We estimate the willingness-to-pay for conserving crop diversity in the Czech Republic. Discrete choice experiments are used to elicit preferences for the conservation of wine, hop, and fruit tree varieties, while a double-bounded dichotomous choice approach is used to elicit preferences for the conservation of unspecified, "general" crop diversity. The WTP values are derived for both of these contingent products from a sample representative of the general Czech population (n=731) and a sample of respondents living in the South Moravian region that is characterized by agriculture and wine production (n=418). We demonstrate a strong preference for conserving fruit trees over hops and wine varieties, and derive positive mean WTP of the general Czech population (ages 18-69) of 56 Kč ($2.26). Mean WTP for the conservation of general crop diversity is 167 Kč ($6.80). On average, residents of South Moravia have a greater WTP for "general" crop as well as fruit tree conservation. In total, the Czech adult population (ages 18-69) has an aggregate WTP of ~1.25 billion Kč ($50.5 million) for the conservation of general crop diversity, and ~410 million Kč ($16.8 million) for the conservation of fruit trees, revealing the previously unmeasured social welfare benefits of these activities. The estimated benefits...

Les modèles de régressions à inflation de zéros constituent un outil très puissant pour l’analyse de données de comptage avec excès de zéros, émanant de divers domaines tels que l’épidémiologie, l’économie de la santé ou encore l’écologie. Cependant, l’étude théorique dans ces modèles attire encore peu d’attention. Ce manuscrit s’intéresse au problème de l’inférence dans des modèles de comptage à inflation de zéro.Dans un premier temps, nous revenons sur la question de l’estimateur du maximum de vraisemblance dans le modèle binomial à inflation de zéro. D’abord nous montrons l’existence de l’estimateur du maximum de vraisemblance des paramètres dans ce modèle. Ensuite, nous démontrons la consistance de cet estimateur, et nous établissons sa normalité asymptotique. Puis, une étude de simulation exhaustive sur des tailles finies d’échantillons est menée pour évaluer la cohérence de nos résultats. Et pour finir, une application sur des données réelles d’économie de la santé a été conduite.Dans un deuxième temps, nous proposons un nouveau modèle statistique d’analyse de la consommation de soins médicaux. Ce modèle permet, entre autres, d’identifier les causes du non-recours aux soins médicaux. Nous avons étudié rigoureusement les propriétés mathématiques du modèle. Ensuite nous avons mené une étude numérique approfondie à l’aide de simulations informatiques et enfin, nous l’avons appliqué à l’analyse d’une base de données recensant la consommation de soins de plusieurs milliers de patients aux USA.Un dernier aspect de ces travaux de thèse a été de s’intéresser au problème de l’inférence dans le modèle binomial à inflation de zéro dans un contexte de données manquantes sur les covariables. Dans ce cas nous proposons la méthode de pondération par l’inverse des probabilités de sélection pour estimer les paramètres du modèle. Ensuite, nous établissons la consistance et la normalité asymptotique de l’estimateur proposé. Enfin, une étude de simulation sur plusieurs échantillons de tailles finies est conduite pour évaluer le comportement de l’estimateur. / The zero-inflated regression models are a very powerful tool for the analysis of counting data with excess zeros from various areas such as epidemiology, health economics or ecology. However, the theoretical study in these models attracts little attention. This manuscript is interested in the problem of inference in zero-inflated count models.At first, we return to the question of the maximum likelihood estimator in the zero-inflated binomial model. First we show the existence of the maximum likelihood estimator of the parameters in this model. Then, we demonstrate the consistency of this estimator, and let us establish its asymptotic normality. Then, a comprehensive simulation study finite sample sizes are conducted to evaluate the consistency of our results. Finally, an application on real health economics data has been conduct.In a second time, we propose a new statistical analysis model of the consumption of medical care. This model allows, among other things, to identify the causes of the non-use of medical care. We have studied rigorously the mathematical properties of the model. Then, we carried out an exhaustive numerical study using computer simulations and finally applied to the analysis of a database on health care several thousand patients in the USA.A final aspect of this work was to focus on the problem of inference in the zero inflation binomial model in the context of missing covariate data. In this case we propose the weighting method by the inverse of the selection probabilities to estimate the parameters of the model. Then, we establish the consistency and asymptotic normality of the estimator offers. Finally, a simulation study on several samples of finite sizes is conducted to evaluate the behavior of the estimator.

A credit card as a banking product has a dual nature both as a convenient loan and a payment tool. Credit card profitability prediction is a complex problem because of the variety of the card holders' behaviour patterns, a fluctuating balance, and different sources of interest and transactional income. The state of a credit card account depends on the type of card usage and payments delinquency, and can be defined as inactive, transactor, revolver, delinquent, and default. The proposed credit cards profit prediction model consists of four stages: i) utilisation rate and interest rate income prediction, ii) non-interest rate income prediction, iii) account state prediction with conditional transition probabilities, and iv) the aggregation of the partial models into total income estimation. This thesis describes an approach to credit card account-level profitability prediction based on multistate and multistage conditional probabilities models with different types of income and compares methods for the most accurate predictions. We use application, behavioural, card state, and macroeconomic characteristics as predictors. This thesis contains nine chapters: Introduction, Literature Review, six chapters giving descriptions of the data, methodologies and discussions of the results of the empirical investigation, and Conclusion. Introduction gives the key points and main aims of the current research and describes the general schema of the total income prediction model. Literature Review proposes a systematic analysis of academic work on loan profit modelling and highlights the gaps in the application of profit scoring to credit cards income prediction. Chapter 3 describes the data sample and gives the overview of characteristics. Chapter 4 is dedicated to the prediction of the credit limit utilisation and contains the comparative analysis of the predictive accuracy of different regression models. We apply five methods such as i) linear regression, ii) fractional regression, iii) beta-regression, iv) beta-transformation, and v) weighted logistic regression with data binary transformation for utilisation rate prediction for one- and two-stage models. Chapters 5 and 6 are dedicated to modelling the transition probabilities between credit card states. Chapter 5 describes the general model setups, model building methodology such as transition probability prediction with conditional binary logistic, ordinal, and multinomial regressions, the data sample description, the univariate analysis of predictors. Chapter 6 discusses regression estimation results for all types of regression and a comparative analysis of the models. Chapter 7 describes an approach to the non-interest rate income prediction and contains a comparative analysis of panel data regression techniques such as pooled and four random effect methods. We consider two sources of non-interest income generation: i) interchange fees and foreign exchange fees from transactions via pointof- sales (POS) and ii) ATM fees from cash withdrawals. We compare the predictive accuracy of a one-stage approach, which means the usage of a single linear model for the income amount estimation, and a two-stage approach, which means that the income amount conditional on the probability of POS and ATM transaction. Chapter 8 aggregates the results from the partial models into a single model for total income estimation. We assume that a credit card account does not have a single particular state and a single behavioural type in the future, but has a chance to move to any of possible states. The income prediction model is selected according to these states, and the transition probabilities are used as weights for the particular interest rate and non-interest rate income prediction models. Conclusion highlights the contributions of this research. We propose an innovative methodological approach for credit card income prediction as a system of models, which considers the estimation of the income from different sources and then aggregates the income estimations weighted by the states transition probabilities. The results of comparative analysis of regression methods for: i) utilization rate of credit limit and ii) non-interest income prediction, iii) the use of panel data with pooled and random effect for profit scoring, and iv) account level non-binary target transition probabilities estimation for credit cards can be used as benchmarks for further research and fill the gaps of empirical investigations in the literature. The estimation of the transition probability between states at the account level helps to avoid the memorylessness property of the Markov Chains approach. We have investigated the significance of predictors for models of this type. The proposed modelling approach can be applied for the development of business strategies such as credit limit management, customer segmentation by the profitability and behavioural type.

