Basic econometrics / Damodar N. Gujarati, Dawn C. Porter.

Includes bibliographical references (p. 902-903) and indexes.

Introduction -- Nature of regression analysis -- Two-variable regression analysis : some basic ideas -- Two-variable regression model: the problem of estimation -- Classical normal linear regression model -- Two-variable regression: interval estimation and hypothesis testing -- Extensions of the two-variable linear regression model -- Multiple regression analysis : the problem of estimation -- Multiple regression analysis : the problem of inference -- Dummy variable regression model -- Multicollinearity : what happens in the regressors are correlated? -- Heteroscedasticity: what happens if the error variance is nonconstant? -- Autocorrelation: what happens if the error terms are correlated? -- Economic modeling: model specification and diagnostic testing -- Nonlinear regression models -- Qualitative response regression models -- Panel data regression models -- Dynamic econometric models : autoregressive and distributed-lag models -- Simultaneous-equation models -- Identification problem -- Simultaneous-equation methods -- Time series econometrics : some basic concepts -- Time series econometrics : forecasting -- Appendix A : a review of some statistical concepts -- Appendix B : rudiments of matrix algebra -- Appendix C : matrix approach to linear regression model -- Appendix D : statistical tables -- Appendix E : computer output of EViews, MINITAB, Excel, and STATA -- Appendix F : economic data on the World Wide Web.