住宅可負擔性為都市研究與空間規劃領域中備受關注的重要議題，其中房價所得比（Price-to-Income Ratio, PIR）為衡量住宅可負擔性的常用指標之一，其核心概念在於衡量住宅價格相對家戶所得之購屋門檻。然而，臺灣現行統計多以縣市尺度呈現，較難辨識都市內部不同鄰里、所得條件及住宅產品所形成之負擔差異。基於此，本研究以臺南市為實證範圍，建構2014年至2023年間之鄰里尺度PIR，分析住宅負擔之長期趨勢、空間分布、跨期變動、所得基準差異，以及不同發展節點與住宅產品之負擔特徵。
本研究整合內政部實價登錄、臺南市家庭收支調查及村里綜合所得稅統計資料，以鄰里住宅成交總價中位數作為住宅價格基礎，並分別以全市可支配所得中位數及鄰里推估可支配所得，建構全市所得基準房價所得比（PIR_C）與鄰里所得基準房價所得比（PIR_L）。分析方法包括PIR級距與跨期變動分析、PIR_C與PIR_L比較、Global Moran’s I與LISA空間自相關分析、長期穩定樣本檢驗，以及主要發展節點距離分帶與屋齡10年內新成屋之產品分層分析。
研究結果顯示，臺南市住宅負擔於2014年至2023年間持續提高，本研究樣本計算之PIR由約6.44上升至10.28；2019年至2023年間ΔPIR達4以上之鄰里比例亦高於2014年至2019年間，顯示後一階段高幅度增加之鄰里範圍較為廣泛。高負擔鄰里由早期原臺南市核心區及其周邊，逐步延伸至永康、安南、善化、新市及歸仁等新興發展地區。空間自相關分析顯示，2014年與2023年PIR_C均呈現顯著正向空間自相關；惟234里長期穩定樣本之前後期群聚程度大致相近，且2019年至2023年ΔPIR未呈現顯著之全域空間自相關，表示高負擔區位之分布有所改變，但負擔增加幅度未形成全市一致之空間群聚。
PIR_C與PIR_L之比較顯示，住宅負擔差異不僅來自住宅價格，也與在地所得條件有關；前者反映一般臺南市家戶進入不同鄰里住宅市場之門檻，後者則呈現當地住宅價格與在地所得之相對關係。主要發展節點之距離分帶結果未呈現一致之距離遞減型態，顯示南科、高鐵特定區、臺鐵主要車站及交流道周邊之住宅負擔，會隨節點機能、生活圈範圍、既有都市結構及住宅產品組成而有所差異。新成屋PIR則普遍高於整體住宅市場，但其交易比重、負擔水準及跨期變動在不同發展節點間亦呈現不同特徵。
綜合而言，臺南市住宅負擔具有明顯之空間異質性、所得基準差異及住宅產品分層特徵。鄰里尺度分析可補充縣市平均指標較難呈現之都市內部差異，並作為細尺度住宅負擔監測、重大建設周邊住宅市場追蹤，以及社會住宅與可負擔住宅布局之參考。

Housing affordability is an important issue in urban studies and spatial planning, yet city-level statistics may conceal substantial differences within urban areas. This study constructs neighborhood-level price-to-income ratio (PIR) indicators for Tainan City from 2014 to 2023 to examine temporal changes, spatial patterns, income-benchmark differences, development-node characteristics, and housing product segmentation. Real estate transaction data, the Tainan Family Income and Expenditure Survey, and village-level income tax statistics are integrated to develop a citywide-income-based PIR (PIR_C) and a neighborhood-income-based PIR (PIR_L). The analysis applies intertemporal comparison, Global Moran’s I, LISA, a long-term stable sample assessment, distance-band analysis, and a separate analysis of housing aged ten years or less. The sample-based PIR_C increased from approximately 6.44 in 2014 to 10.28 in 2023, while high-burden neighborhoods extended from the traditional urban core toward emerging development areas. PIR_C showed significant positive spatial autocorrelation in both 2014 and 2023; however, clustering remained broadly similar in the 234-neighborhood stable sample, and PIR changes during 2019–2023 showed no significant global spatial autocorrelation. Major development nodes showed no uniform distance-decay pattern, and newly built housing generally had higher PIR values than the overall market. The findings demonstrate the value of neighborhood-scale monitoring for housing and spatial planning.

