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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/101315完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 張宏浩 | zh_TW |
| dc.contributor.advisor | Hung-Hao Chang | en |
| dc.contributor.author | 曾彥儒 | zh_TW |
| dc.contributor.author | Yan-Ru Tseng | en |
| dc.date.accessioned | 2026-01-14T16:12:30Z | - |
| dc.date.available | 2026-01-15 | - |
| dc.date.copyright | 2026-01-14 | - |
| dc.date.issued | 2025 | - |
| dc.date.submitted | 2026-01-06 | - |
| dc.identifier.citation | 林左裕(2020)。少子化及高房價下的住宅政策。消費者報導雜誌,(472),62-67。
林昱翔、江穎慧(2025)。租屋負擔有多重?以臺中市為例檢視租屋協助政策效果。物業管理學報,16(1),1-12。 林進益、林元興(2018)。不動產市場在資訊時代的革新。土地問題研究季刊,17(2),8-18。 馬毓駿(2024)。臺灣房價是否已經泡沫化?經濟前瞻,(214),45-50。 劉佩真(2020)。武漢疫情對台灣不動產業的影響。臺灣經濟研究月刊,43(3),38-39。 鄧鎮銘、謝明媛(2020)。新冠肺炎難纏 房市第一季呈現萎縮-疫情延燒不止 危機入市有機會嗎?禪天下,(180),6-12。 賴碧瑩(2020)。新冠肺炎對臺灣及澳洲房地產市場影響之研究。土地問題研究季刊19(4),33- 41。 Ali, W. (2020). Online and Remote Learning in Higher Education Institutes: A Necessity in light of COVID-19 Pandemic. Higher Education Studies, 10(3), 16. https://doi.org/10.5539/hes.v10n3p16 Boesel, M., Chen, S., & Nothaft, F. E. (2021). Housing preferences during the pandemic: effect on home price, rent, and inflation measurement. Business Economics, 56(4), 200–211. https://doi.org/10.1057/s11369-021-00241-4 Braesemann, F., Kluge, J., & Lorenz, H. (2025). How have urban housing preferences developed in response to the COVID-19 pandemic? A case study of Vienna. PLoS ONE, 20(5), e0322629. https://doi.org/10.1371/journal.pone.0322629 Case, K. E., & Shiller, R. J. (2003). Is there a bubble in the housing market? Brookings Papers on Economic Activity, 2003(2), 299–362. https://doi.org/10.1353/eca.2004.0004 Diewert, W. E., & Shimizu, C. (2016). Hedonic regression models for Tokyo condominium sales. Regional Science and Urban Economics, 60, 300–315. https://doi.org/10.1016/j.regsciurbeco.2016.08.002 Gallant, J., Kroft, K., Lange, F., & Notowidigdo, M. (2020). Temporary unemployment and labor market dynamics during the COVID-19 recession. National Bureau of Economic Research. https://doi.org/10.3386/w27924 Gupta, A., Mittal, V., & Van Nieuwerburgh, S. (2022). Work from home and the office real estate apocalypse. National Bureau of Economic Research. https://doi.org/10.3386/w30526 Hargreaves, B. (2008). What do rents tell us about house prices? International Journal of Housing Markets and Analysis, 1(1), 7–18. https://doi.org/10.1108/17538270810861120 Helbich, M., Brunauer, W., Vaz, E., & Nijkamp, P. (2013). Spatial heterogeneity in hedonic house price models: the case of Austria. Urban Studies, 51(2), 390–411. https://doi.org/10.1177/0042098013492234 Koenker, R., & Bassett, G. (1978). Regression quantiles. Econometrica, 46(1), 33. https://doi.org/10.2307/1913643 Leamer, E. (2007). Housing IS the business cycle. National Bureau of Economic Research. https://doi.org/10.3386/w13428 Lo, D., Yau, Y., McCord, M., & Haran, M. (2022). Lead-Lag Relationship between the Price-to-Rent Ratio and the Macroeconomy: An Empirical Study of the Residential Market of Hong Kong. Buildings, 12(9), 1345. https://doi.org/10.3390/buildings12091345 Muhyi, M. M., & Adianto, J. (2021). Literature Review: The Effects of COVID-19 Pandemic-Driven Home Behavior in Housing Preference. Smart City, 1(1). https://doi.org/10.56940/sc.v1.i1.2 Ramani, A., & Bloom, N. (2021). The donut effect of COVID-19 on cities. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3850758 Rosen, S. (1974). Hedonic prices and implicit markets: product differentiation in pure competition. Journal of Political Economy, 82(1), 34–55. https://doi.org/10.1086/260169 Sirmans, S., Macpherson, D., & Zietz, E. (2005a). The composition of hedonic pricing models. Journal of Real Estate Literature, 13(1), 1–44. https://doi.org/10.1080/10835547.2005.12090154 Sirmans, S., Macpherson, D., & Zietz, E. (2005b). The composition of hedonic pricing models. Journal of Real Estate Literature, 13(1), 1–44. https://doi.org/10.1080/10835547.2005.12090154 Tanrıvermiş, H. (2020). Possible impacts of COVID-19 outbreak on real estate sector and possible changes to adopt: A situation analysis and general assessment on Turkish perspective. Journal of Urban Management, 9(3), 263–269. https://doi.org/10.1016/j.jum.2020.08.005 Wang, Z., & Tang, K. (2020). Combating COVID-19: health equity matters. Nature Medicine, 26(4), 458. https://doi.org/10.1038/s41591-020-0823-6 Wing, C. K., & Chin, T. (2003). A critical review of literature on the Hedonic price model. International Journal for Housing Science and Its Applications. 27. 145-165. https://www.researchgate.net/publication/255726402_A_Critical_Review_of_Literature_on_the_Hedonic_Price_Model | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/101315 | - |
| dc.description.abstract | COVID-19 疫情的爆發不僅是一場公共衛生危機,更深刻地改變了人們的工作與生活模式。隨著居家辦公與遠距學習的普及,「家」的功能從單純的居住空間,轉變為同時承載工作、學習與休閒等多重功能的綜合場域。此一轉變促使租客對居住空間的需求產生根本性改變,也重新塑造了住宅市場的運作邏輯。
本研究以 COVID-19 疫情作為外生衝擊,運用民國 106 年至 113 年台灣實價登錄的租賃資料,透過特徵價格模型、市場需求模型與分量迴歸模型,系統性地檢視疫情對台灣租賃市場價格與交易量的影響。研究將樣本期間劃分為疫情前(109 年 2 月前)、疫情期間(109 年 2 月至 112 年 5 月)與疫情後(112 年 5 月後)三個階段,並深入探討不同住宅類型(套房、公寓、華廈、住宅大樓、透天厝)與用途(住家、商業)在疫情衝擊下的異質性反應。 實證結果顯示,疫情帶來的經濟不確定性與預算緊縮壓力,迫使租客在有限預算下重新權衡空間配置的優先順序。市場價值觀念發生了結構性的轉變,從單純追求大坪數,轉向更重視空間的功能性、獨立性與使用效率。疫情期間,租賃面積與房數的隱含價值顯著下降,反映出租客為控制總租金支出而做出的妥協;然而疫情後,房數價值大幅反彈提升 5.53%,交易量增長 15.78%,呈現價量齊揚的趨勢,證實多房格局產品已成為後疫情時代的核心需求。 不同住宅類型間的影響也呈現顯著的差異。公寓與華廈因親民的總租金、低公設比與高實用坪數,在後疫情時代下較具優勢,房數與廳數的價量皆顯著上揚。相較之下,套房因其單一的混合型空間結構,難以滿足生活與工作功能分區的需求,陷入價量齊跌的困境。商業用途物件則因居家辦公趨勢的普及,需求大幅萎縮。分量迴歸的結果進一步顯示,疫情對不同價位市場的影響具有異質性,高價位市場對多房格局的溢價效應更為強烈,反映出具高消費能力租客對私密性與功能性空間的強烈需求。 本研究證實,疫情作為重大外部衝擊,加速了租賃市場偏好由疫情前對大坪數、大物件的偏好,轉為疫情期間對公共空間的重視,並在疫情後轉向有良好空間區隔的配置。這些發現不僅為理解疫情對住宅需求的長期影響提供實證依據,也為租賃市場政策制定者與房地產業者提供有價值的參考。 | zh_TW |
| dc.description.abstract | The COVID-19 outbreak was not merely a public health crisis but profoundly transformed people's work and lifestyle patterns. With the widespread adoption of remote work and distance learning, the role of "home" has evolved from a simple living space into a multifunctional space that simultaneously accommodates work, study, and leisure activities. This transformation fundamentally altered tenants' housing needs and reshaped the operational logic of the residential market.
