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題名 小區域生育率與人口推計研究
Small Population Projections:Modeling and Evaluation
作者 曹郁欣
Eunice Y. Tsao
貢獻者 余清祥
Jack C. Yue
曹郁欣
Eunice Y. Tsao
關鍵詞 人口推估
小區域推估
修勻
區塊拔靴法
隨機推估
Population Projection
Small Area Population Projection
Graduation
Block Bootstrap
Stochastic Projection
日期 2012
上傳時間 1-Feb-2013 16:50:11 (UTC+8)
摘要 由於許多國家死亡率下降快速、壽命延長幅度超乎預期,加上生育率持續低於替代水準,人口老化現象愈發明顯,近年來個人生涯規劃及政府施政,都格外強調退休後經濟生活及老年相關社會資源分配的比重。以臺灣為例,行政院經濟建設委員會 (簡稱經建會) 從1990年代開始,每兩年公布一次未來的人口推估,但過去十年來經建會屢次修正歷年的推估假設,以因應生育率及死亡率變化快速,適時提醒臺灣日益加速的人口老化。正因為人口推估可能受到人口數、社會變遷、資料品質等因素,影響統計分析的可靠性,常用於國家層級的推估方法,往往無法直接套用至縣市及其以下的層級 (即小區域),使得小區域人口推估較為棘手,需要更加謹慎面對。
本文延續王信忠等人 (2012) 的研究,以小區域人口推估為目標,著重在生育率推估研究,結合隨機模型與修勻方法,尋找適合臺灣縣市層級的小區域人口推估方法。本文考量的隨機模型計有區塊拔靴法 (Block Bootstrap) 和 Lee-Carter 模型 (Lee and Carter 1992),以預測未來的生育率和死亡率,並套用年輪組成推計法 (或稱為人口要素合成法;Cohort Component Method) 及修勻 (Graduation) 方法,探討這些方法與人口規模之間的關係,評估用於小區域人口推估之可行性。
本文首先以電腦模擬,探討生育率的推估,討論是否可直接推估總生育率,類似增加樣本數的概念,取代各縣市的年齡別生育率,以取得較為穩定的推估。根據模擬結果,發現人口規模對出生數的推估沒有明顯的關係,只要使用總生育率、再結合區塊拔靴法,就足以提供穩定的推估結果。實證研究方面,以臺灣縣市層級的人口及其年齡結構 (例如:0-14歲、15-64歲、65歲以上) 為驗證對象,發現分析結果也與電腦模擬相似,發現以區塊拔靴法推估臺灣各縣市的總生育率、年齡組死亡率,其推估精確度不因人口規模而打折扣,顯示以區塊拔靴法推估總生育率、年齡組死亡率,可用於推估臺灣小地區的未來人口。
Due to the rapid mortality reduction, prolonging human longevity is a common phenomenon and longevity risk receives more attention in 21st century. Many developed countries encounter many problems brought up by prolonging life, such as poor community infrastructure and insufficient financial pension funds for the elderly. Population Projection thus becomes essential in government planning in dealing with the population aging. However, rapid changes in mortality and fertility make the projection very tricky. It would be even more difficult to project areas with fewer populations (i.e., small areas) since it takes extra efforts to deal with the larger fluctuations in small population.
The objective of the study is to construct a standard operating procedure (SOP) for small population projection. Unlike the previous study, e.g., Wang et al. (2012), we will take both the fertility and mortality into account (but set migration aside for simplicity). First, for the fertility projection, we evaluate if total fertility rates (TFR) are more appropriate than the age-specific fertility rates for small population. Also, we compare two fertility projection methods: Lee-Carter model and block bootstrap, and check which shows better results. Based on the computer simulation, we found that TFR performs better and the block bootstrap method is more sensitive to rapid fertility changes. As for mortality rate projection, we also recommend the standard operating procedure by Wang et al. (2012). However, the smoothing methods have limited impacts on mortality projection and can be ignored.
In addition to simulation, we also apply the SOP for projecting the small population to Taiwan counties and it achieves satisfactory results. However, due to the availability of data, our method can only be used for short-term projection (at most 30 years) and these results might not apply to long-term projection. Also, similar to the previous work, the fertility rates have the larger impact on small population projection, although we think that the migration has large impact as well. In this study, only the stochastic projection is considered and we shall consider including expert opinions as the future study.
參考文獻 中文部分
王信忠、金碩、余清祥 (2012)。小區域死亡率推估之研究。Journal of Population Studies (TSSCI), 45, 121–154.
余清祥 (1997)。修勻:統計在保險的應用。台北市:雙葉書廊。
金碩與余清祥 (2011)。修勻與小區域人口之研究。碩士論文。
徐茂炫、陳建亨、黃彥豪 (2011)。逾百年臺灣縣市人口興衰之轉折:1987-2010。人口學刊,43,109–135。
陳政勳與余清祥 (2010)。小區域人口推估研究:臺北市、雲嘉兩縣、澎湖縣的實證分析。人口學刊,41,153–183。
陳寬政 (1997)。臺灣地區人口出生數量的動態模擬。人口學刊,18,1–18。
黃意萍與余清祥 (2002)。台灣地區生育率推估方法的研究。Journal of Population Studies (TSSCI), 25, 145–171.
郭孟坤與余清祥 (2008)。電腦模擬、隨機方法與人口推估的實證研究。人口學 刊,36,67–98。
英文部分
Booth H. (2006). Demographic forecasting: 1980 to 2005 in review. International Journal of Forecasting, 22(3), 547–581.
Brown R. L. (1991). Introduction to the Mathematics of Demography, ACTEXublications, Inc.
Cannan E. (1985). The probability of a cessation of the growth of population in England and Wales during the next century.The Economic Journal, 5(20), 505–515.
Denton F. T., Feaver C. H., & Spencer B. G. (2005). Time series analysis and stochastic forecasting an econometric study of mortality and life expectancy. Journal of Population Economics, 18(2), 203–227.
Hall P. (1985). Resampling a coverage pattern. Stochastic Processes Applications, 20(2), 231–246.
Koissi M. C., Shaporo A. F., & Högnäs G. (2006). Evaluation and extending the Lee-Cater model for mortality forecasting: Bootstrap confidence interval. Insurance: Mathematics and Economics, 38(1), 1–20.
Künsch H. R. (1989). The Jackknife and the Bootstrap for general stationary observations. Annals of Statistics, 17, 1217–1261.
Lawson C. L., Hanson R. J. (1974). Solving least squares problems. New Jersey: Prentice-Hall, EngleWood Cliffs.
Lee R. D., Carter L. R. (1992). Modeling and forecasting US mortality. Journal of the American Statistical Association, 87(419), 659–671.
Lee R. D. (2000). The Lee-Carter method for forecasting mortality, with variousextensions and applications. North American Actuarial Journal, 4(1), 80–93.
Lee W. (2003). A partial SMR approach to smoothing age-specific rates. Annals of Epidemiology, 13(2), 89–99.
Leslie P. H. (1945). On the use of matrices in certain population dynamics. Biometrika, 33, 183–212.
Leslie P. H. (1948). Some further notes on the use of matrices in population mathematics. Biometrika, 35, 213–245.
Lewis C. D. (1982). Industrial and business forecasting methods : a practical guide to exponential smoothing and curve fitting. London: Butterworth Scientific.
Li N., Lee R., & Tuljapurkar S. (2004). Using the Lee-Carter method to forecast mortality for populations with limited data. International Statistical Review, 72 (1), 19–36.
Myers G. C. (1990). Demography of Aging. Handbook of Aging and the Social Science, Third Edition, 19–44.
Stoto M. A. (1983). The Accuracy of Population Projections. Journal of the American Statistical Association ,78, 13-20.
Whelpton P. K. (1936). An empirical method for calculating future population. Journal of the American Statistical Association, 31, 457–473.
