<P ><FONT face="Times New Roman">Jeffrey M. Wooldridge</FONT>专门讨论横截面数据和面板数据的教材。全书简介如下。<o:p></o:p></P>
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<Palign=left><FONT face="Times New Roman">The analysis of general estimation methods for nonlinear models in Part III begins with a general treatment of asymptotic theory of estimators obtained from nonlinear optimization problems. Maximum likelihood, partial maximum likelihood, and generalized method of moments estimation are shown to be generally applicable estimation approaches. The method of nonlinear least squares is also covered as a method for estimating models of conditional means.<o:p></o:p></FONT></P>
<Palign=left><FONT face="Times New Roman">Part IV covers several nonlinear models used by modern applied researchers.Chapters 15 and 16 treat limited dependent variable models, with attention given to handling certain endogeneity problems in such models. Panel data methods for binary response and censored variables, including some new estimation approaches, are also covered in these chapters.<o:p></o:p></FONT></P>
<Palign=left><FONT face="Times New Roman">Chapter 17 contains a treatment of sample selection problems for both cross section and panel data, including some recent advances. The focus is on the case where the population model is linear, but some results are given for nonlinear models as well. <o:p></o:p></FONT></P>
<Palign=left><FONT face="Times New Roman">Chapter 18 treats recent approaches to estimating average treatment effects.<o:p></o:p></FONT></P>
<Palign=left><FONT face="Times New Roman">Chapter 19 treats Poisson and related regression models, both for cross section and panel data. These rely heavily on the method of quasi-maximum likelihood estimation.<o:p></o:p></FONT></P>
<Palign=left><FONT face="Times New Roman">Chapter 20 briefly discusses modern treatment of duration models .</FONT><o:p></o:p></P><BR>