations between sensory and instrumental data were not significant (p > 0.05) and low Pearson coefficients were obtained. The results showed that RSM is a useful tool to develop soy-based emulsions and model some chromatic features of guava-based emulsions through RSM.

Influence of process parameters on the color and texture of passion fruit albedo preserved in syrup

The industrialization of passion fruit in the form of juice produces considerable amounts of residue that could be used as food. The objective of the present study was to determine the effects of the volume of passion fruit juice added to the syrup and the cooking time on the color and texture of passion fruit albedo preserved in syrup. Multi-linear models were well fit to describe the value for a* (for the albedo) the values for b* (for the albedo and syrup), which exhibited high correlation coefficients of 98%, 84%, and 88%, respectively. The volume of passion fruit juice added and the cooking time of the albedos in the syrup, involved in the processing of passion fruit albedo preserves in syrup, significantly affected color analyses. The texture was not affected by the parameters studied. Therefore, the use of larger volumes of passion fruit juice and longer cooking time is recommended for the production of passion fruit albedo preserves in syrup to achieve the characteristic yellow color of the fruit.

Modeling Energy Futures Returns With Markov Regime Switching Model

Financial time series have a tendency of abruptly changing their behavior and maintain this behavior for several consecutive periods, and commodity futures returns are not an exception. This quality proposes that nonlinear models, as opposed to linear models, can more accurately describe returns and volatility. Markov regime switching models are able to match this behavior and have become a popular way to model financial time series. This study uses Markov regime switching model to describe the behavior of energy futures returns on a commodity level, because studies show that commodity futures are a heterogeneous asset class. The purpose of this thesis is twofold. First, determine how many regimes characterize individual energy commodities’ returns in different return frequencies. Second, study the characteristics of these regimes. We extent the previous studies on the subject in two ways: We allow for the possibility that the number of regimes may exceed two, as well as conduct the research on individual commodities rather than on commodity indices or subgroups of these indices. We use daily, weekly and monthly time series of Brent crude oil, WTI crude oil, natural gas, heating oil and gasoil futures returns over 1994–2014, where available, to carry out the study. We apply the likelihood ratio test to determine the sufficient number of regimes for each commodity and data frequency. Then the time series are modeled with Markov regime switching model to obtain the return distribution characteristics of each regime, as well as the transition probabilities of moving between regimes. The results for the number of regimes suggest that daily energy futures return series consist of three to six regimes, whereas weekly and monthly returns for all energy commodities display only two regimes. When the number of regimes exceeds