1. Acevedo-Garcia, D., McArdle, N., Hardy, E., Dillman, K.-N., Reece, J., Crisan, U., Norris, D., & Osypuk, T. (2016). Neighborhood Opportunity and Location Affordability for Low-Income Renter Families. Housing Policy Debate, 26, 607-645. https://doi.org/10.1080/10511482.2016.1198410
2. Althobaiti, S., Alghumayjan, S., Frank, M. R., Moro, E., Alabdulkareem, A., & Pentland, A. (2021). Housing Prices and the Skills Composition of Neighborhoods [Original Research]. Frontiers in Big Data, 4. https://doi.org/10.3389/fdata.2021.652153
3. Angel, S. (2000). Housing Policy Matters: A Global Analysis. https://doi.org/10.1093/oso/9780195137156.001.0001
4. Bayer, P., & McMillan, R. (2011). Tiebout Sorting and Neighborhood Stratification. National Bureau of Economic Research Working Paper Series, No. 17364. https://doi.org/10.3386/w17364
5. Bereitschaft, B. (2019). Neighborhood Walkability and Housing Affordability among U.S. Urban Areas. Urban Science, 3(1), 11. https://www.mdpi.com/2413-8851/3/1/11
6. Bourassa, S. C. (1996). Measuring the Affordability of Home-ownership. Urban Studies, 33(10), 1867-1877. http://www.jstor.org/stable/43083238
7. Bourassa, S. C., Hoesli, M., & Peng, V. S. (2003). Do housing submarkets really matter? Journal of Housing Economics, 12(1), 12-28. https://doi.org/10.1016/S1051-1377(03)00003-2
8. Cox, W. (2025). Demographia International Housing Affordability 2025 Edition. https://www.demographia.com/dhi.pdf
9. Downs, A. (2004). Growth Management and Affordable Housing: Do They Conflict? Rowman & Littlefield Publishers. https://books.google.com.tw/books?id=ypeGhWchdIAC
10. Engel, E. (1857). Die Productions- und Consumtionsverhältnisse des Königreichs Sachsen. Zeitschrift des Statistischen Bureaus des Königlich Sächsischen Ministeriums des Innern, 8, 1-54.
11. Fotheringham, A. S., & Wong, D. W. S. (1991). The Modifiable Areal Unit Problem in Multivariate Statistical Analysis. Environment and Planning A, 23(7), 1025-1044. https://EconPapers.repec.org/RePEc:sae:envira:v:23:y:1991:i:7:p:1025-1044
12. Gan, Q., & Hill, R. J. (2009). Measuring housing affordability: Looking beyond the median. Journal of Housing Economics, 18(2), 115-125. https://doi.org/10.1016/j.jhe.2009.04.003
13. Glaeser, E. L., & Gyourko, J. E. (2003). The Impact of Building Restrictions on Housing Affordability. Economic Policy Review, 9(2). https://ssrn.com/abstract=790487
14. Goodman, A. C., & Thibodeau, T. G. (1998). Housing Market Segmentation. Journal of Housing Economics, 7(2), 121-143. https://doi.org/10.1006/jhec.1998.0229
15. Hamidi, S., & Ewing, R. (2015). Is Sprawl Affordable for Americans?:Exploring the Association Between Housing and Transportation Affordability and Urban Sprawl. Transportation Research Record, 2500(1), 75-79. https://doi.org/10.3141/2500-09
16. Hulchanski, J. D. (1995). The concept of housing affordability: Six contemporary uses of the housing expenditure‐to‐income ratio. Housing Studies, 10(4), 471-491. https://doi.org/10.1080/02673039508720833
17. International Monetary Fund. (2023). Global Financial Stability Report. https://www.imf.org/en/Publications/GFSR
18. Miao. (2017). Housing the knowledge economy in China: An examination of housing provision in support of science parks. Urban Studies, 54(6), 1426-1445. https://doi.org/10.1177/0042098015627106
19. NAR. (2026). Housing Affordability Index. https://www.nar.realtor/research-and-statistics/housing-statistics/housing-affordability-index
20. OECD. (2021). Building for Inclusive Communities: OECD Housing Affordability Indicators and Monitoring. https://www.oecd.org/housing/data/affordable-housing-database/
21. Openshaw, S. (1983). The Modifiable Areal Unit Problem. Geo Books. https://books.google.com.tw/books?id=OJbgswEACAAJ
22. Quigley, J. M., & Raphael, S. (2004). Is Housing Unaffordable? Why Isn't It More Affordable? Journal of Economic Perspectives, 18(1), 191–214. https://doi.org/10.1257/089533004773563494
23. 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
24. Singer, M. E. (2021). How affordable are accessible locations? Neighborhood affordability in U.S. urban areas with intra-urban rail service. Cities, 116, 103295. https://doi.org/10.1016/j.cities.2021.103295
25. Stephen Ezennia, I., & Hoskara, S. O. (2019). Methodological weaknesses in the measurement approaches and concept of housing affordability used in housing research: A qualitative study. PLoS One, 14(8), e0221246. https://doi.org/10.1371/journal.pone.0221246
26. Stone, M. E. (2006). What is housing affordability? The case for the residual income approach. Housing Policy Debate, 17(1), 151-184. https://doi.org/10.1080/10511482.2006.9521564
27. Sweeney, J. L. (1974). A commodity hierarchy model of the rental housing market. Journal of Urban Economics, 1(3), 288-323. https://doi.org/10.1016/0094-1190(74)90010-2
28. Tiebout, C. M. (1956). A Pure Theory of Local Expenditures. Journal of Political Economy, 64(5), 416-424. http://www.jstor.org/stable/1826343
29. United Nations. (2015). Transforming Our World: The 2030 Agenda for Sustainable Development. https://sdgs.un.org/2030agenda
30. Vaidya, H., & Chatterji, T. (2020). SDG 11 Sustainable Cities and Communities: SDG 11 and the New Urban Agenda: Global Sustainability Frameworks for Local Action. In (pp. 173-185). https://doi.org/10.1007/978-981-32-9927-6_12
31. Watkins, C. A. (2001). The Definition and Identification of Housing Submarkets. Environment and Planning A: Economy and Space, 33(12), 2235-2253. https://doi.org/10.1068/a34162
32. Weicher, J. C. (1977). The Affordability of New Homes. Real Estate Economics, 5(2), 209-226. https://doi.org/10.1111/1540-6229.00827
33. Weicher, J. C., & Thibodeau, T. G. (1988). Filtering and housing markets: An empirical analysis. Journal of Urban Economics, 23(1), 21-40. https://doi.org/10.1016/0094-1190(88)90003-4
