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    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/59289
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/59289


    Title: 結合專家意見與隨機方法:台灣生育率推估
    Combining Expert Opinion with Stochastic Forecast: A Study of Taiwan Fertility Projection
    Authors: 李政豫
    Contributors: 余清祥
    蔡紋琦

    李政豫
    Keywords: 人口推估
    隨機推估
    專家意見
    電腦模擬
    修正式德菲法
    貝氏分析
    Date: 2012
    Issue Date: 2013-09-02 15:36:55 (UTC+8)
    Abstract: 政府制訂與規劃政策,需要未來人口數或人口結構的資訊,以期能針對國家需求對症下藥;預測未來人口總數及人口結構通稱為人口推估(Population Projection),台灣的官方人口推估由行政院經濟建設委員會負責。人口推估通常使用人口變動要素合成法(The Cohort Component Method),根據現有人口總數及結構,加上對未來生育(Fertility)、死亡(Death)、遷移(Migration)三要素的預期,推估出未來的人口數及其結構;除了參考歷史資料外,目前三要素大多參考專家意見(Expert opinion)決定變動範圍。
    在三要素之中,生育和遷移由於變動趨勢較大,較不容易以歷史資料找出趨勢,過去大多倚賴專家意見進行生育和遷移的假設。但專家意見也有蒐集上的疑慮,例如意見沒有固定的形成格式,推估結果也難以機率角度詮釋發生可能性,亦即推估數值大多不隨時間波動。為了彌補專家意見的不足,近年不少國家的人口推估使用隨機方法(Stochastic Methods),大致可分為三種:隨機推估法(Stochastic Forecast)、模擬情境法(Random Scenario Method)和推估誤差法(ex post Method),這三種方法可組合使用,例如Lutz (1995)合併隨機推估和模擬情境,而郭孟坤與余清祥(2008)則是以隨機推估和推估誤差的組合來進行推估,使隨機方法更具有彈性,適用於不同情境的人口推估。
    本文目的在於結合專家意見與隨機方法,希冀綜合兩者的優點,提出適用於台灣的人口推估方法。首先,本文提出將專家方法數量化的幾種作法,配合德菲法蒐集專家意見,先以電腦模擬找出較佳的數量化方法;接著再參考由歷史資料及隨機方法(區塊拔靴法)得出的推估結果,分別以主觀角度、貝氏分析(Bayesian Analysis)和貝氏可信度(Bayesian Credibility)的角度進行加權平均,結合專家意見及隨機方法的推估。
    Reference: 中文書目
    李永山、黃錦川、許譽勝,2008. 《以修正式德菲法探討台灣資訊軟體公司競爭策略之研究》,資訊電子學刊。第三卷,第一期,頁39-50。
    何正羽,2006. 《高齡人口Gompertz死亡率推估模型的建構與應用》,東吳大學商用數學系碩士論文。
    余純君,2000.《願付價值及其前測的研究》,國立政治大學統計研究所論文。
    余清祥與藍銘偉,2003.《台灣地區生育率模型之研究》,人口學刊第 27期,頁105-131。
    余清祥與郭孟坤,2008.《電腦模擬、隨機方法與人口推估的實證研究》,人口學刊第36期,頁67-98。
    余清祥、蔡紋琦、李芯柔、郭孟坤、王泰期,2008. 《隨機模型與電腦模擬的人口研究》行政院經濟建設委員會委託國立政治大學統計系研究。
    周雅容,1997.《焦點團體法在調查研究上的應用》,中央研究院調查研究。
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    莊慶達、趙聚誠,(2000). 《經濟名詞釋典》,台北:華泰文化。
    林金定、嚴嘉楓、陳美花,2006. 《質性研究方法:訪談模式與實施步驟分析》,中華啟能基金會身心障礙研究,卷3:2,頁122-136。
    潘淑滿,2003.《質性研究:理論與應用》,心理出版社,頁114。

