近年隨著油價、物價上漲所導致的通貨膨脹風險，壽險業者以增額型終身壽險來吸引潛在消費者。另外，由於醫療技術的進步，使得死亡率逐年改善，因此將造成保單在設計時可能將遭受到長壽風險的影響。本篇文章的主要目的即探討長壽風險對於保單責任準備金的影響，並以增額型終身壽險作為本文主要分析標的。首先建構死亡率模型(Lee-Carter模型)，用來配適並模擬死亡率，接著探討增額型終身壽險在各保單年度下之現金流量以及責任準備金的提存，進一步再引進不同的死亡率來探討其現金流量分佈情形與責任準備金之提存。本文研究結果發現，在保險公司未採用遞迴方式計算保費時，當繳費期間愈短、複利利率愈高以及投保年齡愈低時，保險公司所面臨之長壽風險愈大，其後在帶入各種不同死亡率模型，發現死亡改善率愈高，保險公司所面臨之長壽風險愈大，而保險公司在提存責任準備金時，並未考慮到死亡改善率的部分，此對保險公司的財務健全將造成隱憂，本文於此部分建議監理機關透過法規(RBC)的制訂，調整準備金提存的係數，以降低長壽風險對保險公司財務之衝擊。 關鍵字：長壽風險、死亡率模型、增額型終身壽險、保單責任準備金、增額準備金、Lee-Carter Model以及RBC制度。 / With the improvement of medical technology, the life expectancy around the world is increasing year by year during the past decade. Therefore, the increasing whole life insurance policy is popular during these years because its benefits are escalating with time and policyholders think they could gain more benefits when they live longer. Like annuity policies, the increasing whole life insurance could also suffer from the longevity risk, which may have enormous impact on the financial statements of insurers. The purpose of this paper is to discuss the impact of longevity risk on reserves, based on increasing whole life insurance policy. First, we construct Lee-Carter model to fit and simulate mortality rate and assume different mortality improvements from the 2002 Taiwan Standard Ordinary Experience Mortality Table (2002TSO) for further comparisons. And then, we construct a simple model to analyze the cash flows of the increasing whole life policies based on the mortality rates we observed. By constructing a simple model and simulation, we find that if the insurance company does not correctly estimate longevity risk, the insurance company will lose money on the increasing whole life policies. In order to mitigate the insufficiency of life insurers for the increasing whole life policies, we try to provide some supervision suggestion from the view of the risk-based capital (RBC) requirements. We calculate the factor of insurance risk (C2) of RBC requirements because this factor represents the surplus needed to provide for excess claims over expected, both from random fluctuations and from inaccurate pricing for future levels of claims. Keywords: longevity risk, increasing whole life insurance policy, Lee-Carter model, risk-based capital (RBC).

本篇論文主要討論在死亡率改善不確定性之下的避險策略。當保險公司負債面的人壽保單是比年金商品來得多的時候，公司會處於死亡率的風險之下。我們假設死亡率和利率都是隨機的情況，部分的死亡率風險可以經由自然避險而消除，而剩下的死亡率風險和利率風險則由零息債券和保單貼現商品來達到最適避險效果。我們考慮mean variance、VaR和CTE當成目標函數時的避險策略，其中在mean variance的最適避險策略可以導出公式解。由數值結果我們可以得知保單貼現的確是死亡率風險的有效避險工具。 / This paper proposes hedging strategies to deal with the uncertainty of mortality improvement. When insurance company has more life insurance contracts than annuities in the liability, it will be under the exposure of mortality risk. We assume both mortality and interest rate risk are stochastic. Part of mortality risk is eliminated by natural hedging and the remaining mortality risk and interest rate risk will be optimally hedged by zero coupon bond and life settlement contract. We consider the hedging strategies with objective functions of mean variance, value at risk and conditional tail expectation. The closed-form optimal hedging formula for mean variance assumption is derived, and the numerical result show the life settlement is indeed a effective hedging instrument against mortality risk.

