報告題目：平滑轉(zhuǎn)移回歸建模方法及應用研究進展
報告人：經(jīng)濟學院 王正新 博士
報告時間：2016年12月8日15點10分
報告地點：經(jīng)濟學院6號樓210室
組織發(fā)起：經(jīng)濟學院前沿文獻與經(jīng)典著作讀書會
主辦單位：經(jīng)濟學院
協(xié)辦單位：科研處
內(nèi)容摘要：
作為非線性體制轉(zhuǎn)換模型之一，平滑轉(zhuǎn)移回歸模型能夠較為細致地刻畫變量在不同狀態(tài)間的非線性轉(zhuǎn)換,，有效地從現(xiàn)實數(shù)據(jù)中挖掘線性模型無法揭示的經(jīng)濟學含義,。近年來,，該類模型被廣泛應用于經(jīng)濟、金融領域,，在理論方法研究方面也是非線性時間序列分析的前沿內(nèi)容,。此外，隨著經(jīng)濟領域面板數(shù)據(jù)可得性的增強和面板數(shù)據(jù)建模技術(shù)的發(fā)展,，非線性面板模型也逐漸成為學界研究的熱點,。本次沙龍將系統(tǒng)地介紹時間序列平滑轉(zhuǎn)移回歸模型和面板平滑轉(zhuǎn)移回歸模型的理論及應用研究進展，并結(jié)合主講人近期的相關(guān)研究成果展開討論,。
參考文獻：
1.Terasvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425): 208-218.
2.Van Dijk, D., and Franses, P. H. (1999), "Modeling Multiple Regimes in the Business Cycle," Macroeconomic Dynamics, 3: 311-340.
3.Van Dijk, D., Tersvirta, T. and Franses, P.H. (2002) Smooth Transition Autoregressive Models—A Survey of Recent. Developments. Econometric Reviews, 21: 1-47.
4.Lundbergh, S., Terasvirta, T., (2003). Time-Varying Smooth Transition Autoregressive Models. Journal of Business and Economic Statistics, 21(1) : 104-121.
5.Fok, D., Van Dijk, D., Franses, P.H. (2005). A multi-level panel STAR model for US manufacturing sectors. Journal of Applied Econometrics, 20(6):811-827 .
6.Fouquau, J., Hurlin, C. and Rabaud, I. (2008). The Feldstein-Horioka Puzzle: A Panel Smooth Transition Regression. Approach. Economic Modelling, 25, 284-299.
7.McAleer, M., Medeiros, M.C. (2008). A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries. Journal of Econometrics, 147: 104–119.
8.Bekiros, S.D. (2009). A robust algorithm for parameter estimation in smooth transition autoregressive models. Economics Letters 103: 36-38.
9.K?l??, R. (2011). Long memory and nonlinearity in conditional variances: A smooth transition FIGARCH model. Journal of Empirical Finance 18: 368-378.
10.Cai, N., Cai, Z., Fang, Y. et al. (2015). Forecasting major Asian exchange rates using a new semiparametric STAR model. Empirical Economics, 48(1): 407–426.
