Estimation and Inference in Econometrics

Offering students a unifying theoretical perspective, this innovative textemphasizes nonlinear techniques of estimation, including nonlinear leastsquares, nonlinear instrumental variables, maximum likelihood and thegeneralized method of moments, but nevertheless relies heavily on simplegeometrical arguments to develop intuition. One theme of the book is the use ofartificial regressions for estimation, inference, and specification testing ofnonlinear models, including diagnostic tests for parameter constancy, seriescorrelation, heteroskedasticity and other types of misspecification. Othertopics include the linear simultaneous equations model, non-nested hypothesistests, influential observations and leverage, transformations of the dependentvariable, binary response models, models for time-series/cross-section data,multivariate models, seasonality, unit roots and cointegration, and Monte Carlomethods, always with an emphasis on problems that arise in applied work.Explaining throughout how estimates can be obtained and tests can be carriedout, the text goes beyond a mere algebraic description to one that can be easilytranslated into the commands of a standard econometric software package. Acomprehensive and coherent guide to the most vital topics in econometrics today,this text is indispensable for all levels of students of econometrics,economics, and statistics on regression and related topics.