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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/30947


    Title: 臺灣地區服務業就業趨勢之年齡、年代及世代分析
    Authors: 郭雅雅
    Contributors: 江振東
    郭雅雅
    Keywords: 服務業就業趨勢
    年齡－年代－世代模型
    本質估計量
    The trend of employment in service-producing industries
    Age-Period-Cohort model
    Intrinsic Estimator
    Date: 2005
    Issue Date: 2009-09-14
    Abstract: 隨著經濟發展與所得水準提升，臺灣地區就業人口由早期的第一級產業－農林漁牧業逐漸移向第二級產業－工業，再由第二級產業轉移至第三級產業－服務業。為瞭解臺灣地區服務業就業之趨勢，國內多數研究僅就蒐集資料以年齡、年代或世代三方面分別作探討，本文則改採流行病學領域中所廣泛使用之年齡－年代－世代模型（Age-Period-Cohort Model），就行政院主計處「人力資源調查」資料來作分析。但年齡、年代與世代三者間存在共線性問題（即世代＝年代－年齡），導致迴歸模型產生無限多組解，為了自其中選出一組較適當之參數估計值，文獻中提供了許多不同形式的解決方法。本文則採用Fu（2000）所提出之本質估計量（Intrinsic Estimator，簡稱IE），這是一種不受參數限制式影響的估計方式。我們除了藉以取得惟一的參數估計值，進而分析年齡、年代及世代效應對服務業就業比率之影響外，並與傳統之受限廣義線性模型估計量（Constrained Generalized Linear Models Estimator，簡稱CGLIME）作一比較，來說明採用本質估計量之優點及方便之處。
    Along with economical development and higher income level, Taiwan area employed population has gradually been switching from farming, forestry, fishing and animal husbandry to goods-producing industries, and then onto services-producing industries. In order to understand the trend of employment in service-producing industries in Taiwan, most domestic studies focus on the aspects of age, period or cohort separately. We, instead, adopt the Age-Period-Cohort (APC) model, which is well recognized in the epidemiology, to analyze the data from “Manpower Surveys” conducted by the Directorate-General of Budget, Accounting and Statistics, Executive Yuan, R.O.C. in this study.
    However, due to the collinearity among the age, period, and cohort effects, the APC model suffers from the identifiability problem. Some possible solutions have been provided in the literature. Among them, the Constrained Generalized Linear Models Estimator (CGIME) is undoubtedly the most popular choice, while the Intrinsic Estimator (IE) (Fu (2000)), which is invariant to the constraint selected to obtain the parameter estimates, is less well-known. We compare the results obtained from IE with that of CGIME in this study, and discuss the advantages of using the Intrinsic Estimator.
    Reference: 1.行政院主計處（2005）。中民國台灣地區國民經濟動向統計季報，108，7。
    2.行政院主計處（2004）。中華民國臺灣地區人力資源調查統計年報，48–51。
    3.李文宗（1994）。年齡─年代─世代分析方法新探，國立台灣大學公共衛生研究所博士論文。
    4.Decarli, A., and La Vecchia, C.（1987）,“Age, Period and Cohort Models: A Review of Knowledge and Implementation in GLIM”, Rivista Statistica Applicata 20: 397–410.
    5.Fienberg,S.E., and Mason,W.M.（1978）,“Identification and Estimation of Age-Period-Cohort Models in the Analysis of Discrete Archival Data”, Sociological Methodology 8: 1–67.
    6.Frost,W.H. (1939),“The Age Selection of Mortality from Tuberculosis in Successive Decades”, Amreican Joural of Hygiene 30: 92–96.
    7.Fu,W.J.（2000）,“Ridge Estimator in Singular Design with Application to Age-Period-Cohort Analysis of Disease Rates”, Communications in Statistics–Theory and Method 29: 263–278.
    8.Kupper,L.L., Janis,J.M., Salama,I.A., Yoshizawa,C.N., and Greenberg,B.G.（1983）,“Age-Period-Cohort Analysis: An Illustration of the Problems in Assessing Interaction in One Observation Per Cell Data”, Communications in Statistics–Theory and Method 12: 2779–2807.
    9.Osmond,C., and Gardner,M.J.（1982）,“Age, Period and Cohort Models Applied to Cancer Mortality”, Statistics in Medicine 1: 245–259.
    10.Robertson, C., and Boyle, P. （1986）,“ Age, Period and Cohort Models: The Use of Individual Records”, Statistics in Medicine 5: 527–538.
    11.Yang,Y., Fu,W.J., and Land,K.C.(2004),“A Methodological Comparison of Age-Period-Cohort Models: The Intrinsic Estimator and Conventional Generalized Linear Models”, Sociological Methodology 34: 75–110.
    Description: 碩士
    國立政治大學
    統計研究所
    92354015
    94
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0923540151
    Data Type: thesis
    Appears in Collections:[Department of Statistics] Theses

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