經過30年的經濟改革，中國已成為國際直接投資的熱門地區。聯合國貿易發展委員會（UNCTAD）的報告中也指出，中國在2007年僅次於美國，成為全球吸引外資金額第二高的國家。然而，隨著中國總體國力大增，近幾年來，中國對外直接投資的腳步也加緊了起來。外資的流入不但促進了中國的經濟成長，也給中國企業學習如何對外直接投資，提供了絕佳的機會。 相較於中國吸引外資方面（Inward FDI）的研究，中國對外直接投資（Outward FDI）的議題較少引起研究者注意。然而，中國對外直接投資對於全球經濟有其重要性，研究影響中國對外直接投資因素更具有理論與實質意義，因為中國既投資於未開發國家和開發中國家，也同時在已開發國家中投資，這是一般後進國家少有的特質。因此，本研究將利用2003-2007年中國各省市地區對外直接投資的追蹤資料（panel data），搭配固定效果模型（fixed effect model）的估計，希望透過本研究分析影響中國對外直接投資的決定因素。 實證結果發現，影響中國對外直接投資的決定因素中，顯著的變數有各省市國內生產毛額、各省市每人國內生產毛額、各省市職工平均工資、各省市國有企業產值佔工業總產值比，以及工業總產值佔國內生產毛額比。而其餘的變數如各省市貿易開放程度、匯率與借款利率皆不顯著，反映了其皆非中國對外直接投資時所考量的決定因素。不過，整體來說中國對外直接投資有逐年成長的趨勢。

長期性資料(longitudinal data)，是指對同一個觀察個體(subject)或實驗單位(experiment unit)，在不同時間點上重複觀察或測量一個或多個變數。雖然觀察個體之間互相獨立，但就同一個個體而言，不同時間的觀察或測量常常是有相關性的。且觀察的個體之間可能由於一些無法測量的環境因素造成個體之間有差異，因此在傳統橫斷面分析中，假設其有相同迴歸係數的邊際模型可能不合理。隨機效果模型可以解決長期資料分析的相關，並假設每個個體的迴歸係數不同；此模型不但可以說明橫斷面資料的cohort效果，也可直接解釋長期資料的age效果；更可以區分個體之間與個體之內的變異。 本研究以1995年至2000年台灣11個產業中的100家公司之每股盈餘與各財務比率，作為實證分析的資料；分別配適每股盈餘與時間、產業別、時間產業別交互作用及財務比率及排除每股盈餘有異常值後之邊際效果模型(一般迴歸分析)及隨機效果模型，並比較其參數估計之異同。實證結果顯示，一般迴歸分析與假設誤差不相關且等變異下的隨機效果模型參數估計相似，但後者能區分變異為個體之間(between-subjects)與個體之內(within-subject)的變異。而假設誤差不相關且不等變異與假設誤差服從AR(1)且不等變異下的隨機效果模型估計相近。實證結果並顯示，在排除異常值後的模型參數估計，一般迴歸分析不論是估計值及顯著性大多沒有很大差別；而隨機效果模型的估計在排除異常值前後較有差別。特別是現金流量比率(CFR)原本為不顯著變數，在排除異常值後的模型配適全部變顯著性變數。 / The defining characteristic of a longitudinal study is that individuals are measured repeatedly through time. Although it is independent between subjects, the set of observations on one subject tends to be inter-correlated. Because there is some natural heterogeneity due to unmeasured factors between subjects, it is not corrected to assume they have the same regression coefficients. A random effect model is a reasonable description about the different regression coefficients, and it can resolve the inter-correlation of the observations on one subject. The major advantages of the random effect model are its capacity to separate what in the context of population studies are called cohort and age effects, and it can distinguish the variations between subjects and within subjects. This study describes the marginal model and random effect model, and shows their difference by real data analysis. We apply these models to the earnings per share (EPS) and other financial ratios of one hundred companies in Taiwan, which are distributed in eleven industries. The results show that the parameter estimates of the marginal model and random effect model are similar when error structure is independent and of equal variance. Furthermore, the latter can distinguish the variations between subjects and within subjects. However, the residual analysis reveals that the error structure may not be constant. Therefore, we consider heteroscedasticity error in random effect model. We also assume that error follows an autoregressive process (e.g. AR(1) model), which leads to the optimum among our results in terms of residual analysis. There are some observations that appear to be outlying from the majority of data. The results show little difference in the marginal models no matter whether those outliers are included. However, we obtain different results in the random effect models. Especially, the variable of “cash flow ratio” becomes significant once those potential outliers have been excluded, while it is not significant when all cases are fitted in the model.

