| DC 欄位 |
值 |
語言 |
| DC.contributor | 產業經濟研究所在職專班 | zh_TW |
| DC.creator | 藍鈺婷 | zh_TW |
| DC.creator | Yu-Ting Lan | en_US |
| dc.date.accessioned | 2021-6-11T07:39:07Z | |
| dc.date.available | 2021-6-11T07:39:07Z | |
| dc.date.issued | 2021 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=108454021 | |
| dc.contributor.department | 產業經濟研究所在職專班 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 臺灣在2003年遭遇SARS的流行性傳染威脅，當時人人自危，又2003年4月和平醫院被無預警封院，住在醫院附近的居民深陷恐懼；2020年年初以來，新冠肺炎疫情席捲全球，中央流行疫情指揮中心呼籲民眾避免不必要的探病，若是非急迫性的醫療需求或檢查，應延後處理，減少進醫院的次數來降低被傳染的風險。醫院是否為嫌惡設施，一直以來眾說紛紜，而在新冠肺炎疫情的升溫下，是否更左右民眾在挑選不動產時的抉擇。
本研究透過直線距離模型、距離間距模型及差異中的差異法(DID)模型來探討新冠肺炎發生前後對距離醫院不同距離的房價帶來的影響。在第一組DID模型裡，將距離最近醫院距離限縮在2公里內比較實驗組與控制組時，可以發現實驗組的房價確實會因疫情影響，而較控制組的房價下跌，但若是將範圍放大至4公里時，不論是直線距離模型、距離間距模型或第二組及第三組DID模型，結果皆呈現相反或不具統計顯著性，可能係因目前新冠肺炎疫情尚未停止，購屋者多半會審慎思考病毒傳染的風險性，而減少購買醫院宅。 | zh_TW |
| dc.description.abstract | Taiwan was threatened by the SARS in 2003. Everyone was in danger at the time. In April 2003, Taipei City’s Heping Hospital was closed without warning. Residents living near the hospital were in deep fear. In the beginning of 2020, the COVID-19 began to spread widely. The government appeals to the public to avoid unnecessary hospital visits. Whether a hospital is a Yes-In-My-Back-Yard(YIMBY) or a Not-In-My-Back-Yard(NIMBY) has always been divergent. So, we discuss that people will change their idea of buying a real estate besides the hospital due to the impact of the COVID-19 or not.
This study uses the straight-line distance model, the spacing distance model and the DID models to discuss the impact of the COVID-19 on housing prices at different distances from the hospital before and after the outbreak. In the first group of DID models, when comparing the experimental group with the control group, the distance to the nearest hospital is limited to 2 kilometers. The house price of the experimental group will indeed be lower than the house price of the control group due to the impact of the epidemic. But if the range is enlarged to 4 kilometers, whether it is the straight-line distance model, the spacing distance model or the second and third groups of DID models, the results show the opposite or are not statistically significant. It may be because the COVID-19 has not stopped, and most home buyers will carefully consider the risk of virus infection and reduce the purchase of the house near the hospital. | en_US |
| DC.subject | 新冠肺炎 | zh_TW |
| DC.subject | 醫院 | zh_TW |
| DC.subject | 新竹 | zh_TW |
| DC.subject | 房價 | zh_TW |
| DC.subject | 迎毗設施 | zh_TW |
| DC.subject | 鄰避設施 | zh_TW |
| DC.subject | 差異中的差異 | zh_TW |
| DC.subject | COVID-19 | en_US |
| DC.subject | hospital | en_US |
| DC.subject | Hsinchu | en_US |
| DC.subject | housing prices | en_US |
| DC.subject | YIMBY | en_US |
| DC.subject | NIMBY | en_US |
| DC.subject | difference-in-differences method | en_US |
| DC.title | 新冠肺炎 (COVID 19) 對醫院附近房價的影響－以新竹地區為例 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |