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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73803完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳宜廷(Yi-Ting Chen) | |
| dc.contributor.author | Bo-Hao Wang | en |
| dc.contributor.author | 王柏皓 | zh_TW |
| dc.date.accessioned | 2021-06-17T08:10:37Z | - |
| dc.date.available | 2020-08-18 | |
| dc.date.copyright | 2019-08-18 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-08-15 | |
| dc.identifier.citation | Almon, S. (1965): “The distributed lag between capital appropriations and expenditures,” Econometrica, 33, 178-196.
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73803 | - |
| dc.description.abstract | 在本文中，我們評估總體資料、廠商資料和高頻資料能否幫助預測美國工業生產指數和通貨膨脹，並藉由動態因子模型和因子混頻抽樣迴歸模型(MIDAS)進行實證研究。研究結果顯示，除了廣泛使用於預測工業生產指數和通貨膨脹的總體資料外，廠商以及高頻資料可能也包含有助於長期預測的訊息。 | zh_TW |
| dc.description.abstract | In this thesis, we assess the performance of a large-dimensional set of macro-level, firm-level and daily predictors in forecasting the industrial production and inflation of the U.S. We base this empirical study on the dynamic factor model and the factor mixed data sampling regression (MIDAS). The empirical study shows that the firm-level and high-frequency predictors may contain useful information in addition to the widely used macro-level predictors in the long-term forecast of the industrial production and inflation. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T08:10:37Z (GMT). No. of bitstreams: 1 ntu-108-R06323044-1.pdf: 1042900 bytes, checksum: 9119974a7d9a6bdda6ae3a757791bc0a (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 論文口試委員審定書 i
摘要 ii Abstract iii Contents iv List of Figures v List of Tables vi 1 Introduction 1 2 Econometric Models 4 2.1 Dynamic factor model 4 2.2 Factor MIDAS 5 3 Empirical Analysis 7 3.1 Data 7 3.2 Empirical Design 8 3.3 Empirical Findings 10 4 Conclusion 21 References 22 A Appendix 25 A.1 Macro-level data 25 A.2 Firm-level data 25 A.3 Daily data 30 A.4 Model selection 34 | |
| dc.language.iso | en | |
| dc.subject | 高頻資料 | zh_TW |
| dc.subject | 經濟預測 | zh_TW |
| dc.subject | 廠商資料 | zh_TW |
| dc.subject | 因子模型 | zh_TW |
| dc.subject | MIDAS迴歸 | zh_TW |
| dc.subject | Economic forecasting | en |
| dc.subject | Firm-level data | en |
| dc.subject | High-frequency data | en |
| dc.subject | MIDAS | en |
| dc.subject | Factor model | en |
| dc.title | 以總體、廠商及高頻資料所進行之經濟預測 | zh_TW |
| dc.title | Economic Forecasts by Macro-level, Firm-level and High-frequency Data | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 107-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 殷壽鏞(Shou-Yung Yin) | |
| dc.contributor.oralexamcommittee | 許育進(Yu-Chin Hsu),劉祝安(Chu-An Liu) | |
| dc.subject.keyword | 經濟預測,廠商資料,高頻資料,MIDAS迴歸,因子模型, | zh_TW |
| dc.subject.keyword | Economic forecasting,Firm-level data,High-frequency data,MIDAS,Factor model, | en |
| dc.relation.page | 37 | |
| dc.identifier.doi | 10.6342/NTU201903326 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2019-08-16 | |
| 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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