DC 欄位 |
值 |
語言 |
DC.contributor | 產業經濟研究所 | zh_TW |
DC.creator | 陳芋君 | zh_TW |
DC.creator | Yu-Jyun Chen | en_US |
dc.date.accessioned | 2019-7-11T07:39:07Z | |
dc.date.available | 2019-7-11T07:39:07Z | |
dc.date.issued | 2019 | |
dc.identifier.uri | http://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=106424008 | |
dc.contributor.department | 產業經濟研究所 | zh_TW |
DC.description | 國立中央大學 | zh_TW |
DC.description | National Central University | en_US |
dc.description.abstract | 本篇論文主要探討一個地區的空氣污染與該地區相關解釋變數的關係,例如所得、年齡人口、交通等,而經濟成長與環境污染之關係也是民眾所關注的議題,故也進行EKC假說之驗證。本研究自行將被解釋變數細懸浮微粒區分為三種型態,並將年齡人口主要分為三組,分別為六歲以下的幼年人口、十五歲以下的青幼年人口及六十五歲以上的老年人口,並蒐集其他解釋變數進行實證分析。
首先使用最小平方法進行迴歸分析,但因為本研究所採用的資料為兼具時間序列資料及橫斷面資料,若採用最小平方法會有偏誤的情形,故較適合追蹤資料迴歸分析,而想瞭解三種細懸浮微粒的被解釋變數與解釋變數之間的關係沒有很大的差異,而實證結果得知與過去文獻不同,本研究並不符合EKC假設,故所得與細懸浮微粒之間呈現U形關係;解釋變數人口年齡結構的分組,六歲以下的幼年人口並沒有統計顯著的意義,十五歲以下的青幼年人口及六十五歲以上的老年人口對細懸浮微粒濃度都有顯著的影響效果;本研究的解釋變數工廠數量並沒有統計意義,可能是每年的工廠數量變化較不大所造成的結果;本研究衡量交通變數的加油站數量,其對細懸浮微粒濃度也有顯著的影響。
| zh_TW |
dc.description.abstract | This study mainly discusses about the factors how effect on air pollution, like age structure、income、traffic and so on. The relationship between economic growth and environmental quality has been drawn considerable attention for the last three decades, so this study also validates the EKC hypothesis. My contributions is to further disaggregate PM2.5 into three types and further disaggregate population into three particularly key age groups: 0-6, 0-15, and over 65, and by doing so demonstrate that population’s environmental impact differs considerably across age groups.
First, the Ordinary least squares method is used, but the data of study has both time series data and cross-sectional data, the estimate results of OLS is biased. This study model using a seventy – seven stations panel data set in Taiwan over the period 2012–2017. Findings indicate that income U-shaped relationship with PM2.5, so this study does not support the environmental Kuznets curve hypothesis. The variables of 0-15 and the number of gas stations has a positive relationship with the PM2.5, the variables of population over 65 years old has a negative relationship with the PM2.5.
| en_US |
DC.subject | 空氣汙染 | zh_TW |
DC.subject | 細懸浮微粒 | zh_TW |
DC.subject | 人口結構 | zh_TW |
DC.subject | 追蹤資料 | zh_TW |
DC.subject | 所得 | zh_TW |
DC.subject | air pollution | en_US |
DC.subject | PM2.5 | en_US |
DC.subject | population structure | en_US |
DC.subject | panel data | en_US |
DC.subject | income | en_US |
DC.title | 人口結構及所得對空氣汙染的探討 | zh_TW |
dc.language.iso | zh-TW | zh-TW |
DC.title | Analysis of air pollution on age structure and income | en_US |
DC.type | 博碩士論文 | zh_TW |
DC.type | thesis | en_US |
DC.publisher | National Central University | en_US |