過去文獻對於不動產擔保品估值的研究，通常以銀行最終核定之價格做實證分析，本研究從銀行內部不動產擔保品價格變動情形，來探討影響銀行辦理授信程序時內部各單位決定不動產擔保品價值之因素，就不動產擔保品估值為依變數，實證分析申請人與不動產擔保品各項條件，研究結果顯示分行內部承辦人員估值及總行授審處估值之各項變數中以申請額度、區位、建物面積、屋齡、車位之有無等五項變數對估值具顯著影響。總行鑑價科則在區位、建物面積、屋齡、車位之有無等四項變數呈現顯著，影響總行授審處估值與鑑價科估值差額之因素則以是否為年齡、六個月平均存款餘額及申請額度等變數呈現顯著。分析結果顯示，分行承接業務時，考量擔保品條件與申貸金額。鑑價科則可能因此受到分行內部承辦人員估值的錨點影響，產生干擾效果。而授審處調整擔保品估值金額時，考量還款能力時，可能更重視的是借款戶於本行的往來存款實績。 / Previous studies on the appraised values of real estate collaterals are mostly empirical analyses on the final value approved by the creditor bank. The study, directing its attention to the changes in the appraised value of real estate collateral within a bank, examined the factor affecting the value of real estate collateral appraised by the different units of a bank. With the appraised value set as the dependent variable, the study conducted an empirical analysis on the loan applicants and the various features of the pledged collaterals. According to the study results, loan amount, location of the pledged collateral, floor area, age of the building, and provision of parking space emerged to be variables reaching statistical significance in the appraisal at both a local branch and the head office. Location, floor area, age, and parking space remained the statistically significant variable for the head office. Age of the applicant, average deposit account balance for the past six months, and loan amount appeared to be the statistically significant variable influencing the discrepancy in the values appraised by the local branch and the head office. As indicated by the analysis results, the local branch tended to place greater emphasis on the features of the pledged collateral and the loan amount; the appraisal office at the local branch might therefore be interfered by the value assessed by the responsible appraiser due to the anchoring effect. On the other hand, in adjusting the value appraised by the local branch, the head office would pay considerable attention to the applicant’s overall performance as a bank client in addition to repayment capacity.

根據2001年台灣國際觀光旅舘資料，本研究首先利用資料包絡分析方法評估個別國際觀光旅舘之經營績效；然後，以複迴歸模型評估國際觀光旅舘經營績效差異之原因。由經營效率評估結果發現：(一)在不同投入、產出組合下，台灣國際觀光旅舘之整體技術效率平均值介於79.02 %與89.41 %之間，亦即台灣國際觀光旅舘在投入資源運用上仍存有改善的空間；同時在產出不變的情況下，平均可節省10.59 %-20.98 %之資源使用量；(二)規模效率平均值近乎於1，顯示：造成技術無效率之主要原因在於資源浪費。複迴歸模型實證結果顯示：(一)技術效率與獲利率具正向關係，意指技術效率愈高者，更能有效運用投入要素，以降低成本，獲得較高之利潤；(二)總營業收入與獲利率具負向關係，意謂市場競爭壓力，將促使國際觀光旅舘，改善其本身獲利能力，以存活於市場；(三)業務集中度與獲利率具負向關係，意即國際觀光旅舘將業務分散於客房部門及餐飲部門，以多樣化經營。因此，可提升國際觀光旅舘獲利能力；(四) 加入國際觀光旅舘連鎖集團，一方面可分享其國際商譽與管理風險，另一方面則為符合加入標準，而使得經營成本上升。因此，需視產出變數之選擇而定；(五)新加入國際觀光旅舘之獲利率，低於既有之國際觀光旅舘。因此，新加入國際觀光旅舘，需經過一段時間的調整，才能逐漸改善其獲利能力；(六)位於台北市之國際觀光旅舘，因係外國觀光旅客、商務必經之地，故需求較高，使得進入該市場之國際觀光旅舘，獲利能力較高。

會計的目的在於幫助會計資訊的使用者從事經濟性的決策，亦即解決其所面對的問題。尤其在今日，隨著社會的繁榮與商業活動的頻繁與複雜，企業與個人對會計資訊的需求與依賴也日漸加深；會計從業人員在提供資訊的同時，是否曾了解這些資訊的真正內涵？而使用者又應該如何的使用這些資訊呢？ 　　本研究係由探討國內外相關文獻為起點，並參酌國內環境現況及個人的見解，加以延伸；依循現有的理論，試圖使用財務報表資訊建立一個可以衡量企業真實價值(intrinsic value)的模型；除欲證實財務報表資訊有其功用外，也可進一步認識財務報表究竟包含有多少資訊價值，並或許可以協助投資人選擇適當的投資標的，進行投資。 　　經由實證研究結果，本研究獲致如下的結論： 　　1.吾人可利用公開的財務報表資訊建立一個模型，用以估算公司的真實價值(intrinsic value)，而在本研究中所建立的模型，其調整過後的R2可以達到0.5958。 　　2.不同的產業環境下，影響公司價值的財務比率項目可能也會有所不同。本研究所設立的三個產業虛擬變數中，紡織纖維業在90%的信賴區間下具有顯著性。

