Wind power becomes one of the most promising energy sources in the electricity generation sector in Texas over the past decade by declining levelized cost of wind energy. However, recent studies show that the wind farms in Texas are relatively less productive. Hence, this study aims to find out reasons of inefficiencies by constructing a two-stage performance assessment of wind farms in Texas. In the first stage of analysis, comprehensive input- and output-oriented Data Envelopment Analysis (DEA) models are applied to evaluate productive efficiencies of the 95 large utility-scale wind farms by using pre-determined three input and two output variables. The sensitivity analysis is provided for the robustness of the DEA models with different combinations of input and output variables of the original model. The slack analysis and projection data are obtained for inefficient wind farms to find out optimal input-output variables. Tobit regression models are conducted for the second stage of the analysis to investigate the reasons of inefficiencies. DEA results indicate that half of the wind farms were operated efficiently in Texas during 2016. 13 wind farms were performed at the most productive scale size, ten wind farms should reduce their operational size to improve production efficiency, and 72 wind farms have the notable potential to increase their production efficiency by expanding operational sizes with modern wind turbine technologies. The sensitivity analysis shows the importance of each input-output variables. Tobit regression models indicate that elevation of the site, rotor diameter, hub height, and brand of the turbine have significant contributions to the relative efficiency scores of the wind farms, and the age of turbine has a negative impact on the productive efficiency of the wind farms.

Wind power is one of the most promising renewable energy sources that has gained enormous attention, especially in the electricity generation sector over the past decade in the United States. In this study Data Envelopment Analysis (DEA) is implemented to quantitatively evaluate the relative efficiencies of the 236 large utility-scale wind farms. Input- and output-oriented CCR (Charnes, Cooper, and Rhodes) and BCC (Banker, Charnes, and Cooper) models are applied to pre-determined three input and three output variables. The sensitivity analysis is conducted for the robustness of DEA by introducing seven new models with the various combinations of input and output variables of the original model. Tobit regression models are developed for the second stage of the analysis to investigate the effects of specifications of the wind turbine technologies. DEA results indicate that two-thirds of the wind farms are operated efficiently. On average, 70% of the wind farms have a considerable potential for further improvement in operational productivity by expanding these wind farm projects, 24% of them should reduce their operational size to increase their productivity level, and 6% of them are operating wind power at the most productive scale size. Nonparametric statistical tests show that the most efficient wind farms are located in Oklahoma because of the relatively high wind speed resources. Tobit regression model indicates the selection of the brand of the wind turbine has a significant contribution to the productive efficiency of the wind farms. The results of this study shed some light on the current efficiency assessments of the 236 large utility-scale wind farms in the United States and the future of wind energy for both energy practitioners and policy makers.

The average global surface temperature increased by 0.85 °C since 1850 because of irrepressible increase of the concentration of greenhouse gases (GHG). Electricity generation is the primary source of GHG emissions in the United States. Hence, renewable energy sources, which produce a negligible amount of GHG emissions, have gained enormous attention, especially in the electricity generation sector over the past decade. Wind power is the second largest renewable energy source to generate electricity in the United States. Therefore, in this study, a two-stage Data Envelopment Analysis (DEA) is developed to quantitatively evaluate the relative efficiencies of the 39 state's wind power performances for the electricity generation. Both input- and output-oriented CCR (Charnes, Cooper, and Rhodes (1978)) and BCC (Banker, Charnes, and Cooper (1984)) models are applied to pre-determined four input and six output variables. The sensitivity analysis is conducted to test the robustness of the DEA models. Tobit regression models are conducted by using the DEA results for the second stage analysis. The DEA results indicate that more than half of the states operate wind power efficiently. Tobit regression indicates that early installed wind power was more expensive and less productive relative the currently installed wind power. Findings of this study shed some light on the current efficiency assessments of the states and the future of wind energy for both energy practitioners and policy makers.

Different management regimes consisting of range of site indices and planting densities were simulated to evaluate price premiums required for growing high-quality southern pines across the southern United States. Optimal management regimes were identified maximizing the land expectation value. Growing high-quality pines on longer rotations are economically feasible, however, forest landowners need premiums which ranged from $1.40/ton to $9.81/ton for 10-year rotation extension and increased significantly with rotation ages. In uneven-aged management, price premiums for 5-year cutting cycle extension ranged from $1.75/ton to $2.25/ton. Additionally, sawmill’s willingness-to-pay price premiums for high-quality pine sawtimber were calculated using a mail survey. Sawmills showed a considerable interest in paying price premiums which ranged from $4.22/ton to $12.98/ton. Factors affecting mean WTP price premiums were sawlog size, procurement radius, grade, mill’s capacity, and employees. These findings will help landowners in deciding whether to extend rotation ages of their forest for growing higher quality pines.