The dissertation deals with the accounting aspects of assessing the financial health of a company with a focus on agriculture. The main objective of this study is to assess individual methods designed to evaluate the financial health of a company, to determine their sensitivity to risk data in accounting. The study is focused on the field of agriculture mainly as a result of knowledge about the difficult process of compiling and using agricultural accounting. Agriculture fall within the primary sector of the economy, is very important for landscaping and a lot of subsidies flow from the budget of state and the European Union. Due to the specifics and stated problematic areas, which cannot be fully captured by legislation, incomplete or distorted information is transmitted, being also transferred to the methods of the financial health assessment of the company. Attention is also paid to the influence of legislative changes on the values in accounting as well as creative accounting. Following the findings from the theoretical basis, the application part analyses the impact of different accounting solutions on the financial statements. A paired t-test, used for the analysis, was preceded by data normality testing using the histogram and Shapiro-Wilk test. According to these tests, statistically significant differences were found com-paring the current method of accounting used for investment subsidies and leases with the IFRS accounting, between the accounting of changes in inventories and capitalization before and after 1 January 2016, and in land valuation using historical cost and market price. All these areas influence the values of all the analysed methods of financial health assessment. Only the CH-index showed no statistically significant difference in land valuation and accounting solution of inventory activation and changes. Furthermore, the reliability and controllability of the selected methods used for the evaluation of financial health in the field of agriculture is assessed. According to the results, none of the evaluated models can be used in its original variant, but it is possible to use them to compare the company with similar enterprises or over time thanks to the proven dependence of partial indicators and even the whole models on the productivity. Another type of analysis is designed to determine the indicators that have a statistically significant impact on the actual financial situation of businesses. The method of generalized linear models - multinomial linear regression - is used for this test. To determine whether an enterprise is at risk or not, it would be possible to use the stock / income and short-term liabilities / income indicators, and the cash flow / assets indicator to determine the type of threat.

The aim of this thesis is to provide an overview of methods used in cause-of-death mortality analysis and to demonstrate the application on real data. In Chapter 1 we present the continuous model based on the force of mortality and review the approach using copula functions. In Chapter 2 we focus on the multinomial logit model formulated for cause-specific mortality data, discuss life tables construction and derive life expectancy. In Chapter 3 we apply the multinomial logit model on the data from Czech Statistical Office. We identify the regression model, check its assumptions, present the outputs including the fitted life expectancy, and predicted mortality rates. Later in Chapter 3 we consider several stress scenarios in order to demonstrate the impact of shocked mortality rates on the life expectancy.