過去都市更新相關文獻中，多在分析都市更新制度與探討相關法令缺失，且多以權利變換方式探討地主權益之分配，較少以量化分析來研究都市更新協議合建分配型態，對於地主所關注合建分配比率之影響因素也未能深入研究。本研究透過文獻回顧與台北市都市更新之現況分析後，掌握可能之影響變數，藉由實證資料之蒐集與相關變數之選取，將資料進行複迴歸實證分析，以探討影響都市更新合建分配比率之顯著變數。 本研究篩選出可能影響合建分配比率之14個自變項，並排除相關係較高之土地所有權人數及建築成本兩變數後，透過複迴歸分析，結果顯示有8項達顯著性之影響因素，其中個別屬性變數包括每人土地面積、每容積公告土地現值、平均容積率、臨路寬度與臨路寬度平方、都市更新容積獎勵率、區域房價等6項達顯著性，除臨路寬度平方與都市更新合建分配比率呈負向關係外，其他皆呈正向關係，而在總體經濟變數有上一月基準利率及上一季M2年增率等2項達顯著性，其中上一月基準利率與都市更新合建分配比率呈負向關係，而上一季M2年增率與都市更新合建分配比率呈正向關係。 由實證結果得知，增加都市更新容積獎勵，確實有助提昇地主合建分配比率，因此，政府應適度調整容積獎勵項目及上限，使地主參加都市更新後，能獲得較佳之居住環境與較高之居住面積水準，甚至保障地主原居住面積水準，以增加地主參與都市更新之意願。期望政府持續大力推動都市更新政策，透過建築規劃及設計，達到改善市容、美化環境、增進公共安全及提昇居住水準等政策目的，進而達到政府、地主及開發商三贏之目標。 / Most of the past research studies on urban renewal involves analysis in the related regulations and their shortcomings. Furthermore, studies based on allocation of land owners’ equity rights are mostly done from perspective of the rules set from the government supervised appraisal process known as Rights Transformation. Few of them are conducted using the quantitative approach to derive the equity rights of the landowners from the perspective of the process known as Joint Development --- a process of private negotiation and derived terms. Thus, through analysing research articles and the current state of the urban renewal projects in Taipei, this study first intends to identify the possible variables that might affect the equity share distribution. Then using regression analysis based on the selected variables and collections of empirical data, this study explores and derives variables of significant impacts on the equity share distribution between developers and landowners in jointly developed urban renewal projects. This research has screened 14 independent variables that might have impact the equity share distribution. Results of regression analysis identify 8 significant factors, including land area per owner, government assesed land value per floor area, average floor area ratio, road width, square of road width, floor area incentive for urban renewal, and surrounding area housing value. Most of the variables have positive relationships with the landowners’ equity except for the square of road width. Macroeconomic variables such as last month’s prime interest rate and M2 growth rate in the previous quarter are found to have significant impact as well. Of which, prime interest rate is found to have negative relationship with landowners’ equity, and M2 growth rate is found to have positive relationship. Based on this empirical study, the result shows that increasing urban renewal floor area incentives indeed enhances landowners’ equity rights in a jointly developed urban renewal project. Thus, government should adjust appropriately each of the floor area incentives and their maximum allowed limits, giving the original residents a better living environment and a slightly larger living space from the redeveloped project. Furthermore, to increase the willingness of the original residents’ participation in urban renewal projects, the government could guarantee the retention of their floor area in the redeveloped projects to be the same as the floor area before urban renewal. The government should continue to promote its urban renewal policy. Proper architecture planning and design will improve the city’s appearance and the environment, as well as enhancing public safety and living standards - through which the government will not only achieve its policy objectives, but also create a win-win situation between the developers, landowners, and the government itself.

