The Theory and Practice of Econometrics

SAMPLING THEORY AND BAYESIAN APPROACHES TO INFERENCE; The Classical Inference Approach for the General Linear Model; Statistical Decision Theory and Biased Estimation; The Bayesian Approach to Inference; INFERENCE IN GENERAL STATISTICAL MODELS AND TIME SERIES; Some Asymptotic Theory and Other General Results for the Linear Statistical Model; Nonlinear Statistical Models; Time Series; DYNAMIC SPECIFICATIONS; Autocorrelation; Finite Distributed Lags; Infinite Distributed Lags; SOME ALTERNATIVE COVARIANCE STRUCTURES; Heteroskedasticity; Disturbance-Related Sets of Regression Equations; Inference in Models that Combine Time Series and Cross-Sectional Data; INFERENCE IN SIMULTANEOUS EQUATION MODELS; Specification and Identification in Simultaneous Equation Models; Estimation and Inference in a System of Simultaneous Equations; Multiple Time Series and Systems of Dynamic Simultaneous Equations; FURTHER MODEL EXTENSIONS; Unobservable Variables; Qualitative and Limited Dependent Variable Models; Varying and Random Coefficient Models; Non-Normal Disturbances; On Selecting the Set of Aggressors; Multicollinearity; Appendices.