一般認為醫療費用隨著年齡增加而增加，因此人口老化將加重醫療費用上漲壓力。然而，部分研究指出老年人的平均醫療費用比年輕人高的關鍵不只是年齡較大，還有老年人較年輕人更接近死亡，因此主張討論人口老化與醫療費用的關聯時，必須納入「死亡距離」的考量。本文從死亡距離角度分析臺灣不同年齡人口之死亡距離別醫療費用的分佈，以檢視年齡、死亡距離與醫療費用三者的關聯。最後結合人口推計結果，比較年齡與死亡距離兩種取向下未來全民健保整體支出的趨勢。研究結果顯示，個人醫療費用的高峰集中於死亡前一段時間，而死亡年齡越高，死亡距離別平均醫療費用越低，隱含壽命延長一方面因增加高齡人數而對整體醫療費用帶來壓力，另一方面也對整體費用的上漲有遞延作用。此外，從歷年資料來看，平均每人醫療支出開始快速增加的時間與死亡時間的距離逐漸擴大，顯示罹患疾病的時間拉長，又加大醫療支出。綜合而言，總體醫療費用將隨著人口老化而逐漸成長，但是費用推計的結果顯示年齡模型的估計值明顯較死亡距離模型估計值來得高，顯然單從年齡取向探討人口老化與醫療費用的關聯，容易高估人口老化對醫療費用的影響。

The effects of ageing on health care spending are uncertain. Some argue that health care expenditures increase substantially with age primarily because mortality rates increase with age, and expenditures increase with closeness to death. The main reason why healthcare costs increase with age is that older people are closer to death than younger people. The pattern of health expenditure by age is considerably influenced by the concentration of expenditure in the final years of life. The greater expenditure on the elderly is a consequence of the heavy weight of so-called death costs. In addition, increases in longevity may be expected to lead to postponement of these costs of the final years of life, and declines in age-specific mortality may be expected to lead to declines in age-specific costs because declining mortality reduces the proportion of those near death. If we overlook this aspect, we envisage a misleading scenario of health expenditure increase.Incorporating the concept of time to death, this paper reexamines the relationship of population aging and healthcare expenditure in Taiwan. Results indicate that different death age groups have similar average expenditures patterns against time to death, but expenditures are higher for younger people than for older people. These imply that increases in longevity delay the high costs associated with the final stage of life. Projections failing to take time to death into account might result in upward biased simulations, while total expenditures will still be raised by the absolute number of elderly people.

自二十世紀中葉以來，人類平均壽命屢創歷史紀錄，高齡（65歲以上）人口在許多國家已經或即將超過全國人口的五分之一，老年族群成為二十一世紀的熱門研究議題。然而，由於高齡人口資料在1990年代以後才有較完整紀錄，對於何種高齡死亡率模型為較佳，至今仍無定論。本文引入吃角子老虎問題（Bandit Problem）的規律折扣數列（Regular Discount Sequence），用來描述老年人的平均餘命變化，以及預測未來的高齡死亡率。許多常用的死亡率模型，例如：Gompertz法則、均勻死亡假設（Uniform Distribution of Death）、定死力假設（Constant Force）、以及雙曲線假設（Hyperbolic）等，都滿足規律折扣數列的條件。除了理論推導之外，我們採用美國加州大學柏克萊分校（University of California, Berkeley）的Human Mortality Database（HMD）資料庫，包括臺灣、日本及美國的死亡率資料，驗證規律折扣數列，三個國家的生存數與平均餘命均大致符合折扣數列的假設。另外，我們也使用布朗運動（Brownian Motion）隨機微分方程式，建立折扣數列模型，用來預測未來的高齡人口死亡率，電腦模擬顯示無論是數列比值或是死亡率預測，折扣數列模型都有不錯的結果，亦即本文提出的模型可用於預測高齡死亡率。

Life expectancies of the human male and female have been increasing significantly since the turn of the 20th century, and the trend is expected to continue. The study of elderly mortality has thus become a favorite research topic. However, because there were not enough elderly data before 1990, there is still no conclusion about which mortality model is appropriate for describing elderly mortality. In this study, we modify the regular discount sequence in the Bandit Problem and use it to describe elderly mortality. We found that many frequently used mortality models, such as the Gompertz Law, and famous mortality assumptions (Uniform Distribution of Death, Constant Force, and Hyperbolic assumption) all satisfy the requirement of a regular discount sequence.We also use empirical data from the HMD (Human Mortality Database from University of California, Berkeley), including data from Japan, the US, and Taiwan, to evaluate the proposed approach. The discount sequences of life expectancy and surviving number ratio do satisfy the regularity condition. In addition, we use the Brownian Motion Stochastic Differential Equation to model the discount sequence. Using this model, we predict the future mortality rates and life expectancy. The simulation study shows some promising results.

Excess female mortality during childhood is a distinct and unrelieved phenomenon in India, particularly in the two northern Indian states- Punjab and Haryana. This paper investigates the basic facts of sex differentials in child mortality in a very comprehensive manner using the three rounds of NFHS data sets from 1992 to 2006. More specifically, this paper examines the following three basic questions: (1) Have the sex differentials in child mortality in Punjab and Haryana narrowed down during the past two decades? (2) Does discrimination in food as well as preventive and curative care explain the existing sex differentials in child mortality? And (3) What are factors that explain the sex differentials in child mortality? The determinants of childhood mortality have been studied through Poisson regression. The survival curves resulted from Cox regression reveal two important findings: survival chances for females during neonatal period is higher, while an opposite phenomenon appears in the post-neonatal and childhood ages.

在印度，過盛的女性孩童死亡率一直是個無法紓解的特有現象，尤其是在北印度的旁遮普省與哈里亞納省。本文欲運用三份1992－2006期間之印度國家家庭衛生調查（National Family Health Survey, NFHS）統計資料，全面性的探討孩童死亡率性別差距之基本真相。更詳細的說，本文欲探討以下三個問題：（一）旁遮普省與哈里亞納省的孩童死亡率之性別差距在過去二十年間是否有減少？（二）糧食、預防與治療照護之分配不均，是否能解釋既有的孩童死亡率之性別差距？（三）有哪些因素能夠解釋孩童死亡率之性別差距？本文使用卜瓦松迴歸（Poisson Regression）研究孩童死亡率性別差距之決定因素。考克斯迴歸（Cox Regression）研究結果所呈現的存活曲線，顯示兩個重要的發現：初生女嬰的存活率較男嬰高；而在嬰兒後期與孩童時期則有相反現象。

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本文擬利用百年臺灣廿三縣市人口統計資料，嘗試對臺灣地區的人口變遷之長期趨勢進行研究，以期有助於當前人口相關研究之開展。經本研究處理之人口資料橫跨日治時期與國府時期，呈現了臺灣縣市人口興衰之轉折，也可為相關的研究議題提供基礎資訊。本文以縣、市層級之人口數排名資料指出，歷來擁有人口數最多之縣市逐年由南而中、由中而北的漸進過程。藉由此等臺灣各地長期人口之數據，文中發現：日治迄今，全臺人口重心的位置，就戰前而言，日治前期先呈北移、日治後期則現南降，至於戰後迄今則一路呈現持續北移之勢。此外，總計全臺人口數排名首位亦有三次轉折，第一次為彰化縣取代臺南縣，第二次為臺北市取代彰化縣，第三次為臺北縣取代臺北市，然其背後所對應之各時期全臺人口分布型態有所不同。

This paper seeks to examine Taiwan's long-term trend in population distribution using the twenty-three-county (hsien) population statistical database from 1897 to 2010, in the hope of aiding any current studies regarding population. The information presented in this paper covers the time span from the Japanese Colonial Period to Early Nationalist Rule in China, providing the rise and fall of county population in Taiwan. That said, this paper can also be of reference for related studies. From records of city and county population ranking, this paper finds the trend in city with largest population developing from south-to-mid and mid-to-north of Taiwan. And from long-term population statistics, this paper finds that from the Japanese Colonial Period to this day, before WWII, the majority of the Taiwanese population changed from migrating northward during Early Japanese Rule, to migrating south during Late Japanese Rule. Then, settling at a steady trend of migrating northward occurred after WWII. In addition, the city with largest population has changed three times in history: first, Changhua County surpassed Tainan County; second, Taipei City outgrew Changhua County; and lastly, Taipei County replaced Taipei City as the largest. Yet, keep in mind that each transition matches a different national population distribution.

本文欲釐清戰後至今（1966－2011年）近四十五年間，大臺南市製造業的發展脈絡與其空間變遷關係。研究首先透過大臺南市歷年（1971－2006年）製造業工廠數、員工數及生產總值，計算都市各分帶之成長指數變化，同時藉「工業強度」、「區位商數」及「過剩員工數」等三大工業指數，以製圖方法釐清市內各區產業發展及郊區化概況，呈現製造業「入」字型聚集現象。其次利用都市計畫圖、編定工業區位圖、土地利用圖及交通路網圖，闡明該產業空間佈局與都市土地發展存在「住宅與工商混合使用」及具有強化「地方化經濟」成長的機能。最後研究分析「工業區—村里居住人口—製造業及業人口」三因子之集中分布趨勢，結果顯示受高科技工業區外部效益擴散的影響，該類園區周圍各里之製造業就業與及業人口大為增加。未來，唯有持續調適並克服產業結構再組織的挑戰，方能邁向創新轉型並強化其產業競爭力。

Although political and economic circumstances deteriorated in Tainan, its industrial base has since improved with the issuing of industrial law in 1960. The district has since been revived in 2010 with the merger of Tainan City and Tainan County. This paper aims to explore Tainan's historical and special manufacturing changes between 1966 to 2011. We offer to holistically explore Tainan's manufacturing development through four aspects: the growth index, the aggregation trend of symbol ”入”, the interdependency of location-urban development, and Tainan's other potentials.The growth index is computed from the number of factory, labor, and total output value from every district. The aggregation trend of symbol ”入” is obtained by analyzing industrial indexes such as industrial strength, location quotient (L.Q.), and surplus labor-space analysis. The interdependency of location-urban development can be examined from city planning blueprints, distribution of industry maps, land use maps, traffic network maps, etc.Finally, the paper provides suggestions on ”industrial zone-population center village” and ”industrial zone-labor center of manufacturing village” in regards to future development trends in manufacturing in Tainan.

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