two, there is a tendency for the time series of energy commodities to form groups of regimes. These groups are usually quite persistent as a whole because probability of a regime switch inside the group is high. However, individual regimes in these groups are not persistent and the process oscillates between these regimes frequently. Regimes that are not part of any group are generally persistent, but show low ergodic probability, i.e. rarely prevail in the market. This study also suggests that energy futures return series characterized with two regimes do not necessarily display persistent bull and bear regimes. In fact, for the majority of time series, bearish regime is considerably less persistent. Rahoituksen aikasarjoilla on taipumus arvaamattomasti muuttaa käyttäytymistään ja jatkaa tätä uutta käyttäytymistä useiden periodien ajan, eivätkä hyödykefutuurien tuotot tee tähän poikkeusta. Tämän ominaisuuden johdosta lineaaristen mallien sijasta epälineaariset mallit pystyvät tarkemmin kuvailemaan esimerkiksi tuottojen jakauman parametreja. Markov regiiminvaihtomallit pystyvät vangitsemaan tämän ominaisuuden ja siksi niistä on tullut suosittuja rahoituksen aikasarjojen mallintamisessa. Tämä tutkimus käyttää Markov regiiminvaihtomallia kuvaamaan yksittäisten energiafutuurien tuottojen käyttäytymistä, sillä tutkimukset osoittavat hyödykefutuurien olevan hyvin heterogeeninen omaisuusluokka. Tutkimuksen tarkoitus on selvittää, kuinka monta regiimiä tarvitaan kuvaamaan energiafutuurien tuottoja eri tuottofrekvensseillä ja mitkä ovat näiden regiimien ominaisuudet. Aiempaa tutkimusta aiheesta laajennetaan määrittämällä regiimien lukumäärä tilastotieteellisen testauksen menetelmin sekä tutkimalla energiafutuureja yksittäin; ei indeksi- tai alaindeksitasolla. Tutkimuksessa käytetään päivä-, viikko- ja kuukausiaikasarjoja Brent-raakaöljyn, WTI-raakaöljyn, maakaasun, lämmitysöljyn ja polttoöljyn tuotoista aikaväliltä 1994–2014, siltä osin kuin aineistoa on saatavilla. Likelihood ratio -testin avulla estimoidaan kaikille aikasarjoille regiimien määrä,jonka jälkeen Markov regiiminvaihtomallia hyödyntäen määritetään yksittäisten regiimientuottojakaumien ominaisuudet sekä regiimien välinen transitiomatriisi. Tulokset regiimien lukumäärän osalta osoittavat, että energiafutuurien päiväkohtaisten tuottojen aikasarjoissa regiimien lukumäärä vaihtelee kolmen ja kuuden välillä. Viikko- ja kuukausituottojen kohdalla kaikkien energiafutuurien prosesseissa regiimien lukumäärä on kaksi. Kun regiimejä on enemmän kuin kaksi, on prosessilla taipumus muodostaa regiimeistä koostuvia ryhmiä. Prosessi pysyy ryhmän sisällä yleensä pitkään, koska todennäköisyys siirtyä ryhmään kuuluvien regiimien välillä on suuri. Yksittäiset regiimit ryhmän sisällä eivät kuitenkaan ole kovin pysyviä. Näin ollen prosessi vaihtelee ryhmän sisäisten regiimien välillä tiuhaan. Regiimit, jotka eivät kuulu ryhmään, ovat yleensä pysyviä, mutta prosessi ajautuu niihin vain harvoin, sillä todennäköisyys siirtyä muista regiimeistä niihin on pieni. Tutkimuksen tulokset osoittavat myös, että prosesseissa, joita ohjaa kaksi regiimiä, nämä regiimit eivät välttämättä ole pysyvät bull- ja bear-markkinatilanteet. Tulokset osoittavat sen sijaan, että bear-markkinatilanne on energiafutuureissa selvästi vähemmän pysyvä.

