An introductory textbook (requiring no previous knowledge of probability and statistics) that offers students a solid foundation in regression analysis. This unique introduction to econometrics provides undergraduate students with a command of regression analysis in one semester, enabling them to grasp the empirical literature and undertake serious quantitative projects of their own. It does not assume any previous exposure to probability and statistics but does discuss the concepts in these areas that are essential for econometrics. The bulk of the textbook is devoted to regression analysis, from simple to advanced topics. Students will gain an intuitive understanding of the mathematical concepts; Java applet simulations on the book's website demonstrate how the algebraic equations are derived in the text and are designed to reinforce the important concepts. After presenting the essentials of probability and statistics, the book covers simple regression analysis, multiple regression analysis, and advanced topics including heteroskedasticity, autocorrelation, large sample properties, instrumental variables, measurement error, omitted variables, panel data, simultaneous equations, and binary/truncated dependent variables. Two optional chapters treat additional probability and statistics topics. Each chapter offers examples, prep problems (bringing students "up to speed" at the beginning of a chapter), review questions, and exercises. An accompanying website offers students easy access to Java simulations and data sets (available in EViews, Stata, and Excel files). After a single semester spent mastering the material presented in this book, students will be prepared to take any of the many elective courses that use econometric techniques. * Requires no background in probability and statistics * Regression analysis focus * "Econometrics lab" with Java applet simulations on accompanying Website
His profit , if he wins , equals v - s . Hence his expected profit is simply 2s ( v – s ) . This function takes its maximum at the point s = v / 2 , as is easily checked by difBox 2.2 ( continued ) 1 ( c ) ( b Some Models That Work 53.
本书围绕20世纪80年代以来的时间序列分析方法的研究成果,着重讨论适用于经济时间序列分析的各种非线性时间序列模型及其应用实践。本书在说明时间序列分析的基本概念与非线性 ...
Following Leontief , Rosenberg ( 1992 , p . 65 ) allows that agricultural economics has exhibited substantial predictive improvement . But Rosenberg discounts this on the ground that the confirmed predictions in agricultural economics ...
The purpose of this booklet is to introduce readers to the appropriate econometric techniques for use with different forms of survey data - known collectively as microeconometrics.
Statistics and Econometric Models: Testing, confidence regions, model selection, and asymptotic theory ; Christian Gourieroux, Alain Monfort ; translated by...
[ 83 ] J. Durbin , Maximum Likelihood Estimation of the Parameters of a System of Simultaneous Regression Equations ... [ 97 ] R.C. Fair , Specification , Estimation , and Analysis of Macroeconometric Models , Harvard University Press ...
Cette 7e édition, mise à jour et enrichie d'un nouveau chapitre, présente de façon extrêmement pédagogique les concepts de l'économétrie moderne et plus particulièrement : les domaines classiques de l'économétrie (modèle ...
For advanced undergraduate/graduate- level courses in Econometrics. This text surveys the theories, techniques (model-building and data collection), and applications of econometrics.
An attempt has been made in this work to provide a selective set of contributions on economic thinking in their applied aspects. Prof.
... économétrie appliquée plus avancées:lesméthodes d'évaluationdes politiquespubliques,le traitementdesdonnées de panel,puis les méthodes d'estimation non linéaire. Les premiers chapitres peuvent servir de base à un cours d'introduction à ...