自1978年鄧小平南巡，中國大陸在經濟上採取改革開放政策以後，開始一連串的經濟制度改革，由中央集權的計劃經濟逐漸走向市場經濟。使得中國大陸有充裕資金、技術長足進步、經濟快速成長、人民生活水準提高、生產總值和人均所得皆大幅提升。但就總體整個大陸因區域經濟結構與政策等因素影響，東部沿海地區發展快速，西部地區發展停滯落後，內部各區經濟發展仍存在極大差異。因此，自江澤民在1999年6月9日「中央扶貧開發會議」上首次提出了「西部大開發」戰略概念，中國大陸就陸續提出多項區域發展政策，期能撫平區域發展不均衡的差距。而西部大開發政策實施迄今將屆10年，經濟建設與發展成果豐碩，並將進入第2階段，西部大開發政策的實施方針是否真正提升西部地區經濟發展？且解決東西部區域經濟差距問題？此外，在2008年國際金融危機開始蔓延，外部市場需求萎縮情況下，西部地區生產總值同比增幅超越東部地區，但隨著中國大陸整體經濟成長，東、西部地區、城鄉差距仍然懸殊，西部地區要脫離落後狀態應該發展的方向究竟為何？ 因此本文的研究目的在於以1997年至2009年西部地區各項有關經濟成長追蹤資料，搭配固定效果模型的估計，分析影響大陸西部地區經濟成長的趨勢及決定因素為何，並以估計之結果檢視「西部大開發」政策是否為西部地區發展所需，並確實提升西部地區經濟成長。 根據實證結果顯示，影響西部地區經濟成長的決定性因素有七：就業、工資率、固定資產投資、利用外資投資總額、能源消費量、西部大開發的優惠政策及金融危機。其他的變數如貿易開放程度及時間趨勢等，皆未有顯著影響。 / Since Xiaoping Deng’s Southern tour in 1978, China has adopted economic reforms and open policy, there are series of economic reforms, changed from the central planning economy to the market economy gradually, which resulted in capital abundance, advance in technology, rapid growth of economy, living standard enhanced, both GDP and per capita income has increased significantly in mainland China. But overall due to the regional economic structure, the policy and some other factors, the rapid development of the Eastern coast and the lagging behind of the West, has created significant differenence in the economic development of each region. Therefore, since Zemin Jiang launched the "The West Development" strategy in the "Central Poverty Alleviation and Development Conference" on June 9, 1999, Mainland Chain has a number of regional development policies, to solve the unbalanced gap of regional development . The implementation of Western Dvelopment Policy has been over 10 years， there are fruitful result on economic construction and development, it is going to enter Phase 2. Has the approaches of Western development policy really enhanced the economic development in the West ? Has it solved the economic gap between the East and the West ? In addition, under the condition of the spreading of international economic crisis in 2008 and the shrinkage of external demand, the West's GDP growth is lower than the East. But following the economic growth of China overall, the gap between The East and the West, the City and the Country is still huge. What will be the development direction of the West to escape from the lagging ? Therefore, the purpose of this research will base on the relevant tracking data of 1997-2009 economic growth in the the West and the estimate of fixed-effect model, to analyze what are the the economic growth trends and decisive factors of the West ? And use the estimate results to check whether "The West development policy” is right for the development ？ Has it actually enhanced the economic growth of the West ? According to experience, there are seven decisive factors to influence the economic growth of the West: Employment, Wage rate, Fix Asset Investment, Amount of Foreign Investment, Energy Consumption, The Beneficial Policies of West Development，and Economic Crisis. Other variables such as trade openness and time trends, also has significant impact.