Smallholder households in Haiti face many natural resource management challenges. Agricultural production occurs on deforested hillsides prone to erosion. Charcoal is in an important source of income, and woodfuel stocks are often over-exploited. Donor-funded projects and non- governmental organizations have made large investments in programs that promote soil conservation practices and reforestation. Despite the magnitude of the problems and the amount invested, there are relatively few economic analyses of the long-term adoption of soil conservation practices and woodfuel management. This dissertation uses an economics approach to examine the adoption of conservation practices and the management of woodfuel resources in Central Haiti using cross-sectional data covering 600 households. The results show that plot and household characteristics have different effects on adoption across different classes of soil practices, particularly with regard to perceived soil quality, market access, and household health status. The results also provide evidence of the management of charcoal woodfuel stocks on private land. These findings inform the design and targeting of new programs related to soil conservation and reforestation in Haiti and other developing countries. / Ph. D.

本研究依據2003年「行政院新聞局廣播電視白皮書」、「公開上市、上櫃資訊觀測網站有線電視系統業者財務報告書」等文獻資料，先以資料包絡分析法評估個別系統業者的技術效率，再應用Tobit截斷迴歸方法，探討影響台灣有線電視系統業者經營效率的因素。 評估結果顯示，造成個別有線電視系統業者經營技術無效率的因素，主要歸咎於浪費資源所造成之無效率，而非因生產規模不適當所造成之無效率，迴歸結果發現，營業收入與技術效率間具正向關係，而頻道數、廣告密集度、經營區面積、集團化及業務集中度對技術效率間具負向關係。 / Based on the information of 2003 “The Broadcasting television paper of Government Information Office of Executive Yuan” and “Finance Statements of The Cable System Operators of Listed Companies and OTC Listed Companies from Market Observation Post System in Taiwan”, this study first uses DEA to assess technical efficiency of cable system operators, and then applies the Tobit censored regression technique to investigate the determinants of technical efficiency. The efficiency-evaluating result shows that the main factor, which causes inefficient management, is an ineffective use of resource; an improper production scale has less impact on it. The regression result also shows that the revenue has a positive impact on technical efficiency, but the number of channels, Area, the density of advertisement, conglomeration, and business focus has negative impacts on technical efficiency.

兩岸在2001年底加入世界貿易組織（WTO），使得兩岸壽險市場受到經濟自由化及國際化的衝擊。因此，要如何提高自身的經營績效及競爭能力，便成為兩岸壽險公司最重要的目標。本研究以資料包絡分析法為基礎，並結合共同邊界（metafrontier）分析法，針對兩岸地區在2004年至2007年共59家壽險公司，進行經營效率與Malmquist生產力指數的實證研究。在生產力變動來源的拆解上，本文延伸Pastor and Lovell（2005）的固定規模報酬模型，利用變動規模報酬的生產邊界來衡量各公司的技術變動及技術差距比率變動，使生產力變動的來源上獲得更明確的意涵。最後本文利用Tobit迴歸模型，探討影響兩岸壽險公司經營效率的因素。 / After joining the WTO in December 2001, there is the advent of economic liberalization and internationalization on the life insurance market of Taiwan and Mainland China. Therefore, how to improve the operating performance and the industrial competitiveness in the present economic circumstance is the critical and important goal of the life insurance industry in Taiwan and Mainland China. This study applies data envelopment analysis with metafrontier model to measure the managerial efficiency and Malmquist productivity index of 59 firms of life insurance industry in Taiwan and Mainland China from 2004 to 2007. On decomposing the sources of productivity change, we extend Pastor and Lovell’ s CRS model (2005) to a VRS frontier benchmark to measure technical change and technical gap ratio change, which apparently provides us a more meaningful decomposition of productivity change. Finally, this study uses Tobit regression model to examine the factors which influence the managerial efficiency of the life insurance industry in Taiwan and Mainland China.

