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題名 所得的分位數迴歸和空間統計分析
Quantile regression and spatial statistical analysis of income
作者 李承翰
Lee, Cheng-Han
貢獻者 鄭宗記
Cheng, Tsung-Chi
李承翰
Lee, Cheng-Han
關鍵詞 所得分析
分位數迴歸
空間統計
Quantiles Regression for longitudinal data
Spatial Statistics
Moran's I
Spatial Weight Matrix
日期 2024
上傳時間 4-九月-2024 14:56:59 (UTC+8)
摘要 所得收入不平等是當今許多經濟學和社會科學研究的焦點問題。了解導致所得收入不平等的原因對於制定有效政策、促進經濟均衡發展具有重要意義。本研究將分別使用分位數迴歸和空間統計分析方法，深入探討不同解釋變數在不同分位數下對所得收入的影響。透過分位數迴歸，我們能夠揭示不同影響因素（如教育水準、職業類型等）對於不同所得分位數的影響差異，從而更精確地理解收入分配的不平等現象。同時，透過空間統計分析，我們將觀察地理區域對所得的潛在影響，地理位置可能通過資源分配、區域經濟結構和市場機制等方面對個體的收入產生顯著影響，這種影響在不同地區可能存在顯著差異。根據分位數迴歸和空間統計分析的結果，本研究旨在研究所得收入的影響因素，以供政策制定者在針對緩解收入不平等問題制定因應措施，解決不平等的問題。
參考文獻 內政部社經資料服務平台. (2024). 2011年至2021年台灣各鄉鎮市區相關統計數據. 取得自內政部社經資料服務平台：https://segis.moi.gov.tw/STATCloud/Index 財政部財政資訊中心. (2024). 2010年至2021年台灣各鄉鎮市區所得中位數資料. 取得自財政部財政資訊中心賦稅資料平台：https://www.fia.gov.tw/ Alfó, M., Trovato, G., & Waldmann, E. (2017). Estimating generalized linear mixed models by nonparametric maximum likelihood: A Monte Carlo EM approach. Computational Statistics & Data Analysis, 108, 56-68. Alfo, M., Marino, M. F., Ranalli, M. G., & Salvati, N. (2023). lqmix: an R package for longitudinal data analysis via linear quantile mixtures. arXiv. https://arxiv.org/abs/2302.11363v2 Anselin, L. (1988). Spatial econometrics: Methods and models. Springer. Baum, L. E., Petrie, T., Soules, G., & Weiss, N. (1970). A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains. The Annals of Mathematical Statistics, 41(1), 164-171. Blanchflower, D. G., & Oswald, A. J. (1994). The wage curve. MIT Press. Blundell, R., Dearden, L., & Sianesi, B. (2005). Evaluating the effect of education on earnings: Models, methods and results from the National Child Development Survey. Journal of the Royal Statistical Society: Series A (Statistics in Society), 168(3), 473-512. Blau, F. D., & Kahn, L. M. (2000). Gender differences in pay. Journal of Economic Perspectives, 14(4), 75-99. Bloom, D. E., Canning, D., & Fink, G. (2010). Implications of population aging for economic growth. Oxford Review of Economic Policy, 26(4), 583-612. Cai, F., & Wang, M. (2005). Demographic transition: Implications for growth. In The Oxford companion to economics in India (pp. 55-59). Oxford University Press. Card, D. (1999). The causal effect of education on earnings. In Handbook of labor economics (Vol. 3, pp. 1801-1863). Elsevier. Cliff, A. D., & Ord, J. K. (1973). Spatial autocorrelation. Pion. Cressie, N. (1993). Statistics for spatial data. Wiley. Cutler, D. M., & Lleras-Muney, A. (2007). Education and health: Evaluating theories and evidence. In Making Americans healthier: Social and economic policy as health policy (pp. 29-60). Russell Sage Foundation. Darmofal, D. (2015). Spatial analysis for the social sciences. Cambridge University Press. Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society: Series B (Methodological), 39(1), 1-22. Elhorst, J. P. (2003). Specification and estimation of spatial panel data models. International Regional Science Review, 26(3), 244-268. Faggian, A., McCann, P., & Sheppard, S. (2007). Some evidence that women are more mobile than men: Gender differences in UK graduate migration behavior. Journal of Regional Science, 47(3), 517-539. Friedman, M. (1962). Capitalism and freedom. University of Chicago Press. Geraci, M., & Bottai, M. (2014). Linear quantile mixed models. Statistics and Computing, 24(3), 461-479. Glaeser, E. L., Kallal, H. D., Scheinkman, J. A., & Shleifer, A. (1995). Economic growth in a cross-section of cities. Journal of Monetary Economics, 36(1), 117-143. Glaeser, E. L., & Resseger, M. G. (2009). The complementarity between cities and skills. Journal of Regional Science, 50(1), 221-244. Gravelle, H. (1998). How much of the relation between population mortality and unequal distribution of income is a statistical artifact? BMJ, 316(7128), 382-385. Koenker, R. (2004). Quantile regression for longitudinal data. Journal of Multivariate Analysis, 91(1), 74-89. Koenker, R., & Bassett, G. (1978). Regression quantiles. Econometrica, 46(1), 33-50. Laird, N. M. (1978). Nonparametric maximum likelihood estimation of a mixing distribution. Journal of the American Statistical Association, 73(364), 805-811. Lindsay, B. G. (1983a). The geometry of mixture likelihoods: A general theory. The Annals of Statistics, 11(1), 86-94. Lindsay, B. G. (1983b). The geometry of mixture likelihoods, Part II: The exponential family. The Annals of Statistics, 11(3), 783-792. McLachlan, G. J., & Peel, D. (2000). Finite mixture models. Wiley. Moretti, E. (2004). Estimating the social return to higher education: Evidence from longitudinal and repeated cross-sectional data. Journal of Econometrics, 121(1-2), 175-212. Piketty, T. (2014). Capital in the twenty-first century. Harvard University Press Slemrod, J. (1990). Optimal taxation and optimal tax systems. Journal of Economic Perspectives, 4(1), 157-178. Soja, E. W. (2010). Seeking spatial justice. University of Minnesota Press. Ward, M. D., & Gleditsch, K. S. (2008). Spatial Lag and Spatial Error Models. Cambridge University Press Yu, K., & Moyeed, R. A. (2001). Bayesian quantile regression. Statistics and Probability Letters, 54(4), 437-447.
描述 碩士
國立政治大學
統計學系
111354024
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0111354024
資料類型 thesis
dc.contributor.advisor 鄭宗記zh_TW
dc.contributor.advisor Cheng, Tsung-Chien_US
dc.contributor.author (作者) 李承翰zh_TW
dc.contributor.author (作者) Lee, Cheng-Hanen_US
dc.creator (作者) 李承翰zh_TW
dc.creator (作者) Lee, Cheng-Hanen_US
dc.date (日期) 2024en_US
dc.date.accessioned 4-九月-2024 14:56:59 (UTC+8)-
dc.date.available 4-九月-2024 14:56:59 (UTC+8)-
dc.date.issued (上傳時間) 4-九月-2024 14:56:59 (UTC+8)-
dc.identifier (其他 識別碼) G0111354024en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/153367-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計學系zh_TW
dc.description (描述) 111354024zh_TW