本研究主要目標在探討有關員工認股選擇權租稅政策訊息之發布，是否對國內發行員工認股權憑證之上市及上櫃公司— 資訊電子業的股票報酬造成異常影響。在五個事件期間中，以第一、二及第五個事件期（即員工認股選擇權初步比照員工分紅入股依面額課徵所得稅、財政部初步擬定員工執行認股權時，須以執行價與當初認購價格間的價差，核課所得稅以及財政部在民國93年4月30日發布員工認股權證課稅行政命令，依照財政部當初的規劃，在執行日課徵員工認股權證的所得稅之兩事件期）中發現以面額或價差課稅之消息初步規劃和發布，確實對市場造成負向異常報酬。而有利員工之認股選擇權租稅政策消息發布（即財政部未對課稅政策做出最後決定）時，市場對資訊電子業股價產生正向累積異常報酬。 另外，研究亦發現，不利員工之員工認股選擇權課稅行政命令發布之特定事件時期，發行比例愈高及發行員工認股權之公司，過去研究發展支出愈高者，將產生較小之負向累積異常報酬。 相較於員工分紅入股制度，員工認股選擇權之激勵效果更能提供長期之誘因，但單就對工之課稅制度而言，收到的似乎是相對不利之懲罰效果。 / In this thesis, event study methodology is employed to examine the electronics industry’s stock market reaction to the announcement of tax policy changes of employee stock option. Market model and Ordinary Least Square (OLS) are adopted to estimate abcdrmal returns (AR) and accumulated abcdrmal returns (CAR) during event periods. A related issue also examined is the relation between the ratio of employee’s stock options and the CAR. Specifically, the effects of five events are examined. The first、second and fifth event (when Minister of Finance proposed to tax employee Stock options based on their par value. The second is when the Ministry of Finance announced that employee stock options would be taxed at the difference between the market price employee execute the option and the execute price．The fifth event is when Minister of Finance indeed announced an administrative decree) really show up the negative CAR. Findings concluded by the thesis are as follows: 1. When the Finance Minister proposed to tax employee stock options based on their par value or at the difference between the market price employee execute the option and the execute price, electronics companies on average had negative CAR. 2. During the fifth event period, companies with higher ratio of employee stock options and R＆D expenses had lower negative CAR than those with lower ratio of employee stock options and R＆D expenses.

我國經濟發展過程中，工業部門係我國經濟成長的重要推手。為推動工業發展，由政府主動編定工業區，早期皆已出售方式提供土地，至80年代因產業外移，致使工業區土地滯銷，為去化工業區土地，由政府以優惠政策提供廠商較低價之出租優惠方案及貼近市場行情之出售優惠方案，惟出售之土地並未要求購地者須限期建廠，本研究目的是為了解影響廠商建廠之因素為何，回顧工業區位理論及過去製造業區位選擇相關研究，以複迴歸實證影響廠商之建廠因素。 研究結果顯示影響廠商建廠因素主要為工業區整體環境，包含工業區年產值、廠商家數、公共設施面積、地價、引進產業類別等，除此之外，二級產業人均薪資、工業支出及政府政策等亦對於廠商建廠有影響。故針對目前未建廠之土地，主管機關應儘速提出改善計畫，促使廠商儘速建廠；另未來新開發工業區時，應於規劃前期詳實調查產業需求、定價策略，並訂定限期完成建廠使用，提升整體工業區土地使用效率。 / In the process of economic development, the industrial sector is an important promoter of economic growth in Taiwan. In order to promote industrial development, the government takes the initiative to set up industrial areas. Due to offshore migration of Manufacturing Industry, the industrial lands were slow-selling in 1990. In order to closing out the slow-selling industrial land, the government provided manufacturers for preferential lease and sell projects. But the government didn’t regulate manufacturers to set a time limit about constructing factory building. The purpose of this study is to understand the factors that affect the manufacturers to build factories. This study reviews the theory of industrial location and the past manufacturing location selection related research and uses multiple regression analysis to understand the factors that affect the manufacturers to build factories. The research results show that the main factors is industrial area environment, including industrial annual production value, number of manufacturers, industrial area of public facilities, industrial land price and industrial classification, in addition, the manufacturing industry per capita salary, industrial expenditure and government policy also affect the manufacturers to build factories. As a result, the government should raise plan of improvement to urge manufacturers to build factories. If the government develops new industrial areas in the future, it is important to investigate industrial demand on manufacturing, land price strategy and Set the deadline to complete the construction that will enhance the efficiency of land use in industrial areas.

