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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳業寧(Yehning Chen) | |
| dc.contributor.author | Cheng-Shuo Chang | en |
| dc.contributor.author | 張辰碩 | zh_TW |
| dc.date.accessioned | 2021-05-11T05:00:50Z | - |
| dc.date.available | 2019-07-15 | |
| dc.date.available | 2021-05-11T05:00:50Z | - |
| dc.date.copyright | 2019-07-15 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-07-09 | |
| dc.identifier.citation | [1]Bank for International Settlements (2019, June 30). BIS to set up Innovation Hub for central banks. Retrieved from https://www.bis.org/press/p190630a.htm
[2]Cleveland, W. S. (1979). Robust locally weighted regression and smoothing scatterplots. Journal of the American Statistical Association, 74(368), 829-836. doi:10.1080/01621459.1979.10481038 [3]Demir, İ., Kılıç, S., & Ünal, H. (2010). Effects of students’ and schools’ characteristics on mathematics achievement: Findings from PISA 2006. Procedia Social and Behavioral Sciences, 2(2), 3099-3103. doi:10.1016/j.sbspro.2010.03.472 [4]Heidi, K.. (2010). What PISA tells us about the quality and inequality of Japanese education in mathematics and science. International Journal of Science and Mathematics Education, 8(3), 389-408. doi:10.1007/s10763-010-9196-5 [5]Huber, P. J. (1967). The behavior of maximum likelihood estimates under nonstandard conditions. In L. M. Le Cam & J. Neyman (Eds.), Proceedings of the fifth Berkeley symposium on mathematical statistics and probability (Vol.1, pp.221-233). Berkeley, CA: University of California Press. [6]Ito, J., Narula, N., & Ali, R. (2017, March 9). The blockchain will do to the financial system what the Internet did to media. Harvard Business Review. Retrieved from https://hbr.org/2017/03/the-blockchain-will-do-to-banks-and-law-firms-what-the-internet-did-to-media [7]Kohler, U., Karlson, K. B., Holm, A. (2011). Comparing coefficients of nested nonlinear probability models. The Stata Journal, 11(3), 420-438. [8]Libra Association (2019). Partner with Libra. Retrieved from https://libra.org/en-US/partners/ [9]Lin, E., & Shi, Q. (2014). Exploring individual and school-related factors and environmental literacy: Comparing U.S. and Canada using PISA 2006. International Journal of Science and Mathematics Education, 12(1), 73-97. doi:10.1007/s10763-012-9396-2 [10]Little, R. J. A., & Rubin, D. B. (2002). Statistical analysis with missing data (2nd ed.). Hoboken, New Jersey: John Wiley & Sons. doi:10.1002/9781119013563 [11]Organisation for Economic Co-operation and Development (2002). PISA 2000 technical report. Paris: Author. [12]Organisation for Economic Co-operation and Development (2017). PISA 2015 technical report. Paris: Author. [13]Organisation for Economic Co-operation and Development (2017). Students' financial literacy (PISA 2015 Results, Vol. 4). Paris: Author. [14]Perry, L., & Mcconney, A. (2010). Does the SES of the school matter? An examination of socioeconomic status and student achievement using PISA 2003. Teachers College Record, 112(4), 1137-1162. [15]Riitsalu, L., & Poder K. (2016). A glimpse of the complexity of factors that influence financial literacy. International Journal of Consumer Studies, 40(6), 722-731. doi:10.1111/ijcs.12291 [16]Schuhen, M., & Schürkmann, S. (2016). Construct validity with structural equation modelling. In C. Aprea, E. Wuttke, K. Breuer, N. K. Koh, P. Davies, B. Greimel-Fuhrmann, & J. S. Lopus (Eds.), International handbook of financial literacy (pp. 383-396). Singapore: Springer. doi:10.1007/978-981-10-0360-8_26 [17]Societe Generale (2019, April 23). Societe Generale issued the first covered bond as a security