Wilson T., Rees P. (2005). Recent developments in population projection methodology: a review. Population, Space and Place, 19(1), 1–126
描述 碩士
國立政治大學
統計研究所
99354007
101
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0099354007
資料類型 thesis
dc.contributor.advisor 余清祥zh_TW
dc.contributor.advisor Jack C. Yueen_US
dc.contributor.author (Authors) 曹郁欣zh_TW
dc.contributor.author (Authors) Eunice Y. Tsaoen_US
dc.creator (作者) 曹郁欣zh_TW
dc.creator (作者) Eunice Y. Tsaoen_US
dc.date (日期) 2012en_US
dc.date.accessioned 1-Feb-2013 16:50:11 (UTC+8)-
dc.date.available 1-Feb-2013 16:50:11 (UTC+8)-
dc.date.issued (上傳時間) 1-Feb-2013 16:50:11 (UTC+8)-
dc.identifier (Other Identifiers) G0099354007en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/56828-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計研究所zh_TW
dc.description (描述) 99354007zh_TW
dc.description (描述) 101zh_TW
dc.description.abstract (摘要) 由於許多國家死亡率下降快速、壽命延長幅度超乎預期,加上生育率持續低於替代水準,人口老化現象愈發明顯,近年來個人生涯規劃及政府施政,都格外強調退休後經濟生活及老年相關社會資源分配的比重。以臺灣為例,行政院經濟建設委員會 (簡稱經建會) 從1990年代開始,每兩年公布一次未來的人口推估,但過去十年來經建會屢次修正歷年的推估假設,以因應生育率及死亡率變化快速,適時提醒臺灣日益加速的人口老化。正因為人口推估可能受到人口數、社會變遷、資料品質等因素,影響統計分析的可靠性,常用於國家層級的推估方法,往往無法直接套用至縣市及其以下的層級 (即小區域),使得小區域人口推估較為棘手,需要更加謹慎面對。
本文延續王信忠等人 (2012) 的研究,以小區域人口推估為目標,著重在生育率推估研究,結合隨機模型與修勻方法,尋找適合臺灣縣市層級的小區域人口推估方法。本文考量的隨機模型計有區塊拔靴法 (Block Bootstrap) 和 Lee-Carter 模型 (Lee and Carter 1992),以預測未來的生育率和死亡率,並套用年輪組成推計法 (或稱為人口要素合成法;Cohort Component Method) 及修勻 (Graduation) 方法,探討這些方法與人口規模之間的關係,評估用於小區域人口推估之可行性。
本文首先以電腦模擬,探討生育率的推估,討論是否可直接推估總生育率,類似增加樣本數的概念,取代各縣市的年齡別生育率,以取得較為穩定的推估。根據模擬結果,發現人口規模對出生數的推估沒有明顯的關係,只要使用總生育率、再結合區塊拔靴法,就足以提供穩定的推估結果。實證研究方面,以臺灣縣市層級的人口及其年齡結構 (例如:0-14歲、15-64歲、65歲以上) 為驗證對象,發現分析結果也與電腦模擬相似,發現以區塊拔靴法推估臺灣各縣市的總生育率、年齡組死亡率,其推估精確度不因人口規模而打折扣,顯示以區塊拔靴法推估總生育率、年齡組死亡率,可用於推估臺灣小地區的未來人口。
zh_TW
dc.description.abstract (摘要) Due to the rapid mortality reduction, prolonging human longevity is a common phenomenon and longevity risk receives more attention in 21st century. Many developed countries encounter many problems brought up by prolonging life, such as poor community infrastructure and insufficient financial pension funds for the elderly. Population Projection thus becomes essential in government planning in dealing with the population aging. However, rapid changes in mortality and fertility make the projection very tricky. It would be even more difficult to project areas with fewer populations (i.e., small areas) since it takes extra efforts to deal with the larger fluctuations in small population.
The objective of the study is to construct a standard operating procedure (SOP) for small population projection. Unlike the previous study, e.g., Wang et al. (2012), we will take both the fertility and mortality into account (but set migration aside for simplicity). First, for the fertility projection, we evaluate if total fertility rates (TFR) are more appropriate than the age-specific fertility rates for small population. Also, we compare two fertility projection methods: Lee-Carter model and block bootstrap, and check which shows better results. Based on the computer simulation, we found that TFR performs better and the block bootstrap method is more sensitive to rapid fertility changes. As for mortality rate projection, we also recommend the standard operating procedure by Wang et al. (2012). However, the smoothing methods have limited impacts on mortality projection and can be ignored.
In addition to simulation, we also apply the SOP for projecting the small population to Taiwan counties and it achieves satisfactory results. However, due to the availability of data, our method can only be used for short-term projection (at most 30 years) and these results might not apply to long-term projection. Also, similar to the previous work, the fertility rates have the larger impact on small population projection, although we think that the migration has large impact as well. In this study, only the stochastic projection is considered and we shall consider including expert opinions as the future study.
en_US
dc.description.tableofcontents 第一章 緒 論 8
第一節 研究動機 8
第二節 研究背景 9
第三節 研究目的 10

第二章 資料介紹與研究方法 11
第一節 資料介紹 11
第二節 名詞解釋 12
第三節 生育率、死亡率推估方法 13
第四節 修勻方法及資料插補 15
第五節 人口推估及結果衡量方法 18

第三章 電腦模擬與實證分析 21
第一節 電腦模擬與情境分析 21
第二節 臺灣地區生育率推估 24
第三節 縣市生育率推估 32
第四節 嬰兒出生性別比推估 35
第五節 死亡率推估 38
第六節 人口數推估 40

第四章 結論與建議 44
第一節 結論 44
第二節 後續研究建議 46

參考文獻 48
zh_TW
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0099354007en_US
dc.subject (關鍵詞) 人口推估zh_TW
dc.subject (關鍵詞) 小區域推估zh_TW
dc.subject (關鍵詞) 修勻zh_TW
dc.subject (關鍵詞) 區塊拔靴法zh_TW
dc.subject (關鍵詞) 隨機推估zh_TW
dc.subject (關鍵詞) Population Projectionen_US
dc.subject (關鍵詞) Small Area Population Projectionen_US
dc.subject (關鍵詞) Graduationen_US
dc.subject (關鍵詞) Block Bootstrapen_US
dc.subject (關鍵詞) Stochastic Projectionen_US
dc.title (題名) 小區域生育率與人口推計研究zh_TW
dc.title (題名) Small Population Projections:Modeling and Evaluationen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 中文部分
王信忠、金碩、余清祥 (2012)。小區域死亡率推估之研究。Journal of Population Studies (TSSCI), 45, 121–154.
余清祥 (1997)。修勻:統計在保險的應用。台北市:雙葉書廊。
金碩與余清祥 (2011)。修勻與小區域人口之研究。碩士論文。
徐茂炫、陳建亨、黃彥豪 (2011)。逾百年臺灣縣市人口興衰之轉折:1987-2010。人口學刊,43,109–135。
陳政勳與余清祥 (2010)。小區域人口推估研究:臺北市、雲嘉兩縣、澎湖縣的實證分析。人口學刊,41,153–183。
陳寬政 (1997)。臺灣地區人口出生數量的動態模擬。人口學刊,18,1–18。
黃意萍與余清祥 (2002)。台灣地區生育率推估方法的研究。Journal of Population Studies (TSSCI), 25, 145–171.
郭孟坤與余清祥 (2008)。電腦模擬、隨機方法與人口推估的實證研究。人口學 刊,36,67–98。
英文部分
Booth H. (2006). Demographic forecasting: 1980 to 2005 in review. International Journal of Forecasting, 22(3), 547–581.
Brown R. L. (1991). Introduction to the Mathematics of Demography, ACTEXublications, Inc.
Cannan E. (1985). The probability of a cessation of the growth of population in England and Wales during the next century.The Economic Journal, 5(20), 505–515.
Denton F. T., Feaver C. H., & Spencer B. G. (2005). Time series analysis and stochastic forecasting an econometric study of mortality and life expectancy. Journal of Population Economics, 18(2), 203–227.
Hall P. (1985). Resampling a coverage pattern. Stochastic Processes Applications, 20(2), 231–246.
Koissi M. C., Shaporo A. F., & Högnäs G. (2006). Evaluation and extending the Lee-Cater model for mortality forecasting: Bootstrap confidence interval. Insurance: Mathematics and Economics, 38(1), 1–20.
Künsch H. R. (1989). The Jackknife and the Bootstrap for general stationary observations. Annals of Statistics, 17, 1217–1261.
Lawson C. L., Hanson R. J. (1974). Solving least squares problems. New Jersey: Prentice-Hall, EngleWood Cliffs.
Lee R. D., Carter L. R. (1992). Modeling and forecasting US mortality. Journal of the American Statistical Association, 87(419), 659–671.
Lee R. D. (2000). The Lee-Carter method for forecasting mortality, with variousextensions and applications. North American Actuarial Journal, 4(1), 80–93.
Lee W. (2003). A partial SMR approach to smoothing age-specific rates. Annals of Epidemiology, 13(2), 89–99.
Leslie P. H. (1945). On the use of matrices in certain population dynamics. Biometrika, 33, 183–212.
Leslie P. H. (1948). Some further notes on the use of matrices in population mathematics. Biometrika, 35, 213–245.
Lewis C. D. (1982). Industrial and business forecasting methods : a practical guide to exponential smoothing and curve fitting. London: Butterworth Scientific.
Li N., Lee R., & Tuljapurkar S. (2004). Using the Lee-Carter method to forecast mortality for populations with limited data. International Statistical Review, 72 (1), 19–36.
Myers G. C. (1990). Demography of Aging. Handbook of Aging and the Social Science, Third Edition, 19–44.
Stoto M. A. (1983). The Accuracy of Population Projections. Journal of the American Statistical Association ,78, 13-20.
Whelpton P. K. (1936). An empirical method for calculating future population. Journal of the American Statistical Association, 31, 457–473.
Wilson T., Rees P. (2005). Recent developments in population projection methodology: a review. Population, Space and Place, 19(1), 1–126
zh_TW