在全球化趨勢下，地方競爭將取代國家的競爭，地方是國家能否與全球競爭之關鍵，提高地方的競爭優勢與發展地方經濟是各國政府努力的目標。財政制度對長期地方發展扮演重要角色。透過政府間的權限與財源之劃分，一方面可使政府所提供之財貨和勞務適應不同地方人民偏好之制度效率目標，進而使所得成長；另方面可維持全國一致性和地方間的發展平衡，避免各地方所得分配過度懸殊的公平目標。良好的財政制度必須能提升各政府部門自我負責性及經濟效率，促進地方所得成長卻不會傷害地方間均衡發展之公平目標。本文以單根檢定法分析發現民國72年至93年間我國政府部門財政制度變遷，以及民國88年以後財政收支劃分法修正後財政制度調整，的確使政府間財政資源分配更趨向公平，但多個地方政府間財政自主程度並未提升且差異大。又透過民國79年至93年23個直轄市與縣市地方政府長期追蹤資料，分析發現我國財政制度在地方發展上扮演非常重要角色。財政分權制度與地方政府財政收支制度的確對各地方所得成長率與地方所得分配有顯著影響效果。但地方政府財政收支制度無法發揮效率，對地方發展有不利影響。88年財政制度調整後地方財政制度對地方發展之不利影響並未有所改善。本文根據研究結果提出制度建議，以作為未來制定地方財政制度與地方發展政策之參考。 / Local governments faced severe fiscal imbalance problems for a long time, caused in part by long-term structural imbalances between their spending and revenue requirements. May be financial structural has positive consequences on local economic development. The article examines the relationship between the fiscal structure of local government and local economic development. Although most prior empirical studies present inconsistent findings about the effects of local taxing and spending policies, but more empirical works conclude that local income growth relates negatively to tax increases if the revenue finances income redistribution, but not if the revenue finances public services. The study examines these issues with more recent panel data of Taiwan and with more careful attention the effects of fiscal decentralization. We conclude that local economic development relates negatively to local tax increases if the revenue finances local public service . Local Financial structural and fiscal decentralization have negative consequences on local economic development.

本論文包括3篇時間序列方法在財務的應用。第一篇以門檻向量自我迴歸模型(threshold vector autoregression)分析股市訊息傳遞的不對稱效果；第二篇利用不對稱共整合模型(asymmetric cointegration)分析中國大陸股市之間長期均衡關係；第三篇根據追蹤資料共整合檢定(panel Cointegration test)檢定購買力平價說。 第一篇文章利用門檻向量自我迴歸模型分析Nasdaq股市對台灣、日本與韓國股市不對稱的訊息傳遞效果。實證結果發現，當Nasdaq市場處於下跌狀態時（壞消息狀態），Nasdaq市場干擾對亞洲股市的衝擊較大，反之，當Nasdaq市場處於上漲狀態時（好消息狀態）時，Nasdaq市場干擾對亞洲股市的衝擊較小，而在壞消息狀態時，Nasdaq指數大跌對Jasdaq指數與Kosdaq指數的衝擊效果大於Nasdaq指數大漲的效果，Nasdaq指數小跌所產生的衝擊與小漲所產生的效果具有對稱性。 第二篇文章以Enders and Siklos(2001)不對稱共整合模型探討，中國大陸上海及深圳A股與B股股價指數之間長期不對稱的均衡關係，實證結果發現，在1992年10月至2001年8月，上海A股指數與深圳A股指數之間具有不對稱共整合關係，且當上海A股處於好消息狀態（股市上漲）時，其誤差修正項的調整速度較壞消息狀態（股市下跌）之下為快，此外，上海A股指數與深圳A股指數之間其有雙向的連動關係。在B股開放之後，則是深圳股市A股與B股指數存在不對稱共整合關係，同時Granger因果關係檢定顯示深圳B股指數領先A股指數。 第三篇文章利用Pedroni(2001)追蹤資料共整合檢定，探討大麥克漢堡價格與CPI兩種不同的價格指數用於檢定購買力平價說的有效性，根據14個國家1992-1999年的追蹤資料得到的實證結果顯示，以名目匯率作為被解釋變數，則大麥克漢堡價格與CPI都是支持PPP假說，然而若以相對價格為被解釋變數，則只有大麥克漢堡價格是支持PPP假說，而以CPI為基礎的PPP假說則是無法得到支持。除此之外，本文的實證結論並不受生產力差異的影響。 