token on a public blockchain. Retrieved from https://www.societegenerale.com/en/newsroom/first-covered-bond-as-a-security-token-on-a-public-blockchain [18]Taiwan PISA National Center (2015). About PISA. Retrieved from http://pisa.nutn.edu.tw/pisa_en.htm [19]The Global Innovation Index (2018). GII framework. Retrieved from https://www.globalinnovationindex.org/about-gii#framework [20]White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838. doi:10.2307/1912934 [21]White, H. (1982). Maximum likelihood estimation of misspecified models. Econometrica, 50(1), 1-25. doi:10.2307/1912526 [22]Wößmann, L. (2008). How equal are educational opportunities? Family background and student achievement in Europe and the United States. Zeitschrift für Betriebswirtschaft, 78(1), 45–70. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/handle/123456789/770 | - |
| dc.description.abstract | 本文針對2015年經濟合作暨發展組織(Organisation for Economic Co-operation and Development， OECD) 主辦的學生能力國際評量計劃(the Programme for International Student Assessment，PISA)，進行金融素養評量分析，探討父母經濟社會文化地位對於子女金融素養的影響。本文主要發現，父母經濟社會文化地位對於子女PISA金融素養有顯著的正向影響，且此正向影響的大小會因國家而有所不同；平均每人GDP、GDP成長率或全球創新指數(the Global Innovation Index，GII)愈高，則此正向影響愈大；吉尼指數(GINI index)愈大，則此正向影響越小。 | zh_TW |
| dc.description.abstract | Using the data of financial literacy in PISA (the Programme for International Student Assessment, PISA) coordinated by OECD (Organisation for Economic Co-operation and Development, OECD) in 2015, this thesis analyzes the impact of parents’ economic, social, and cultural status on children’s financial literacy performance. It finds that parents’ economic, social, and cultural status has a positive effect on children’s financial literacy performance, and this positive effect varies in different countries. The positive effect is stronger if a country’s GDP per capita, GDP growth rate, or Global Innovation Index (GII) is higher, and is weaker if a country’s GINI index is higher. | en |
| dc.description.provenance | Made available in DSpace on 2021-05-11T05:00:50Z (GMT). No. of bitstreams: 1 ntu-108-R99723019-1.pdf: 1561420 bytes, checksum: 07a382a690e2a00edd801e5ed9739643 (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 第壹章 緒論
第一節 研究動機 1 第二節 研究問題 1 第三節 研究架構 2 第貳章 文獻整理 第一節 PISA介紹 3 第二節 文獻整理 5 第參章 研究方法 第一節 研究假說 6 第二節 資料來源 7 第三節 實證模型 8 第肆章 實證結果與分析 第一節 主要實證結果 14 第二節 進一步分析 24 第伍章 結論 30 參考文獻 32 | |
| dc.language.iso | zh-TW | |
| dc.subject | 經濟合作暨發展組織 | zh_TW |
| dc.subject | PISA金融素養評量 | zh_TW |
| dc.subject | 經濟社會文化地位指數 | zh_TW |
| dc.subject | GDP | zh_TW |
| dc.subject | 全球創新指數 | zh_TW |
| dc.subject | 吉尼指數 | zh_TW |
| dc.subject | PISA index of economic | en |
| dc.subject | OECD | en |
| dc.subject | GINI index | en |
| dc.subject | Global Innovation Index | en |
| dc.subject | PISA financial literacy | en |
| dc.subject | GDP | en |
| dc.subject | social and cultural status | en |
| dc.title | 父母經濟社會文化地位對子女金融素養之影響 | zh_TW |
| dc.title | The Impact of Parents’ Economic, Social, and Cultural Status on Children’s Financial Literacy | en |
| dc.date.schoolyear | 107-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 胡星陽(Shing-Yang Hu),陳彥行(Yan-Shing Chen) | |
| dc.subject.keyword | 經濟合作暨發展組織,PISA金融素養評量,經濟社會文化地位指數,GDP,全球創新指數,吉尼指數, | zh_TW |
| dc.subject.keyword | OECD,PISA financial literacy,PISA index of economic, social and cultural status,GDP,Global Innovation Index,GINI index, | en |
| dc.relation.page | 34 | |
| dc.identifier.doi | 10.6342/NTU201901331 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2019-07-10 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 財務金融學研究所 | zh_TW |
| 顯示於系所單位： | 財務金融學系 | |
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