主要章節為：第一章是緒論，第二章是市場結構與利潤率的主要概念，第三章是台灣 製造業的市場結構與利潤率的一般觀察，第四章是台灣製造業的市場結構與利潤率的 一般關係，第五章是開放經濟下市場結構與利潤率的關係，第六章是摘要及結論。 市場結構的概念來自個體經濟學，是由完全競爭、寡占、完全壟斷的理論，來觀察經 濟體系中的市場是處於那一種結構狀態。由此探尋這些市場結構的決定因素，以及其 對廠商、產業、整個經濟體系的影響。第二章中除討論上述概念外，並介紹各國研究 的結果。 第三章中將利用六十五年工商普查資料及中華徵信所各年出版的最大民營企業統計， 台灣地區工商財務總分析；就第二章的概念，對台灣製造業作實證觀察。 第四章中將利用單一方程式的複迴歸模型，對六十五年製造業產業利潤率及廠商利潤 率，與市場結構的關係作橫斷面的分析。 第五章中將討論開放經濟下，進口競爭，對國外市場依存度，外人投資，（關稅）保 護等因素對國內市場結構的影響。並利用第四章的方法，對六十五年製造業產業利潤 率與市場結構的關係作進一步的探討。最後一章為結論。

本文旨在檢定台電公司現行季節電價月份劃分之合理性，並探討影響用戶別售電量與電費收入之經濟因素。為達成此目的，本文先就負載觀點與成本觀點進行群集分析，以檢定季節電價是否具統計意義之正當性；其次建立經濟計量模型，分別採用戶別之總售電量與總電費收入做為被解釋變數，運用民國88年1月至民國91年12月之月資料進行實證分析。本文建立之經濟模型有二，分別為時間序列以及複迴歸方程式模型。經檢定分析後，本文就各實證參數之經濟意涵加以闡示，最後並提出結論以及未來研究之方向。 本文透過月資料之群集分析，顯示夏月相對於非夏月之群集差異與台電公司現行季節電價夏月與非夏月之月份相一致，證實台電公司季節電價月份劃分之合理性。其次，透過ARIMA時間序列建立之短期電力需求預測模型，經實證結果顯示：電燈與電力用戶別之售電量均逐年增加，預測民國93年1月至民國99年12月，電燈用戶之年售電量平均成長率為3.33%、電力用戶為3.23%。再者，利用複迴歸模型進行實證分析之結果發現：(一)影響售電量之主要變數為溫度。惟因電燈用戶每隔兩月抄表一次，與電力用戶按月抄表之作業方式不同，故電燈用戶每月售電量係受前期(月)溫度影響，而電力用戶則受當期(月)溫度影響。(二)各用戶別之總電費收入與售電量有明顯相關，且經估算出各月售電量之電費收入彈性顯示：電燈用戶約為0.5，電力用戶約為1。由於總電費收入為總售電量與平均電價之乘積，故電燈用戶之電費收入增加1% 時，其售電量僅增加0.5%，顯示總電費的收入增加係有部分來自於平均電價的提高；換言之，就電燈用戶別而言，其電費收入增減變化之百分比除了會受到售電量增減幅度之影響外，亦反映了平均電價變化的情形。同理，對電力用戶來說，其各月售電量之電費收入彈性接近於1，表示電費收入變化1% 時，售電量亦增加1%，即電費收入之增減變化比例主要受到售電量之同向等幅變化所影響。 至於各用戶別之電費收入方面，電燈與電力兩類用戶自民國88年初至91年底四年期間均有逐年增加之趨勢，惟電力用戶之年增加幅度有隨時間遞減之現象，且歷年大抵以7-10月份較高，2月份最低。此外，影響用戶別電費收入之解釋變數中，各類用戶之售電量最為顯著，其參數值係隱示每增加一度售電量對其電費收入之影響。其中，電燈用戶之估計參數值為2.69，而電力用戶則為1.35。再者，由其電費收入之售電量彈性係數可以發現：電燈用戶約為1.2，電力用戶約為0.7，顯示電燈用戶總售電量增加1%時，總電費收入增加的幅度大於1%，而電力用戶則相反。推估電力用戶此一彈性係數較電燈用戶低之原因在於：電力用戶與電燈用戶之電價結構不同，前者係採需量電費與能量電費之兩部電價制，而後者僅包含流動電費之一部電價。最後，實證結果亦顯示電力系統之尖峰負載與負載率會影響電費收入，惟其影響幅度不大。 / A Study on Customer-by-Category Energy Sales and Power Sales Revenue Model: The Case of Taiwan Power Company Abstract The main purposes of this study are to examine the rationality of the seasonal pricing scheme defined by summer and non-summer months and to identify economic factors influencing customer-by-category energy sales and power sales revenue, utilizing the data of Taiwan Power Company (Taipower) as an empirical case. In order to achieve this objective, the cluster analysis from the perspective of load pattern and cost pattern are examined respectively to see if the seasonal pricing scheme has statistical meaning in its pattern differences in terms of summer vs. non-summer season. Second, two economic models including time-series analysis and multiple regression equations are formulated for the empirical case study. The subtotal energy sales and the subtotal power sales revenue by different type of customer categories, i.e. lighting and industrial customers, are set to be the explained variables. Data from January 1999 to December 2002 are collected for modeling simulation tests. The economic meanings and policy implications of the modeling results are elaborated on. And conclusions with directions for further research are presented. Through the cluster analysis utilizing monthly data within the time frame mentioned above, empirical research results on the grouping cluster of summer vs. non-summer months shows a consistent trend with those defined by Taipower’s present seasonal pricing scheme. Second, the empirical results of ARIMA time-series model show that the forecasted energy sales of both lighting and industrial customers will be gradually increasing through January 2004 to December 2010, and the average annual growth rate of energy sales for the lighting customer is 3.33%, and for the industrial customer is 3.23%. On the other hand, the empirical research results through the multiple regression equations show that the main factor affecting the energy sales is temperature. Due to the different time schedules for reading electricity meters between the lighting customer and the industrial customer, i.e. the time interval for reading the meter of lighting customers is every two months and for industrial customers is every month, the monthly energy sales of the lighting customer are directly related to the temperature of the previous month, while the monthly sales of the industrial customer are directly related to the temperature of the present month. In addition, for each type of customers, there is an obvious correlation between the total power sales revenue and the total energy sales. Furthermore, the estimated elasticity of the total power sales revenue versus total energy sales is about 0.5 for the lighting customer, and about 1 for the industrial customer. Since the total power sales revenue is the product of total energy sales times the average electricity price, when the total power sales revenue increases 1% with the total energy sales only increases 0.5%, it implies that the increase of total power sales revenue not just only comes from the increase of energy sales, but also partially affected by the increase of average electricity price. Similarly, for the industrial customer, when the elasticity of their monthly total power sales revenue versus total energy sales is close to 1, it implies that when the total power sales revenue increases 1%, the total energy sales also increase about 1%. In other words, the change of percentage of the total power sales revenue is mostly attributed to the variation of total energy sales, not because of the average electricity price. As for the simulation results of the total power sales revenue, those of the lighting and industrial customers are both gradually increasing between the years 1999 to 2002. However, the increasing pace of the industrial customer tended to slow down. Moreover, both types of the customers possess a similar trend that their total power sales are higher in statistical meaning for the months from July to October, and lower for February, for those above three years. Besides, among the variables affecting each type of customer’s power sales revenue, the energy sales is the most significant one, its parameter implies that whenever the total energy sales increases one unit, i.e. one kwh, it would affect the total power sales revenue by that amount equivalent to the figure of the parameter. According to the empirical results, the estimated parameter mentioned-above of the lighting customer is 2.69, and 1.35 of the industrial customer respectively. That implies one kwh unit price for the lighting customer is 2.69 N.T. dollars, and 1.35 N.T. dollars for the industrial customer. Moreover, from the elasticity of the total energy sales versus the total power sales revenue, it shows that the elasticity of the lighting customer is around 1.2, and the elasticity of the industrial customer is around 0.7. The underlining reason of the difference between the two figures could be that the electricity pricing structure of the lighting and industrial customers are quite different. The industrial customer is charged by two-part tariff including a demand charge for the capacity use and an energy charge for the kwh use. While the lighting customer is charged simply by a single rate, i.e. the energy use. Finally, the empirical results also show that the magnitude of the peak load and the load factor of the whole electricity system also affect the total power sales revenue of each type of the customer, though with much less effect.

