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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 管中閔(Chung-Ming Kuan) | |
| dc.contributor.author | Lin Chen | en |
| dc.contributor.author | 陳霖 | zh_TW |
| dc.date.accessioned | 2022-11-23T08:59:31Z | - |
| dc.date.available | 2021-11-03 | |
| dc.date.available | 2022-11-23T08:59:31Z | - |
| dc.date.copyright | 2021-11-03 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-10-28 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/79392 | - |
| dc.description.abstract | 在實證研究中通常可以觀察到處置效果會隨著個人的特性有異質性，因此根據個人特性決定要給予哪個處置的處置規則隨之受到來自各領域的注意。這篇論文研究在內生處置下並且有工具變數時如何分配處置的問題。這裡所考慮的處置規則只能決定誰會被鼓勵去接受處置。我們提供了認定的條件以及估計的方法。跟 Athey and Wager (2021) 比較，他們在這個背景下研究的處置規則可以直接改變人們的決定。另一方面，我們也指出當研究者想要考量處置成本的時候，有兩種方式可以引入我們的方法。由於研究方式以及處置成本的兩者選擇都需要根據問題而決定，我們討論了一些例子並指出這些例子中可以幫助研究者們決定的因素。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-23T08:59:31Z (GMT). No. of bitstreams: 1 U0001-2310202100460100.pdf: 387935 bytes, checksum: e323db7071ad6f03e0a46f5005142234 (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | "Acknowledgements i 摘要 ii Abstract iii Contents iv List of Figures vi List of Tables vii Chapter 1 Introduction 1 Chapter 2 Optimal Treatment Allocation under Binary Exogenous Treatment 5 2.1 Framework 5 2.2 Estimation Strategy Review 8 Chapter 3 Optimal Treatment Allocation under Selfselection 12 3.1 Framework Modification, Assumptions, and Identification 12 3.2 Estimation 16 3.3 Comparison 17 Chapter 4 Empirical Implementation 19 4.1 The JTPA Program 20 Chapter 5 Concluding Remarks 24 References 25 Appendix A — Computation of Generalized Random Forest 28 " | |
| dc.language.iso | en | |
| dc.title | 自我選擇下的最適處置分配 | zh_TW |
| dc.title | Optimal Treatment Allocation under Self-Selection | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 許育進(Hsin-Tsai Liu),陳宜廷(Chih-Yang Tseng) | |
| dc.subject.keyword | 異質性處置效果,工具變數,個人處置規則,最適政策學習, | zh_TW |
| dc.subject.keyword | Heterogeneous treatment effects,instrumental variable,individualized treatment rules,optimal policy learning, | en |
| dc.relation.page | 31 | |
| dc.identifier.doi | 10.6342/NTU202104059 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2021-10-28 | |
| 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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