This study treats the COVID-19 pandemic as an exogenous shock. It employs Taiwan's Actual Price Registration rental data from 2017 to 2024, utilizing hedonic price models, market demand models, and quantile regression models to systematically examine the pandemic's impact on rental market prices and transaction volumes. The study divides the sample period into three phases: pre-pandemic (before February 2020), during pandemic (February 2020 to May 2023), and post-pandemic (after May 2023), and investigates the heterogeneous responses of different housing types (studio apartments, walk-ups, mid-rise apartments, high-rise residential buildings, and townhouses) and uses (residential and commercial) under pandemic shocks. Empirical results reveal that economic uncertainty and budget constraints brought by the pandemic forced tenants to reconsider spatial allocation priorities under limited budgets. Market value perceptions underwent a fundamental transformation, shifting from simply pursuing larger floor areas to emphasizing functionality, independence, and spatial efficiency. During the pandemic, the implicit values of rental area and number of rooms declined significantly, reflecting tenants' compromises to control total rent expenditure. However, post-pandemic, room value rebounded substantially by 5.53%, with transaction volumes increasing 15.78%, demonstrating price-volume co-movement and confirming that multi-room properties have become core demand in the post-pandemic era. Different housing types exhibited significantly differentiated responses. Walk-ups and mid-rise apartments demonstrated strong market resilience in the post-pandemic period due to their affordable total rent, low public facility ratios, and high usable floor area advantages, with both price and volume of rooms and living rooms rising significantly. In contrast, studio apartments, with their singular mixed-space structure unable to meet the needs for functional zoning between living and working, fell into a price-volume decline trap. Commercial properties experienced substantial demand contraction due to the prevalence of remote work trends. Quantile regression results further revealed heterogeneous pandemic impacts across different price segments, with high-price markets showing stronger premium effects for multi-room layouts, reflecting strong demand from high-income tenants for privacy and functional spaces. This study demonstrates that the COVID-19 pandemic, as a major exogenous shock, accelerated a shift in rental-market preferences: from a pre‑pandemic emphasis on larger floor areas and larger units, to a pandemic-period focus on public and shared spaces, and, in the post‑pandemic phase, toward configurations featuring robust internal spatial partitioning and functional zoning. These findings provide empirical evidence on the long-run effects of the pandemic on housing demand and offer valuable guidance for rental‑market policymakers and real estate practitioners. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2026-01-14T16:12:30Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2026-01-14T16:12:30Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 謝辭 I
摘要 II ABSTRACT III 目次 V 圖次 VII 表次 VIII 第一章 緒論 1 第一節 研究背景與動機 1 第二節 研究目的 3 第三節 研究流程 3 第二章 文獻回顧 5 第一節 疫情對住宅市場影響之國外相關研究 5 第二節 疫情對住宅市場影響之國內相關研究 7 第三節 租金與房價的動態關係 8 第四節 小結 9 第三章 資料介紹及敘述統計 11 第一節 實價登錄資料介紹 11 第二節 資料處理過程 12 第三節 變數定義和選取 13 第四節 敘述統計 14 第四章 實證模型與方法 25 第一節 特徵價格模型 25 第二節 市場需求模型 27 第三節 分量迴歸模型 29 第五章 實證結果與討論 31 第一節 疫情對租賃市場價格與交易量影響 31 第二節 分量迴歸模型估計結果 53 第六章 結論 57 第一節 結論與建議 57 第二節 研究限制與未來研究方向 58 參考文獻 60 | - |
| dc.language.iso | zh_TW | - |
| dc.subject | COVID-19 | - |
| dc.subject | 租賃市場 | - |
| dc.subject | 特徵價格模型 | - |
| dc.subject | 分量迴歸 | - |
| dc.subject | 居家辦公 | - |
| dc.subject | COVID-19 | - |
| dc.subject | rental market | - |
| dc.subject | hedonic price model | - |
| dc.subject | quantile regression | - |
| dc.subject | remote work | - |
| dc.title | 疫情對台灣租賃市場的重構:全台實價登錄資料之實證研究 | zh_TW |
| dc.title | Taiwan Rental Market Reconstruction During Covid-19: An Empirical Study Based on Taiwan Actual Price Registration Data | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 114-1 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.coadvisor | 巫凱琳 | zh_TW |
| dc.contributor.coadvisor | Karin Wu | en |
| dc.contributor.oralexamcommittee | 林子欽;廖培安 | zh_TW |
| dc.contributor.oralexamcommittee | Tzu-Chin Lin;Pei-An Liao | en |
| dc.subject.keyword | COVID-19,租賃市場特徵價格模型分量迴歸居家辦公 | zh_TW |
| dc.subject.keyword | COVID-19,rental markethedonic price modelquantile regressionremote work | en |
| dc.relation.page | 63 | - |
| dc.identifier.doi | 10.6342/NTU202504864 | - |
| dc.rights.note | 同意授權(限校園內公開) | - |
| dc.date.accepted | 2026-01-06 | - |
| dc.contributor.author-college | 生物資源暨農學院 | - |
| dc.contributor.author-dept | 農業經濟學系 | - |
| dc.date.embargo-lift | 2026-01-15 | - |
| 顯示於系所單位: | 農業經濟學系 | |
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