本研究係針對台灣股票市場中新上市與現金增資普通股配售方式的選定及其和中長期績效之關聯做探討，研究議題如下： (1) 探討發行公司營運風險對配售方式選定的影響 參酌國內外相關研究，選定可能反應公司營運風險及攸關配售方式選定的因子為自變數，使用複迴歸的方式進行檢定，找出對於集中市場發行個案配售方式的選定具有顯著影響能力的因子。 (2) 比較採用不同配售方式對於發行折價之影響，分組計算各種配售方式之發行折價程度 本研究分組比較以原有股份公開承銷的新上市發行股份其銷價與新股上市後至停止上漲（下跌）日價格的變動百分比，檢定採用不同配售方式對於發行折價之影響。 (3) 驗證發行公司配售方式的決策是否極大化股東財富 採用 Probit 模型來消除自我選擇性偏誤(Self-Selection Biases)，估算以原有股份公開承銷的新上市發行公司，於理論上改採另一配售方式時，其發行折價的變化情形。 (4) 檢定採用不同配銷方式的新上市普通股，其中長期績效的表現是否有所差異 於計算相對財富指標及平均報酬率後，比較採不同配售方式的新上市股與市場加權股價指數的相對績效表現是否有所差異，並檢定採特定方式的新上市股是否有績效低落的現象，或是特殊的價格變化趨勢，以為投資人、發行公司及承銷商相關決策之參考。 藉由分組討論發行公司所採行的配售方式與中長期股價行為的關聯，可以檢定各種配售方式其承銷價格訂定的適當性及該訊息因子（採行的配售方式）對於中長期價格行為推估的參考價值，所獲致的結論亦可提供投資人豐富的決策意涵。因為： 1.以投資人的角度而言，中長期價格表現的掌握，或許能提供賺取報酬的積極交易機會。 2.長期之下，如果初次公開發行的股價變化程度很大，意味著發行公司掌握「機會窗」(Opportunity Windows)的發行時機。 3.公司募集權益資金的成本與投資人交易成本、實際獲得的報酬皆有關聯，投資人所獲得的報酬越低，代表著公司資金成本越低。 4.藉由本研究的實證結果，投資人可以特性發行案所採行的配售方式為訊息因子，依其採行的配售方式推論發行公司的營運風險及特質。 實證結果發現，台灣證券交易所現金增資及新上市發行案的配售方式選定與發行公司經營風險的關連並不顯著，有顯著關連者為發行規模及發行時市況兩因素。但資訊不對稱程度相對較高的現金增資案發行公司，其配售方式選定受公司風險影響假說獲得支持。 採競價拍賣配售方式之新上市發行公司，在配售方式的選定上不存在選擇性偏誤的現象，亦即經營當局對於配售方式的選擇符合極大化股東財務原則，符合本研究臆測。而採公開申購配售方式之新上市股存在未追求極大化股東財富的反功能決策現象，但其成因並不若本研究之推論為內部人持股比例過低所造成。 採行公開申購方式的發行公司其 180 交易天、270 交易天、360 交易天期的相對財富指標平均數及中位數皆優於採行競價拍賣的公司。僅考量新上市電子類股的中長期股價績效結果，其 180 交易天、270 交易天期的相對財富指標平均數及中位數皆顯著優於採行競價拍賣的公司，360 交易天期的相對財富指標則無顯著差異。

This dissertation considers three topics under the themes of wetland restoration, urban sprawl, and recreation demand employing spatial data and analysis. A key question addressed in the first essay is how we can identify priority areas for wetlands restoration along the Louisiana coast under the Coastal Wetlands Planning, Protection, and Restoration Act by estimating amenity values received by nearby residents from hypothetical wetlands restoration projects. The second essay evaluates the effectiveness of alternative land-use policy variables for controlling development in a sprawling metropolitan area during two extreme market conditions. The third essay estimates the effect on consumer welfare from improved satisfaction of recreation information availability.