關鍵字：門檻向量自我迴歸模型、不對稱共整合、追蹤資料共整合、股票市場、購買力平價說 / This dissertation includes three financial applications using time series methods. The first article investigates the asymmetric effects of information transmissions in stock markets using threshold vector autoregression model. The second article uses asymmetric cointegration to study the long-run equilibium relationships among Chinese stock markets. The third article uses panal cointegration to test purchasing-power parity (PPP). Firstly, we examines the asymmetric effects of information transmissions of Nasdaq stock market on Taiwan, Japan, and Korea stock markets by using a threshold vector autoregressive model. And also, we check whether Nasdaq stock market have different impacts on organized stock exchanges (including TAIEX, NIKKEI 225 Index, Korea Composite Index) and over-the-counter markets (including Taisdaq Index, Jasdaq Index, and Kosdaq Index) or not. The empirical results indicate that negative innovations in Nasdaq market (bad news regime) have large influence on Asia stock markets. Particularly, the positive innovations in Nasdaq market (good news regime) have small influence on Asia stock market. The large negative innovations in Nasdaq market have great influence than those of the large positive innovations on Jasdaq Index and Kosdaq Index in bad news regime. The second article uses Enders and Sikios's (2001) asymmetric cointegration model to investigate the long-run asymmetric equihbrium relationships. The empirical results find that there exits an asymmetric cointegrated relationship between Shanghai A share index and Shenzhen A share index for the period from October 1992 to August 2001. The adjustment parameters of error correction term at Shanghai A share market are larger in bad-news regime than those in good-news regime. This result reveals investors at Shanghai possess over-reaction behavior on news of stock market. Moreover, there exists a bi-directional Granger causality between Shanghai A share index and Shenzhen A share index. We find there exists an asymmetric cointegrated relationship between Shenzhen A share index and Shenzhen B share index after 19 February 2001. Furthermore, the Shenzhen B share index leads Shenzhen A share index after 19 February 2001. The third article uses Pedroni's (2001) panel cointegration test to examine the validity of PPP hypothesis by two different price indces, i.e. Big Mac prices and CPI. Our panel observations include 14 countries from 1992 to 1999. The empirical evidence indicates Big Mac PPP and CPI PPP is supposed if we use nominal exchange rate as the explanatory variable. Nevertheless, the Big Mac PPP is valid but CPI PPP not valid if we use price level as the explanatory variable. Moveover, our concludtion does not influenced by productivity bias. Keywords: threshold vector autoregression, asymmetric cointegration, panel cointegration, stock markets, purchasing-power parity

本論文的研究主軸圍繞於自我迴歸模型的估計與推論上。文獻上自我迴歸模型的估計多直接採用最小平方法, 但此估計方式卻有兩個缺點:(一)當序列具單根時,最小平方估計式的漸近分配為非正規型態,因此檢定時需透過電腦模擬得到臨界值;(二)最小平方估計式雖具一致性,但卻有嚴重的有限樣本偏誤問題。有鑑於此,我們提出一種「二階差分轉換估計式」,並證明該估計式的偏誤遠低於前述最小平方估計式,且在序列為粧定與具單根的環境下具有相同的漸近常態分配。此外,二階差分轉換估計式相當適合應用於固定效果追蹤資料模型,而據以形成的追蹤資料單根檢定在序列較短的情況下仍有不錯的檢定力。 本論文共分四章,茲分別簡單說明如下: 第1章為緒論,回顧文獻上估計與推論自我回歸模型時的問題,並說明本論文的研究目標。估計自我迴歸模型的傳統方式是直接採取最小平方法,但在序列具單根的情況下由於訊息不隨時間消逝而快速累積,使估計式的收斂速度高於序列為恒定的情況。不過,這也導致最小平方估計式的漸近分配為非標準型態,並使得進行假設檢定前必須先透過電腦模擬來獲得臨界值。