Vigor and field emergence in "high oleic" sunflower seeds, in southeast of Buenos Aires province

Sunflower crop was based, as yet, on high linoleic cultivars, but in the last years request for oil with higher content of oleic acid has increased, due to their dietary characteristics. At the beginning, high oleic cultivars were used to be sown in warm regions, but then the concern about growing it in temperate areas, as the south-east of Buenos Aires Province, was posed. In this region, early sowings are recommended, so that grain filling matches with a period of appropriate hydric and light conditions, as to result in greater yields. However, early sowings are limited by low soil temperature, that delays seedling emergence, resulting in heterogeneous stand establishment. The aim of this work was to evaluate seed performance of four high oleic cultivars in the southern area of Buenos Aires Province, by means of vigor tests and field trials. Germination, cold, tetrazolium viability, tetrazolium viability with cold, accelerated ageing tests and three field sowings at different soil temperatures were performed. Data were analyzed by Anova using generalised linear models, and tests and cultivars were contrasted among themselves. Similar seedling emergence under optimal and suboptimal temperatures for high oleic and high linoleic cultivars was recorded. The success of seedling establishment does not appear to be related to the acidic composition of seeds.

Semi-Parametric Weak Instrument Regressions with an Application to the Risk-Return Trade-off

Recent work shows that a low correlation between the instruments and the included variables leads to serious inference problems. We extend the local-to-zero analysis of models with weak instruments to models with estimated instruments and regressors and with higher-order dependence between instruments and disturbances. This makes this framework applicable to linear models with expectation variables that are estimated non-parametrically. Two examples of such models are the risk-return trade-off in finance and the impact of inflation uncertainty on real economic activity. Results show that inference based on Lagrange Multiplier (LM) tests is more robust to weak instruments than Wald-based inference. Using LM confidence intervals leads us to conclude that no statistically significant risk premium is present in returns on the S&P 500 index, excess holding yields between 6-month and 3-month Treasury bills, or in yen-dollar spot returns.

Essays in partial identification and applications to treatment effects and policy evaluation.

Dans cette thèse, je me suis interessé à l’identification partielle des effets de traitements dans différents modèles de choix discrets avec traitements endogènes. Les modèles d’effets de traitement ont pour but de mesurer l’impact de certaines interventions sur certaines variables d’intérêt. Le type de traitement et la variable d’intérêt peuvent être défini de manière générale afin de pouvoir être appliqué à plusieurs différents contextes. Il y a plusieurs exemples de traitement en économie du travail, de la santé, de l’éducation, ou en organisation industrielle telle que les programmes de formation à l’emploi, les techniques médicales, l’investissement en recherche et développement, ou l’appartenance à un syndicat. La décision d’être traité ou pas n’est généralement pas aléatoire mais est basée sur des choix et des préférences individuelles. Dans un tel contexte, mesurer l’effet du traitement devient problématique car il faut tenir compte du biais de sélection. Plusieurs versions paramétriques de ces modèles ont été largement étudiées dans la littérature, cependant dans les modèles à variation discrète, la paramétrisation est une source importante d’identification. Dans un tel contexte, il est donc difficile de savoir si les résultats empiriques obtenus sont guidés par les données ou par la paramétrisation imposée au modèle. Etant donné, que les formes paramétriques proposées pour ces types de modèles n’ont généralement pas de fondement économique, je propose dans cette thèse de regarder la version nonparamétrique de ces modèles. Ceci permettra donc de proposer des politiques économiques plus robustes. La principale difficulté dans l’identification nonparamétrique de fonctions structurelles, est le fait que la structure suggérée ne permet pas d’identifier un unique processus générateur des données et ceci peut être du soit à la présence d’équilibres multiples ou soit à des contraintes sur les observables. Dans de telles situations, les méthodes d’identifications traditionnelles deviennent inapplicable d’où le récent développement de la littérature sur l’identification dans les modèles incomplets. Cette littérature porte une attention particuliere à l’identification de l’ensemble des fonctions structurelles d’intérêt qui sont compatibles avec la vraie distribution des données, cet ensemble est appelé : l’ensemble identifié. Par conséquent, dans le premier chapitre de la thèse, je caractérise l’ensemble identifié pour les effets de traitements dans le modèle triangulaire binaire. Dans le second chapitre, je considère le modèle de Roy discret. Je caractérise l’ensemble identifié pour les effets de traitements dans un modèle de choix de secteur lorsque la variable d’intérêt est discrète. Les hypothèses de sélection du secteur comprennent le choix de sélection simple, étendu et généralisé de Roy. Dans le dernier chapitre, je considère un modèle à variable dépendante binaire avec plusieurs dimensions d’hétérogéneité, tels que les jeux d’entrées ou de participation. je caractérise l’ensemble identifié pour les fonctions de profits des firmes dans un jeux avec deux firmes et à information complète. Dans tout les chapitres, l’ensemble identifié des fonctions d’intérêt sont écrites sous formes de bornes et assez simple pour être estimées à partir des méthodes d’inférence existantes.

Study of baleen whales’ ecology and interaction with maritime traffic activities to support management of a complex socio-ecological system

Thesis written in co-mentorship with Robert Michaud.