股利政策之選擇攸關公司資金成本效益與投資者權益，投資者依據公司未來股利發生時點、金額與不確定性等因素來判斷公司的內涵價值（intrinsic value），亦即股利的配發是公司管理當局與股東利益間的抵換。本論文將考量我國企業實務上股利支付內容，將股利形式細分為無股利分配及有股利配發，包含單一股利政策－現金股利、盈餘配股、公積配股，複合股利政策－現金股利搭配盈餘配股、現金股利搭配公積配股、盈餘配股搭配公積配股及綜合股利政策（現金股利、盈餘配股、公積配股三者兼發）之發放模式，共計有八種股利支付類型。 　　共同基金乃證券市場中連接有價證券與投資者間之專業投資管道，由於基金收益直接進行再投資產生之租稅規避濾網（tax-free filter）效果，藉以探討公司選擇股利政策時之顧客效應。同時將影響股利政策制定之構面因素－公司的股利配發來源、獲利性狀況、資金融通與債務償還能力、企業未來投資成長機會、產業類別與租稅改革制度等一併納入分析檢證。 　　本論文採用實證模型分析為主，文獻檢閱分析為輔，以1995- 2000年我國上市公司曾被國內股票型投信基金選為投資標的者，運用Mutinomial logit model及股利政策相關文獻，建構本研究實證模型；在政策意涵上，股利稅制的規劃與共同基金租稅課徵問題亦一併討論，以檢討我國現行稅制環境是否健全。 　　本研究所獲結論歸納如下： 　　(1) 共同基金持股比重變動對股利政策影響存在明顯差異 　　　　股票型基金持股比重大小對現金股利搭配盈餘配股與盈餘配股搭配公積配股選擇皆有顯著正效果，但是否基於股東特性而論則難以斷定。現行我國共同基金持股率占公司股權結構比重不大、透過除權日規避股利發放及大股東利用共同基金進行投信交叉持股等問題，皆是造成實證結果與預期相左之可能原因。 　　(2) 租稅制度改革對股利配發內容的選擇扮演要角 　　　　兩稅合一制度實施後，總股利支付率較實施前為高，主要在於規避保留盈餘加徵10﹪的稅負及股利的發放具有抵稅權，使公司不再傾向保留盈餘而提高發放股利之意願。 　　(3) 股利配發形式選擇 　　　　◎支持股利配發來源與股利政策的關係 　　　　◎公司舉債程度高低與現金股利配發機率呈負相關 　　　　◎公司獲利性狀況攸關股利發放與否 　　　　◎未來成長機會與現金股利配發呈反向關係 　　　　◎股利政策具有產業差異性，高科技產業傾向選擇股票股利偏 高之股利組合政策 　　以公司立場而言，宜需定期評估經營利基與股利政策選擇因素，建立一套合理之股利預測分析模式，並考量平衡股利政策（現金股利與股票股利搭配）模式，以減緩我國企業普遍採股票股利配發造成股權過度膨脹及盈餘稀釋之弊。從投資者角度來看，共同基金係專業化投資管道，藉由大眾資金匯集之規模效益，能使資金有效配置（或風險分散）並提升國內專業法人比重，減緩市場投機風氣。然共同基金投資相關法令之設立仍需更臻完備，稅制環境對公司股利決策具重要影響性，對追求租稅中立目標而言，證券交易所得是否復徵所得稅，亦是政府單位需審慎考量的議題。

La tesi si compone di tre saggi su disoccupazione e mobilità del lavoro in Italia, presentando anche un focus sulla regione Lombardia, oltre che da una parte iniziale che inquadra tali tematiche. Il primo capitolo offre infatti una disamina degli sviluppi ed empirici connessi a disoccupazione e mobilità del lavoro. L’obiettivo di questa parte introduttiva è duplice. Da un lato si cerca di fornire un quadro pressochè esaustivo sulle evoluzioni teoriche ed empiriche connesse alle tematiche citate. D’altro lato si introducono le analisi oggetto dei successivi saggi come evoluzione degli sviluppi proposti dalla letteratura, enfatizzandone logiche sottostanti ed originalità. Il primo saggio analizza le determinanti della durata della disoccupazione ed i relativi “competing risks” per la regione Lombardia. La scelta di tale contesto non è casuale. La Lombardia, infatti, rappresenta una delle regioni economicamente più sviluppate ed i risultati ottenuti con tali metodologie di stima possono fornire spunti utili e rappresentativi sia delle regioni europee maggiormente sviluppate, sia di altre rilevanti regioni italiane (Emilia Romagna e Toscana). Il secondo saggio estende l’applicazione di modelli di durata e modelli a rischi competitivi all’intero territorio nazionale. In questo modo è possibile enfatizzare la rilevanza di tali tematiche per il contesto italiano, ed ottenere un quadro esaustivo circa l’evoluzione del fenomeno della durata della disoccupazione. Le tecniche utilizzate per tali analisi, ovviamente, differiscono ripetto a quelle impegate per la regione Lombardia, ed anche questo aspetto consente interessanti considerazioni. Il terzo saggio sposta l’attenzione alla rilevante tematica della mobilità del mercato del lavoro. Tale aspetto è ovviamente connesso al fenomeno della disoccupazione, e consente di approfondirne nonché di delinearne le possibili cause. In tale capitolo vengono proposte due metodologie di analisi. In primo luogo, ed a livello macro, sono fornite le stime aggregate dei flussi fra i principali stati o condizioni (occupazione, disoccupazione, inattività) del mercato del lavoro. Questo primo step consente appunto una prima quantificazione del fenomeno della mobilità. La seconda parte del capitolo si focalizza invece su una stima - a livello micro - delle determinanti delle transizioni fra gli stati del mercato del lavoro. Tale aspetto consente appunto di investigare ed esaminare le cause sottese alla mobilità riscontrata a livello macro. / Structured in three essays, this thesis focus on unemployment and labour mobility in Italy and Lombardy (the biggest Italian’s region). The first essay offers a picture of the