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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/92712完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 郭漢豪 | zh_TW |
| dc.contributor.advisor | Hon-Ho Kwok | en |
| dc.contributor.author | 連士鈞 | zh_TW |
| dc.contributor.author | Shi-Chung Lien | en |
| dc.date.accessioned | 2024-06-13T16:09:47Z | - |
| dc.date.available | 2024-06-14 | - |
| dc.date.copyright | 2024-06-13 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-06-11 | - |
| dc.identifier.citation | ANSELIN, L. (1988): Spatial Econometrics: Methods and Models, Dordrecht: Kluwer Academic Publishers.
BENITO, E. M. (2015): “Model Averraging in Economics: An Overview,” Journal of Economic Surveys, 29, 46–75. CLAESKENS, G. AND N. L. HJORT (2008): Model Selection and Model Averaging, no.9780521852258 in Cambridge Books, Cambridge University Press. HANSEN, B. E. (2007): “Least Square Model Averaging,” Econometrica, 75, 1175–1189. KELEJIAN, H. H. AND I. R. PRUCHA (1998): “A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Auto regressive Model with Autoregressive Disturbances,” Journal of Real Estate Finance and Economics, 17:1, 99–121. KUERSTEINER, G. AND R. OKUI (2010): “Constructing Optimal Instruments by First-Stage Prediction Averaging,” Econometrica, 78, 697–718. KWOK, H. H. (2019): “Identification and estimation of linear social interaction models,” Journal of Econometrics, 210, 434–458. LEE, L. F. (2001.a): “Generalized Method of Moments Estimation of Spatial Autoregressive Processes,” Manuscript. Department of Economics, Ohio State University. ——— (2003): “Best Spatial Two‐Stage Least Squares Estimators for a Spatial Autoregressive Model with Autoregressive Disturbances,” Econometric Reviews, 22, 307–335. ——— (2007): “GMM and 2SLS Estimation of Mixed Regressive, Spatial Autoregressive Models,” Journal of Econometrics, 137, 489–514. LEE, L. F. AND X. D. LIU (2010): “Efficient GMM Estimation of High Order Spatial Autoregressive Models with Autoregressive Disturbances,” Econometric Theory, 26, 187–230. LIU, C. A. (2015): “Distribution theory of the least squares averaging estimator,” Journal of Econometrics, 186, 142–159. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/92712 | - |
| dc.description.abstract | 在一階社會互動模型下，Kelejian and Prucha (1998) 提出一般空間二階最小平方回歸估計法 (general spatial 2SLS) 而Lee (2003) 建議使用更有效率的工具變數，稱為最佳工具變數 (best IV)。本文延伸Lee (2003) 的最佳工具變數至高階社會互動模型 (high-order social interaction model)，並在一般空間二階最小平方回歸估計法計算漸進分配。為了增加高階模型的估計效率，本文再應用Liu (2015) 的最小平方回歸模型平均法 (least square model averaging) 至本文的高階社會互動模型。藉由最小平方回歸模型平均估計法中的局部誤差假設 (local misspecification assumption)，本文得以比較一般空間二階最小平方回歸估計法與最小平方回歸模型平均估計法的估計效率。 | zh_TW |
| dc.description.abstract | Kelejian and Prucha(1998) proposed a general spatial 2SLS estimating framework and Lee (2003) suggested the use of best instrument variables with first-order spatial models. This paper extends such best IV to a high-order social interactions model and derives the asymptotic distribution of the 2SLS estimators. Further, this paper applies the least square model averaging framework proposed by Liu (2015) to improve the estimating performance of the high-order model. Under the local misspecification assumption of the least square model averaging framework, this paper compares the estimating efficiency between the 2SLS estimators and model averaging estimators. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-06-13T16:09:47Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-06-13T16:09:47Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 口試委員審定書 i
摘要 ii Abstract iii Contents iv List of Tables vi Chapter 1 Introduction 1 Chapter 2 Models and GMM Estimation 4 2.1 Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 Assumptions and Interpretation . . . . . . . . . . . . . . . . . . . . 4 2.3 GMM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.4 Lee’s Best IV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Chapter 3 Model Averaging 10 3.1 Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.2 Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Chapter 4 Monte Carlo Simulation 17 Chapter 5 Conclusion 22 References 23 Appendix A Proofs 25 A.1 Proof of theorem 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 A.2 Proof of the asymptotic matrix of best IV . . . . . . . . . . . . . . . 25 A.3 Proof of theorem 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 A.4 Proof of theorem 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 A.5 Proof of theorem 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 A.6 Proof of theorem 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Appendix B Lemmas for Proofs 30 B.1 Lemma(Lee (2003), Lemma A.1) . . . . . . . . . . . . . . . . . . . 30 B.2 Lemma(Lee (2003), Lemma A.2) . . . . . . . . . . . . . . . . . . . 30 B.3 Lemma(Kelejian and Prucha, Theorem A.1) . . . . . . . . . . . . . . 31 B.4 Lemma(Lee (2003), Lemma A.3) . . . . . . . . . . . . . . . . . . . 31 B.5 Lemma(Lee (2003), Lemma A.4) . . . . . . . . . . . . . . . . . . . 31 | - |
| dc.language.iso | en | - |
| dc.subject | 一般化動差法 | zh_TW |
| dc.subject | 一致性估計法 | zh_TW |
| dc.subject | 模型選擇 | zh_TW |
| dc.subject | 模型平均 | zh_TW |
| dc.subject | 二階最小平方回歸法 | zh_TW |
| dc.subject | two-stage least square | en |
| dc.subject | Model selection | en |
| dc.subject | Model averaging | en |
| dc.subject | GMM | en |
| dc.subject | consistent estimation | en |
| dc.title | 社會互動模型的一般化動差估計法和模型平均 | zh_TW |
| dc.title | Generalized Method of Moments and Model Averaging for Social Interactions Models | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 謝志昇;劉祝安 | zh_TW |
| dc.contributor.oralexamcommittee | Chih-Sheng Hsieh;Chu-An Liu | en |
| dc.subject.keyword | 一致性估計法,一般化動差法,二階最小平方回歸法,模型平均,模型選擇, | zh_TW |
| dc.subject.keyword | consistent estimation,GMM,two-stage least square,Model selection,Model averaging, | en |
| dc.relation.page | 32 | - |
| dc.identifier.doi | 10.6342/NTU202401119 | - |
| dc.rights.note | 同意授權(限校園內公開) | - |
| dc.date.accepted | 2024-06-12 | - |
| dc.contributor.author-college | 社會科學院 | - |
| dc.contributor.author-dept | 經濟學系 | - |
| 顯示於系所單位： | 經濟學系 | |
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