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題名 台灣地區失業率的時空數列分析
作者 陳雅玫
CHEN, YA-MEI
貢獻者 吳柏林
陳雅玫
CHEN, YA-MEI
關鍵詞 區域經濟
失業率
時空數列
預測模式
日期 1992
1991
上傳時間 2-May-2016 15:17:07 (UTC+8)
摘要 三十多年來，台灣經濟快速成長，由開發中國家擠身新興工業國家之列，但是經濟區域卻未能兼顧整體之均衡發展。而產業轉型時期的人力供需及失業率問題，一直為社會學者所關切。另一方面亦產生了都市化的問題，造成南北大都會區(台北市、高雄市)的人口密度激增，且勞動力亦往此少數地區移轉。
     時空數列模型描述地區本身及地區與地區之間的時空動態關係。基在區域經濟及環境科學上應用極為廣泛。本文即以失業率代表勞動市場供需變數的指標，考慮台北市、高雄市與台灣省的地緣關係，應用時空數列的方法，分析台灣地區勞動市場的變動情況，最後並預測未來幾期失業率的變動趨勢。
參考文獻 (1)中文部分
     吳忠林，〝台灣的勞動市場與經濟發展〞，台灣經濟研究論叢：第一輯
     經濟發展與政策，中華經濟研究院，民國80年7月，頁82-112
     林忠正，〝揭開我國失業問題的面紗〞，財經風雲，敦理出版社，民國75年9月，頁232-237
     SAS/ETS-套裝程式集中文手冊，松崗電腦圖書資料有限公司
     
     (2) 英文部分
     Akaike,H.(1976), Cononical correlations analysis of time series and the use of information criterian`, in Mehra R. and Lainiotis, D.G.( eds.), Advances and Case Studies in System Identification, New York: Academic Press
     Bennett.Robert J(1979),Spatial time series: analysis forecasting and control. Pion London
     Bennett,Roben J.(1984),`Advances in the analysis of spatial time series`, Sratistics and Models, 235-251
     Bohara,A.K.and Sauer,C(1992),Competing Macro-hypotheses in the United States : a Kalman Filtering approach.Applied Economics ,24,389-399
     Bronars, Stephen G. and Dennis W. Jansen(1987),`The geograghic distribution of unemployment rates in the U.S.`, Journal of Econimetrics,36,251-279
     Cliff, A.D. and J.K. Ord (1981), Spatial processes: models and applications, Pion London
     Deutsch, Stuart Jay and Phillip E. Pfeifer(1980), `Identification and interpretation of first-order space-time ARMA models`, Technometrics,22, 397-408
     Flahault. A.et.al. (1988), ` Modelling the 1985 influenza epidemic in France`, Statistic in Medicine,7, 1147-1155
     Funke, Michael (1992) "Time series forecasting of Gennan unemployment rate `, J. of forecasting,11, 111- 125
     Hamada, koichi and yoshio kurosaka (1986),` Trend in unemployment. Wages and productivity: the case of Japan`, Economica,53, S275-S296
     Harrison`p.J.and Stevens,C.F(1976),` Bayesian Forecasting`, 1 Roy. Stat. Soc, 8,38, 205-247
     Harvey, A.C. and Todd, P.H.J. (1983), I Forecasting economic time series with structural and Box-Jenkins models: A case study with comments`, 1. Of business and economics stat,1, 299-315
     Jones ,R.H. (1984) , Fitting mutivariate models to unequal spaced data, In Parzen, 158-188
     Kalman. R.E.(1960), `A new approach to linear filtering and prediction problems `,Trans. ASME J. Basic Engineering, 82, 34-45
     Kitagawa,G. and Gresch (1984),`A Smoothness Priors-Modeling of Tune Series with Trend and Seasonity`, 1 AMER.StatAssoc,79, 278-289
     Mann, H.B. and Wald, A.(1943) ,`On the statistical treatment of linear stochastic difference equations`, Econometrika,11, 173-270
     Pfeifer .Phillips E. and Samuel R Bodily( 1990),`A test of space-time ARMA modeling and forecastingof hotel data`, Journal of Forecasting ,9, 255-272
     Pfeifer. phillip E. and Stuart Jay Deutsch(l980),`A three-stage iterative procedure for space-time modelling " Technometrics ,22, 35-47
     Shumway, R.H. (1985),`Time series in the soil science is there life after kriging?
