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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 郭漢豪 | zh_TW |
| dc.contributor.advisor | Hon-Ho Kwok | en |
| dc.contributor.author | 楊睿哲 | zh_TW |
| dc.contributor.author | Rui-Zhe Yang | en |
| dc.date.accessioned | 2024-07-29T16:21:11Z | - |
| dc.date.available | 2024-07-30 | - |
| dc.date.copyright | 2024-07-29 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-07-22 | - |
| dc.identifier.citation | [1] Yang Feng, Qingfeng Liu, Qingsong Yao, and Guoqing Zhao (2021). Model Averaging for Nonlinear Regression Models. Journal of Business and Economic Statistics, 40, 785-798.
[2] Harry H. Kelejian and Ingmar R. Prucha (1998). A generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances. The Journal of Real Estate Finance and Economics, 17, 99-121. [3] Lung-fei Lee (2003). Best Spatial Two-Stage Least Squares Estimators for a Spatial Autoregressive Model with Autoregressive Disturbances. Econometric Reviews, 22, 307-335. [4] Lung-fei Lee (2004). Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models. Econometrica, 72, 1899-1925. [5] Lung-fei Lee (2001). Generalized Method of Moments Estimation of Spatial Autoregressive Processes. Manuscript. Department of Economics, Ohio State University. [6] Mudit Kapoor, Harry H. Kelejian and Ingmar R. Prucha (2007). Panel Data Models with Spatially Correlated Error Components. Journal of Econometrics, 140, 97-130. [7] Hon-Ho, Kwok (2019). Identification and Estimation of Linear Social Interaction Models. Journal of Econometrics, 210, 434-458. [8] Xinyu Zhang and Chu-An Liu (2024). A Unified Approach to Focused Information Criterion and Plug-in Averaging Method. Statistica Sinica, 34, 771-792. [9] Mark F.J. Steel (2020). Model Averaging and Its Use in Economics. Journal of Economic Literature, 58, 644-719. [10] Enrique Moral-Benito (2015). Model Averaging in Economics: An Overview. Journal of Economic Surveys, 29, 46-75. [11] Claeskens, G. and Hjort, N. (2008). Model Selection and Model Averaging. Cambridge University Press. [12] Luc E. Anselin (1988). Spatial Econometrics: Methods and Models. Springer Science and Business Media. [13] Whitney K. Newey and Daniel McFadden (1994). Large Sample Estimation and Hypothesis Testing. Handbook of Econometrics, 2111-2245. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/93342 | - |
| dc.description.abstract | 本論文首先討論一般化動差法如何估計高階空間迴歸模型，為了估計效率而使用最佳化權重矩陣並列出其極限分配。接下來探討模型平均的權重決定的準則以及準則的大樣本性質，概念參考自Feng, Liu, Yao and Zhao (2021)的非線性迴歸模型(nonlinear regression model)的模型平均，討論在一般化動差法估計以及樣本外誤差的基準下，準則的函數以及它的大樣本性質。最後，從蒙地卡羅模擬中可以得知我們的模型平均方法與LASSO在估計以及預測的表現不相上下。 | zh_TW |
| dc.description.abstract | This paper first discusses how the generalized method of moments (GMM) is used to estimate high-order spatial regression models, employing the optimal weight matrix for estimation efficiency and listing its limiting distribution. Next, it explores the criteria for determining model averaging weights and the asymptotic properties of these criteria, drawing on the concept from Feng, Liu, Yao, and Zhao (2021) for model averaging in nonlinear regression models. The discussion focuses on the criterion function and its asymptotic properties under GMM estimation and out-of-sample error benchmarks. Finally, Monte Carlo simulations demonstrate that our model averaging method performs on par with LASSO in terms of estimation and prediction. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-07-29T16:21:11Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-07-29T16:21:11Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | Verification Letter from the Oral Examination Committee i
摘要 iii Abstract v Contents vii List of Tables ix Chapter 1 Introduction 1 Chapter 2 The Model and GMM Estimation 3 2.1 High-Order Spatial Model . . . . . . . . . . . . . . . . . . . . . . . 3 2.2 Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.3 GMM Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Chapter 3 Model Averaging 9 3.1 Sub-Models and GMM . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.2 Model Averaging (Parameter Averaging) . . . . . . . . . . . . . . . 11 3.3 Theorems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Chapter 4 Monte Carlo Simulation 15 Chapter 5 Conclusion 19 References 21 Appendix A — Derivation of the Proposed Criterion 23 A.1 Proposed Criterion 1 . . . . . . . . . . . . . . . . . . . . . . . . . . 23 A.2 Proposed Criterion 2 . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Appendix B — Lemmas 29 B.1 Lemma 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 B.2 Lemma 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 B.3 Lemma 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 B.4 Lemma 4 (Kelejian and Prucha (1998)) . . . . . . . . . . . . . . . . 31 B.5 Lemma 5 (Yang Feng, Qingfeng Liu, Qingsong Yao, and Guoqing Zhao (2021)) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Appendix C — Proofs of the Theorems 33 C.1 Theorem 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 C.2 Theorem 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 C.3 Theorem 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 | - |
| dc.language.iso | en | - |
| dc.subject | 空間迴歸模型 | zh_TW |
| dc.subject | 一般化動差法 | zh_TW |
| dc.subject | 模型平均 | zh_TW |
| dc.subject | 樣本外誤差 | zh_TW |
| dc.subject | 樣本內誤差 | zh_TW |
| dc.subject | 空間權重矩陣 | zh_TW |
| dc.subject | 社會網路 | zh_TW |
| dc.subject | GMM | en |
| dc.subject | Social Interaction | en |
| dc.subject | Spatial Weight Matrix | en |
| dc.subject | In Sample Prediction Error | en |
| dc.subject | Out-of-Sample Prediction Error | en |
| dc.subject | Model averaging | en |
| dc.subject | Spatial model | en |
| dc.title | 高階社會網路模型的一般化動差估計與模型平均 | zh_TW |
| dc.title | Generalized Method of Moments Estimation and Model Averaging for High-Order Social Interaction Model | 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 | 空間迴歸模型,一般化動差法,模型平均,樣本外誤差,樣本內誤差,空間權重矩陣,社會網路, | zh_TW |
| dc.subject.keyword | Spatial model,GMM,Model averaging,Out-of-Sample Prediction Error,In Sample Prediction Error,Spatial Weight Matrix,Social Interaction, | en |
| dc.relation.page | 39 | - |
| dc.identifier.doi | 10.6342/NTU202401083 | - |
| dc.rights.note | 同意授權(限校園內公開) | - |
| dc.date.accepted | 2024-07-23 | - |
| 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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