自1978年中國開始經濟的改革開放政策以來，吸引外資便成為其推動經濟成長的重要手段之一。1992年鄧小平南巡，再一次宣示建立「社會主義的市場經濟體制」後，由於開放的經濟政策更為明朗，使越來越多的國家到中國直接投資。自此，中國成為全世界最受歡迎的外資投資國之一。甚至在2002年超越美國，成為全世界最大的外資接受國。如此多的國家對中國展開大規模的投資，其投資的規模與投資地區的選擇卻有相當大的差異。因此，本文的研究目的，將以1993至2003年世界各國對中國投資的追蹤資料（panel data），搭配固定效果模型（fixed-effect model）與隨機效果模型（random-effect model）的估計，並以目前中國沿海發展具代表性的北京、上海與廣東三個省（市）之比較，探究影響世界各國對中國直接投資的決定因素。 實證結果發現影響外商直接投資北京、上海與廣東的決定因素中，顯著影響的變數為相對工資率、對中國貿易依存度、相對匯率以及相對借貸成本。而其餘的變數，如相對國內生產毛額、相對每人國內生產毛額和相對國家風險等皆不顯著，反映了其皆非外商直接投資中國時所考量的決定因素。 / Since 1978, China has adopted the so-called “open door policy”, attracting foreign direct investment (FDI) has become one of the most important methods to facilitate its economic growth. However, foreign countries didn’t invest large amount toward China until Deng Xiaoping’s southern trip in 1992. The purpose of this study is thus to investigate the determinants of FDI from different foreign countries to different regions in China after foreign countries started to invest tremendous amount toward China. This study adopts fixed-effect model and random-effect model to investigate the determinants of FDI in China with panel data of Beijing, Shanghai and Guangdong during the period of 1993-2003. The result shows relative wage rate, trade dependence to China, relative exchange rate and relative borrowing cost are the most important factors in attracting FDI in Beijing, Shanghai and Guangdong during 1993-2003. Finally, in order to reduce the mistakes occurred in positive models and enable the study more rigorous, then uses more methods to test the models and the result.

This thesis consists of two parts. The first part focuses on design and analysis for computer experiments and the second part deals with binary time series and its application to kinetic studies in micropipette experiments. The first part of the thesis addresses three problems. The first problem is concerned with optimal design of computer experiments. Latin hypercube designs (LHDs) have been used extensively for computer experiments. A multi-objective optimization approach is proposed to find good LHDs by combining correlation and distance performance measures. Several examples are presented to show that the obtained designs are good in terms of both criteria. The second problem is related to the analysis of computer experiments. Kriging is the most popular method for approximating complex computer models. Here a modified kriging method is proposed, which has an unknown mean model. Therefore it is called blind kriging. The unknown mean model is identified from experimental data using a Bayesian variable selection technique. Many examples are presented which show remarkable improvement in prediction using blind kriging over ordinary kriging. The third problem is related to computer experiments with nested and branching factors. Design and analysis of experiments with branching and nested factors are challenging and have not received much attention in the literature. Motivated by a computer experiment in a machining process, we develop optimal LHDs and kriging methods that can accommodate branching and nested factors. Through the application of the proposed methods, optimal machining conditions and tool edge geometry are attained, which resulted in a remarkable improvement in the machining process. The second part of the thesis deals with binary time series analysis with application to cell adhesion frequency experiments. Motivated by the analysis of repeated adhesion tests, a binary time series model incorporating random effects is developed in this chapter. A goodness-of-fit statistic is introduced to assess the adequacy of distribution assumptions on the dependent binary data with random effects. Application of the proposed methodology to real data from a T-cell experiment reveals some interesting information. These results provide some quantitative evidence to the speculation that cells can have ¡§memory¡¨ in their adhesion behavior.

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.

