Closed-end funds’ (CEF) discount and discount fluctuations have been puzzling researchers for decades. Up to date, there are no multidimensional or cross-sectional variables that have been proved to influence CEFs simultaneously. Fact is that, earlier research and theories on the subject are contradictious and several suggestions on the origin of the CEF’s discount and its fluctuations have been proposed. To mention a few, investor sentiments, taxation issues, dividend policies, agency costs and agency problems are considered to influence these discounts. The purpose of this report is to examine the relationship between micro- and macroeconomic variables fluctuations, and how these can explain the discount fluctuation of the Swedish CEFs. This report focuses upon the CEFs traded at NASDAQ OMX Stockholm, which have been selected through a comprehensive multistage selection process. 10 CEFs were selected. Monthly data for calculating micro- and macroeconomic variables was collected for the period March 2003 – February 2013, which resulted in approximately 1 200 observations. OLS regression analysis, Fixed- and Random Effect Models and Hausman tests were conducted. The findings conclude that some of this report’s chosen micro- and macro variables influence on the Swedish CEFs’ discount fluctuation, although these findings are conditioned. The CEFs’ individual characteristics or traits result in a significant impact on the fluctuation of CEFs’ discount. Hence, only by controlling these characteristics, multidimensional or cross-sectional micro- and macroeconomic variables can be proved to affect the CEFs’ discount fluctuation.

This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision.  Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes.  The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).

Submitted by Cristiane Oliveira (cristiane.oliveira@fgv.br) on 2011-05-26T13:39:21Z No. of bitstreams: 1 72060100768.pdf: 1142615 bytes, checksum: 508d6ace6f99f9c9e09a9f9345567224 (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia(suzinei.garcia@fgv.br) on 2011-05-26T15:00:01Z (GMT) No. of bitstreams: 1 72060100768.pdf: 1142615 bytes, checksum: 508d6ace6f99f9c9e09a9f9345567224 (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia(suzinei.garcia@fgv.br) on 2011-05-26T15:00:49Z (GMT) No. of bitstreams: 1 72060100768.pdf: 1142615 bytes, checksum: 508d6ace6f99f9c9e09a9f9345567224 (MD5) / Made available in DSpace on 2011-05-26T17:18:30Z (GMT). No. of bitstreams: 1 72060100768.pdf: 1142615 bytes, checksum: 508d6ace6f99f9c9e09a9f9345567224 (MD5) Previous issue date: 2010-07-06 / Most studies around that try to verify the existence of regulatory risk look mainly at developed countries. Looking at regulatory risk in emerging market regulated sectors is no less important to improving and increasing investment in those markets. This thesis comprises three papers comprising regulatory risk issues. In the first Paper I check whether CAPM betas capture information on regulatory risk by using a two-step procedure. In the first step I run Kalman Filter estimates and then use these estimated betas as inputs in a Random-Effect panel data model. I find evidence of regulatory risk in electricity, telecommunications and all regulated sectors in Brazil. I find further evidence that regulatory changes in the country either do not reduce or even increase the betas of the regulated sectors, going in the opposite direction to the buffering hypothesis as proposed by Peltzman (1976). In the second Paper I check whether CAPM alphas say something about regulatory risk. I investigate a methodology similar to those used by some regulatory agencies around the world like the Brazilian Electricity Regulatory Agency (ANEEL) that incorporates a specific component of regulatory risk in setting tariffs for regulated sectors. I find using SUR estimates negative and significant alphas for all regulated sectors especially the electricity and telecommunications sectors. This runs in the face of theory that predicts alphas that are not statistically different from zero. I suspect that the significant alphas are related to misspecifications in the traditional CAPM that fail to capture true regulatory risk factors. On of the reasons is that CAPM does not consider factors that are proven to have significant effects on asset pricing, such as Fama and French size (ME) and price-to-book value (ME/BE). In the third Paper, I use two additional factors as controls in the estimation of alphas, and the results are similar. Nevertheless, I find evidence that the negative alphas may be the result of the regulated sectors premiums associated with the three Fama and French factors, particularly the market risk premium. When taken together, ME and ME/BE regulated sectors diminish the statistical significance of market factors premiums, especially for the electricity sector. This show how important is the inclusion of these factors, which unfortunately is scarce in emerging markets like Brazil.

