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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 林建甫 | |
| dc.contributor.author | PO-CHUN CHEN | en |
| dc.contributor.author | 陳柏鈞 | zh_TW |
| dc.date.accessioned | 2021-06-17T07:37:34Z | - |
| dc.date.available | 2024-04-11 | |
| dc.date.copyright | 2019-04-11 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-03-24 | |
| dc.identifier.citation | 中文文獻
中央銀行 (2017)。金融穩定報告。第11期。 中央銀行 (2018)。金融穩定報告。第12期。 中央存款保險公司 (2011)。「2008年全球金融危機紀要」IV-全球金融監理改革與存保制度之發展趨勢。存款保險叢書之127，178-181。 沈中華 (2002)。金控公司的銀行與獨立銀行CAMEL比較：1997~1998。台灣金融財務季刊，第三輯第二期。 沈中華、王建安、林昆立 (2014)。房價偏離值與銀行績效關係的研究：跨國的實證分析。證券市場發展季刊，26卷4期，1-37。 英文文獻 Berger, Allen N. and Humphrey, David B. (1992). “Measurement and Efficiency Issues in Commercial Banking,” NBER Chapters,in: Output Measurement in the Service Sectors, pages 245-300. National Bureau of Economic Research, Inc. Bernanke, Ben S. and Gertler, Mark (1999). “Monetary policy and asset price volatility,” Economic Review, Federal Reserve Bank of Kansas City, issue Q IV, pages 17-51. Claessens, Stijn and Bongini, Paola and Ferri, Giovanni (2001). “The Political Economy of Distress in East Asian Financial Institutions,” Journal of Financial Services Research, vol. 19(1), pages 5-25. Collyns, C. and Senhadji, A. (2002). “Lending Booms, Real Estate Bubbles, and the Asian Crisis,” IMF Working Papers 02/20, International Monetary Fund. Davis, E. Philip and Zhu, Haibin (2004). “Bank lending and commercial property cycles: some cross-country evidence,” BIS Working Papers 150, Bank for International Settlements. Gilbert, R. Alton and Meyer, Andrew P. and Vaughan, Mark D. (2002). “Could a CAMELS downgrade model improve off-site surveillance?,' Review, Federal Reserve Bank of St. Louis, issue Jan., pages 47-63. He, Ling T. and Myer, F.C. Neil and Webb, James R. (1996). “The Sensitivity of Bank Stock Returns to Real Estate,” Journal of Real Estate Finance and Economics, Vol.12,pp203-220. Herring, Richard J. and Wachter, Susan M. (1999). “Real Estate Booms and Banking Busts: An International Perspective,” The Wharton School Research Paper 99-27. Loutskina, Elena and Strahan, Philip E. (2015). “Financial integration, housing, and economic volatility,” Journal of Financial Economics, Elsevier, vol. 115(1), pages 25-41. Makinen, Mikko and Solanko, Laura (2017). “Determinants of bank closures : Do changes of CAMEL variables matter?,” BOFIT Discussion Papers 16/2017, Bank of Finland, Institute for Economies in Transition. Thomson, James B. (1991). “Predicting bank failures in the 1980s,” Federal Reserve Bank of Cleveland, Economic Review, vol. 27, no. 1, pp. 9-20. West, Robert Craig (1985). “A factor-analytic approach to bank condition,” Journal of Banking and Finance, Elsevier, vol. 9(2), pages 253-266. Whalen, Gary (1991). “A Proportional Hazards Model of Bank Failure: An Examination of Its Usefulness as an Early Warning Tool,” Federal Reserve Bank of Cleveland, Economic Review, vol. 27, no. 1, pp. 21-31. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73484 | - |
| dc.description.abstract | 本研究探討房價變動對銀行CAMELS評等系統之影響，資料來源來自TEJ台灣經濟新報。銀行選取台灣不動產放款佔比較高之27家銀行，資料時間自2007年至2017年。被解釋變數為銀行CAMELS指標評分，解釋變數為房價指數，控制變數包括實質GDP成長率、通貨膨脹率、房貸利率、失業率、人口數、貨幣供給、銀行資產規模。
實證結果發現，房價變動對資本適足性、資產品質、獲利能力、流動性、市場風險敏感性具顯著正相關；對管理能力具顯著負相關。房價變動對CAMELS評分具顯著正相關，實質GDP成長率對CAMELS指標呈正相關，但統計上並不顯著。通貨膨脹率對CAMELS指標具顯著負相關，房貸利率對CAMELS指標具顯著負相關，失業率對CAMELS指標具顯著負相關，人口成長率對CAMELS指標具顯著正相關，貨幣供給成長率對CAMELS指標具顯著負相關，銀行資產規模對CAMELS指標具顯著正相關。 | zh_TW |
| dc.description.abstract | This study explores the impact of house price changes on CAMELS rating system of the Taiwan banking industry, with the sample data drawn from the Taiwan Economic Journal (TEJ) database. The 27 banks selected for this study each has mortgage loans account for higher proportion of its total loan, and the sample period is from 2007 through 2017. Response variable is the CAMELS rating, explanatory variable is the house price index, and control variable include GDP growth rate, inflation, mortgage rate, unemployment rate, population, money supply, and total bank assets.
Our empirical results indicate that there is a significant positive correlation between house price and capital adequacy, asset quality, earnings, liquidity, sensitivity to market risk; a significant negative correlation between house price and management. House price significantly correlates positively with CAMELS rating; GDP growth rate is positively correlated with CAMELS rating, but not statistically significant. There is a significant negative correlation between inflation and CAMELS rating, between mortgage rate and CAMELS rating, between unemployment rate and CAMELS rating, and between growth rate of money supply and CAMELS rating. There is a significant positive correlation between population growth rate and CAMELS rating, and between total bank assets and CAMELS rating. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T07:37:34Z (GMT). No. of bitstreams: 1 ntu-108-P05323023-1.pdf: 801249 bytes, checksum: 24b5e4d76ca2c27d7c4ee9c06cc82b3d (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 口試委員會審定書 #
誌謝 i 中文摘要 ii ABSTRACT iii 目錄 iv 圖目錄 vi 表目錄 vii 第一章 緒論 1 1.1 研究背景與動機 1 1.2 研究目的 2 1.3 研究架構 3 第二章 CAMELS評等系統簡介及現況 4 2.1 CAMELS評等系統簡介 4 2.2 CAMELS評估指標 5 2.2.1 資本適足性(C) 5 2.2.2 資產品質(A) 6 2.2.3 管理能力(M) 7 2.2.4 獲利能力(E) 8 2.2.5 流動性(L) 9 2.2.6 市場風險敏感性(S) 10 2.3 CAMELS評等現況 10 第三章 文獻探討 17 3.1 CAMELS指標相關文獻探討 17 3.2 房地產價格與銀行相關文獻探討 18 第四章 研究方法與模型建立 19 4.1 研究範圍與資料來源 19 4.2 研究方法 20 4.3 Panel data單根檢定 20 4.3.1 LLC追蹤資料單根檢定 (Levin, Lin and Chu, 2002) 20 4.4 Panel data 迴歸模型 21 4.4.1 最小平方法(Ordinary Least Squares method，OLS) 21 4.4.2 固定效果模型(Fixed effect model) 22 4.4.3 隨機效果模型(Random effect model) 22 4.5 Panel data模型選擇 23 4.5.1 最小平方法與固定效果模型之選擇 23 4.5.2 最小平方法與隨機效果模型之選擇 24 4.5.3 固定效果模型與隨機效果模型之選擇 24 4.6 實證模型 25 4.6.1 探討房價指數對CAMELS評分之影響 25 4.6.2 探討房價指數對CAMELS各面向之影響 26 4.7 本文實證研究架構 27 第五章 實證結果分析 28 5.1 Panel單根檢定結果 28 5.2 共線性檢定 29 5.3 敘述統計量分析 31 5.4 模型適用檢定 32 5.5 實證結果分析 33 5.5.1 房價變動對CAMELS各面向之影響 33 5.5.2 各解釋變數對銀行CAMELS指標之影響 36 第六章 結論 40 6.1 研究結論 40 6.2 研究建議 41 參考文獻 42 | |
| dc.language.iso | zh-TW | |
| dc.subject | 資本適足性 | zh_TW |
| dc.subject | CAMELS評等系統 | zh_TW |
| dc.subject | 房價指數 | zh_TW |
| dc.subject | GDP成長率 | zh_TW |
| dc.subject | 通貨膨脹率 | zh_TW |
| dc.subject | 房貸利率 | zh_TW |
| dc.subject | 失業率 | zh_TW |
| dc.subject | 人口數 | zh_TW |
| dc.subject | 貨幣供給 | zh_TW |
| dc.subject | 銀行資產規模 | zh_TW |
| dc.subject | 資產品質 | zh_TW |
| dc.subject | 管理能力 | zh_TW |
| dc.subject | 獲利能力 | zh_TW |
| dc.subject | 流動性 | zh_TW |
| dc.subject | 市場風險敏感性 | zh_TW |
| dc.subject | house price index | en |
| dc.subject | liquidity | en |
| dc.subject | earnings | en |
| dc.subject | management | en |
| dc.subject | asset quality | en |
| dc.subject | capital adequacy | en |
| dc.subject | total bank assets | en |
| dc.subject | money supply | en |
| dc.subject | population | en |
| dc.subject | unemployment rate | en |
| dc.subject | GDP growth rate | en |
| dc.subject | sensitivity to market risk | en |
| dc.subject | CAMELS rating system | en |
| dc.subject | mortgage rate | en |
| dc.subject | inflation | en |
| dc.title | 房價變動對CAMELS評等系統之影響：以台灣銀行業為例 | zh_TW |
| dc.title | The Influence of House Price Changes on CAMELS Rating System : Evidences from Taiwan’s Banking Industry | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 107-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 翁永和,姚睿,張焯然 | |
| dc.subject.keyword | CAMELS評等系統,房價指數,GDP成長率,通貨膨脹率,房貸利率,失業率,人口數,貨幣供給,銀行資產規模,資本適足性,資產品質,管理能力,獲利能力,流動性,市場風險敏感性, | zh_TW |
| dc.subject.keyword | CAMELS rating system,house price index,GDP growth rate,inflation,mortgage rate,unemployment rate,population,money supply,total bank assets,capital adequacy,asset quality,management,earnings,liquidity,sensitivity to market risk, | en |
| dc.relation.page | 43 | |
| dc.identifier.doi | 10.6342/NTU201900671 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2019-03-25 | |
| dc.contributor.author-college | 社會科學院 | zh_TW |
| dc.contributor.author-dept | 經濟學研究所 | zh_TW |
| 顯示於系所單位： | 經濟學系 | |
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