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1	要素投入量不確定與競爭性廠商要素需求之研究黃碧雪, HUANG, BI-XIE Unknown Date (has links) 第一章導論─說明研究動機，及概括性介紹本論文主要內容。本文對「生產不確定」就二個層面分析，一為要素投入量不確定二為產量坏確定。前者第二章予以探討，後者第三章予以探討。第二章分析要素投入量不確定的情況─藉由RATTI 和ULLAH （１９７７）的模型並且加以擴充下，探討廠商對風險的態度（愛好、逃避、中立三種類型）和何影響其要素的要求。其次研究在生產不確定下，要素投入價格、產品價格改變和不同的稅收方式，對廠商要素需求的影響，在分析過程，我們和確定情況下廠商對要素需求，做個比較分析。第三章分析產量不確定的情況─本章將利用第一章的分析，研究產量不確定，以BATR A 產量不確定的模型，加入要素使用率的變數，研究廠商對要素的需求，其探討過程與第二章相同。第四章結論─對本論文做連貫性的說明和摘要，並且比較產量不確定與要素投入量不確定的異同，及和其他文獻的結果估比較說明。生產不確定性要素需求要素投入量 RATTI ULLAH BATRA
2	Comparison of the 1st and 2nd order Lee–Carter methods with the robust Hyndman–Ullah method for fitting and forecasting mortality rates Willersjö Nyfelt, Emil January 2020 (has links) The 1st and 2nd order Lee–Carter methods were compared with the Hyndman–Ullah method in regards to goodness of fit and forecasting ability of mortality rates. Swedish population data was used from the Human Mortality Database. The robust estimation property of the Hyndman–Ullah method was also tested with inclusion of the Spanish flu and a hypothetical scenario of the COVID-19 pandemic. After having presented the three methods and making several comparisons between the methods, it is concluded that the Hyndman–Ullah method is overall superior among the three methods with the implementation of the chosen dataset. Its robust estimation of mortality shocks could also be confirmed. Mortality rate Death rate Data fitting Lee-Carter 2nd order Lee–Carter Hyndman–Ullah Modeling ARIMA Random walk Singular Value Decomposition Penalized Regression Splines Forecasting Spanish flu COVID-19 Mathematics Matematik

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要素投入量不確定與競爭性廠商要素需求之研究

Comparison of the 1st and 2nd order Lee–Carter methods with the robust Hyndman–Ullah method for fitting and forecasting mortality rates