Abstract Monitoring regional variation in the survival of cancer patients is an important tool for assessing realisation of regional equity in cancer care. When regions are small or sparsely populated, the random component in the total variation across the regions becomes prominent. The broad aim of this doctoral thesis is to develop methods for assessing regional variation in the cause-specific and relative survival of cancer patients in a country and for quantifying the public health impact of the regional variation in the presence of competing hazards of death using summary measures that are interpretable also for policy-makers and other stakeholders. Methods for summarising the survival of a patient population with incomplete follow-up in terms of the mean and median survival times are proposed. A cure fraction model with two sets of random effects for regional variation is fitted to cause-specific survival data in a Bayesian framework using Markov chain Monte Carlo simulation. This hierarchical model is extended to the estimation of relative survival where the expected survival is estimated by region and considered as a random quantity. The public health impact of regional variation is quantified by the extra survival time and the number of avoidable deaths that would be gained if the patients achieved the most favourable level of relative survival. The methods proposed were applied to real data sets from the Finnish Cancer Registry. Estimates of the mean and the median survival times of colon and thyroid cancer patients, respectively, were corrected for the bias that was caused by the inherent selection of patients during the period of diagnosis with respect to their age at diagnosis. The cure fraction model allowed estimation of regional variation in cause-specific and relative survival of breast and colon cancer patients, respectively, with a parsimonious number of parameters yielding reasonable estimates also for sparsely populated hospital districts. / Tiivistelmä Syöpäpotilaiden elossaolon alueellisen vaihtelun seuraaminen on tärkeää arvioitaessa syövänhoidon oikeudenmukaista jakautumista alueittain. Kun alueet ovat pieniä tai harvaan asuttuja, alueellisen kokonaisvaihtelun satunnainen osa kasvaa merkittäväksi. Tämän väitöstutkimuksen tavoitteena on kehittää menetelmiä, joilla pystytään arvioimaan maan sisäistä alueellista vaihtelua lisäkuolleisuudessa, jonka itse syöpä potilaille aiheuttaa, ja tiivistämään alueellisen vaihtelun kansanterveydellinen merkitys mittalukuihin, jotka ottavat kilpailevan kuolleisuuden huomioon ja ovat myös päättäjien tulkittavissa. Ehdotetuilla menetelmillä voidaan potilaiden ennustetta kuvailla käyttäen elossaolo-ajan keskiarvoa ja mediaania, vaikka potilaiden seuruu olisi keskeneräinen. Potilaiden syykohtaiselle kuolleisuudelle sovitetaan bayesiläisittäin MCMC-simulaatiota hyödyntäen malli, jossa parantuneiden potilaiden osuuden kuvaamisen lisäksi alueellinen vaihtelu esitetään kahden satunnaisefektijoukon avulla. Tämä hierarkkinen malli laajennetaan suhteellisen elossaolon estimointiin, jossa potilaiden odotettu elossaolo estimoidaan alueittain ja siihen liittyvä satunnaisvaihtelu otetaan huomioon. Alueellisen vaihtelun kansanterveydellistä merkitystä mitataan elossaoloajan keskimääräisellä pidentymällä sekä vältettävien kuolemien lukumäärällä, jotka voitaisiin saavuttaa, mikäli suotuisin suhteellisen elossaolon taso saavutettaisiin kaikilla alueilla. Kehitettyjä menetelmiä käytettiin Suomen Syöpärekisterin aineistojen analysointiin. Paksusuoli- ja kilpirauhassyöpäpotilaiden elinaikojen keskiarvojen ja mediaanien estimaatit oikaistiin harhasta, joka aiheutui potilaiden luontaisesta valikoitumisesta diagnosointijakson aikana iän suhteen. Parantuneiden osuuden satunnaisefektimalli mahdollisti rintasyöpäpotilaiden syykohtaisen kuolleisuuden ja paksusuolisyöpäpotilaiden suhteellisen elossaolon kuvaamisen vähäisellä määrällä parametreja ja antoi järkeenkäyvät estimaatit myös harvaan asutuille sairaanhoitopiireille.