    英文書目
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    Gordon, T. J. und Helmer, O. (1964). “Report on a Long-Range Forecasting Study,” Rand Corporation, Santa Monica/ California.
    Green, B., Jones, M., Hughes, D., and Williams, A. (1999). “Applying the Delphi technique in a study of GP`s information requirements,” Health and Social Care in the Community 7, pp.198-205.
    Hall, P. (1985). “Resampling a Coverage Pattern”, Stochastic Processes Applications, vol. 20, pp.231-246.
    Hanemann, W.M. (1984). “Welfare evaluations in contingent valuation experiments with discrete responses, ”American Journal of Agricultural Economics, Vol. 66, No. 3, pp.332-341.
    —(1987). “Welfare evaluations in contingent valuation experiments with discrete response data reply, ”American Journal of Agricultural Economics, Vol. 69, No. 1, pp. 185-186.
    Hsu, C. (2007). “The Delphi Technique: Making Sense of Consensus,” Practical Assessment, Research & Evaluation, vol.12, No. 10. pp. 1-8.
    Jones, H. and Twiss, B. C. (1978). “Forecasting technology for planning decision,” London, UK: Macmillan Press Ltd.
    Keilman, N., Pham, D.Q., and Hetland, A. (2002), “Why Population Forecasts should be Probabilistic - Illustrated by the Case of Norway”, Demographic Research, Vol. 6, pp.410-454.
    Künsch, H.R. (1989). “The Jackknife and the Bootstrap for General Stationary Observations,” The Annuals of Statistics, vol. 17, pp.1217-1261.
    Lee, R.D. and Tuljapurkar, S.(1994), “Stochastic Population Forecasts for the United States: Beyond High, Medium and Low,” Journal of the American Statistical Association, vol. 89, pp.1175-1189.
    Lu, M. and Yue, C. J. (1996), “The Advantage of Second Guesser in a Two-person, zero-sum Game,”政大學報 (TSSCI), vol. 73, 439-450.
    Lutz, W., Sanderson, W., and Scherbov, S. (1996). “Probabilistic population projections based on expert opinion,” Earthscan, London, UK, pp. 397-428.
    —(1998). “Expert-Based Probabilistic Population Projections.” Population and Development Review, Vol. 24, pp.139-155.
    Lutz, W., and Scherbov, S. (1997). “Sensitivity Analysis of Expert-Based Probabilistic Population Projections in the Case of Austria,” IIASA Interim Report IR-97-048.
    —(1998a). “An expert-based framework for probabilistic national population projections: The example of Austria,” European Journal of Population, vol. 14, pp.1-17.
    —(1998b). “Probabilistische Bevölkerungsprognosen für Deutschland,” Zeitschrift für Bevölkerungswissenschaft, vol. 23, pp.83-109.
    —(2001). “The end of world population,” growth.Nature, 412, pp.543-545.
    —(2003). “The End of Population Growth in Asia,” Journal of Population Research, pp.125-141.
    McKenna, H.P. (1994). “The Delphi technique: a worthwhile research approach for nursing?” J Adv Nurs. vol. 19, pp.1221-5.
    Mead, D.M. (1992). “Innovations in nursing care. The development of primary nursing in Wales Unpublished report.” Department of Health, London.
    Morgan, D. L. (1988). “Focus Groups as Qualitative Research. Newbury Park,” SAGE Publications.
    Mowbray, A.H. (1914). “How Extensive a Payroll Exposure Is Necessary to give a Dependable Pure Premium?” Proceedings of the Casually Actuarial Society, I, pp.24-30
    Murry, J. W. and Hammons, J. O. (1995). “Delphi: a versatile methodology for conducting qualitative research.” Review of Higher Education Vol. 18, pp.423-36
    Norman, C. D. (1969). “The Delphi Method:An Experimental Study of Group Opinion.” Futures, Vol. 1, pp.408–426
    Payne, J. W. (1976). “Task complexity and contingent processing in decision making: An information search and protocol analysis,” Organizational Behavior and Human Performance, vol. 16, pp.366-387.
    Stoto, M. A. (1983). “The Accuracy of Population Projections,” Journal of the American Statistical Association, vol. 78, pp.13-20.
    Stuart A. K., Harry H. P. and Gordon E. W. (2012).“LOSS MODELS:From Data to Decisions.” WILEY.
    William R. B. (1997). “Comparing and Assessing Time Series Methods for Forecasting Age-Specific Fertility and Mortality Rates,” Journal of Official Statistics, Vol.13, pp.279-303.
    Description: 碩士
    國立政治大學
    統計研究所
    100354021
    101
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0100354021
    Data Type: thesis
    Appears in Collections:[統計學系] 學位論文

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