dc.description.abstract (摘要) 所得收入不平等是當今許多經濟學和社會科學研究的焦點問題。了解導致所得收入不平等的原因對於制定有效政策、促進經濟均衡發展具有重要意義。本研究將分別使用分位數迴歸和空間統計分析方法，深入探討不同解釋變數在不同分位數下對所得收入的影響。透過分位數迴歸，我們能夠揭示不同影響因素（如教育水準、職業類型等）對於不同所得分位數的影響差異，從而更精確地理解收入分配的不平等現象。同時，透過空間統計分析，我們將觀察地理區域對所得的潛在影響，地理位置可能通過資源分配、區域經濟結構和市場機制等方面對個體的收入產生顯著影響，這種影響在不同地區可能存在顯著差異。根據分位數迴歸和空間統計分析的結果，本研究旨在研究所得收入的影響因素，以供政策制定者在針對緩解收入不平等問題制定因應措施，解決不平等的問題。zh_TW
dc.description.tableofcontents 摘要 i 目錄 ii 表目錄 iii 圖目錄 iii 第一章、緒論 1 第一節、 研究動機與目的 1 第二節、 研究架構 2 第二章、文獻回顧 3 第一節、 所得資料的特性 3 第二節、 影響所得的原因 3 第三節、分位數迴歸 6 2.3.1 分位數迴歸的介紹 6 2.3.2 分位數迴歸模型 7 2.3.3 分位數迴歸模型的估計 8 第四節、空間統計 9 2.4.1 空間統計的介紹 9 2.4.2 空間自相關性 10 2.4.3 空間滯留模型 10 2.4.4 空間滯留模型的係數估計 12 2.4.5 Moran’s I 13 第三章、 資料分析 15 第一節、 資料介紹 15 第二節、 研究結果 23 3.2.1 分位數迴歸研究結果 23 3.2.2 空間統計研究結果 29 第四章、結論 36 第一節、分位數迴歸的結果整理 36 第二節、空間統計的結果整理 37 第三節、建議 38 參考文獻 40 表目錄 表 1 反應變數和解釋變數敘述統計表 16 表 2 分位數迴歸係數總覽 24 表 3 每年份的所得中位數空間自相關性檢驗結果 29 表 4 空間滯留模型係數總覽 30 圖目錄 圖 1 台灣各鄉鎮市區的所得中位數2010年至2021年時間序列圖 --1 17 圖 2 台灣各鄉鎮市區的所得中位數2010年至2021年時間序列圖 --2 18 圖 3 台灣各鄉鎮市區的所得中位數2010年至2021年時間序列圖 --3 19 圖 4 2010到2021年各縣市所得中位數的LISA Cluster Map 21 圖 5 2021年各解釋變數的LISA Cluster Map --1 22 圖 6 2021年各解釋變數的LISA Cluster Map --2 23 圖 7 分位數迴歸分析係數的信賴區間圖 25 圖 8 空間滯留模型係數的信賴區間圖 31zh_TW
dc.format.extent 3717075 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0111354024en_US
dc.subject (關鍵詞) 所得分析zh_TW
dc.subject (關鍵詞) 分位數迴歸zh_TW
dc.subject (關鍵詞) 空間統計zh_TW
dc.subject (關鍵詞) Quantiles Regression for longitudinal dataen_US
dc.subject (關鍵詞) Spatial Statisticsen_US
dc.subject (關鍵詞) Moran's Ien_US
dc.subject (關鍵詞) Spatial Weight Matrixen_US
dc.title (題名) 所得的分位數迴歸和空間統計分析zh_TW
dc.title (題名) Quantile regression and spatial statistical analysis of incomeen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 內政部社經資料服務平台. (2024). 2011年至2021年台灣各鄉鎮市區相關統計數據. 取得自內政部社經資料服務平台：https://segis.moi.gov.tw/STATCloud/Index 財政部財政資訊中心. (2024). 2010年至2021年台灣各鄉鎮市區所得中位數資料. 取得自財政部財政資訊中心賦稅資料平台：https://www.fia.gov.tw/ Alfó, M., Trovato, G., & Waldmann, E. (2017). Estimating generalized linear mixed models by nonparametric maximum likelihood: A Monte Carlo EM approach. Computational Statistics & Data Analysis, 108, 56-68. Alfo, M., Marino, M. F., Ranalli, M. G., & Salvati, N. (2023). lqmix: an R package for longitudinal data analysis via linear quantile mixtures. arXiv. https://arxiv.org/abs/2302.11363v2 Anselin, L. (1988). Spatial econometrics: Methods and models. Springer. Baum, L. E., Petrie, T., Soules, G., & Weiss, N. (1970). A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains. The Annals of Mathematical Statistics, 41(1), 164-171. Blanchflower, D. G., & Oswald, A. J. (1994). The wage curve. MIT Press. Blundell, R., Dearden, L., & Sianesi, B. (2005). Evaluating the effect of education on earnings: Models, methods and results from the National Child Development Survey. Journal of the Royal Statistical Society: Series A (Statistics in Society), 168(3), 473-512. Blau, F. D., & Kahn, L. M. (2000). Gender differences in pay. Journal of Economic Perspectives, 14(4), 75-99. Bloom, D. E., Canning, D., & Fink, G. (2010). Implications of population aging for economic growth. Oxford Review of Economic Policy, 26(4), 583-612. Cai, F., & Wang, M. (2005). Demographic transition: Implications for growth. In