The hospitality industry has experienced significant changes in its competitive environment over the past 30 years, driven by the growth of alternative accommodations, the widespread use of the internet for searching and booking accommodations, and the adoption of asset-light business models. In this new competitive landscape, hospitality firms struggle to gain a competitive advantage, particularly as they lack rare and inimitable resources, which are considered crucial for achieving competitive advantage according to resource-based view literature. This dissertation explores three sets of strategies that enable hotel firms to attain a competitive edge despite their resources being non-rare and easily imitated by competitors. The first essay examines the potential for hotel firms to benefit from competitors' resources by co-locating with them. Although this strategy has been widely studied in organizational research, recent developments in the competitive market, such as internet adoption and the growth of short-term leases, have not been considered. Evidence suggests that internet adoption decreases the likelihood of low-level hotels entering markets with high-level hotels and negatively moderates the positive effect of branded hotels on independent hotels' performance, as well as nullifying the effect of low-level hotels on high-level hotels' performance. Additionally, short-term leases impact hotels' decisions and performance, as hotels tend to avoid co-locating with short-term leases with similar price points, and short-term leases can appropriate positive agglomeration externalities created by high-level hotels. The second essay investigates whether hotels can outperform competitors by gaining an advantage in resource appropriation through entering the market with a dual-branded hotel. Results indicate that a competitive advantage is achieved when at least one brand in the composition possesses better resources than competitors. Lastly, the third essay concentrates on the potential for hotels to leverage tacit knowledge transmission to increase the difficulty for competitors to imitate them. Findings reveal that the closer a hotel or short-term lease is to the nearest accommodation managed by the same hotel management company or host, the higher the chances of achieving a competitive advantage. Moreover, short-term leases can base their competitive advantage on idiosyncratic knowledge transferred from the platform, and they can compete in size with incumbent hotels if they have a high concentration of ownership in the market. / Doctor of Philosophy / The lodging industry has undergone numerous changes in the past 30 years, with the widespread adoption of the internet, the growth of the short-term lease market, and the implementation of asset-light strategies significantly impacting how hotels compete locally. This dissertation examines various market-entry strategies that can enable hotel firms to achieve a competitive advantage in local markets. The first essay explores the advantages of co-locating with competitors. Results indicate that previously identified benefits, such as reduced search costs for customers leading to higher performance for clustered competitors, have been diminished or nullified by the extensive use of the internet for searching and booking hotels. Independent hotels may still gain agglomeration advantages by co-locating with branded hotels, but the benefits are substantially reduced due to internet usage. Furthermore, the presence of different levels of short-term leases in the market affects hotels' entry patterns, which tend to diverge from short-term leases. Additionally, low-level short-term leases tend to capture agglomeration benefits created by high-level hotels, resulting in decreased performance for low-level hotels. The second essay investigates the optimal strategy for entering the market with a dual-branded hotel. Results show that, overall, adopting a vertically diversified strategy (i.e., where one of the two brands in the composition is of a higher class compared to the other) is preferable, with the higher class above the market's average class and the lower class below it. Conversely, the least effective strategy is to adopt a vertically diversified approach where both brands are below the market's average class. The third essay examines knowledge sharing among hotels and short-term leases managed by the same hotel management company or short-term lease host. Findings suggest that accommodations should be located near other properties managed by the same entity to facilitate operating knowledge transmission through face-to-face interactions, coordination among units, and the easy transfer of key personnel. Additionally, the study found that hotels should carefully consider entering a market with a high concentration of short-term lease ownership, as a higher concentration of short-term leases owned by the same host leads to lower hotels' RevPAR in the market.

自一九七七年Ainger,Lovell,and Schmidt 發表隨機性邊界生產函數估計方法一文以 後，這項方法便廣泛地應用於廠商生產技術效率的估計。然而， Ainger，et al的方 法係利用單一年度橫斷面資料，方法中有一些缺失，例如：技術無效率部份的統計分 配假設、技術無效率部份與生產投入可能存在某些相關，以及技術無效率可能會隨廠 商經營期間而變化。本文的目的，即嚐試利用橫斷面與時間數列混合資料來修正上述 缺點，分析對象為台灣地區的外人投資廠商，包含電子電器、基本金屬、橡塑膠製品 、化學等產業，時間由民國64年至71年共八年。 台灣地區自一九五二年引進直接外人投資，外資在我國的經濟發展過程扮演重要角色 。過去有關台灣地區外人投資的文獻甚多，然而有關外資廠商生產效率的研究卻不多 見，直至目前僅 Chen and Tang(1987)，劉錦添與蔡偉德(1989)兩篇，且均偏重於橫 斷面的分析。本文將利用近年來發展的Panel Data生產技術效率測定方法來進行，文 中主要參考Schmidt and Sickles(1984) 與Cornwell，Schmidt and Sickles (1988) 兩篇著作。在實證中，假設廠商生產函數為Cobb-Douglas函數，分別利用「固定效果 」(fixed effect)及「隨機效果」(random effect) 二種模型。固定效果模型認為廠 商生產技術效率差異為一固定係數，反映於迴歸式截距項的差異；而隨機效果模型假 設生產術效率項目為隨機變數，效率的差異反映於迴歸式中殘差項的差異。此外，由 於生產因素投入與效率可能存在相關，為得到具有一致性的估計值，本文將利用工具 變數方法來修正。最後，本文分析不同年度廠商效率之變化，並探討造成效率變化之 原因。

