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.

中文部份
中華民國內政部統計資訊網，http://www.moi.gov.tw/W3/stat。
內政部統計處（1949-2009）中華民國台閩地區人口統計，內政部編印。
王錫美（2005）台灣地區有偶率與婚姻移民對生育率之影響，國立台北大學統計所碩士論文。
朱伯長（2006）台灣與世界各國生育率的比較，國立政治大學統計所碩士論文。
余清祥、藍銘偉（2003）台灣地區生育率模型之研究，人口學刊，27：105-131。
李美玲（1990）台灣地區婦女的生育步調與生育轉型，人口學刊，13：145-166。
黃意萍、余清祥（2002）台灣地區生育率推估方法的研究，人口學刊，25：145-171。
曾奕翔、余清祥（2002）台灣地區死亡率推估的實證方法研究，2002年臺灣人口學年會。
賴思帆、余清祥（2006）台灣與各國生育率模型之實證與模擬比較，人口學刊，33：33-59。
劉ㄧ龍、王德睦（2005）台灣地區總生育率的分析：完成生育率與生育步調之變化，人口學刊，30：97-123。

英文部分
Bongaarts, J. and Feeney G. (1998),“On the quantum and tempo of fertility”, Population and Development Review 24(2), 271-291.
Booth, H. (1984),“Transforming Gompertz’s function for fertility analysis: The development of a standard for the relational Gompertz function”, Population studies, 38(3), 495-506.
Brown, R. L. (1997), Introduction to the Mathematics of Demography, ACTEX publications, Inc.
Cheng, P. C. R. and Lin, E. S. (2010),“Complete incomplete cohort fertility schedules”, Demographic Research, 23(9), 223-256.
Goldstein, J. R. (2010),“A Behavioral Gompertz Model for Cohort Fertility Schedules in Low and Moderate Fertility Populations”, Max Planck Institute for Demographic Research, MPIDR WORKING PAPER WP 2010-021.
Goldstein J. R. and Cassidy T. (2010),“Cohort postponement and period measures”, Max Planck Institute for Demographic Research, MPIDR WORKING PAPER WP 2010-015.
Lee, R. D. and Carter, L. R. (1992),“Modeling and Forecasting U.S. Mortality”, Journal of the American Statistical Association, 87(419), 659-675.
Leridon, H. (2004),“Can assisted reproduction technology compensate for the natural decline in fertility with age? A model assessment”, Human Reproduction, 19(7), 1549-54.
Leridon, H. (2005),“A new estimate of permanent sterility by age: Sterility defined as the inability to conceive”, PAA 2005 Annual Meeting(Phladephia), Session 105 ‘Biodemography’.
Lewis, E. B. (1982),“Control of body seqment differentiation in Drosophila by the bithorax gene complex”, Embryonic Development, Part A: Genetics Aspects, Edited by Burger, M. M. and R. Weber. Alan. R. Liss, New York , 269-288
, H. (2010),“Cohort and Period Mortality in Sweden in a very long perspective and projection strategies”, CONFERENCE OF EUROPEAN STATISTICIANS
Ryder, N. B. (1960),“The Structure and Tempo of Current Fertility”, Demographic and Economic Change in Developed Countries, out-of-print volume from National Bureau of Economic Research, 117-136.
Ryder, N. B. (1964),“The Process of Demographic Transition”, Demography, 1(1), 74-82.
Statistics Japan, http://www.stat.go.jp
Statistics France, http://www.humanfertility.org/cgi-bin/main.php
Statistics United States, http://www.humanfertility.org/cgi-bin/main.php
Wilmoth, J. R. (1996),“Mortality projections for Japan: a comparison of four methods”, Health and Mortality Among Elderly Populations, 266-287