臺灣的男女死亡率皆呈現逐年遞減的趨勢，自1993年進入高齡化社會後，預計將會在2018年進入高齡社會；人口不斷老化的結果讓社會上不論人民或是如保險公司等年金提供者皆面臨愈來愈嚴重的長壽風險；目前現有文獻提出了許多方式以解決長壽風險，其中多數的方法皆需使用到對未來死亡率之預估。 本研究為了能夠更準確的預估未來死亡率的趨勢，參考了Lee Carter (1992)所提出之模型以及Li and Lee (2005)、Li (2013)提出之共同改善趨勢效果，提出考慮商品與商品間以及商品與整體人口間共同改善趨勢之死亡率模型；本研究利用臺灣之保險公司壽險及年金業務經驗死亡率和Human Mortality Database之臺灣人口資料對模型進行配適，並以MAE、MAPE、RMSE三項指標比較與Lee Carter模型之優劣。 最後，本研究利用所配適之模型進行預測，模擬自然避險之效果，檢視臺灣保險業進行自然避險的可能效益，並對決策者在於決定是否要進行自然避險方面給出建議。 / Taiwan became an aging society in 1993 and is expected to become an aged society in 2018. The progressive decrease in Taiwan mortality since the 20th century for both genders has made longevity risk a serious problem for both people and annuity provider in Taiwan. So far, the literature has discussed about how to deal with longevity risk and came out with several solutions which can be categorize as “industry self-insurance”, “ mortality projection improvement” and “capital market solutions” , most of them are related to the projection of mortality. In order to provide a more precise projection of future mortality trend, this article designs several models which collaborates Lee Carter Model (1992) and the common improvement trend suggested by Li and Lee (2005). Based on our models, the Taiwan insurance industry experience mortality data and the Taiwan population mortality data, we test the performance of our models and make comparison. Lastly, we use the model we find to project future mortality trend and try to make a simulation of natural hedging strategy in Taiwan. The purpose we do this is to test the performance of natural hedging method and give suggestion for the decision-maker when they are considering whether to execute a natural hedging strategy.

台灣地區居民近年的死亡率下降速度加快，使得我國國民的平均壽命在公元2000年已超過美國，成為長壽的國家之一。其中我國國民死亡率的下降幅度因年齡而不同，且各個年代、世代也不相同，與APC（Age-Period-Cohort）模型採年齡、年代與世代三個因子分析死亡率頗為一致，因此本文計畫以APC模型研究台灣的死亡率。然而，由於「年代＝年齡＋世代」之線性相關，參數估計值有甄別問題（Identification Problem），使得參數估計值不唯一。 文獻中有不同方法解決APC模型的參數估計問題，近年又有Fu（2000）提出之本質估計量（Intrinsic Estimator），可直接解決參數估計及其變異數。因此本文首先以電腦模擬驗證本質估計量，以及過去其他估計方法，檢測這些方法是否可得出理論的結果。本文的第二部分則以西元1961至2005年的資料探討APC模型的實用性，分析APC與Lee-Carter模型的優劣；研究發現APC模型用於估計死亡率時，整體而言雖不如Lee-Carter模型，但可彌補Lee-Carter模型在高年齡有較大誤差的不足，唯在年輕族群則仍有改善空間，未來或可考慮APC與Lee-Carter模型的結合。 / The mortality rates in Taiwan area have been experiencing dramatic decreases in recent years. The life expectancy has surpassed that in the United States in 2000 and Taiwan has become one of the longevity countries. Besides, the falling of mortality rates varies in different age, period, and cohort groups, which corresponds to the APC (Age-Period-Cohort) model. Therefore, the goal of this paper is to study the mortality rates in Taiwan area with APC model. However, due to the linear dependency of age, period and cohort (Period = Age + Cohort), there is the identification problem, that is, the parameter estimates are not unique. A number of solutions to the identification problem in APC model have been provided in the literature. Fu (2000) introduce a new estimator, the Intrinsic Estimator (IE), which can solve parameter estimates and variance directly. In the first part of this research, computer simulation is conducted to examine the IE, compared with other methodologies. In the second part of this research, data from 1961 to 2005 are used for verifying the validity of APC model in fitting mortality rates, and we analyze the strengths and weaknesses between the APC and Lee-Carter model. The results from our study indicate that the APC model in estimating mortality rates does not show as well as the Lee-Carter model as a whole. However, the APC model performs better than the Lee-Carter model for the elderly mortality rates, but is still needed to be improved in young groups. In the future, it can be considered to combine the APC and Lee-Carter model.