Wavelet methods possess versatile properties for statistical applications. We would like to explore the advantages of using wavelets in the analyses in two different research areas. First of all, we develop an integrated tool for online detection of network anomalies. We consider statistical change point detection algorithms, for both local changes in the variance and for jumps detection, and propose modified versions of these algorithms based on moving window techniques. We investigate performances on simulated data and on network traffic data with several superimposed attacks. All detection methods are based on wavelet packets transformations. We also propose a Bayesian model for the analysis of high-throughput data where the outcome of interest has a natural ordering. The method provides a unified approach for identifying relevant markers and predicting class memberships. This is accomplished by building a stochastic search variable selection method into an ordinal model. We apply the methodology to the analysis of proteomic studies in prostate cancer. We explore wavelet-based techniques to remove noise from the protein mass spectra. The goal is to identify protein markers associated with prostate-specific antigen (PSA) level, an ordinal diagnostic measure currently used to stratify patients into different risk groups.

The main role of roadway lighting is to produce quick, accurate and comfortable visibility during nighttime conditions. It is commonly known that good lighting levels enable motorists, pedestrians and bicyclists to obtain necessary visual information in an effective and efficient manner. Many previous studies also proved that roadway lighting minimizes the likelihood of crashes by providing better visibility for roadway users. Appropriate and adequate roadway lighting illuminance levels for each roadway classification and pedestrian areas are essential to provide safe and comfortable usage. These levels are usually provided by national, or local standards and guidelines. The Florida Department of Transportation (FDOT) Plan Preparation Manual recommends a roadway lighting illuminance level average standard of 1.0 horizontal foot candle (fc) for all the roadway segments used in this research. The FDOT Plan Preparation Manual also states that this value should be considered standard, but should be increased if necessary to maintain an acceptable uniformity illuminance ratio. This study aimed to find the relationship between nighttime crash injury severity and roadway lighting illuminance. To accomplish this, the research team analyzed crash data and roadway lighting illuminance measured in roadway segments within the West Central Florida Region. An Ordered Probit Model was developed to understand the relationship between roadway lighting illuminance levels and crash injury severity. Additionally, a Negative Binomial Model was used to determine which roadway lighting illuminance levels can be more beneficial in reducing the counts of crashes resulting in injuries. A comprehensive literature review was conducted using longitudinal studies with and without roadway lighting. Results showed that on the same roadways there was a significant decrease in the number of nighttime crashes with the presence of roadway lighting. In this research, roadway lighting illuminance was measured every 40 feet using an Advanced Lighting Measurement System (ALMS) on a total of 245 centerline miles of roadway segments within the West Central Florida Region. The data were mapped and then analyzed using the existing mile post. During the process of crash data analysis, it was observed that rear-end collisions were the most common first harmful event observed in all crashes, regardless of the lighting conditions. Meanwhile, the average injury severity for all crashes, was found to be possible injury regardless of the lighting conditions (day, dark, dusk, and dawn). Finally, this research presented an Ordered Probit Model, developed to understand the existing relationship between roadway lighting illuminance levels and injury severity within the West Central Florida Region. It was observed that having a roadway lighting average moving illuminance range between 0.4 to 0.6 foot candles (fc) was more likely to have a positive effect in reducing the probability of injury severity during a nighttime crash. A Negative Binomial Model was conducted to determine if the roadway lighting average moving illuminance level, found on the Ordered Probit Model was beneficial in reducing crash injury severity during nighttime, would also be beneficial in reducing the counts of crashes resulting in injuries. It was observed that a roadway lighting average moving illuminance, range between 0.4 to 0.6 fc, was more likely to reduce the count of crashes resulting in injuries during nighttime conditions, thus increasing roadway safety. It was also observed that other factors such as pavement condition, site location (intersection or no intersection), number of lanes, and traffic volume can affect the severity and counts of nighttime crashes. The results of this study suggest that simply adding more roadway lighting does not make the roadway safer. The fact is that a reduction in the amount of roadway lighting illuminance can produce savings in energy consumption and help the environment by reducing light pollution. Moreover, these results show that designing roadway lighting systems go beyond the initial design process, it also requires continuous maintenance. Furthermore, regulations for new developments and the introduction of additional lighting sources near roadway facilities (that are not created with the intent of being used for roadway users) need to be created.

Safety at intersections is of significant interest to transportation professionals due to the large number of possible conflicts that occur at those locations. In particular, rural intersections have been recognized as one of the most hazardous locations on roads. However, most models of crash frequency at rural intersections, and road segments in general, do not differentiate between crash type (such as angle, rear-end or sideswipe) and injury severity (such as fatal injury, non-fatal injury, possible injury or property damage only). Thus, there is a need to be able to identify the differential impacts of intersection-specific and other variables on crash types and severity levels. This thesis builds upon the work of Bhat et al., (2013b) to formulate and apply a novel approach for the joint modeling of crash frequency and combinations of crash type and injury severity. The proposed framework explicitly links a count data model (to model crash frequency) with a discrete choice model (to model combinations of crash type and injury severity), and uses a multinomial probit kernel for the discrete choice model and introduces unobserved heterogeneity in both the crash frequency model and the discrete choice model, while also accommodates excess of zeros. The results show that the type of traffic control and the number of entering roads are the most important determinants of crash counts and crash type/injury severity, and the results from our analysis underscore the value of our proposed model for data fit purposes as well as to accurately estimate variable effects. / text

Many databases involve ordered discrete responses in a temporal and spatial context, including, for example, land development intensity levels, vehicle ownership, and pavement conditions. An appreciation of such behaviors requires rigorous statistical methods, recognizing spatial effects and dynamic processes. This dissertation develops a dynamic spatial ordered probit (DSOP) model in order to capture patterns of spatial and temporal autocorrelation in ordered categorical response data. This model is estimated in a Bayesian framework using Gibbs sampling and data augmentation, in order to generate all autocorrelated latent variables. The specifications, methodologies, and applications undertaken here advance the field of spatial econometrics while enhancing our understanding of land use and air quality changes. The proposed DSOP model incorporates spatial effects in an ordered probit model by allowing for inter-regional spatial interactions and heteroskedasticity, along with random effects across regions (where "region" describes any cluster of observational units). The model assumes an autoregressive, AR(1), process across latent response values, thereby recognizing time-series dynamics in panel data sets. The model code and estimation approach is first tested on simulated data sets, in order to reproduce known parameter values and provide insights into estimation performance. Root mean squared errors (RMSE) are used to evaluate the accuracy of estimates, and the deviance information criterion (DIC) is used for model comparisons. It is found that the DSOP model yields much more accurate estimates than standard, non-spatial techniques. As for model selection, even considering the penalty for using more parameters, the DSOP model is clearly preferred to standard OP, dynamic OP and spatial OP models. The model and methods are then used to analyze both land use and air quality (ozone) dynamics in Austin, Texas. In analyzing Austin's land use intensity patterns over a 4-point panel, the observational units are 300 m × 300 m grid cells derived from satellite images (at 30 m resolution). The sample contains 2,771 such grid cells, spread among 57 clusters (zip code regions), covering about 10% of the overall study area. In this analysis, temporal and spatial autocorrelation effects are found to be significantly positive. In addition, increases in travel times to the region's central business district (CBD) are estimated to substantially reduce land development intensity. The observational units for the ozone variation analysis are 4 km × 4 km grid cells, and all 132 observations falling in the study area are used. While variations in ozone concentration levels are found to exhibit strong patterns of temporal autocorrelation, they appear strikingly random in a spatial context (after controlling for local land cover, transportation, and temperature conditions). While transportation and land cover conditions appear to influence ozone levels, their effects are not as instantaneous, nor as practically significant as the impact of temperature. The proposed and tested DSOP model is felt to be a significant contribution to the field of spatial econometrics, where binary applications (for discrete response data) have been seen as the cutting edge. The Bayesian framework and Gibbs sampling techniques used here permit such complexity, in world of two-dimensional autocorrelation. / text

人力資本的培養，仍須回到最根本的「教育」問題。隨著家庭結構改變和社會專業化分工的影響，學校和家庭外的社會化機構對於學生教育學習和成長的過程雖已扮演更加重要的角色，然而，我們亦不能忽略家庭教育對於學生教育表現的重要影響力。本文利用中研院台灣教育長期追蹤資料庫(TEPS資料庫)中，第一波(2001)、第二波(2003)國中生調查問卷和第三波(2005)高中職五專學生問卷資料，並利用複迴歸模型 (multiple regression)和Probit機率模型 (probit probability model)進行分析，並將升學發展成果分為考上公立普通高中和未考上公立普通高中兩大類，探討影響中學生升學發展成果之因素。研究結果發現，父/母親教育程度、財務資本、文化資本、母親教育參與和教育期望對於考上公立普通高中之機率有顯著的正向影響，而婚姻狀態、手足數目、社會資本和城鄉別則對考上公立普通高中之機率有顯著的負向影響。

We examine the gender gap in school attendance of children aged 7-14 in India using National Family Health Survey Three (NFHS-3). We demonstrate that the choice of the sample examined has important implications for policy. A household decision model is used to motivate whether a child attends school and/or works. A bivariate probit model and Blinder-Oaxaca Decomposition are applied to see how changing sample groups and adding regressors impact results, and the implications this has upon gender gap and effectiveness of centralized policy as opposed to decentralized policy. Results show the gender gap is sensitive to the sub samples chosen (e.g. a particular state, a specific location (urban or rural), and gender) and to the choice of regressors, and that centralized policy may be less effective than decentralized policy. Parental education, wealth, location and gender are found to be the most volatile and influential variables in the household decision process. / Graduate

Techn. University, Diss., 2004--München.