Régression logistique bayésienne : comparaison de densités a priori

La régression logistique est un modèle de régression linéaire généralisée (GLM) utilisé pour des variables à expliquer binaires. Le modèle cherche à estimer la probabilité de succès de cette variable par la linéarisation de variables explicatives. Lorsque l’objectif est d’estimer le plus précisément l’impact de différents incitatifs d’une campagne marketing (coefficients de la régression logistique), l’identification de la méthode d’estimation la plus précise est recherchée. Nous comparons, avec la méthode MCMC d’échantillonnage par tranche, différentes densités a priori spécifiées selon différents types de densités, paramètres de centralité et paramètres d’échelle. Ces comparaisons sont appliquées sur des échantillons de différentes tailles et générées par différentes probabilités de succès. L’estimateur du maximum de vraisemblance, la méthode de Gelman et celle de Genkin viennent compléter le comparatif. Nos résultats démontrent que trois méthodes d’estimations obtiennent des estimations qui sont globalement plus précises pour les coefficients de la régression logistique : la méthode MCMC d’échantillonnage par tranche avec une densité a priori normale centrée en 0 de variance 3,125, la méthode MCMC d’échantillonnage par tranche avec une densité Student à 3 degrés de liberté aussi centrée en 0 de variance 3,125 ainsi que la méthode de Gelman avec une densité Cauchy centrée en 0 de paramètre d’échelle 2,5.

ARMA modeling of time series based on rational approximation of spectral density function

This study is concerned with Autoregressive Moving Average (ARMA) models of time series. ARMA models form a subclass of the class of general linear models which represents stationary time series, a phenomenon encountered most often in practice by engineers, scientists and economists. It is always desirable to employ models which use parameters parsimoniously. Parsimony will be achieved by ARMA models because it has only finite number of parameters. Even though the discussion is primarily concerned with stationary time series, later we will take up the case of homogeneous non stationary time series which can be transformed to stationary time series. Time series models, obtained with the help of the present and past data is used for forecasting future values. Physical science as well as social science take benefits of forecasting models. The role of forecasting cuts across all fields of management-—finance, marketing, production, business economics, as also in signal process, communication engineering, chemical processes, electronics etc. This high applicability of time series is the motivation to this study.

On the relationship between the Method of Least Squares and Gram-Schmidt orthogonalization

The method of Least Squares is due to Carl Friedrich Gauss. The Gram-Schmidt orthogonalization method is of much younger date. A method for solving Least Squares Problems is developed which automatically results in the appearance of the Gram-Schmidt orthogonalizers. Given these orthogonalizers an induction-proof is available for solving Least Squares Problems.

Compositional analysis of bivariate discrete probabilities

A joint distribution of two discrete random variables with finite support can be displayed as a two way table of probabilities adding to one. Assume that this table has n rows and m columns and all probabilities are non-null. This kind of table can be seen as an element in the simplex of n · m parts. In this context, the marginals are identified as compositional amalgams, conditionals (rows or columns) as subcompositions. Also, simplicial perturbation appears as Bayes theorem. However, the Euclidean elements of the Aitchison geometry of the simplex can also be translated into the table of probabilities: subspaces, orthogonal projections, distances. Two important questions are addressed: a) given a table of probabilities, which is the nearest independent table to the initial one? b) which is the largest orthogonal projection of a row onto a column? or, equivalently, which is the information in a row explained by a column, thus explaining the interaction? To answer these questions three orthogonal decompositions are presented: (1) by columns and a row-wise geometric marginal, (2) by rows and a columnwise geometric marginal, (3) by independent two-way tables and fully dependent tables representing row-column interaction. An important result is that the nearest independent table is the product of the two (row and column)-wise geometric marginal tables. A corollary is that, in an independent table, the geometric marginals conform with the traditional (arithmetic) marginals. These decompositions can be compared with standard log-linear models. Key words: balance, compositional data, simplex, Aitchison geometry, composition, orthonormal basis, arithmetic and geometric marginals, amalgam, dependence measure, contingency table