本研究之研究目的旨在探討國內電子業及食品業上市主併公司進行購併活動對股價所產生的影響。研究期間為民國76年1月1日至88年12月31日，經搜集相關資料後共取得83個符合條件的購併樣本，電子業及食品業分別為53個及30個。本研究以購併宣告日前21日至宣告日前120日為市場模式之估計期，而以購併宣告日前20日至宣告日後20日為事件觀察期，採用事件研究法分析主併公司的購併宣告效果。除此之外，本研究亦以三日累積平均異常報酬為應變數，而以購併地點、購併型態、公司規模、負債比率、稅前淨利率及內部人士持股比例為自變數進行橫斷面複迴歸分析，試圖找出影響累積平均異常報酬的因素，經由實證分析後得到以下研究結論： １.電子業與食品業上市公司購併宣告對股價有正面的影響，但電子業之購併宣告效果大於食品業。 ２.電子業上市公司相關購併宣告對股價的影響程度大於非相關購併宣告，而食品業上市公司相關購併宣告對股價的影響程度小於非相關購併宣告，但效果並不顯著。 ３.電子業上市公司國際購併宣告對股價的影響程度小於國內購併宣告，而食品業上市公司國際購併宣告對股價的影響程度大於國內購併宣告。 ４.不論是電子業或是食品業，負債比率與三日累積平均異常報酬均有顯著的關係，但這兩個產業的結果卻完全相反。 最後，本研究以研究結論，分別針對上市公司、投資者、政府主管機關及後續研究者提出一些建議，期盼這些建議能夠對於其從事相關決策、學術研究時有所助益。

本研究的目的為研究台灣省在1990年之15-17歲的在學率，在找出可能影響因素並蒐集好相關的資料後，我們將蒐集到的資料分成兩個部份，一個部份用來建造模型，而另一個部份則用來測試所建立出來的模型。主要的過程是：先利用簡單迴歸模型了解各個可能的因素對於15-17歲的在學率的影響程度，經過許多分析及了解後再對這些變數採取可能的變數轉換(variable transformations)，而後再利用三種常用的統計迴歸方法﹝包含有逐步迴歸(stepwise regression)方法、前進選擇(forward selection)方法以及後退消除(backward elimination)方法﹞去發展出一個適當的複迴歸模型(multiple regression model)。對於這個模型，以實際的台灣在學情況來看，我們看不出它有任何的不合理；同時也利用圖形及檢定去驗證模型的假設，其次還做有關迴歸參數的推論(inferences about regression parameters)。再其次，我們運用變異數分析的結果(analysis of variance results)以及新觀察值的預測情形(predictions of new observations)來評估模型的預測能力。最後並利用所得到的最適當的模型，對如何提昇15-17歲青少年的在學率給予適當的建議。 / The objective of this research is to study what factors may affect the schooling rates of 15-17 years old in Taiwan province in 1990. After finding out some possible factors and collecting those data regarding those factors, we separate the data (by stratified random sampling) into two sets. One set is used to construct the model, and the other set shall be used to test the model. The main process to build a regression model is as follows. First, we shall use simple linear regression models to help us to see if each factor may have relation with the schooling rates. With the analysis of residuals and so on, we then make appropriate transformations on each of these factors. Finally, we use three common statistical regression techniques (including stepwise regression, forward selection, and backward elimination methods) to develop a suitable multiple regression model. It seems that, by our understanding of schooling rates in Taiwan, this model is not unreasonable. In addition, we verify the assumptions of the model by graphical methods and statistical tests. We also do the inferences about regression parameters. Furthermore, ye use the results of the analysis of variance and predictions of new observations to evaluate the prediction ability of the model. Finally, we use the most appropriate multiple regression model to give some suggestions to improve (or keep) the schooling rates of 15-17 years old.