The overall goal of this study was to analyse the welfare effect of improved wastewater treatment with the view of making policy recommendations for sustainable urban and peri-urban irrigation agriculture in Kenya. This goal was achieved by investigating three specific objectives. The first objective was to assess the farmers’ awareness of health risks in urban and peri-urban wastewater irrigation. Second objective was to analyse the factors that affect the choice of low-risk adaptations in reuse of untreated wastewater for irrigation. The third objective was to estimate the value that urban and peri-urban farmers who practice wastewater irrigation impute to improvements in specific characteristics of the wastewater input in agriculture. In order to achieve the first objective, an ordered probit model was used to identify the factors that influence farmers’ awareness of health risks in untreated wastewater irrigation. The model was fitted to data collected from a cross-sectional survey of 317 urban farm households in the Kibera informal settlement of Kenya. Results of this study show that gender of household head, household size, education level of household head, farm size, ownership of the farm, membership to farmers’ group, and market access for the fresh produce significantly affect awareness of farmers about health risks in wastewater irrigation. Therefore, there is need for awareness programs to promote public education through regular training and local workshops on wastewater reuse in order to improve the human capital of the urban and peri-urban farmers. To achieve the second objective, the study used a multinomial logit model to analyse the farmers’ choice of low-risk adaptations in untreated wastewater irrigation. A survey of 317 urban and peri-urban farmers was conducted and measures for risk-reduction in wastewater reuse were analysed. The urban and peri-urban farmers were found to have adopted low-risk wastewater irrigation techniques such as cessation of irrigation before harvesting, crop restriction and safer application methods. Results of the study show that adoption of risk-reduction measures is significantly influenced by the following factors: household size, age of the household head, education of household head, access to extension, access to media, access to credit, farmers’ group membership, and risk awareness. Also, marginal analysis of the coefficients confirmed the socio-economic characteristics are key determinants in adoption of low-risk measures in wastewater reuse. The study recommends that policies in support of low-risk urban and peri-urban irrigation agriculture should disaggregate farmers according to their socio-economic and institutional characteristics in order to achieve their intended objectives. To achieve the third objective, the study employed the discrete choice experiment approach to estimate the benefits farmers impute to improvements in attributes of the wastewater irrigation input, whose aim is to reduce the health risks associated with untreated wastewater irrigation. Urban and peri-urban farmers who practice wastewater irrigation drawn from Motoine-Ngong River in Nairobi were randomly selected for the study. A total of 241 farmers completed the presented choice cards for the choice model estimation. A random parameter logit model was used to estimate the individual level willingness to pay for wastewater treatment. The results show that urban and peri-urban farmers are willing to pay significant monthly municipality taxes for treatment of wastewater. Conclusion of this study was that, quality of treated wastewater, quantity of treated wastewater and the riverine ecosystem restoration are significant factors of preference over policy alternative designs in wastewater treatment and reuse. / Thesis (PhD)--University of Pretoria, 2013. / gm2014 / Agricultural Economics, Extension and Rural Development / unrestricted

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在金融海嘯之後, 信用風險的重要性益發為銀行金融業所重視。 為深入探索此議題, 本文以 CreditMetrics(TM) 模型為基底, 設定台灣 458 間上市櫃公司為虛擬資產組合, 做出其資產組合價值分配與資產組合損失分配, 以估量信用風險的大小, 提供銀行業計提資本時一個適當的方向。 在模型上, 本文採納 CreditMetrics(TM) 考量交易對手資產報酬率相關性的優點, 此點使我們交易對手評等的移轉產生相關性, 不致低估信用風險; 並修正其以外部評等機構所提供的無條件移轉矩陣為模型參數的設定, 使用排序普羅比模型 (Ordered Probit Model) 在移轉矩陣上引入總體因子, 搭配 Svensson 四因子模型所估計的放款殖利率, 做出條件情境的的經濟資本, 增加資本計提的準確度。 此外, 為了解總體因子的重要性, 本文將之與評等因子做比較。 實證結果發現, 加入總體因子會對信用風險造成一定程度的衝擊, 銀行業實不宜再以無條件情境做為計提資本的標準。 而在評等與曝險額呈現正相關的條件下, 評等因子的重要性比起總體因子有過之而無不及。 銀行業在計提資本時, 與其費盡心思在模型中納入總體因子, 也許應該先看看評等是否已經納入考量。

在全球化浪潮下，廠商為追求利潤極大化，紛紛向外尋找適合的市場，其營運策略已由傳統的國際貿易移轉至全球對外直接投資，並儼然成為各國經濟發展的重要動力。對外直接投資對地主國而言，可帶來經濟成長的動力、創造就業機會、促進技術移轉及創新活動等外溢效果，因此，各國無不積極吸引外商前往投資，台灣亦不例外。由於，僑外來台投資對台灣經濟發展具有重大貢獻，據此，本研究利用經濟部投資審議委員會2008年委外調查之「華僑及外國人投資事業營運狀況調查表（非服務業）」問卷資料，分別由廠商特性、競爭優勢及營運策略等構面，探討僑外來台投資營績效之影響因素，並運用Probit Model進行實證分析。實證結果發現，產業類別、廠商規模、成立時間、租稅負擔、國際化程度及在台設立製造生產部門等，是顯著影響僑外來台投資經營績效的重要因素。因此，政府除鼓勵僑外來台投資非資訊電子工業、擴大公司規模、善用先占優勢、提升國際化程度及設立製造生產部門外，亦應給予租稅優惠，降低其租稅負擔，使其有較佳之經營績效表現，以吸引並提升投資意願。 / Corporations in pursuit of profit maximization have to seek out a suitable market under globalization trend and their business strategy has changed from the international trade shifted to the foreign direct investment. This study explores keys of performance of overseas Chinese and foreign nationals in Taiwan. By using Probit Model analysis based on 2008 statistical data from Investment Commission of Ministry of Economic Outsourcing Survey are empirically analyzed. Findings from the research indicate that “industry category, firm scale, set up time, the taxation, internationalization level and the establishment of manufacturing sector in Taiwan,” are significantly factors on firm's performance. Therefore, in order to have better operating performance and enhance the willingness on investment in Taiwan, the government should encourage overseas Chinese and foreign nations invest in Taiwan on non-information and electronics industry, expand firm scale, use of first mover advantage, enhance the internationalization level and set up manufacturing sector, but should also give tax incentives to reduce their tax burden.

Contemporary research indicates that the era of autonomous vehicles (AVs) is not only inevitable but may be reached sooner than expected; however, not enough research has been done to address road infrastructure readiness for supporting AV operations. Highway agencies at all levels of governments seek to identify the needed infrastructure changes to facilitate the successful integration of AVs into the existing roadway system. Given multiple sources of uncertainty particularly the market penetration of AVs, agencies find it difficult to justify the substantial investments needed to make these infrastructure changes using traditional value engineering approaches. It is needed to account for these uncertainties by doing a phased retrofitting of road infrastructure to keep up with the AV market penetration. This way, the agency can expand, defer, or scale back the investments at a future time. This dissertation develops a real options analysis (ROA) framework to address these issues while capturing the monetary value of investment timing flexibility. Using key stakeholder feedback, an extensive literature review, and discussions with experts, the needed AV-motivated changes in road infrastructure were identified across two stages of AV operations; the transition phase and the fully-autonomous phase. For a project-level case study of a 66-mile stretch of Indiana’s four-six lane Interstate corridor, two potential scenarios of infrastructure retrofitting were established and evaluated using the net present value (NPV) and ROA approaches. The results show that the NPV approach can lead to decisions at the start of the evaluation period but does not address the uncertainty associated with AV market penetration. In contrast, ROA was found to address uncertainty by incorporating investment timing flexibility and capturing its monetary value. Using the dissertation’s framework, agencies can identify and analyze a wide range of possible scenarios of AV-oriented infrastructure retrofitting to enhance readiness, at both the project and network levels.

Neste trabalho discutimos a análise bayesiana em modelos TRI (Teoria da Resposta ao Item) de três parâmetros com respostas binárias e ordinais, considerando a ligação probito. Em ambos os casos usamos técnicas baseadas em MCCM (método de Monte Carlo baseado em Cadeias de Markov) para estimação dos parâmetros dos itens. No modelo com respostas binárias, consideramos dois conjuntos de dados resultantes de provas com itens de múltipla-escolha. Para esses dados, foi feito um estudo da sensibilidade à escolha de distribuições a priori, além de uma análise das estimativas a posteriori para os parâmetros dos itens: discriminação, dificuldade e probabilidade de acerto ao acaso. Um terceiro conjunto de dados foi utilizado no estudo do modelo com respostas ordinais. Estes dados são provenientes de uma disciplina básica de estatística, onde a prova contêm itens dissertativos. As respostas foram classificadas nas categorias: certa, errada ou parcialmente certa. Utilizamos o programa WinBugs para a estimação dos parâmetros do modelo binário e a função MCMCordfactanal do programa R para estimar os parâmetros do modelo ordinal. Ambos os softwares são não proprietários e gratuitos (livres). / In this dissertation the bayesian analysis for three parameters IRT (Item Response Theory) models with binaries and ordinals responses, considering the probit model, was discussed. For both cases, binary and ordinal, techniques based on MCCM (Monte Carlo Markov Chain) were used to estimate the items parameters. For binary response model, was considered two data sets from tests with multipla choices items. For these two data sets, a sensibility study of the priori distributions choice was considered, and also, an analyses of a posteriori estimates of the items parameters: discrimination, difficulties and guessing. A third data set is used to ilustrate the ordinal response model. This come from an elementar statistical course, where a test with open items is considered. The responses are classified in the following categories: correct, wrong or partial correct. The WinBugs software was used to estimate the parameters for the binary model and, for the ordinal model was considered the function MCMCordfactanal from R program.

本研究的目的在暸解教師流動的型態與調動的因素，從83學年度臺灣省國民中學調動教師中抽取384人，並同時抽取380位未調動教師作為參照。 　　本研究採用虛擬依變項的迴歸分析，探討導致教師調動的因素。結果發現教師調動的型態存在往都會地區流動的現象。調動與非調動教師的比較中，在性別、教學年資、婚姻狀況與配偶的勞動參與率、自用住宅的擁有、調動次數、學校規模、以及是否為居民的變項上有顯著的不同。 　　在調動機率的影響方面，性別、教學年資、婚姻狀況與配偶的勞動參與率、調動次數、學校規模、以及薪資與福利措施的滿意度上，有著顯著的預測力。研究的結論是教育人力資源分配仍不平均，從影響教師調動機率的因素中，可以提供導引教育人力資源分配更加均衡的線索。 / The main purpose of this study is to inquire into the style about the teachers' mobility and the factors affecting such mobility. Sampling from 1994 academic year in Taiwan, the researcher focuses on the 384 cases of all mobilized teachers and their counterpart-380 nonmobilized cases. 　　A dummy dependent regression analysis is conducted to explore the factors. As a result, the phenomenon for mobility tends to flow into the metropolis. Factors affecting the mobility exhibits significant differences compared to nonmobility; such as factors among sex, seniority, marriage, inhibition, frequcncy of mobility and the scale of the school. 　　In additions, the propensity to mobile, as this study finds, has to do with their sex, seniority, marriage and the labor participation of spouse, frequcency of mobility, degree of the content about their wages and welfare, and the scale of the school. The conclusions made here are: the human resources in education is still scanty. From the factors influenced mobility probability, it can provide some clues to make the human resources in education more equal.

The main purpose of this study is to inquire into the style about the teachers' mobility and the factors affecting such mobility. Sampling from 1994 academic year in Taiwan, the researcher focuses on the 384 cases of all mobilized teachers and their counterpart-380 nonmobilized cases. A dummy dependent regression analysis is conducted to explore the factors. As a result, the phenomenon for mobility tends to flow into the metropolis. Factors affecting the mobility exhibits significant differences compared to nonmobility; such as factors among sex, seniority, marriage, inhibition, frequcncy of mobility and the scale of the school. In additions, the propensity to mobile, as this study finds, has to do with their sex, seniority, marriage and the labor participation of spouse, frequcency of mobility, degree of the content about their wages and welfare, and the scale of the school. The conclusions made here are: the human resources in education is still scanty. From the factors influenced mobility probability, it can provide some clues to make the human resources in education more equal.

本文使用具有事前訊息的領先指標與期間利差作為預測變數,根據不同利差與落後期選擇的 Probit 模型,利用遞迴的方式預測景氣轉折點發生機率,並進一步將個別預測結果進行組合,試圖找出能降低不確定性且優於個別預測結果的方法。實證結果發現,使用 Diebold and Mariano 檢定的預測包容法為其中最優的組合方法,無論是轉折點訊號或預測誤差都能優於半數以上的個別預測。此外,本文亦估計即期景氣轉折點的發生機率,根據模型的估計結果推斷,自 2012 年 2 月至 2015 年 3 月為止,景氣仍處於擴張階段。

Made available in DSpace on 2016-06-02T20:06:01Z (GMT). No. of bitstreams: 1 2049.pdf: 560086 bytes, checksum: 32b955d6a93e81457f49b0418b1e9514 (MD5) Previous issue date: 2008-06-06 / Financiadora de Estudos e Projetos / A summary of the state of the art relative to regression models for binary response variable and panel data is presented in this work. Those models may include efects from several sources: specific variables of interest, heterogeneity between individuals and lagged values of the response variable. The original contributions of the author are simulation studies to compare two diferent approaches to maximum likelihood estimation of parameters of dynamic models with all three kinds of efects, and also a study of properties of such estimators in group sequential analysis, using the bootstrap methodology. Original codes were developed in R for implementation of simulation studies. The relevance of the subject and the non availability of appropriate codes in commercial software for fitting dynamic models for binary response justify the choice of the theme. / Neste trabalho é apresentado inicialmente um levantamento da literatura referente a modelos de regressão não lineares quando a variável resposta é binária e as observações são um painel de dados. Tais modelos podem incluir efeitos de várias fontes: variáveis específicas de interesse, heterogeneidade não observável dos indivíduos e valores defasados da variável resposta. A parte original do trabalho consiste nos estudos por simulação usando programação criada para esse fim no software R, visando comparar duas propostas recentes da literatura para ajustar, por máxima verossimilhança condicional, modelos dinâmicos que incluem os três tipos de efeitos mencionados. Também é original o estudo empírico, usando a metodologia de reamostragem \bootstrap", de características da distribuição conjunta dos estimadores dos parâmetros em análises intermediárias dos dados. A justificativa do trabalho é a atualidade do tema e a inexistência de programas de ajuste de modelos dinâmicos de resposta binária na maioria dos softwares comerciais.