臺灣婦女生育率下降快速，近年來屢創新低，堪稱全球生育率最低的國家，總生育率自民國89年1.68、降為民國98年1.03，民國99年甚至降至0.90以下，提升生育率成為政府施政的重要課題。因為資料限制，生育率大多以總生育率(Total Fertility Rate)表示，而非較能反映婦女一生生育總數的世代完成生育率(Completed Cohort Fertility Rate)。這兩者間存有不少差異，以生育率下降的臺灣為例，總生育率會因生育時機遞延而低估世代生育率，以總生育率詮釋生育率可能有瑕疵。有鑒於此，本文以比較「世代」及「年代」兩者的差異，以生育率及死亡率為研究對象，探討較適宜描述臺灣特性的模型。 由於世代生育率會有資料不足的問題，本文使用外推法(Extrapolation)補足年齡較高（如35歲以上）的婦女生育率，並以四種模型估計年代生育率與世代生育率，包括Gamma模型、Gompertz模型、主成份分析(Principle Component Analysis)與單一年齡組個別估計法，希望找出適合預測臺灣世代完成生育率的模型。除了台灣資料，也用日本、法國與美國的世代生育率資料，比較各國世代生育率模型的異同。另外，本文也以世代及年代兩種觀點，類似生育率的探討方式，比較常用死亡率模型的優劣。 不論是生育率或是死亡率資料，配適模型結果皆以世代資料可得到較好的估計結果，生育率以單一年齡組個別估計法為最佳的模型，死亡率則以Gamma模型、主成份分析、單一年齡組個別估計法為較佳的模型。 / Taiwan’s fertility rates have been declining radically in recent years, much faster than most countries in the world. For example, the total fertility rate (TFR) is 1.68 in 2000, 1.03 in 2009, and even reduces to 0.90 in 2010. Therefore, one of the top priorities for Taiwan government policies is to enhance the willingness of having children. Due to the data availability, the TFR is used more often, although the completed cohort fertility rate (CFR) is a more reasonable measurement. However, previous studies showed that the TFR is likely to be influenced by the deferring (i.e., tempo effect) of childbearing and produces misleading results. In order to measure the effect of deferring childbearing, this study focuses on exploring the difference of measures in the view of cohort and period (especially the CFR vs. TFR) and evaluates which fertility and mortality model is more appropriate for Taiwan. Because there are fewer complete cohort fertility data, we use extrapolation to make up the higher age-group fertility data (such as aged 35 and above). We consider four fertility models in this study, including Gamma model, Gompertz model, principal component analysis, and individual group estimation. We use the data from Taiwan, Japan, France and United State data to evaluate these fertility models. The results indicate that the parametric models (Gamma and Gompertz) have the worst performance, probably due to the rapid change of fertility behaviors. In addition, similar to evaluating the fertility models, we compare the performance of frequently used mortality models using the cohort and period mortality data. The result shows that using cohort data to estimate fertility and mortality is better than period data. Also individual group estimation is the best model to fit fertility; the better models to fit mortality are Gamma model, principle component analysis and individual group estimation.

壽命延長及生育率下降使得人口老化日益明顯，成為全球多數國家在21世紀必須面對的議題，由於各區域人口老化的速度不同，必須根據各地特性而調整因應對策。其中研究死亡率變化為面對人口老化的必備課題，尤其是高齡族群的死亡率，這也是近年高齡死亡模型廣受重視的主因之一。因為樣本數與變異數成反比，人口較少的區域或是高齡人口，死亡率的觀察值通常會有較大震盪，為了降低震盪多半會經過修勻，以取得較為穩定的死亡率推估值（王信忠等人，2012）。此外，Li and Lee (2005)的Coherent Lee-Carter模型也是另一種可行方法，透過參考大區域的資訊降低小區域的估計誤差。 本文探討結合上述修勻、死亡率模型的可能，希冀能綜合兩者的優點，提高小區域死亡率推估的精確性。因為Coherent Lee-Carter模型的想法類似增加小區域的人數（加入大區域的人數），本文探討人口數與Lee-Carter模型參數估計值的關係，再以修勻調整大小區域的差異，透過電腦模擬及資料分析，驗證本文提出方法是否有效。其中，仿造王信忠等人的作法，假設小區域與大區域死亡率間的七種可能情境，以平均絕對百分誤差(Mean Absolute Percentage Error)為衡量標準，找出調整修勻、相關模型的方法。另外，本文也以臺灣縣市為研究區域，驗證本文方法的估計結果。研究發現適當地使用修勻方法，可降低小區域的死亡率估計值，其效果優於Coherent Lee-Carter模型。