<div><b>1. A Closed-Loop Machine Learning and Compensation Framework for Geometric Accuracy Control of 3D Printed Products</b></div><div><b><br></b></div>Additive manufacturing (AM) systems enable direct printing of three-dimensional (3D) physical products from computer-aided design (CAD) models. Despite the many advantages that AM systems have over traditional manufacturing, one of their significant limitations that impedes their wide adoption is geometric inaccuracies, or shape deviations between the printed product and the nominal CAD model. Machine learning for shape deviations can enable geometric accuracy control of 3D printed products via the generation of compensation plans, which are modifications of CAD models informed by the machine learning algorithm that reduce deviations in expectation. However, existing machine learning and compensation frameworks cannot accommodate deviations of fully 3D shapes with different geometries. The feasibility of existing frameworks for geometric accuracy control is further limited by resource constraints in AM systems that prevent the printing of multiple copies of new shapes.<div><br></div><div>We present a closed-loop machine learning and compensation framework that can improve geometric accuracy control of 3D shapes in AM systems. Our framework is based on a Bayesian extreme learning machine (BELM) architecture that leverages data and deviation models from previously printed products to transfer deviation models, and more accurately capture deviation patterns, for new 3D products. The closed-loop nature of compensation under our framework, in which past compensated products that do not adequately meet dimensional specifications are fed into the BELMs to re-learn the deviation model, enables the identification of effective compensation plans and satisfies resource constraints by printing only one new shape at a time. The power and cost-effectiveness of our framework are demonstrated with two validation experiments that involve different geometries for a Markforged Metal X AM machine printing 17-4 PH stainless steel products. As demonstrated in our case studies, our framework can reduce shape inaccuracies by 30% to 60% (depending on a shape's geometric complexity) in at most two iterations, with three training shapes and one or two test shapes for a specific geometry involved across the iterations. We also perform an additional validation experiment using a third geometry to establish the capabilities of our framework for prospective shape deviation prediction of 3D shapes that have never been printed before. This third experiment indicates that choosing one suitable class of past products for prospective prediction and model transfer, instead of including all past printed products with different geometries, could be sufficient for obtaining deviation models with good predictive performance. Ultimately, our closed-loop machine learning and compensation framework provides an important step towards accurate and cost-efficient deviation modeling and compensation for fully 3D printed products using a minimal number of printed training and test shapes, and thereby can advance AM as a high-quality manufacturing paradigm.<br></div><div><br></div><div><b>2. Multiple Imputation and the Bootstrap for the Analysis of Big Data with Missingness</b></div><div><br></div><div>Inference can be a challenging task for Big Data. Two significant issues are that Big Data frequently exhibit complicated missing data patterns, and that the complex statistical models and machine learning algorithms typically used to analyze Big Data do not have convenient quantification of uncertainties for estimators. These two difficulties have previously been addressed using multiple imputation and the bootstrap, respectively. However, it is not clear how multiple imputation and bootstrap procedures can be effectively combined to perform statistical inferences on Big Data with missing values. We investigate a practical framework for the combination of multiple imputation and bootstrap methods. Our framework is based on two principles: distribution of multiple imputation and bootstrap calculations across parallel computational cores, and the quantification of sources of variability involved in bootstrap procedures that use subsampling techniques via random effects or hierarchical models. This framework effectively extends the scope of existing methods for multiple imputation and the bootstrap to a broad range of Big Data settings. We perform simulation studies for linear and logistic regression across Big Data settings with different rates of missingness to characterize the frequentist properties and computational efficiencies of the combinations of multiple imputation and the bootstrap. We further illustrate how effective combinations of multiple imputation and the bootstrap for Big Data analyses can be identified in practice by means of both the simulation studies and a case study on COVID infection status data. Ultimately, our investigation demonstrates how the flexible combination of multiple imputation and the bootstrap under our framework can enable valid statistical inferences in an effective manner for Big Data with missingness.<br></div>

台灣和中國大陸於2010年六月正式簽署「經濟合作架構協議」（ECFA）。無疑地，這是兩岸交流有史以來規模最大、最具官方性質的制度性協商。在象徵意義上，意味著兩岸經濟整合邁入一個嶄新的階段。在實質意義上，透過早期收穫計畫的制度安排，使得兩岸之間的部分貨品和服務享有關稅調降的特殊待遇，對於台灣的整體經濟和部分產業具有立即性的影響。因此，本文旨在探討兩岸簽署ECFA前後，台灣民眾的統獨態度有無發生變化？在影響選民統獨態度因素中，有長期穩定與短期變動，也有感性與理性面向，選民對於兩岸簽訂ECFA的經濟效應評估又扮演了何種角色？最後，隨著兩岸經濟整合的腳步加速，理性層次的麵包效應又是否可能抵銷情感認同的作用？ 本研究使用2008年到2012年「台灣選舉與民主化調查」的定群追蹤資料（panel data），並以「固定與隨機效果並用法」（hybrid method of fixed and random effect model）來分析兩個時間點民眾統獨立場的動態變化。研究結果發現從08年到12年這段時間，民眾的統獨立場呈現往現狀/統一方向移動的趨勢，儘管變化的量不大，但在統計上卻是顯著的。在兩個時間點的動態架構中，選民對於ECFA經濟效益評估的態度變化，不僅與統獨立場的變遷模式與變化方向互相連動，在控制其他變數之後，ECFA經濟評估的態度變化對於統獨立場也有獨立性的影響效果。最後，當短期經濟利益和情感認同相互牴觸時，ECFA經濟的效果甚至會削弱感性認同的作用力。這意味在給定台灣人認同沒有改變的情況下，民眾仍有可能因為簽署ECFA的經濟因素而移動其統獨立場。因此，隨著兩岸經濟整合日益加深，影響個人統獨態度中理性層面利害考量的因素應該予以重視。 / The Taiwanese government has signed the ECFA with China in June 2010. Undoubtedly, ECFA is one of the largest and most official institutional negotiations in the history of cross-strait interactions and exchanges. Signing ECFA with China not only represents that cross-strait economic integration has entered into a new stage, through the arrangements of early harvest program, its impacts on Taiwan’s economy and industry are also immediate. Accordingly, this study aims to explore whether Taiwan people’s attitude toward the independence/unification changed or not after signing ECFA? How the economic inducement from China affect Taiwanese voters’ policy stances on independence/unification issue? Finally, as the accelerated pace of cross-strait economic integration, whether economic factors such as ECFA evaluation may offset the effects of emotional identity on the issue of independence/unification? By using individual panel data from ‘Taiwan Election and Democratization Study’ (TEDS), and taking advantage of hybrid method of fixed and random effect model, the empirical results show that respondents in 2012 are statistically significantly more inclined to maintain status quo or unification in comparison with their attitudes in 2008. Moreover, the attitudinal change of ECFA evaluation are not only systematically associated with the change of policy stance on independence/unification issue, it also reveals independent effect in the statistical model after controlling for other variables. Finally, although emotional affective identity is an important factor to determine public’s policy stances on the issue of Independence/Unification, its effects have begun to weaken especially when the economic interests are large and visible. The implication is that we shouldn’t underestimate the logic importance of political economy played in the trend of regional economic integration, and short-term economic fluctuations may have influence on long-term affective identity.

在全球化的趨勢之下，國際分工不可避免地成為跨國公司運作的趨勢。2013年2月，OECD發布《處理稅基侵蝕及利潤移轉》的報告表示，跨國公司利潤移轉策略的採取被認為是稅基侵蝕的主要原因。基於BEPS已經成為各國非常重視的議題，世界各國也為了保全稅基及防杜利潤移出，紛紛訂出反制措施。這些反制措施是否能遏制利潤不當的移動，是一個值得重視議題。惟目前學術文獻上並未有一篇全面盤點這些反制措施及地主國租稅制度對利潤移轉的影響。 故本篇研究以2005年至2012年台灣電子工業作為研究對象，利用橫斷面及時間序列的追蹤資料 (panel data) 之隨機模型做估計，探討台灣跨國公司之電子業海外子公司的利潤移轉是否會受到租稅規避行為的影響。結果顯示，利潤移轉會受到以下四種國際租稅規避工具所影響，分別是地主國是否有移轉訂價的規範、是否有預先移轉訂價規範、是否有反資本弱化條款以及地主國是否為租稅天堂。

