Econometrics

Preface.- What is Econometrics?: Introduction; A Brief History; Critiques of Econometrics.- A Review of Some Basic Statistical Concepts: Introduction; Methods of Estimation; Properties of Estimators; Hypothesis Testing; Confidence Intervals. Problems. References. Appendix.- Simple Linear Regression: Introduction; Least Squares Estimation and the Classical Assumptions; Statistical Properties of the Least Squares Estimators; Estimation of o2; Maximum Likelihood Estimation. A Measure of Fit; Prediction; Residual Analysis; Numerical Example; Empirical Example. Problems. References. Appendix.- Multiple Regression Analysis: Introduction; Least Squares Estimation; Residual Interpretation of Multiple Regression Estimates; Overspecification and Underspecification of the Regression Equation; R-Squared versus R-Bar-Squared; Testing Linear Restrictions; Dummy Variables. Problems. References. Appendix.- Violations of the Classical Assumptions: Introduction; The Zero Mean Assumption; Stochastic Explanatory Variables; Normality of the Disturbances; Heteroskedasticity; Autocorrelation. Problems. References.- Distributed Lags and Dynamic Models: Introduction; Infinite Distributed Lags; Estimation and Testing of Dynamic Models with Serial Correlation; Autoregressive Distributed Lag. Problems. References.- The General Linear Model: The Basics: Introduction; Least Squares Estimation; Partitioned Regression and the Frisch-Waugh Lovell Theorem; Maximum Likelihood Estimation; Prediction; Confidence Intervals and Test of Hypotheses; Joint Confidence Intervals and Test of Hypotheses; Restricted MLE and Restricted Least Squares; Likelihood Ratio, Wald and Lagrange Multiplier Tests. Problems. References. Appendix.- Regression Diagnostics and Specification Tests: Influential Observations; Recursive Residuals; Specification Tests; Non-Linear Least Squares and the Gauss-Newton Regression;Testing Linear Versus Log-Linear Functional Form. Problems. References.- Generalized Least Squares: Introduction; Generalized Least Squares; Special Forms of O; Maximum Likelihood Estimation; Test of Hypotheses; Prediction; Unknown O; The W, LR, and LM Statistics Revisited. Problems. References.- Seemingly Unrelated Regressions: Introduction; Feasible GLS Estimation; Testing Diagonality of the Variance-Covariance Matrix; Seemingly Unrelated Regressions with Unequal Observations; Empirical Example. Problems. References.- Simultaneous Equations Model: Introduction; Single Equation Estimation: Two-Stage Least Squares; System Estimation: Three-Stage Least Squares; The Identification Problem Revisited: The Rank Condition of Identification; Test for Over-Identification Restrictions; Hausman`s Specification Test; Empirical Example. Problems. References.- Pooling Time-Series of Cross-Section Data: Introduction; The Error Components Procedure;. Time-Wise Autocorrelated and Cross-Sectionally Heteroskedastic Procedures; A Comparison of the Two Procedures. Problems. References.- Limited Dependent Variables: Introduction; The Linear Probability Model; Functional Form: Logit and Probit; Grouped Data; Individual Data: Probit and Logit; The Binary Response Model Regression; Asymptotic Variances for Predictions and Marginal Effects; Goodness of Fit Measures; Empirical Example; Multinomial Choice Models; The Censored Regression Model; The Truncated Regression Model; Sample Selectivity. Problems. References. Appendix.- Time Series Models: Introduction; Stationarity; The Box and Jenkins Method; Vector Autoregression; Unit Root; Trend Stationary Versus Difference Stationary; Cointegration; Autoregressive Conditional Heteroskedasticity. Problems. References. Index.