     Soil Spatial Variability`, ed .J. Bouma and D. R. Nielson, 35-60, Pudoc Wageningen, the Netherlands
     Stoffer, Davis S.(1986),` Estimation and identification of space-time ARMAX models in the presence of missing data`, J. of the American Statistical Association ,81, 762-772
     Vandaele,Walter (1985), Applied time series and Box-Jenkins models, Academic press, New York
     Wei, Willian W.S.(1990), Time series analysis: univariate and multivariate methods, Addison-Wesley, New York
描述 碩士
國立政治大學
統計學系
資料來源 http://thesis.lib.nccu.edu.tw/record/#B2002004643
資料類型 thesis
dc.contributor.advisor 吳柏林zh_TW
dc.contributor.author (Authors) 陳雅玫zh_TW
dc.contributor.author (Authors) CHEN, YA-MEIen_US
dc.creator (作者) 陳雅玫zh_TW
dc.creator (作者) CHEN, YA-MEIen_US
dc.date (日期) 1992en_US
dc.date (日期) 1991en_US
dc.date.accessioned 2-May-2016 15:17:07 (UTC+8)-
dc.date.available 2-May-2016 15:17:07 (UTC+8)-
dc.date.issued (上傳時間) 2-May-2016 15:17:07 (UTC+8)-
dc.identifier (Other Identifiers) B2002004643en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/89232-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計學系zh_TW
dc.description.abstract (摘要) 三十多年來，台灣經濟快速成長，由開發中國家擠身新興工業國家之列，但是經濟區域卻未能兼顧整體之均衡發展。而產業轉型時期的人力供需及失業率問題，一直為社會學者所關切。另一方面亦產生了都市化的問題，造成南北大都會區(台北市、高雄市)的人口密度激增，且勞動力亦往此少數地區移轉。
     時空數列模型描述地區本身及地區與地區之間的時空動態關係。基在區域經濟及環境科學上應用極為廣泛。本文即以失業率代表勞動市場供需變數的指標，考慮台北市、高雄市與台灣省的地緣關係，應用時空數列的方法，分析台灣地區勞動市場的變動情況，最後並預測未來幾期失業率的變動趨勢。		zh_TW
dc.description.tableofcontents 壹、 前言--------------------1
     貳、 時空數列理論與應用--------------------4
     2.1 時空數列模式的定義--------------------4
     2.2 三階段循環過程--------------------10
     2.2.1 穩定性與可逆性--------------------10
     2.2.2 模式認定--------------------10
     2.2.3 參數估計--------------------13
     2.2.4 模式診斷--------------------16
     參、 實證資料分析--------------------18
     肆、 模式的建立與預測--------------------21
     4.1 模式的建立--------------------21
     4.2 三種模式預測值的比較--------------------26
     伍、 結論--------------------26
     參考書目--------------------33
     附圖、表--------------------36		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#B2002004643en_US
dc.subject (關鍵詞) 區域經濟zh_TW
dc.subject (關鍵詞) 失業率zh_TW
dc.subject (關鍵詞) 時空數列zh_TW
dc.subject (關鍵詞) 預測模式zh_TW
dc.title (題名) 台灣地區失業率的時空數列分析zh_TW
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) (1)中文部分
     吳忠林，〝台灣的勞動市場與經濟發展〞，台灣經濟研究論叢：第一輯
     經濟發展與政策，中華經濟研究院，民國80年7月，頁82-112
     林忠正，〝揭開我國失業問題的面紗〞，財經風雲，敦理出版社，民國75年9月，頁232-237
     SAS/ETS-套裝程式集中文手冊，松崗電腦圖書資料有限公司
     
     (2) 英文部分
     Akaike,H.(1976), Cononical correlations analysis of time series and the use of information criterian`, in Mehra R. and Lainiotis, D.G.( eds.), Advances and Case Studies in System Identification, New York: Academic Press
     Bennett.Robert J(1979),Spatial time series: analysis forecasting and control. Pion London
     Bennett,Roben J.(1984),`Advances in the analysis of spatial time series`, Sratistics and Models, 235-251
     Bohara,A.K.and Sauer,C(1992),Competing Macro-hypotheses in the United States : a Kalman Filtering approach.Applied Economics ,24,389-399
     Bronars, Stephen G. and Dennis W. Jansen(1987),`The geograghic distribution of unemployment rates in the U.S.`, Journal of Econimetrics,36,251-279
     Cliff, A.D. and J.K. Ord (1981), Spatial processes: models and applications, Pion London
     Deutsch, Stuart Jay and Phillip E. Pfeifer(1980), `Identification and interpretation of first-order space-time ARMA models`, Technometrics,22, 397-408
     Flahault. A.et.al. (1988), ` Modelling the 1985 influenza epidemic in France`, Statistic in Medicine,7, 1147-1155
     Funke, Michael (1992) "Time series forecasting of Gennan unemployment rate `, J. of forecasting,11, 111- 125
     Hamada, koichi and yoshio kurosaka (1986),` Trend in unemployment. Wages and productivity: the case of Japan`, Economica,53, S275-S296
     Harrison`p.J.and Stevens,C.F(1976),` Bayesian Forecasting`, 1 Roy. Stat. Soc, 8,38, 205-247
     Harvey, A.C. and Todd, P.H.J. (1983), I Forecasting economic time series with structural and Box-Jenkins models: A case study with comments`, 1. Of business and economics stat,1, 299-315
     Jones ,R.H. (1984) , Fitting mutivariate models to unequal spaced data, In Parzen, 158-188
     Kalman. R.E.(1960), `A new approach to linear filtering and prediction problems `,Trans. ASME J. Basic Engineering, 82, 34-45
     Kitagawa,G. and Gresch (1984),`A Smoothness Priors-Modeling of Tune Series with Trend and Seasonity`, 1 AMER.StatAssoc,79, 278-289
     Mann, H.B. and Wald, A.(1943) ,`On the statistical treatment of linear stochastic difference equations`, Econometrika,11, 173-270
     Pfeifer .Phillips E. and Samuel R Bodily( 1990),`A test of space-time ARMA modeling and forecastingof hotel data`, Journal of Forecasting ,9, 255-272
     Pfeifer. phillip E. and Stuart Jay Deutsch(l980),`A three-stage iterative procedure for space-time modelling " Technometrics ,22, 35-47
     Shumway, R.H. (1985),`Time series in the soil science is there life after kriging?
     Soil Spatial Variability`, ed .J. Bouma and D. R. Nielson, 35-60, Pudoc Wageningen, the Netherlands
     Stoffer, Davis S.(1986),` Estimation and identification of space-time ARMAX models in the presence of missing data`, J. of the American Statistical Association ,81, 762-772
     Vandaele,Walter (1985), Applied time series and Box-Jenkins models, Academic press, New York
     Wei, Willian W.S.(1990), Time series analysis: univariate and multivariate methods, Addison-Wesley, New York		zh_TW