Dans le but de faire face aux défis interdépendants en termes d’épuisement des ressources énergétiques, de dégradation environnementale et des préoccupations de santé publique dans le contexte chinois en réponse au développement durable, nous nous concentrons sur l'étude des politiques en matière d’énergie, d’environnement et de santé en Chine. Dans le chapitre 1, nous donnons un aperçu des politiques chinoises en matière d’énergie, d’environnement et de santé au cours des 20 dernières années afin de connaître les orientations politiques futures auxquelles le gouvernement n'a pas donné une attention suffisante. Dans les trois chapitres suivants, nous proposons une série d'études empiriques afin de tirer quelques implications politiques utiles. Dans le chapitre 2, nous étudions l'impact de l'urbanisation, de l'adaptation de la structure industrielle, du prix de l'énergie et de l'exportation sur les intensités énergétiques agrégés et désagrégés des provinces. Dans le chapitre 3, nous étudions les facteurs qui expliquent la transition énergétique vers des combustibles propres des ménages ruraux. Dans le chapitre 4, nous examinons les effets conjoints des risques environnementaux, du revenu individuel, des politiques de santé sur l'état de santé des adultes chinois. En particulier, nos résultats empiriques suggèrent d’intégrer le développement urbain dans la stratégie d'économies d'énergie; de considérer des substitutions/complémentarités complexes parmi les sources d'énergie et entre l'énergie et l’alimentation pour les ménages ruraux; d’aligner les politiques environnementales, énergétiques et alimentaires avec les politiques de santé. / With the purpose of coping with the intertwined challenges of energy depletion, environmental degradation and public health concerns in the Chinese-specific context in response to sustainable development, we focus on investigating China’s energy, environment and health policies. In chapter 1, we provide an overview of China’s energy, environment and health policies over the past 20 years in order to know about the future policy directions to which the government has not given a sufficient attention. In the following three chapters, we provide a series of empirical studies so as to derive some useful policy implications. In chapter 2, we investigate the impact of urbanization, industrial structure adjustment, energy price and export on provincial aggregate and disaggregate energy intensities. In chapter 3, we study the factors explaining the switches from dirty to clean fuel sources in rural households. In chapter 4, we examine the joint effects of environmental hazards, individual income and health policies on the health status of Chinese adults. Our empirical findings particularly suggest integrating urban development into the strategy of energy saving; considering the complex substitutions/complementarities among energy sources and between energy and food for rural households; aligning the environment, energy and food policies with health policies.

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人類慾望無窮而資源有限，所以如何將資源做最有效的使用一直是經濟學所追求的課題。有關效率的規範分析中，巴瑞圖最適（Pareto optimality）為接受度最高的準則。基於巴瑞圖效率的觀點，不論是營利組織或非營利組織其經營之基本理念皆是希望以最少的投入獲得最大的產出，因此衡量投入與產出間之相對表現即為效率的評估。非營利組織及公共部門因為有許多產出、投入不易量化，故其效率不易評定。此一情況一直到DEA（Data Envelopment Analysis；資料包絡分析法）發展才逐漸改善。另外，有關DEA的運用幾乎都集中在個別決策單位的效率衡量，將之應用在衡量總體經濟的表現上非常少見。所以論文第肆章是按傳統方式以DEA衡量我國地方政府的效率並分析造成效率差異的原因，第參章則將DEA的概念應用於經濟成長上，探討使經濟成長達到極大化之租稅負擔及租稅結構。又效率的追求為經濟學的主軸，但中央政府的效率目標與地方政府並不相同，由於目標不同，因此彼此所訂的租稅政策亦不相同。本文第伍章試圖提出一理論模型說明中央政府在面對異質地區的垂直外部性下如何有效率的訂定其租稅政策。 / The human desires are infinite but resources are scarce. Using resources effectively is the topic of the economics. In efficient analyses, the Pareto optimality is the highest criterion to accept. Based on Pareto efficiency, the basic idea is to obtain the most outputs by the least inputs. Therefore the efficiency measurement is to calculate the relative performance of inputs and outputs. The nonprofit organization and the public agencies have many outputs and inputs not easy to be quantified; hence, their efficiency is not easy to evaluate. This phenomenon doesn’t improve until DEA (Data Envelopment Analysis) was developed. However, the application of DEA concentrates nearly on the efficiency measurement of individual policy-making unit; the application is be rarely used in measuring the performance of the macro-economy. Chapter 4 of this dissertation measures and explains the variation in cost efficiency of the local governments in Taiwan area. Chapter 3 deals with the application the DEA to economic growth, estimating a combination of the tax burden(the ratio of tax revenue to GDP）and the tax structure(the ratio of indirect taxes to direct taxes)which would maximize the rate of growth of GDP of Taiwan. Efficiency is the core of economics, but the national government’s efficient goal is not as same as the local government’s. Because their goals are not consistent, thus the tax policies are different. Chapter 5 attempts to propose a theoretical model to explain how a national or federal government decides its tax policy in the vertical externalities happening in heterogeneous states.