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Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/140178
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Title: | 年輪變動比用於小區域人口推估的探討 A Study of Applying Cohort Component Ratio to Small Population Projection |
Authors: | 余清祥 Yue, Jack C. 王信忠;陳譽騰 Wang, Hsin-chung;Chen, Yu-teng |
Contributors: | 統計系 |
Keywords: | 小區域人口推估;年輪變動比;電腦模擬;回測法;遷移 Small area population projection;Cohort change ratio;Simulation;Backcast;Migration |
Date: | 2021-12 |
Issue Date: | 2022-05-30 16:01:58 (UTC+8) |
Abstract: | 人口推估常用於制訂國家發展方針的依據,根據歷史數據及政策 方向預測全國人口數及年齡結構,作為政府研擬政策及分配資源的依 據。年輪組成法為我國官方的人口推估方法,需要詳細生育、死亡、 遷移等資料,很難直接套用至縣市層級及以下之人口推估。小區域推 估可採Hamilton-Perry法(簡稱HP法)的年輪變動比(cohort change ratio, CCR),本文以臺灣各級行政區域為研究區域,驗證HP法是否 能用於推估臺灣縣市、鄉鎮市區層級的人口及結構。本文根據1975- 2019年臺灣全國、縣市、鄉鎮市區的人口紀錄,透過區塊拔靴法與歷 年平均法估計CCR,並運用回測法得出之平均絕對百分比誤差(mean absolute percentage error)作為評估依據。研究發現HP法可用於小區 域人口,15年之內短期推估與年齡組成法相當,但推估誤差未必隨著 人口數減少而增加。另外,推估時建議採用單齡推估(五齡組誤差較 大),基底年數與地區特性有關,推估年數建議不超過15年。 Abstract Population policy is essential to national development and population projection is often used to provide insightful suggestions for planning government policies and allocating public resources. The cohort component method is currently used in projecting the national level population in Taiwan, but this method requires detailed population data, such as the records of births, deaths, and migration. It is difficult to acquire these data in county and township levels and we need to seek an alternative method for the subnational population projection. In this study, we evaluate whether the cohort change ratio (CCR), proposed by Hamilton-Perry method, is suitable for the subnational population projection via backcasting the historical data in Taiwan (1975-2019). In specific, we are interested in comparing the projecting accuracy of CCR and cohort component methods, and we found that the CCR method can be used for short-term projections (e.g., 15 years or less) for county and township levels. Also, our projection errors are smaller by using the single-age data (comparing to 5-age group data), and there are little differences in using block bootstrap or weighted average to predict the future CCR. |
Relation: | 人口學刊, 63期, pp. 99-133 |
Data Type: | article |
DOI 連結: | http://dx.doi.org/10.6191/JPS.202112_(63).0003 |
DOI: | 10.6191/JPS.202112_(63).0003 |
Appears in Collections: | [統計學系] 期刊論文
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