main theoretical and the empirical issues related to these complex phenomena. The purpose of this section is twofold. On one hand we aim to offer an exhaustive picture of the theoretical and empirical developments of such phenomena. On the other hand, we introduce the empirical investigations of the subsequent essays as evolutions of the ones proposed by literature. We also emphases the original contribution and the logic behind. The second essay investigates the determinants of the unemployment duration and of the related competing risks (CRM hereafter) for Lombardy. The choice to concentrate the initial part of this dissertation on Lombardy is primarily driven by two factors. First, there is interest in applying relevant techniques to a regional context characterized by a certain degree of homogeneity of economic indicators. Further, Lombardy is one of the most important Italian regions (confirmed by many economics indicators), and is quite homogeneous in terms of labour market indicators (only little differences between provinces, with the north-east with the fewest unemployment problems), This allows verifying the effectiveness of these investigations of the determinants of unemployment duration and the related CRM without dealing with the typical dualism between north and south which is a structural feature of the Italian labour market. This is a way to investigate in depth the characteristics of the relevant phenomenon of unemployment for a significant partition of Italy, which is representative of both richest regions in Europe and Italian regions as well (such as Tuscany or Emilia Romagna). The third essay enlarges the attention to Italy by employing techniques of unemployment duration and competing risks to analyse the overall Italian unemployment and its main exit routes. Those are tools to get an exhaustive picture and relevant insights on the evolution of the Italian unemployment duration. The techniques employed for the overall country obviously differ from the ones used for the region of Lombardy, and these differences also offer the scope for interesting considerations. The fourth essay deals with the relevant issue of labour market mobility. This is a theme quite linked to unemployment, since it allows understanding and exploring its causes. We focus on two different kind of analysis. At macro level, we estimate the gross flows between the relevant labour market states of employment, unemployment, and inactivity (three-state representation of the labour market) to quantify the overall labour market mobility. The second part of this section, instead, offers micro econometrics estimates of the determinants of such labour market transitions, to investigate the causes of such mobility.

The study of biological diversity has seen a tremendous growth over the past few decades. Among the commonly used indices capturing both the richness and evenness of a community, the Berger-Parker index, which relates to the maximum proportion of all species, is particularly effective. However, when the number of individuals and species grows without bound this index changes, and it is important to develop statistical tools to measure this change. In this thesis, we introduce two estimators for this maximum: the multinomial maximum and the length of the longest increasing subsequence. In both cases, the limiting distribution of the estimators, as the number of individuals and species simultaneously grows without bound, is obtained. Then, constructing the 95% confidence intervals for the maximum proportion helps improve the comparison of the Berger-Parker index among communities. Finally, we compare the two approaches by examining their associated bias corrected estimators and apply our results to environmental data.

從1960年代開始，公部門基於稅務處理需求，使得電腦輔助大量估價（Computer Assisted Mass Assessment，CAMA）成為輔助的工具，大幅提升了估價的效率。在1990年代，金融機構因不動產證券化的發展及不良資產估價等業務，而衍生了對大量不動產進行估價的需求，同時在電腦與統計模型的進步之下，自動估價模型（Automated Valuation Models，AVM）應然而生，並被廣泛應用在金融市場。由此可知因為不動產經濟活動的熱絡發展，大量估價的需求日益增加，其具備的客觀與效率等優點更彰顯其重要性。 雖然大量估價的需求日益增加，然而過去對於估價準確性相關研究，主要著重在估價理論與技術層面、估價行為對估價結果的影響、探討個別估價和大量估價的估值比較，而較少單獨探究影響大量估價準確性的因素。由於特徵價格理論隱含不動產高度異質的特性，不動產價格受到總體經濟、政策、住宅屬性、公共設施、區位等因素影響，然而前述因素是否會對估價準確性造成影響?造成影響的因素為何?為本文所欲探討之問題。 本文在實證部分分成兩階段，首先以特徵價格理論為基礎，利用實價登錄資料建立大量估價模型，以MAPE與Hit Rate來衡量估價準確性，結果指出MAPE達到14.19%，而正負誤差10%的命中率為47.18%、正負誤差20%的命中率為74.75%，跟過往研究所建立的大量估價模型相比具有相當的水準，顯示出官方性質的交易資料具有一定的可信度。在建置大量估價模型後，本文以模型價格及成交價格間的比值作為劃分估價準確程度的依據，以多項羅吉特模型進行實證分析，結果指出住宅大樓、捷運站周遭住宅、大坪數住宅估價結果容易呈現低估情形；而新市區中心估價結果容易呈現高估的情形；另外比較特別的是舊市區中心、北郊區估價結果較容易呈現高估及低估，換言之在這兩個區域估價容易得到不準確的結果。 / Since 1960s, public sector began to take advantage of computer assisted mass assessment(CAMA) based on taxation services and greatly improved the efficiency of appraisal. In 1990s, financial institutions due to the development of securitization of real estate and non-performing asset valuation and other services, generating the demand of mass appraisal. Simultaneously, due to the development of computer and statistical models gradually progress, bring in automated valuation models(AVM) in the financial markets. Hence, with the real estate economic activities gradually booming, the increasing demand for mass appraisal, which has the objective of efficiency and other advantages will be more to highlight its importance. While the increasing demand for mass appraisal, but past studies about the accuracy of appraisal, mainly focused on the theoretical and technical aspects, the impact of behavior on the valuation results, and to explore appraisers and mass appraisal of the valuation. However, past studies less focused on a large number of factors affect the accuracy of the appraisal. Since the hedonic price theory implies highly heterogeneous characteristics of real estate, real estate prices affected by factors of macroeconomic, tax policy, housing properties, public facilities, location and so on, but whether the aforementioned factors will affect the valuation accuracy?Is this research seeking to explore the issue. In this paper, the empirical section is divided into two stages, first with the hedonic price theory based on the use actual price registration to establish the mass appraisal models, and base on MAPE and Hit Rate to measure the accuracy of the appraisal, the results indicate MAPE reached 14.19%, while the margin of error of 10% hit rate of 47.18%, 20% hit rate is 74.75%. Compared with the past studies, this model has established a great performance. This research proved that the official data with reliability. After establishing the mass appraisal models, the research use model prices and the transaction price ratio as the basis for division between the accuracy of the appraisal and use multinomial logistic model to conduct empirical analysis. The results indicated that the residential building, housing around MRT stations, the big area housing was prone to result underestimate valuations, the new urban center appraisal results likely to show overvalued valuations. On the other hand, old city center and the northern suburbs results presented overestimate and underestimate valuations simultaneously, in other words, that is usually get inaccurate results in these two regions.

This study uses conjoint analysis to examine the preferences of buyers for Bureau of Land Management (BLM) wild horses based on physical attributes of wild horses and individual characteristics of the buyers. Generalized ordered logit models and multinomial logit models are used to study the impact of the buyers’ demographic characteristics such as age, gender, knowledge about wild horse care, and number of wild horses previously adopted on physical attributes of the horses such as color, age, height, training status, temperament, conformation, and unique markings. Using a choice experiment, taken together, these attributes determine buyer’s preferences for a wild horse. This study reveals that characteristics of buyers have significant effects on their preferences for wild horses. Their gender, age, knowledge about wild horse care, and the number of horses previously adopted influence the importance that buyers place on physical attributes of a wild horse in their decision to purchase a wild horse.