## Sturdy econometricsEdward E. Leamer s creative and influential essays on the separation of robust from fragile inferences are collected together in Sturdy Econometrics. The econometric topics discussed include the choice of variables, choice of error process, measurement errors, simultaneity, the partial elicitation of prior distributions, and hypothesis discovery. Included in this volume is the popular piece Let s Take the Con out of Econometrics , and 25 other essays, plus an entertaining and provocative introduction. As Professor Leamer argues, the gap between econometric theory and econometric practice is very large, but the proper goal of econometric theory is to improve the practice rather than to narrow this gap. Sturdy Econometrics is a major contribution to this process by making Edward Leamer s essays more accessible to students, teachers and practitioners. |

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### Contents

Global Sensitivity Results for Generalized Least Squares Estimates | 209 |

Sets of Estimates of Location Econometrica 491 January | 229 |

Robust Sets of Regression Estimates with C Zachary Gilstein | 247 |

Copyright | |

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### Common terms and phrases

assumed assumption Bayesian analysis Bayesian Inference bound Chamberlain choice coefficients collinearity collinearity problem computed constraints contract curve convex correlation curve decolletage data analysis data set defined definite dependent diagonal distributed lag doubtful variables Econometric Econometrica Edward effect elicitation diagnostics ellipsoid equal equation example expected explanatory variables family of prior given hypothesis identify implies imprecision indicates inequality inferences inflation interval Journal Keynesian LEAMER least squares estimates Lemma likelihood function linear combination linear regression marginal likelihood Matrix Weighted Averages maximum likelihood estimates measurement error monetarist normal distribution observations orthant parameters positive posterior distribution posterior mean precision matrix pretesting prior covariance matrix prior distribution prior information prior mean prior variance probability Proof random REGRESSION ESTIMATES residual restrictions result sample evidence sensitivity analysis set of estimates set of maximum standard error symmetric Theorem theory tion unemployment vector weighted regressions zero