中國大陸自1978年確定改革開放政策，天津自改革開放初期的經濟發展面對資金和技術不足的問題。1990年末期，因為外商企業在天津長期投資，對天津產業技術提升及企業管理發揮積極作用，使天津市擠身中國大陸最吸引外來投資之地區之一。1992年鄧小平南巡再次確認中國大陸積極對外開放政策後，天津之外來投資呈現倍數之高度成長。2010年度，天津之外來投資金額更是突破百億美元大關。本文之研究目的冀討論天津在1990年第至2010年，影響各國家地區對天津投資之決定因素。本文採用天津此1990年至2010年累計最高投資金額之前九個國家地區之資料，利用固定效果模型估計，結果顯示決定因素有相對實質匯率、相對每人國內生產毛額、工資率及時間趨勢，另外各國家地區對於天津之地理距離透過分析亦可知其自發性投資呈現負相關。為降低實證模型發生錯誤，將各種統計量之檢定方法加以檢定，皆獲得通過。 / China has adopted and confirmed the so-called Open Door Policy since 1978. Tianjin faced the shortage of capital and technology in the early period of the implement of the Policy. However, in the end of 1990, Tianjin became one of the most attracting foreign investment cities in China because the foreign direct investment had played an important role and positively influenced industries upgrade and business management in the city. The amount of foreign direct investment in Tianjin has a high speed growth after Deng Xiaoping’s southern trip in 1992 to confirm the determination of China’s open door policy again. In 2010, the amount of foreign direct investment in Tianjin was impressively over ten billion US dollars. The purpose of this study is to investigate the determinants of foreign direct investment from different countries and districts in Tianjin from 1990 to 2010. The study adopted fixed-effect model to investigate the determinants of foreign direct investment in Tianjin with the top nine countries and districts in the period of 1990 to 2010. The results revealed relative currency rate, relative GDP per capita, relative wage rate and time trend are the most important factor in attracting foreign direct investment in Tianjin in the period. Another result showed the geographical distance has a negative relationship to foreign direct investment in Tianjin by fixed effect analysis. In order to reduce the occurrence of mistakes, the model and result results also have been tested through related tests methods.

Closed-end funds’ (CEF) discount and discount fluctuations have been puzzling researchers for decades. Up to date, there are no multidimensional or cross-sectional variables that have been proved to influence CEFs simultaneously. Fact is that, earlier research and theories on the subject are contradictious and several suggestions on the origin of the CEF’s discount and its fluctuations have been proposed. To mention a few, investor sentiments, taxation issues, dividend policies, agency costs and agency problems are considered to influence these discounts. The purpose of this report is to examine the relationship between micro- and macroeconomic variables fluctuations, and how these can explain the discount fluctuation of the Swedish CEFs. This report focuses upon the CEFs traded at NASDAQ OMX Stockholm, which have been selected through a comprehensive multistage selection process. 10 CEFs were selected. Monthly data for calculating micro- and macroeconomic variables was collected for the period March 2003 – February 2013, which resulted in approximately 1 200 observations. OLS regression analysis, Fixed- and Random Effect Models and Hausman tests were conducted. The findings conclude that some of this report’s chosen micro- and macro variables influence on the Swedish CEFs’ discount fluctuation, although these findings are conditioned. The CEFs’ individual characteristics or traits result in a significant impact on the fluctuation of CEFs’ discount. Hence, only by controlling these characteristics, multidimensional or cross-sectional micro- and macroeconomic variables can be proved to affect the CEFs’ discount fluctuation.

中國在經濟發展的過程中，由於面臨著資金不足和技術落後的問題，以致於在1978年確立改革開放政策後，企圖透過外商直接投資來加速工業化及促進產業升級。然而一直到1992年鄧小平南巡，宣布將堅持中國的改革開放政策後，外商直接投資才開始大量流入中國。本文的研究目的即是鎖定外商直接投資開始大量進入中國後，影響世界各國對中國直接投資的因素。 本文利用24個國家（地區）在1993年至2003年期間的資料，採固定效果模型研究外商對中國直接投資的原因為何。結果顯示在1993到1996年間，顯著的決定因素為相對國內生產毛額、相對每人國內生產毛額，以及相對工資率。而在1997到2003年間，顯著的變項轉變為相對國內生產毛額、相對借貸成本、以及相對國家風險。此外，兩階段的外商直接投資都有增加的趨勢，但1997到2003年間增加的速度有趨緩的現象。另由固定效果的分析中得知，地理距離與對中國的自發性直接投資具有負相關的關係，此可由引力模型和地理距離影響文化的擴散和交流解釋之。最後，為了降低實證模型發生錯誤的機會，並使研究過程更為嚴謹，於是對本文模型和估計結果使用更多的方法加以檢定。 / 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 in China after foreign countries started to invest tremendous amount toward China. This study adopts fixed-effect model to investigate the determinants of FDI in China with 24 countries’ (regions’) data during the period of 1993-2003. The result shows relative GDP, relative GDP per capita, and relative wage are the most important factor in attracting FDI in China during 1993-1996. However, during 1997- 2003, the important factors change into relative GDP, relative borrowing cost, and relative country risk. In addition, the FDI at two periods both have a increasing trend, but the increasing speed during 1997-2003 isn’t increase so quickly as 1993-1996. Furthermore, from the analysis of the fixed effect knows the geographical distance has a negative relationship to FDI in China, and it can be explained by gravity equation and geographical distance influences the diffusion and exchange of culture. 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.

台灣地區在2002年時總生育率已降至1.33，而淨繁殖率為0.63，此種低於替代水準的生育率如果繼續下去，台灣地區的人口成長將於20-30年後，達成人口零成長並轉為負成長；生育率持續降低將造成人口老化，對國家經濟造成負面影響。 而影響生育率的因素很多，鑑於現代家庭在子女養育費用上的支出日益增加，尤以教育費用佔養育成本之比例最大，中低收入的家庭籌措教育費用的負擔，可能比生活開支更為沉重；尤其近年來政府廣開大學之門，但高等教育的經費並沒有比例的提升，因此不論公立或私立學校，從政府所得的補助相形減少；而大學學歷已成為基本的學位，可以預期未來幾乎每個人都會念大學，因此當大學學雜費調漲，將使父母養育子女成本增加，所以要思考是否因為養育成本的提高，而降低了生育子女的意願，使得台灣地區生育率年年下降。 本文的研究目的，主要在探討佔教育費用相當大比重的大學學雜費調漲，對台灣地區生育率的影響，並就其他影響台灣地區生育率的主要因素加以分析。以下為本論文之主要內容：第一章緒論，介紹本文研究背景與動機、研究目的與研究架構及研究限制。第二章文獻回顧，探討影響生育率因素的相關文獻，並就大學學雜費之文獻加以分別整理並予以說明。第三章，分析台灣地區生育率與大學學雜費調漲之變化；為了研究大學學雜費調漲對台灣地區生育率之影響，必須對近年來台灣地區生育率之變化及大學學雜費制度之變化作進一步之了解。第四章是研究方法，在本章中，將介紹本論文的資料來源、研究方法與實證模型及變數說明，以檢視大學學雜費調漲對台灣地區生育率的影響。第五章，就實證結果加以分析說明，第六章是本研究之結論與政策建議。 本文以1991年至2002年台灣地區23個縣市之追蹤資料為研究對象，經由固定效果模型的估計結果發現，大學學雜費對台灣地區生育率的影響有顯著的負相關；而其他影響台灣地區生育率的主要因素，如台灣地區各縣市家庭所得、失業率（尤以男性失業率為顯著）、婦女教育程度等均呈現顯著的負向影響，台灣地區嬰兒死亡率亦呈現負向影響但並不顯著，而婦女25 – 39歲年齡組群佔該縣市15歲以上婦女總人數比例，對台灣地區生育率的影響，呈現顯著的正向關係。 依本研究結果顯示，大學學學雜費是影響台灣地區生育率相當重要的因素，且教育學費與提升生育率皆屬於政府的政策，政府應該高度正視此問題並有所作為。至於控制其他因素後之地區特質效果，`顯示台灣地區之生育率，以東部地區為最高，南部地區最低；各縣市之特質效果則以新竹縣為最高、高雄市最低，可能與原住民比例、人口外移、城鄉差距或其他人文因素有關。因此，如何縮小城鄉差距,平衡人口分佈,使經濟均衡發展,也是值得政府思考與正視的問題。 關鍵詞：大學學雜費、生育率、固定效果模型、台灣地區

