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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-MEI en_US dc.creator (作者) 陳雅玫 zh_TW dc.creator (作者) CHEN, YA-MEI en_US dc.date (日期) 1992 en_US dc.date (日期) 1991 en_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) B2002004643 en_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/#B2002004643 en_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) thesis en_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