Este trabalho apresenta um estudo de dados com resposta em intervalos limitados, mais especificamente no intervalo [0,1], como no caso de taxas e proporções. Em diversos casos práticos esta estrutura de dados apresenta uma quantidade não negligenciável de valores extremos (0 e 1) e que modelos usuais não são adequados para sua análise. Para esta situação propomos, por meio de um enfoque Bayesiano, modelos de regressão beta inflacionado de zeros e uns (BIZU) e modelos de regressão Tobit duplamente censurado adaptados nesse intervalo. Técnicas de diagnóstico e qualidade do ajuste também são discutidas. Apresentamos a análise desta estrutura de dados no contexto de série de tempo por meio da abordagem Bayesiana de modelos dinâmicos. Estudos de comportamento e previsão de séries de tempo foram explorados utilizando técnicas de Monte Carlo sequencial, conhecidas como filtro de partículas. Particularidades e competitividade entre as duas classes de modelos também foram discutidas. / This paper presents a study focused on observations in a limited interval , more specifically in [0,1] , such as rate and proportion data. In many practical cases this data structure has a considerable amount of extreme values (0 and 1) and usual classical models are not suitable for this type of data set. We propose two class of regression models to deal with this context: beta inflated of zeros and ones (BIZU) models and Tobit doubly censored models adapted in this interval. Fit quality and diagnostic techniques are also discussed. Time series of proportions are also developed through Bayesian dynamic models. Forecasting and behavioral analysis were explored using sequential Monte Carlo techniques, known as particle filters. Particularities and competitiveness between the two classes of models were also discussed as well.

Este trabalho apresenta um estudo de dados com resposta em intervalos limitados, mais especificamente no intervalo [0,1], como no caso de taxas e proporções. Em diversos casos práticos esta estrutura de dados apresenta uma quantidade não negligenciável de valores extremos (0 e 1) e que modelos usuais não são adequados para sua análise. Para esta situação propomos, por meio de um enfoque Bayesiano, modelos de regressão beta inflacionado de zeros e uns (BIZU) e modelos de regressão Tobit duplamente censurado adaptados nesse intervalo. Técnicas de diagnóstico e qualidade do ajuste também são discutidas. Apresentamos a análise desta estrutura de dados no contexto de série de tempo por meio da abordagem Bayesiana de modelos dinâmicos. Estudos de comportamento e previsão de séries de tempo foram explorados utilizando técnicas de Monte Carlo sequencial, conhecidas como filtro de partículas. Particularidades e competitividade entre as duas classes de modelos também foram discutidas. / This paper presents a study focused on observations in a limited interval , more specifically in [0,1] , such as rate and proportion data. In many practical cases this data structure has a considerable amount of extreme values (0 and 1) and usual classical models are not suitable for this type of data set. We propose two class of regression models to deal with this context: beta inflated of zeros and ones (BIZU) models and Tobit doubly censored models adapted in this interval. Fit quality and diagnostic techniques are also discussed. Time series of proportions are also developed through Bayesian dynamic models. Forecasting and behavioral analysis were explored using sequential Monte Carlo techniques, known as particle filters. Particularities and competitiveness between the two classes of models were also discussed as well.

目前對於女性董事與財務績效的研究，以國外的文獻居多，台灣的研究僅有3篇，皆是以複迴歸的方式來進行研究分析，僅有一篇是針對金融業進行研究。未來全球經濟的發展，將隨著女性職場上參與程度和社經能力的提升而有所改變。而銀行業對經濟發展有密不可分的關係，故本研究以臺灣21間上市銀行2006年至2011年間的追蹤資料（即126筆樣本觀察值）來進行實證研究。採資料包絡分析法評估績效後，再以Tobit迴歸模型探討女性董監事的比例對台灣上市銀行經營績效的影響，並加入可能影響銀行經營績效的因素作為解釋變數，包括：資本適足率、逾放比率、銀行規模、政府持股比率、銀行是否加入金控、以及時間變數等因素。實證結果發現，女性董事的比例對於銀行的經營績效在統計上有負向的影響，而女性監察人的比例則沒有顯著的影響。建議末來可繼續研究女性董監事與其它產業的績效關係，以增加女性董監事與台灣產業間之關聯性的研究。 / At present, the studies of female directors and financial performances are mostly in foreign documents, and there are only three studies from Taiwan which are based on multiple regression analysis approach of research; only one of those studies focus on financial industry. The global economic development in the future will be changed along with the level of female participation in the workplace and the enhancement of their socio-economic capabilities. Moreover, banking has a close and tight relationship with economic developments. Therefore, this study was based on the traceable data of 21 listed banks in Taiwan from 2006 to 2011 (i.e., 126 sample observations) to proceed the empirical research. After adopting data envelopment analysis to evaluate the performances, it used tobit censored regression model to discuss the influence of the operational performance of listed banks in Taiwan along with the proportion of female directors and supervisors. It also added the possible factors that may affect the banks’ performance as explanatory variables including Capital Adequacy ratio, Non-Performing Loans ratio, size of banks, Public Shareholding ratio, joining in financial holding, time variables and other factors. The result of the study showed that statistically there is a negative effect to the operational performance of the banks along with the proportion of female directors; however, there is no significant impact affected by the proportion of female supervisors. In the future it suggested that the study can be continued researching about the influence of the operational performances in other industries by the proportion of female directors and supervisors in order to increase the research of the correlation between female directors/supervisors and industry performance in Taiwan.