重大傷病是我國全民健康保險的重要特色之一，透過社會保險的風險分擔機制，病患享有免部分負擔等優惠，降低因為罹病帶來的財務負擔，但重大傷病同時也成為全民健保的主要支出項目。民國102年領取重大傷病證明者不過98餘萬人（約總人口的4%），但其一年的醫療費用多達一千五百多億元（接近總支出的27%），平均每位重大傷病患者的醫療費用約為平均值的7.34倍，其中癌症又是重大傷病中人數最多者，大約佔了49%（資料來源：衛生福利部中央健康保險署）。因為許多重大傷病的發生率、盛行率與年齡成正比（黃泓智等人，2004），未來隨著人口老化，全民健保支出也將跟著上升。 　　本文使用全民健保資料庫，探討近十年重大傷病（尤其是癌症）趨勢，估計重大傷病的年齡別發生率、死亡率，評估人口老化對全民健保造成的影響，其中承保資料檔（ID）、重大傷病檔（HV）為本研究主要的依據資料。而由於健保資料庫的資料種類及數量龐雜，在初期資料的偵錯及處理上非常重要但也相當費時，至於發生率、死亡與否的判斷亦十分棘手，因此過程中我們將一一說明資料分析步驟及注意事項。本文發現癌症及重大傷病的盛行率逐年上升，但發生率並沒有明顯變化，加上近年癌症死亡率幾乎不變（但台灣全體國民的死亡率逐年遞降），因為台灣的人口老化，預期未來罹患癌症人數會逐年增加，癌症將繼續蟬聯十大死因之首，但罹癌死亡率的下降也可發現近年醫療進步所造成的影響。此外，我們也考量隨機死亡模型（Lee-Carter Model），發現無論是癌症死亡率、或是罹癌死亡率都有不錯的估計結果。而在文末也提出癌症病患的就醫行為以供後續研究者參考。 / Catastrophic illness (CI) is one of the key features of Taiwan’s National Health Insurance (NHI). Through risk-sharing mechanisms of social insurance, it can reduce the financial burden of the CI patients since treating the CI is usually expensive. However, the CI also becomes a major expenditure item of NHI. The people receiving the CI card are just 0.98 million in 2013 (about 4% of the total population), but their smedical costs are over 150 billion NT dollars (nearly 27% of total expenditures). The average medical cost per CI patient is about 7.34 times of the national average. (Source: Department of Health and National Health Insurance Agency). Because the incidence and prevalence rates increase with age (Huang et al, 2004), the total NHI expenditure is expected to increase in the future due to population aging. This study intends to use the NHI database, including the records of personal identification and out-patient visit from all CI patients, to explore the incidence and mortality rates, for example, of CI patients. Because the NHI database is big and messy, we shall first debug and clean them. Also, since the death of CI patients are not fully reported in the NHI database, we propose a method to identify the deaths and use the official statistics to evaluate. The results show that the prevalence rates of all CI increased every year, but their incidence rates did not change significantly. The mortality rates of cancer patients also did not change much. Based on these findings, we expect the proportion of CI patients and their size will continue to grow. In addition, we applied the Lee-Carter model to the cancer mortality rates, and the fit is pretty good.

Selected Methodical Approaches to Regional Population Forecast: A case study in the South Bohemian Region Abstract The aim of this thesis is to introduce selected methodological approaches to population forecasts, focusing on the regional level and considering different lengths of time series. Specific procedures are applied to create a population forecast for the South Bohemian Region. In the theoretical part of this thesis, the stages of population forecasts processing are determined. The Cohort Component method with migration, which can be used to create population forecast, is characterized. Another part describes selected analytical models and functions for partial mortality, fertility and migration forecasts, including Indirect estimation of net migration. To extrapolate parameters, selected trending functions and the Box-Jenkins methodology are characterized in the part of the time series analysis. The analytical part of this thesis focuses on the creation of the South Bohemian Region forecast from short initial time series and long initial time series. From short initial time series, the partial forecast of mortality is analyzed by the Heligman-Pollard model, the partial forecast of fertility is analyzed by the Beta function and the partial forecast of migration is analyzed by 25%, 50% and 75%...

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal