## Introduction to the theory and practice of econometricsThis Second Edition of the highly acclaimed introduction to econometrics retains its comprehensive nature and strong authorship, while incorporating much new material. New to this edition are a complete treatment of Bayesian inference, sampling theory, an appendix on linear algebra, and a computer handbook. Presentation covers modern statistical models and focuses on the sampling theory process by which the data were generated, and the statistical consequences of alternative decisions under uncertainty. Asymptotics are introduced early on, for use throughout. Includes at least one applied example to illustrate each model, and contains many analytical and numerical exercises. |

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### Contents

THE FOUNDATIONS OF STATISTICAL | 9 |

Estimation | 58 |

Properties of Point Estimators | 69 |

Copyright | |

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### Common terms and phrases

algorithm alternative assumed assumption asymptotic autocorrelation Bayesian best linear unbiased Chapter characteristic roots coefficients column compute consider consistent estimator covariance matrix degrees of freedom denoted density function dependent derived design matrix diagonal dummy variable Econometrics economic elements estimated generalized least example Exercise explanatory variables F-distribution finite sample forecast given heteroskedasticity hypothesis testing independent indirect least squares inference instrumental variable intercept interval estimates known lag length least squares estimator likelihood function linear statistical model maximum likelihood estimator mean square error minimizes multicollinearity multivariate noninformative prior normal random normally distributed null hypothesis obtained plim point estimates posterior p.d.f. prior information prior p.d.f. probability problem procedure properties quadratic random variable random vector regression regressors residuals sample information sampling theory Section seemingly unrelated regression specification standard errors statistical model stochastic structural equation sum of squares Table test statistic time-series transformed unbiased estimator unknown parameters zero