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Preface | |
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Data, Solutions, and Corrections | |
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Regression Models | |
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Introduction | |
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Distributions, Densities, and Moments | |
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The Specification of Regression Models | |
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Matrix Algebra | |
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Method-of-Moments Estimation | |
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Notes on Exercises | |
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Exercises | |
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The Geometry of Linear Regression | |
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Introduction | |
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The Geometry of Vector Spaces | |
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The Geometry of OLS Estimation | |
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The Frisch-Waugh-Lowell Theorem | |
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Applications of the FWL Theorem | |
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Influential Observations and Leverage | |
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Final Remarks | |
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Exercises | |
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The Statistical Properties of Ordinary Least Squares | |
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Introduction | |
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Are OLS Parameter Estimators Unbiased? | |
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Are OLS Parameter Estimators Consistent? | |
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The Covariance Matrix of the OLS Parameter Estimates | |
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Efficiency of the OLS Estimator | |
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Residuals and Error Terms | |
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Misspecification of Linear Regression Models | |
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Measures of Goodness of Fit | |
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Final Remarks | |
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Exercises | |
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Hypothesis Testing in Linear Regression Models | |
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Introduction | |
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Basic Ideas | |
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Some Common Distractions | |
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Exact Tests in the Classical Normal Linear Model | |
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Large-Sample Tests in Linear Regression Models | |
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Simulation-Based Tests | |
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The Power of Hypothesis Tests | |
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Final Remarks | |
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Exercises | |
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Confidence Intervals | |
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Introduction | |
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Exact and Asymptotic Confidence Intervals | |
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Bootstrap Confidence Intervals | |
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Confidence Regions | |
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Heteroskedasticity-Consistent Covariance Matrices | |
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The Delta Method | |
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Final Remarks | |
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Exercises | |
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Nonlinear Regression | |
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Introduction | |
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Method-of-Moments Estimators for Nonlinear Models | |
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Nonlinear Least Squares | |
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Computing NLS Estimates | |
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The Gauss-Newton Regression | |
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One-Step Estimation | |
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Hypothesis Testing | |
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Heteroskedasticity-Robust Tests | |
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Final Remarks | |
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Exercises | |
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Generalized Least Squares and Related Topics | |
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Introduction | |
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The GLS Eliminator | |
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Computing GLS Estimates | |
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Feasible Generalized Least Squares | |
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Heteroskedasticity | |
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Autoregressive and Moving-Average Processes | |
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Testing for Serial Correlation | |
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Estimating Models with Autoregressive Errors | |
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Specification Testing and Serial Correlation | |
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Models for Panel Data | |
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Final Remarks | |
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Exercises | |
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Instrumental Variables Estimation | |
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Introduction | |
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Correlation Between Error Terms and Regressors | |
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Instrumental Variables Estimation | |
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Finite-Sample Properties of IV Estimators | |
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Hypothesis Testing | |
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Testing Overidentifying Restrictions | |
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Durbin-Wu-Hausman Tests | |
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Bootstrap Tests | |
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IV Estimation of Nonlinear Models | |
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Final Remarks | |
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Exercises | |
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The Generalized Methods of Moments | |
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Introduction | |
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GMM Estimators for Linear Regression Models | |
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HAC Covariance Matrix Estimation | |
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Tests Based on the GMM Criterion Function | |
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GMM Estimators for Nonlinear Models | |
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The Method of Simulated Moments | |
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Final Remarks | |
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Exercises | |
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The Method of Maximum Likelihood | |
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Introduction | |
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Basic Concepts of Maximum Likelihood Estimation | |
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Asymptotic Propertied of ML Estimators | |
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The Covariance Matrix of the ML Estimator | |
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Hypothesis Testing | |
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The Asymptotic Theory of the Three Classical Tests | |
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ML Estimation of Models with Autoregressive Errors | |
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Transformations of the Dependent Variable | |
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Final Remarks | |
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Exercises | |
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Discrete and Limited Dependent Variables | |
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Introduction1 | |
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Binary Response Models: Estimation1 | |
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Binary Response Models: Inference | |
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Models for More than Two Discrete Responses | |
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Models for Count Data | |
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Models for Censored and Truncated Data | |
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Sample Selectivity | |
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Duration Models | |
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Final Remarks | |
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Exercises | |
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Multivariate Models | |
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Introduction | |
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Seemingly Unrelated Linear Regressions | |
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Systems of Nonlinear Regressions | |
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Linear Simultaneous Equations Models | |
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Maximum Likelihood Estimation | |
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Nonlinear Simultaneous Equations Models | |
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Final Remarks | |
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Appendix: Detailed Results on FIML and LIML | |
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Exercises | |
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Methods for Stationary Time-Series Data | |
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Introduction | |