| dc.contributor.advisor | 連賢明 | zh_TW |
| dc.contributor.advisor | Lien, Hsien-Ming | en_US |
| dc.contributor.author (Authors) | 洪振倫 | zh_TW |
| dc.contributor.author (Authors) | Hung, Chen-Lun | en_US |
| dc.creator (作者) | 洪振倫 | zh_TW |
| dc.creator (作者) | Hung, Chen-Lun | en_US |
| dc.date (日期) | 2023 | en_US |
| dc.date.accessioned | 2-Aug-2023 13:57:13 (UTC+8) | - |
| dc.date.available | 2-Aug-2023 13:57:13 (UTC+8) | - |
| dc.date.issued (上傳時間) | 2-Aug-2023 13:57:13 (UTC+8) | - |
| dc.identifier (Other Identifiers) | G0110255011 | en_US |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/146542 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 財政學系 | zh_TW |
| dc.description (描述) | 110255011 | zh_TW |
| dc.description.abstract (摘要) | 消費者物價指數（CPI）是一個重要的總體經濟指標，然而，準確計算CPI一直以來都是各國統計機構面臨的問題。這些問題包括樣本偏誤、品質偏誤和替代性偏誤等。本研究旨在解決傳統CPI計算方法中的樣本和新商品偏誤問題，並利用2016年至2021年的B2C電子發票資料進行實證分析。本研究選擇雞蛋和衛生紙作為CPI計算的代表品項，通過蒐集和分析大數據，探討消費者的消費行為和模式。與主計總處公布的CPI相比，使用電子發票計算的CPI顯示了相似的趨勢，但仍存在差距。這些差距可能源於樣本和新商品偏誤，以及不同零售場所之間的消費結構差異。為了控制商品品質的差異，本研究還將項目群分類，以控制商品的品質相同，也區分不同購買場域，分析其中產生的差異。綜上所述，本研究利用電子發票資料庫嘗試解決了傳統CPI計算方法中的樣本偏誤、新商品偏誤等問題。然而，仍需要更進一步的研究來探討CPI計算中的其他問題，並將電子發票資料庫的應用擴展到更廣泛的消費領域。 | zh_TW |
| dc.description.abstract (摘要) | The Consumer Price Index (CPI) is an important macroeconomic indicator. However, accurately calculating the CPI has been a challenge for statistical agencies worldwide. These challenges include sampling biases, quality biases, and substitution biases, among others. This study aims to address sampling and new product biases in traditional CPI calculation methods and conduct empirical analysis using B2C e-invoice data from 2016 to 2021.Eggs and toilet paper are chosen as representative items for CPI calculation in this study. By collecting and analyzing big data, the study explores consumer consumption behavior and patterns. Compared to the CPI published by the statistical agency, the CPI calculated using e-invoice data shows similar trends but still exhibits discrepancies. These differences may arise from sample and new product biases, as well as variations in consumption structures among different retail locations.To control for differences in product quality, this study also categorizes item groups to ensure consistent quality and distinguishes different purchasing domains to analyze the disparities therein.In summary, this study attempts to address sample biases, new product biases, and other issues in traditional CPI calculation methods using e-invoice databases. However, further research is still needed to explore other problems in CPI calculation and extend the application of e-invoice databases to a wider range of consumer domains. | en_US |
| dc.description.tableofcontents | 謝辭 i摘要 iiAbstract iii目次 iv圖目錄 v表目錄 vii第一章 緒論 1第二章 CPI編制方法 4第一節 臺灣編制CPI概況 5第二節 國外編制CPI比較 9第三節 編制CPI問題 16第三章 研究資料及方法 20第一節 研究資料說明 20第二節 研究方法 22第四章 統計結果與分析 29第一節 雞蛋項目群分析 29第二節 衛生紙項目群分析 48第五章 結論與建議 58第六章 參考資料 62 | zh_TW |
| dc.format.extent | 3782126 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0110255011 | en_US |
| dc.subject (關鍵詞) | 消費者物價指數 | zh_TW |
| dc.subject (關鍵詞) | CPI計算方法 | zh_TW |
| dc.subject (關鍵詞) | 電子發票 | zh_TW |
| dc.subject (關鍵詞) | 消費行為 | zh_TW |
| dc.subject (關鍵詞) | Consumer Price Index | en_US |
| dc.subject (關鍵詞) | CPI calculation methods | en_US |
| dc.subject (關鍵詞) | E-invoice | en_US |
| dc.subject (關鍵詞) | Consumer behavior | en_US |
| dc.title (題名) | 使用電子發票資料庫的CPI計算方法：優缺點分析與應用展望 | zh_TW |
| dc.title (題名) | Calculation Methodology of CPI using Electronic Invoice Database: An Analysis of Pros and Cons and Future Prospects | en_US |
| dc.type (資料類型) | thesis | en_US |
| dc.relation.reference (參考文獻) | 臺中市政府主計處, 臺中市政府財政局, & 臺中市政府地方稅務局. （2013, Mar）. 考察日本物價指數查編方法. https://rdnet.taichung.gov.tw/media/517876/001.pdf羅美玲. （2010, Jan）. CPI品質偏誤調整與探討. 公務出國報告資訊網. https://report.nat.gov.tw/ReportFront/ReportSearch/quick/result総務省統計局. （2021, Mar）. 消費者物価指数のしくみと見方-2020年基準消費者物価指数-. https://www.stat.go.jp/data/cpi/2020/mikata/index.htmlBoskin Commission. （1996, Dec）.The Boskin Commission Report. Retrieved from https://www.ssa.gov/history/reports/boskinrpt.html#cpi4Bradley, R., Cook, B., Leaver, S. G., & Moulton, B. R. （1997, April）. An overview of research on potential uses of scanner data in the US CPI. In Third Meeting of the International Working Group on Price Indices, Statistics Netherlands, Voorburg, April （pp. 16-18）.Bradley, R. (2001). Finite sample effects in the estimation of substitution bias in the consumer price index. Journal of Official Statistics, 17(3), 369.Covas, F., & Silva, J. S. (1999). Outlet substitution bias. Economic Bullettin, September.Diewert, W Erwin. （1998）. Index Number Issues in the Consumer Price Index. Journal of Economic Perspectives, 12 （1） 47-58.Hausman, J. A. (2002). Sources of Bias and Solutions to Bias in the CPI.Hausman, J., & Leibtag, E. (2009). CPI bias from supercenters: does the BLS know that Wal-Mart exists?. In Price index concepts and measurement (pp. 203-231). University of Chicago Press.Kish, L. (1995). Survey sampling.Lebow, David E, and Jeremy B Rudd. （2003）“Measurement Error in the Consumer Price Index: Where Do We Stand?” Journal of economic literature. 41.1: 159–201. Web.Reed, S. B., & Rippy, D. A. （2012, Aug）. Consumer Price Index data quality: how accurate is the US CPI?.Shapiro, M. D., & Wilcox, D. W. （1996）. Mismeasurement in the consumer price index An evaluation. NBER macroeconomics annual, 11, 93-142.Statistics Canada. （2023, Feb）. The Canadian Consumer Price Index Reference Paper. Retrieved from https://www150.statcan.gc.ca/n1/pub/62-553-x/62-553-x2023001-eng.htmU.S. Bureau of Labor Statistics. （2023, Feb）. Consumer Price Index: Design. Retrieved from https://www.bls.gov/opub/hom/cpi/design.htm | zh_TW |