臺灣隨著戰後嬰兒潮步入高齡，加上生育率為世界最低國家之一，刻正面臨嚴重的少子化及高齡化問題，除提升生育率、減少本國勞動力外流、並爭取海外留學生、僑民回國就業外，補充外籍勞動力，以減緩工作世代壓力，實為我國的當務之急。 為了解外國勞動力在臺工作縣市分布的影響因素，不同於以往的研究，本文從縣市別角度出發，採用2006年至2015年臺灣21個縣市的追蹤調查資料，以外籍專業人員、外籍勞工、全部外籍勞動力為被解釋變數建立3個模型，並分別以最小平方法、固定效果模型以及隨機效果模型進行迴歸分析，結果顯示，影響外國專業人才來臺工作縣市分布之重要因素為產業因素與教育資源因素，而失業率、產業因素以及教育資源因素則為外籍勞工與全部外籍勞動力的重要影響因素。 / Taiwan, with the post-war baby boom turning into the elderly boom by time, coupled with being one of the lowest birth rate in the world, is currently facing serious population aging problems. In order to deal with this situation, Taiwan government needs to encourage fertility, reduce domestic workforce outflows, and attract overseas students and nationals to return home. In addition, it is also urgent to recruit foreign workforce to ease the pressure of domestic working generation. Different from the previous studies, this study attempted to understand the influencing factors of foreign workforce’s distribution in Taiwan by adopting a new perspective of observing each city and county respectively. This study used the data of 21 cities and counties in Taiwan from year 2006 to 2015, choosing the data of foreign workforce, foreign professionals and foreign labors as the dependent variables. Afterwards, the OLS model, the fixed effect model and the random effect model were conducted to estimate those variables separately. The results indicated that the industrial factors and educational resources factors were the main important factors influencing the distribution of foreign professionals in Taiwan, while the unemployment rate, industrial factors and educational resources factors were the important factors influencing the distribution of foreign labors and all the foreign workforce.

As in any other sector, the Covid-19 outbreak has caused many changes in education, and there is a reasonable expectation for this intervention to have a significant impact on the students and their performance. The purpose of this study was to analyse the effects of the digital semester, imposed on students due to Covid-19 outbreak, on student academic success. Using a quasi-experimental methodological approach called dif-in-dif analysis, three empirical models were constructed to analyse if there is an overall effect when comparing our control and treatment groups, as well as if there were any group-specific differences when it comes to the performance across genders and educational levels. The study found a significant negative effect of the digital semester on student academic success, suggesting that students performed significantly worse after the Covid-19 outbreak caused the University to step away from face-to-face teaching and adapt to remote studies. Furthermore, it was found that gender-specific differences do not affect the academic performance of our treatment group; however, female students performed worse when the digital semester was implemented compared to the control group who had both the classes and exams face-to-face. Lastly, Master students were found to perform significantly worse compared to Bachelor students’ when the Covid-19 outbreak caused the education to transfer to the digital environment.

Diplomová práce se zabývá plánováním a analýzou experimentu. Je zde zkoumán vliv počtu centrálních bodů v plánu experimentu na nalezení významných faktorů procesu. Pro určení tohoto vlivu je použita metoda Monte Carlo, pomocí které hledáme míru nalezení významných faktorů procesu. Simulace experimentu je vytvořena v programu MATLAB, kde se především využívá Statistics toolbox pro generování náhodných čísel. V závěru je zhodnoceno a graficky ukázáno, jak je určení významnosti faktoru procesu závislé na počtu uvažovaných faktorů experimentu a na počtu měření v centrálním bodě.