34. World Bank. (1993). Enabling housing markets to work. In: The World Bank Washington, DC.
35. Wu, X. B., & Sui, D. Z. (2001). An Initial Exploration of a Lacunarity-Based Segregation Measure. Environment and Planning B: Planning and Design, 28(3), 433-446.
36. 內政部營建署. (2010). 房價負擔能力計算方式與國際各國比較案總結報告. https://pip.moi.gov.tw/
37. 王悌伍. (2017). 台北市住房可負擔性–剩餘所得法分析 [碩士論文, 國立臺灣大學]. 臺北市. https://hdl.handle.net/11296/x4d952
38. 李春長, 梁志民, & 林豐文. (2017). 捷運系統對鄰近住宅價格之影響：以差異中之差異法估計. 台灣土地研究, 20(2), 31-58. https://doi.org/10.6677/JTLR.2017.20.02.031-058
39. 柯秀環. (2024). 新成屋與中古屋價格關聯之研究-以臺北市與新北市為例 [碩士論文, 國立臺灣大學]. https://doi.org/10.6342%2fNTU202400042
40. 胡志平. (2015). 住宅負擔能力之分量迴歸分析-以新竹市公寓大廈住戶為例 [Quantile Regression Analysis for the Local Level Housing Affordability-An Example of Households Living in Condominium in HsinChu City]. 建築與規劃學報, 16(2&3), 163-181.
41. 胡勝正. (2015). 從房價所得比看臺灣的社會不公 [Housing Affordability and Social Injustice]. 臺灣經濟預測與政策, 45(2), 23-43.
42. 翁惠雯. (2010). 推估家戶購置住宅之負擔風險率-以高雄市與台北市之實證比較 [碩士論文, 國立成功大學]. http://140.116.207.99/handle/987654321/261941
43. 張金鶚, 高國峰, & 林秋瑾. (2001). 台北市合理房價：需求面分析. 住宅學報, 10(1). https://www.housing.org.tw/journal-articles/thesis-312
44. 張金鶚, 陳明吉, 鄧筱蓉, & 楊智元. (2009). 台北市房價泡沫知多少？—房價vs.租金、房價vs.所得. 住宅學報, 18(2), 1-22. https://doi.org/10.6375/JHS.200912.0001
45. 張金鶚, 楊宗憲, & 洪御仁. (2008). 中古屋及預售屋房價指數之建立、評估與整合：台北市之實證分析. 住宅學報, 17(2), 13-34.
46. 郭人頡. (2023). 住宅負擔能力的空間差異性與影響因素探討—以台灣六都為例 [碩士論文, 國立臺灣師範大學]. AiritiLibrary.
47. 陳建良, 李巧琳, & 張清和. (2022). 臺灣家戶住宅支出負擔的長期檢視 [Housing Affordability of Taiwan's Households: A Long-term Perspective]. 住宅學報, 31(1), 31-62.
48. 陳彥仲, & 呂昭宏. (2013). 房價所得比與購屋能力之研究. 都市與計劃, 40(2), 143-169. https://tci.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi?o=dnclresource&s=id=%22A13021142%22.&searchmode=basic&tcihsspage=tcisearch_opt1_search
49. 曾平毅. (1994). 都會區擁屋力之初探 [Primary Exploration of Housing Affordability in Metropolitan Area]. 都市與計劃, 21(2), 173-190.
50. 黃玉旻. (2013). 從可負擔觀點探討台灣住宅政策演變之研究－1950年～2012年 [Master's thesis, 國立成功大學]. 臺南市. https://hdl.handle.net/11296/fa84s5
51. 賴碧瑩, & 鍾國樑. (2010). 重大公共建設對地區經濟發展影響之研究－房價特徵模型之驗證 [The Local Economic Effects of Major Infrastructure Project: A Case Study of Hedonic Housing Price Model]. 政策與人力管理, 1(2), 111-139. https://doi.org/10.29944/ppm.201012.0004
52. 薛立敏. (1996). 臺灣地區的住宅負擔能力與合理房價. 經濟前瞻(47), 118-121. https://doi.org/10.30071/eob.199609.0023
53. 謝博明. (2024). 台積電擴大設廠是否帶動周圍地區房價上漲？以台南科學園區為例. 住宅學報, 33(1), 1-31.