其次,最小平方估計式雖具一致性,但在有限樣本下卻是偏誤的。實證上, 樣本點不多是研究者時常面臨的窘境,並使得小樣本偏誤程度格外嚴重。本章中透過對前述問題形成因素的瞭解,說明解決與改善的方法,亦即我們提出的「二階差分轉換估計式」。 第2章主要目的在於推導二階差分轉換估計式之有限樣本偏誤。我們亦推導了多階差分自我迴歸模型下二階段最小平方估計式(two stage least squares, 2SLS)與 Phillips andHan (2008)採用的一階差分轉換估計式之偏誤,以同時進行比較。本章理論與模擬結果皆顯示,一階與二階差分轉換估許式與2SLS之 $T^{−1}$ 階偏誤程度皆低於以最小平方法估計原始準模型(level model)的偏誤,其中 T 為時間序列長度。另外,一階差分轉換估計式與二階差分轉換估計式在 $T^{−1}$ 階偏誤上,分別與一階和二階差分模型下2SLS相同,但兩估計式的相對偏誤程度則因自我相關係數的大小而互有優劣。同時,我們發現估計高於二階的差分模型對小樣本偏誤並無法有更進一步的改善。最後,即使在樣本點不多的情況下,本章所推導的偏誤理論對於實際偏誤仍有良好的近似能力。 第3章主要目的在於發展二階差分轉換估計式之漸近理論。與 Phillips and Han (2008) 採用之一階差分轉換估計式相似的是,該估計式在序列為恒定與具單根的情況下收斂速度相同,並有漸近常態分配的優點。值得注意的是, 二階差分轉換估計式的漸近分配為 N(0,2),不受任何未知參數的影響。另外,當序列呈現正自我相關時,二階差分轉換估計式相較於一階差分轉換估計式具有較小的漸近變異數,進而使得據以形成的檢定統計量有較佳的對立假設偵測能力。最後, 誠如 Phillips and Han (2008) 所述,由於差分過程消除了模型中的截距項,使得此類估計方法在固定效果的動態追蹤資料模型(dynamic panel data model with fixed effect) 具相當的發展與應用價值。 本論文第4 章進一步將二階差分轉換估計式推展至固定效果的動態追蹤資料模型。文獻上估計此種模型通常利用差分來消除固定效果後,再以一般動差法 (generalized method of moments, GMM) 進行估計。然而,這樣的估計方式在序列為近單根或具單根時卻面臨了弱工具變數(weak instrument)的問題,並導致嚴重的估計偏誤。相反的,差分轉換估計式所利用的動差條件在近單根與單根的情況下仍然穩固,因此在小樣本下的估計偏誤相當輕微(甚至無偏誤)。另外,我們證明了不論序列長度(T )或橫斷面規模(n)趨近無窮大,差分轉換估計式皆有漸近常態分配的性質。與單一序列時相同的是,我們提出的二階差分轉換估計式在序列具正自我相關性時的漸近變異數較一階差分轉換估計式小;受惠於此,利用二階差分轉換估計式所建構的檢定具有較佳的檢力。值得注意的是,由於二階差分轉換估計式在單根的情況下仍有漸近常態分配的性質,我們得以直接利用該漸近理論建構追蹤資料單根檢定。電腦模擬結果發現,在小 T 大 n 的情況下,其檢力優於文獻上常用的 IPS 檢定(Im et al., 1997, 2003)。 / This thesis deals with estimation and inference in autoregressive models. Conventionally, the autoregressive models estimated by the least squares (LS) procedure may be subject to two shortcomings. First, the asymptotic distribution of the LS estimates for autoregressive coefficient is discontinuous at unity. Test statistics based on the LS estimates thus follow nonstandard distributions, and the critical values obtained need to rely on Monte Carlo techniques. Secondly, as is well known, the LS estimates of autoregressive models are biased in finite samples. This bias could be substantial and leads to serious size distortion for the test statistics built on the estimates and forecast errors. In this thesis,we consider a simple newmethod ofmoments estimator, termed the “transformed second-difference” (hereafter TSD) estimator, that is without the aforementioned problems, and has many useful applications. Notably, when applied to dynamic panel models, the associated panel unit root tests shares a great power advantage over the existing ones, for the cases with very short time span. The thesis consists of 4 chapters, which are briefly described as follows. 1. Introduction: Overview and Purpose This chapter first reviews the literature and states the purpose of this dissertation. We discuss the sources of problems in estimating autoregressive models with the conventional method. The motivation to estimate the autoregressive series with multiple-difference models, instead of the conventional level model, is provided. We then propose a new estimator, the TSD estimator, which can avoid (fully or partly) the drawbacks of the LS method, and highlight its finite-sample and asymptotic properties. 