Econometric Analysis of Panel Data：面板数据的计量分析.pptVIP

* * * * Why a Course on ‘Panel Data?’ Microeconometrics and applications – contemporary broad field in economics/econometrics Behavioral modeling Individual choice and response A platform for surveying econometric models and methods – most of the field Various types Recent developments Prerequisites Econometrics I or equivalent Ph.D. level introduction to econometrics Mathematical statistics Matrix algebra We will do some proofs and derivations. We will examine many empirical applications. You will apply the tools developed in the course. Text Readings Baltagi (2008); Main text: read chapters 1,2 Greene (2012); Recommended: read chapters 1,2,8,11,13 Wooldridge (2010); Suggested: read chapters 1,2,4,10,11 Cameron and Trivedi (2005); Very interesting: Microeconometrics Matyas and Sevestre (2008); Recent survey. Contributed papers. Hsiao(2003); Alternative to Baltagi Frees (2004); Applications from many areas. Course Applications Problem sets Panel data sets: See the course website Software: NLOGIT Version 5.0 Other ‘packages:’ Stata, SAS, EViews Programming environments: R, Matlab, Gauss, Mathematica We will not use class time for software instruction ‘Lab’ work Problem sets Questions and review as requested /wgreene/Econometrics/PanelDataEconometrics.htm Course Outline Class Notes Problem Sets Panel Data Sets Other Data Sets Data sets for Econometric Analysis Data sets for Baltagi’s Text Rosetta Stone for Data Sets:Stat Transfer Where Do We Go From Here? Review of familiar classical procedures Fundamental, familiar regression extensions; common effects models Endogeneity, instrumental variables, GMM estimation Dynamic models Models of heterogeneity Nonlinear models that carry forward the features of the linear, static and dynamic common effects models Recent developments in non- and semiparametric approaches Econometric Models Linear; static and dynamic Discrete choice Censoring and truncation Structural models and demand systems Time series models