In this work, we study the so-called combined models, generalized linear mixed models with extension to allow for overdispersion, in the context of genetics and breeding. Such flexible models accommodates cluster-induced correlation and overdispersion through two separate sets of random effects and contain as special cases the generalized linear mixed models (GLMM) on the one hand, and commonly known overdispersion models on the other. We use such models while obtaining heritability coefficients for non-Gaussian characters. Heritability is one of the many important concepts that are often quantified upon fitting a model to hierarchical data. It is often of importance in plant and animal breeding. Knowledge of this attribute is useful to quantify the magnitude of improvement in the population. For data where linear models can be used, this attribute is conveniently defined as a ratio of variance components. Matters are less simple for non-Gaussian outcomes. The focus is on time-to-event and count traits, where the Weibull-Gamma-Normal and Poisson-Gamma-Normal models are used. The resulting expressions are sufficiently simple and appealing, in particular in special cases, to be of practical value. The proposed methodologies are illustrated using data from animal and plant breeding. Furthermore, attention is given to the occurrence of negative estimates of variance components in the Poisson-Gamma-Normal model. The occurrence of negative variance components in linear mixed models (LMM) has received a certain amount of attention in the literature whereas almost no work has been done for GLMM. This phenomenon can be confusing at first sight because, by definition, variances themselves are non-negative quantities. However, this is a well understood phenomenon in the context of linear mixed modeling, where one will have to make a choice between a hierarchical and a marginal view. The variance components of the combined model for count outcomes are studied theoretically and the plant breeding study used as illustration underscores that this phenomenon can be common in applied research. We also call attention to the performance of different estimation methods, because not all available methods are capable of extending the parameter space of the variance components. Then, when there is a need for inference on such components and they are expected to be negative, the accuracy of the method is not the only characteristic to be considered. / Neste trabalho foram estudados os chamados modelos combinados, modelos lineares generalizados mistos com extensão para acomodar superdispersão, no contexto de genética e melhoramento. Esses modelos flexíveis acomodam correlação induzida por agrupamento e superdispersão por meio de dois conjuntos separados de efeitos aleatórios e contem como casos especiais os modelos lineares generalizados mistos (MLGM) e os modelos de superdispersão comumente conhecidos. Tais modelos são usados na obtenção do coeficiente de herdabilidade para caracteres não Gaussianos. Herdabilidade é um dos vários importantes conceitos que são frequentemente quantificados com o ajuste de um modelo a dados hierárquicos. Ela é usualmente importante no melhoramento vegetal e animal. Conhecer esse atributo é útil para quantificar a magnitude do ganho na população. Para dados em que modelos lineares podem ser usados, esse atributo é convenientemente definido como uma razão de componentes de variância. Os problemas são menos simples para respostas não Gaussianas. O foco aqui é em características do tipo tempo-até-evento e contagem, em que os modelosWeibull-Gama-Normal e Poisson-Gama-Normal são usados. As expressões resultantes são suficientemente simples e atrativas, em particular nos casos especiais, pelo valor prático. As metodologias propostas são ilustradas usando dados de melhoramento animal e vegetal. Além disso, a atenção é voltada à ocorrência de estimativas negativas de componentes de variância no modelo Poisson-Gama- Normal. A ocorrência de componentes de variância negativos em modelos lineares mistos (MLM) tem recebido certa atenção na literatura enquanto quase nenhum trabalho tem sido feito para MLGM. Esse fenômeno pode ser confuso a princípio porque, por definição, variâncias são quantidades não-negativas. Entretanto, este é um fenômeno bem compreendido no contexto de modelagem linear mista, em que a escolha deverá ser feita entre uma interpretação hierárquica ou marginal. Os componentes de variância do modelo combinado para respostas de contagem são estudados teoricamente e o estudo de melhoramento vegetal usado como ilustração confirma que esse fenômeno pode ser comum em pesquisas aplicadas. A atenção também é voltada ao desempenho de diferentes métodos de estimação, porque nem todos aqueles disponíveis são capazes de estender o espaço paramétrico dos componentes de variância. Então, quando há a necessidade de inferência de tais componentes e é esperado que eles sejam negativos, a acurácia do método de estimação não é a única característica a ser considerada.