2. The Bias of 2SLSs and transformed difference estimators in Multiple-Difference AR(1) Models In this chapter, we derive approximate bias for the TSD estimator. For comparisons, the corresponding bias of the two stage least squares estimators (2SLS) in multiple-difference AR(1) models and the transformed first-difference (TFD) estimator proposed by Chowdhurry (1987) are also given as by-products. We find that: (i) All the estimators considered are much less biased than the LS ones with the level regression; (ii)The difference method can be exploited to reduce the bias only up to the order of difference 2; and (iii) The bias of the TFD and TSD estimators share the same order at $O(T^{-1})$ as that of 2SLSs. However, to the extent of bias reductions, neither the 2 considered transformed difference estimators shows a uniform dominance over the entire parameter space. Our simulation evidence lends credible supports to our bias approximation theory. 3. Gaussian Inference in AR(1) Time Series with or without a Unit Root The goal of the chapter is to develop an asymptotic theory of the TSD estimator. Similar to that of the TFD estimator shown by Phillips and Han (2008), the TSDestimator is found to have Gaussian asymptotics for all values of ρ ∈ (−1, 1] with $\sqrt{T}$ rate of convergence, where ρ is the autoregressive coefficient of interest and T is the time span. Specifically, the limit distribution of the TSD estimator is N(0,2) for all possible values of ρ. In addition, the asymptotic variance of the TSD estimator is smaller than that of the TFD estimator for the cases with ρ > 0, and the corresponding t -test thus exhibits superior power to the TFD-based one. 4. Estimation and Inference with Moment Methods for Dynamic Panels with Fixed Effects This chapter demonstrates the usefulness of the TSD estimator when applying to to dynamic panel datamodels. We find again that the TSD estimator displays a standard Gaussian limit, with a convergence rate of $\sqrt{nT}$ for all values of ρ, including unity, irrespective of how n or T approaches infinity. Particularly, the TSD estimator makes use of moment conditions that are strong for all values of ρ, and therefore can completely avoid the weak instrument problem for ρ in the vicinity of unity, and has virtually no finite sample bias. As in the time series case, the asymptotic variance of the TSD estimator is smaller than that of the TFD estimator of Han and Phillips (2009) when ρ > 0 and T > 3, and the corresponding t -ratio test is thus more capable of unveiling the true data generating process. Furthermore, the asymptotic theory can be applied directly to panel unit root test. Our simulation results reveal that the TSD-based unit root test is more powerful than the widely used IPS test (Im et al, 1997, 2003) when n is large and T is small.

當資料屬於類別型的長期追蹤資料（Longitudinal categorical data）時，除了可以透過廣義估計方程式（General estimate equation, GEE）來求解模型參數估計值外，潛在移轉分析（Latent transition analysis, LTA）法也是一種可行的資料分析方法。若資料的期數不多，也可以選擇將資料適度分群後使用羅吉斯迴歸分析（Logistic regression）法。當探討的反應變數為二元（Binary）型態，且觀察對象於每一期提供多個測量變數值的情況之下，廣義估計方程式與羅吉斯迴歸分析法的使用，文獻上常見先將所有的測量變數值加總後，以「中位數」作為分類的切割點。不同於以上兩種方法，潛在移轉分析法則是直接使用原始資料來取得觀察對象的潛在狀態相關訊息，因此與前二者的作法不同，可能導致後續的各項分析結果有所差異存在。 為了能夠了解造成中位數分類法與移轉分析法差異的可能因素，我們架構在潛在移轉分析法的模型下，以不同的參數設定來進行電腦模擬，比較各參數條件下的兩分類方法差異。結果發現各潛在狀態下的測量變數反應機率形式、第一期潛在狀態的組成比例等皆會對兩分類方法是否具有相同分類有所影響。另外，透過分析「青少年媒體使用與健康生活調查」的實際資料得知，潛在移轉分析會將大部分的觀察對象歸屬於「網路成癮」，而中位數分類法則是將大部分的觀察對象歸屬於「無網路成癮」。此外，可以注意到「沮喪」、「線上情色每星期平均使用天數」、及「父母相處狀況」這幾個控制變數與各分組結果的關聯性，於上述三種資料分析方法中有所不同。 / Several methods can be used to analyze longitudinal categorical data, as among them Latent Transition Analysis (LTA), and Generalized Linear Models estimated by Generalized Estimating Equations (GEE) probably the most popular. In addition, if the number of periods is two, then with certain grouping of data, the Logistic Regression can also be applied to perform the analyses. When there are more than one manifest response variable for each study subject, LTA is able to classify the subjects in terms of the original manifest response variables and proceeds with necessary analyses. On the other hand, GEE method and Logistic Regression lack the flexibility, and require certain transformation to transform the manifest response variables into a categorical response variable first. One common way to form a binary response is to sum all manifest variables, and then taking median as a cut-point. In this study, we explore the differences of the classification resulted from LTA directly and using median as a cut-point through simulations. An empirical study is also provided to illustrate the classification differences, and the differences on the subsequent analyses using LTA, GEE method, and Logistic Regression approach.

個人學習動機向來被認為是影響學習成就的重要因素，但是家庭也對學生的學習提供特定的脈絡條件。因此，在探討學生學習成就與時間發展效應之時，若能同時納入個人與家庭因素，並探討其間的交互作用，將能對於兩者的影響力進行客觀的檢驗。本研究的目的主要在探討臺灣青少年學習成就的成長軌跡變化型態，以及家庭文化資本與個人學習動機對於學習成就成長軌跡的影響機制。其中學生的文化資本是來自家庭父母所傳遞下來的先天條件，係屬於一種結構因素；而學生的學習動機則是來自個人後天的努力與學習的正向動力，係屬於一種個人因素。具體而言，本研究目的分為三個主要的研究議題，首先，根據Bourdieu（1977）的文化資本概念，以及Bandura（1977, 1986, 1997）與McInerney和McInerney（1994）的學習動機觀點，探討這兩個重要解釋變數對於各波學生學習成就的影響情形；再者，根據Sternberg（1985, 1986, 1988）的智力三元論觀點探討學生學習成就的成長變化情形；最後，探討文化資本與學習動機對於學生學習成就成長軌跡的交互作用效果。 研究資料取自臺灣教育長期追蹤資料庫（Taiwan Educational Panel Survey）的四波追蹤樣本，以潛在成長曲線模式進行次級資料分析。研究結果發現：1.臺灣青少年的學習成就成長軌跡呈現非線性的遞增漸緩的成長曲線；學生在學習成就的起始能力與成長速率存在個別差異，且學生的起始能力與成長速率具有正向的關係，顯示隨著時間的遞移，起始能力高與低的學生，其能力的差距會逐漸擴大。2.文化資本與學習動機對於學習成就成長軌跡的影響未具交互作用，顯示個人的學習動機並不能減緩或反轉文化資本對於學生學習成就的影響。3.文化資本與學習動機對於學生學習成就的主要效果，在學習的早期階段，存在正向的影響效果，但影響力會隨著時間而逐漸降低。4.文化資本係影響學生學習成就成長軌跡的重要因素，文化資本的豐富與不足會加劇學生學習成就的差距，因而造成強者恆強、弱者恆弱的「馬太效應」現象。最後，依據上述的研究發現，分別提出教育實務上、未來研究與對資料庫研究的建議，以供相關教育人員與研究者參考。 / Individual motivation has always been recognized as the key factor for influencing the students’ learning achievement. However, the family of the students is also considered as an important contextual determinant. As a result, in order to analyze the students’ learning achievement against the temporal effect of time, it is imperative that the factor of family background should be included for understanding the interaction of the factors on the learning achievement. The primary goal of this study is to inquiry the patterns the development and change of learning achievement growth trajectory of the Taiwan adolescent. Particularly, this study explores the effects of family cultural capital and learning motivation on adolescent learning achievement growth trajectory. By definition, family cultural capital which is a structural factor refers to the inherent characteristics that are passed down from the students’ parents. On the other hand, the students’ learning motivation which is a personal factor refers to the extrinsic factor that arises from later days’ hard work and positive learning efforts. In terms of research objectives, this study tries to integrate the Bourdieu’s (1977) perspective of cultural capital, and Bandura’s (1977, 1986, 1997) as well as McInerney and McInerney’s (1994) concept of learning motivation into a framework for examining the effects of the learning growth of different waves of students. Secondly, by applying the Sternberg’s (1985, 1986, 1988) triarchic theory of intelligence to examine the changes of the students’ learning growth trajectory. Finally, to analyze the interaction between the students’ cultural capital and learning motivation on their learning achievement trajectory. The data using in this study was selected from the longitudinal database Taiwan Educational Panel Survey (TEPS). A total of four waves of students’ data were downloaded and analyzed as secondary data using the latent growth curve modeling (LGCM). Major results of the study were followed: First, the learning achievement trajectory of Taiwan adolescents’ seemed to be gradually growing in a non-linear incremental curve; it also shown that at the beginning the students’ learning achievement displayed significant individual differences. Likewise results also revealed a positive relationship between the students’ initial status and growth rate of learning achievement. That is, as the passing of time, the initial status of learning achievement affected the growth of disparity among the students. Second, there were no significant interaction effect between the students’ cultural capital and learning motivation on the learning achievement growth trajectory. This means that the students’ learning motivation cannot moderate the effects of cultural capital towards the learning achievement. Third, results revealed that the main effects of the students’ cultural capital and learning motivation on the learning achievement were occurred on the early stages of learning. A significant positive effect was found in these stages, however, the positive effect gradually decreased along with the passing of time. Fourth, it was found that the minimal effect of students’ cultural capital on their learning achievement growth trajectory was determined by the abundance or deficiency of the former. The amount of cultural capital also determined the distance of the students’ gap. In other words, a phenomenon of the Mathew effect was supported; wherein the students who are in a strong stand will get stronger later on, while the weak shall get weaker. Besides the findings mentioned above, recommendations for further study and limitations of the present study were given at the end.

本研究採用「台灣教育長期追蹤資料庫」（TEPS）調查結果，對台灣地區高中職學生個人特徵、家庭背景以及學生生活進行次級資料分析，探討各種因素與學業表現之關聯性。 　　本研究選取資料庫中之9,750樣本數，以資料庫綜合分析能力測驗成績作為應變數，選取性別及手足數目等12個自變數，以Logit Model為實證模型分析，再以Ordered Probit Model進行實證結果穩健性檢驗（Robustness Check），發現兩者結果呈現一致性，本研究發現： 一、男性成績較女性成績為佳，曾經或現在就讀資優班者成績較為優異。 二、家庭手足數目對學生學業成績表現有負向影響，雙親教育程度、家庭收入愈高及家庭文化資本愈豐富對子女學業表現有正向顯著影響；家庭親子關係、父母閱讀頻率對於子女學業表現則無顯著影響。 三、補習、參加社團活動以及校隊培訓對學業成績有正向影響；打工及結交行為偏差朋友則對學業成績有負向影響。 　　本研究提出教育政策方向建議如下： 一、建議文創產業主管機關以差別取價之價格誘因方式提高親子參與藝文活動之意願，並持續鼓勵文創產業提供學校學生及家長參與藝文展演活動機會。 二、教育主管機關應持續執行對（中）低收入戶子女學雜費補助之政策，並建立對高中職學校社團活動之管理制度，另應加強學生品性教育管理。 / This study analyzes the association between personal characteristics, family background, the life of students and academic achievement of students in senior high school. The data have adapted Taiwan Education Panel Survey (TEPS). The research has used 9,750 samples in the database. The dependent variable is the test scores of students while the independent variables are gender, the number of sibling, etc. This study has used Logit Model for empirical analysis and Ordered Probit Model for robustness check of the results. The research findings indicate that both models have similar conclusions, which are shown as follows. Firstly, the academic achievement of males is better than that of females. Moreover, students who are in the gifted and talented class have a better performance than those who are not in. Secondly, the number of sibling has a negative effect on academic achievement; whereas the education background of the parents, income and cultural capital of the family are as the opposite. The frequency of reading and the relationship between parents and children have no significant influence on academic achievement. Thirdly, the student who goes to cram school or participates in extracurricular activities has a positive influence on his/her academic achievement. However, the student with the part-time job or bad-behavior friends has a negative influence on his/her academic achievement. Therefore, the authorities should encourage parents and their children to participate in cultural activities through offering economic incentives and the tuition subsidies for low-income households continuously.

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.

本研究使用「臺灣教育長期追蹤資料庫」第二波（2003）國三與第三波（2005）高二的CP追蹤數據，採用反事實模型框架下的傾向分數配對法估計單一性別環境對臺灣高中女生選組行爲（自然組／社會組）的因果效應。使用學生進入高中前的國三資料，本研究在學生因素，家庭因素和學校、班級因素三個方面充分平衡處置組（進入女校）和控制組（進入男女合校）的樣本，使配對樣本之間除了進入女校或進入男女合校之外，在以上三個方面儘可能相等，嘗試克服觀察性數據因選擇性偏誤問題對因果效應的估計帶來的阻礙。結果顯示，在進行傾向分數配對後，處置組和控制組之間達到了很好的平衡，進入女校的女生與進入男女合班的男女合校中的女生相比，女校顯著地促進了高中女生選自然組的機率，然而該效應在數學成績水平不同的女生中存在異質性，女校顯著地促進了數學成績處於高水平的女生的選擇自然組的行爲。作爲教育分流的重要組成部分，臺灣高中生選組行爲的性別隔離長期存在，選組行爲與學生未來大學科系選擇和職業選擇關係密切，自然組中低比例的女生組成顯現出隱藏的教育機會不平等。該現象長期存在的背後因素，除了學生個人因素和學生家庭背景因素帶來的影響，本研究關注學校這一角色對高中女生選組行爲的影響。 / Based on the Taiwan Educational Panel Survey’s core panel data from wave 2 (junior high school/9th grade) and wave 3 (high school/11th grade), researcher applies the propensity score analysis in counterfactual framework to study the causal effect of single-sex schooling on high school girls’ curriculum tracking (science track or humanity track) selection. Observational data always be the obstacles of making the causal analysis because it's lacking random assignment and being under threat of selection bias and unobserved variables. Using the pretreatment variables from students in 9th grade, students in the treatment group were matched with those in control groups by the individual factors, family factors and school, classroom environment factors. After matching, students come from different groups are supposed to be relatively equivalent on all the matching variables except for attending single-sex school or not. The researcher can make suitable comparison and prediction between well-matched samples. The result shows that more girls in single-sex high schools tend to choose science track. Effect of single-sex schooling is not the same among girls with different level of math scores. It benefits girls with top math performance significantly. As an important part of the educational tracking system, alternative curriculum tracking selection in Taiwan high school is worth noteworthy. The long lasting gender segregation is closely associated with students college major as well as occupation selection and it reveals the hidden educational inequality between gender. Other than focusing on the individual and family background effect on high school girls’ curriculum tracking selection, this study highlights the school effect on it.