Uma das grandes dificuldades na mensuração monetária dos bens e serviços naturais, ou ambientais, reside na valoração do não-uso dos mesmos. Enquanto que o valor de uso de um recurso ambiental pode ser obtido através do mercado, que revela as preferências do consumidor, o valor de não-uso somente pode ser apropriado através do uso de mercados hipotéticos. Dentre as técnicas utilizadas, o método de valoração contingente (CVM) é o mais tradicional mas na última década, diversos economistas têm se voltado para novas abordagens evoluídas das áreas de marketing e transportes. Esses métodos, classificados como de análise conjunta (conjoint analysis) que podem ser, ainda, subdivididos em rating contingent e ranking contingent, são o estudo desse trabalho. O objetivo principal foi comparar os resultados, obtidos por um mesmo conjunto de observações, para as principais estatísticas referentes a precisão dos métodos, quando sujeitas a várias formas funcionais de utilidade, distintos graus de preferência ambiental dos consumidores e diferentes métodos de estimação. Além disso, é apresentada uma síntese crítica dos métodos em análise e os procedimentos metodológicos para o desenvolvimento e aplicação dos mesmos. Para a realização dessa análise, primeiramente foram definidos coeficientes para as utilidades dos bens – ambiental, não ambiental e monetário. Posteriormente, fez-se uso da técnica de Monte Carlo para a simulação da situação/problema e, ao final, foram utilizados os modelos de variável dependente discreta (probit ou logit ordenados) para a estimação final dos parâmetros definidos ex-ante. Constatou-se que o uso do modelo logit ordered para a estimação dos verdadeiros parâmetros mostrou-se mais preciso para a estimação dos coeficientes do que o uso do probit ordenado. Dentre as técnicas em análise, o método de valoração denominado rating contingente apresentou melhores resultados do que o ranking. No que tange às formas funcionais da utilidade e preferências dos consumidores, não foi possível constatar uma relação entre a qualidade das estimativas e a forma funcional. Foi possível, ainda, verificar que os métodos rating e ranking contingente estão bem fundamentados na teoria microeconômica, contudo, verifica-se a dificuldade de se encontrar um valor econômico total a todas as situações que envolvem bens ambientais, pois existem dificuldades a serem vencidas, não especificas aos métodos de valoração mas comum à economia ambiental. / The difficulties in giving monetary values on natural services and goods comes from valuing the non-use of them. Although the use value of environmental resources can be appropriated from the market that indicates the consumer preferences, the non-use value can only be appropriated through the hypothetic market. The contingent valuation method (CVM) is the most traditional of the techniques in use, but in the last decade, some economists have directed themselves toward new approaches in the marketing and transport areas. The goal of this work are the methods classified as conjoint analysis, which may be separated into rating contingent and ranking contingent. The main objective is the analysis of the statistics to compare the precision of the methods when submitted to different utility function forms, distinct levels of environmental preferences and diverse estimation methods. It presents, also, a synthesis of the analyzed methods and the methodological procedure to the development and application of the methods. The execution of that work was defined ex-ante the coefficients for the utilities of the goods – being monetary, environmental and non-environmental. Later it was necessary the use of Monte Carlo Method to simulate the situation that was posteriorly solved – being the coefficients estimated - with the use of discrete dependent variable models – ordered probit and ordered logit. Ordered logit model showed to be the most precise in estimating real parameters than ordered probit. The rating contingent get the best results when compared to the ranking contingent. It was not possible to get a good relation between the goods estimates and the functional form of consumer preference. In closing, it was possible to verify that the rating and ranking contingent methods have basis in the microeconomic theory although the difficulties into getting the total economic value of ambiental sources was cleared, as the problems aren´t specified to the methods studied but are general to the environmental economy.