The Oxford companion to economics in India (pp. 55-59). Oxford University Press. Card, D. (1999). The causal effect of education on earnings. In Handbook of labor economics (Vol. 3, pp. 1801-1863). Elsevier. Cliff, A. D., & Ord, J. K. (1973). Spatial autocorrelation. Pion. Cressie, N. (1993). Statistics for spatial data. Wiley. Cutler, D. M., & Lleras-Muney, A. (2007). Education and health: Evaluating theories and evidence. In Making Americans healthier: Social and economic policy as health policy (pp. 29-60). Russell Sage Foundation. Darmofal, D. (2015). Spatial analysis for the social sciences. Cambridge University Press. Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society: Series B (Methodological), 39(1), 1-22. Elhorst, J. P. (2003). Specification and estimation of spatial panel data models. International Regional Science Review, 26(3), 244-268. Faggian, A., McCann, P., & Sheppard, S. (2007). Some evidence that women are more mobile than men: Gender differences in UK graduate migration behavior. Journal of Regional Science, 47(3), 517-539. Friedman, M. (1962). Capitalism and freedom. University of Chicago Press. Geraci, M., & Bottai, M. (2014). Linear quantile mixed models. Statistics and Computing, 24(3), 461-479. Glaeser, E. L., Kallal, H. D., Scheinkman, J. A., & Shleifer, A. (1995). Economic growth in a cross-section of cities. Journal of Monetary Economics, 36(1), 117-143. Glaeser, E. L., & Resseger, M. G. (2009). The complementarity between cities and skills. Journal of Regional Science, 50(1), 221-244. Gravelle, H. (1998). How much of the relation between population mortality and unequal distribution of income is a statistical artifact? BMJ, 316(7128), 382-385. Koenker, R. (2004). Quantile regression for longitudinal data. Journal of Multivariate Analysis, 91(1), 74-89. Koenker, R., & Bassett, G. (1978). Regression quantiles. Econometrica, 46(1), 33-50. Laird, N. M. (1978). Nonparametric maximum likelihood estimation of a mixing distribution. Journal of the American Statistical Association, 73(364), 805-811. Lindsay, B. G. (1983a). The geometry of mixture likelihoods: A general theory. The Annals of Statistics, 11(1), 86-94. Lindsay, B. G. (1983b). The geometry of mixture likelihoods, Part II: The exponential family. The Annals of Statistics, 11(3), 783-792. McLachlan, G. J., & Peel, D. (2000). Finite mixture models. Wiley. Moretti, E. (2004). Estimating the social return to higher education: Evidence from longitudinal and repeated cross-sectional data. Journal of Econometrics, 121(1-2), 175-212. Piketty, T. (2014). Capital in the twenty-first century. Harvard University Press Slemrod, J. (1990). Optimal taxation and optimal tax systems. Journal of Economic Perspectives, 4(1), 157-178. Soja, E. W. (2010). Seeking spatial justice. University of Minnesota Press. Ward, M. D., & Gleditsch, K. S. (2008). Spatial Lag and Spatial Error Models. Cambridge University Press Yu, K., & Moyeed, R. A. (2001). Bayesian quantile regression. Statistics and Probability Letters, 54(4), 437-447.zh_TW