處理類別型的資料時，常由於變異數與平均數間具有函數關係，因此資料呈現出來的變異程度會比預期的變異程度來的大，這種現象就稱為資料具有額外變異。一般的分析方法是利用廣義線性模型先作估計，再對估計之標準誤做調整。本文中將探討處理額外變異的另外兩種方法—準概似估計和隨機效果模型，並分別利用紡織原料與毒物學研究之資料作為範例來比較此兩種方法與前者的異同。 / Overdispersion is a common phenomenon in practice when modelling categorical data, and the scaled Pearson chi-square is usually used to measure it. In this study, we examine two other methods—the quasi-likelihood and the random-effect models. In addition, two examples are provided for illustration.

The United States cheese consumption has grown considerably over the years. Using Nielsen Homescan panel data for calendar years 2005 and 2006, this dissertation examines the effect of economic and socio-demographic factors on the demand for disaggregated cheese varieties and on the cheese industry in general. In the first essay, we estimated the censored demand for 14 cheese varieties and identified the respective own-price and cross-price elasticities. Also, non-price factors were determined affecting the purchase of each variety as well as the impact of generic dairy advertising. Results revealed that most of the natural cheese varieties have an elastic demand while the processed cheese products exhibited inelastic demands. Strong substitution and complementarity relationships were identified as well, and a two quarter carry-over effect of advertising was observed for most of cheese demands. Results also showed that household demographics affected the demands differently, depending on the nature of the cheese varieties. The second essay examined the impact of retail promotion on the decision to purchase private label processed cheese products using a probit model. A strong negative relationship was found between national brand manufacturer couponing activity and the private label purchase decision. Therefore, national brand couponing appears to be an effective strategy for manufacturers to deter private label growth. This analysis also shows that the decision of purchasing a private label cheese product is influenced by socio-demographic characteristics of the household, namely household income and size, age and education level of the household head, race, ethnicity, and location. In the third study, the feasibility of fortifying processed cheese with omega-3 is investigated. This ex-ante analysis took into account the market conditions and evaluates the increase in the demand for processed cheese needed to offset the costs of fortification in order to maintain the profitability of manufacturers like Kraft. Initially, the censored demand for processed cheese products is estimated using panel data; subsequently, the profitability of manufacturing such product is determined.This analysis shows that, within reasonable market conditions and reasonable marginal costs, the fortification of processed cheese products with omega-3 fatty acids indeed is feasible from a profitability standpoint to manufacturers.

處理多重事件或再發事件之事件發生時間的資料時，常會以Cox模式為基礎而予以延伸，其中較適合再發事件的模式為：A-G模式、GT-UR 模式、PWP-CP 模式及PWP-GT模式。這些模式又可按照是否以發生次數為分層變數，而分為未分層模式(包含A-G模式、 GT-UR 模式)，及分層模式(包含PWP-CP模式、 PWP-GT 模式)。 本論文將以改良的Cox延伸模式，包括對變異數進行修正或加入事故傾向(或隨機效果)，探討公務人員升等的快慢與哪些變數有關。變異數修正方式利用穩健標準誤以解決事件之再發時間之間的相依問題；事故傾向模式則主要是以隨機效果代表無法觀察到的個體間之異質性，且同一個體的各次發生時間共享相同的異質性，並假定異質性服從某種特定分配。對於各種Cox的延伸模式，我們可比較採用穩健變異數與否對估計及推論結果的差異，以及事故傾向加入前後，估計及推論結果與模式配適上的差異。 由本論文對公務人員升等資料的分析可發現，採用變異數修正方法時，未分層的模式有較小的變異數估計值，所以顯著的變數較多，包括性別、官等、教育程度及年齡；分層模式中顯著變數則只有官等及教育程度。若假定事故傾向服從對數Gamma分配，並加入於上述四種模式中，則顯著的變數與未加入事故傾向時一致，且各模式之下均無法拒絕所有人的事故傾向同為0的假設。這種現象或許是因為我們無法取得教育程度與公務人員考試及格種類之歷史資料，也有可能是因為公務人員升等的體制健全，且法規制定嚴謹，運作也有正常的模式可循所致。