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Informationen zum Autor Peter Kennedy is Professor of Economics at Simon Fraser University. In addition to A Guide to Econometrics , he is author of Macroeconomic Essentials: Understanding Economics in the News, 2e (2000), and is Associate Editor of the International Journal of Forecasting , the Journal of Economic Education , and Economics Bulletin . Klappentext This is the perfect (and essential) supplement for all econometrics classes--from a rigorous first undergraduate course, to a first master's, to a PhD course. It explains what is going on in textbooks full of proofs and formulas. Kennedy's A Guide to Econometrics offers intuition, skepticism, insights, humor, and practical advice (do's and don'ts). The sixth edition contains new chapters on instrumental variables and on computation considerations, more information on GMM and nonparametrics, and an introduction to wavelets. Zusammenfassung This is the perfect (and essential) supplement for all econometrics classes--from a rigorous first undergraduate course, to a first master's, to a PhD course. It explains what is going on in textbooks full of proofs and formulas. Kennedy's A Guide to Econometrics offers intuition, skepticism, insights, humor, and practical advice (do's and don'ts). Inhaltsverzeichnis Preface. Dedication. 1. Introduction. 1.1 What is Econometrics?. 1.2 The Disturbance Term. 1.3 Estimates and Estimators. 1.4 Good and Preferred Estimators. General Notes. Technical Notes. 2. Criteria for Estimators. 2.1 Introduction. 2.2 Computational Cost. 2.3 Least Squares. 2.4 Highest R2. 2.5 Unbiasedness. 2.6 Efficiency. 2.7 Mean Square Error (MSE). 2.8 Asymptotic Properties. 2.9 Maximum Likelihood. 2.10 Monte Carlo Studies. 2.11 Adding Up. General Notes. Technical Notes. 3. The Classical Linear Regression Model. 3.1 Textbooks as Catalogs. 3.2 The Five Assumptions. 3.3 The OLS Estimator in the CLR Model. General Notes. Technical Notes. 4. Interval Estimation and Hypothesis Testing. 4.1 Introduction. 4.2 Testing a Single Hypothesis: the t Test. 4.3 Testing a Joint Hypothesis: the F Test. 4.4 Interval Estimation for a Parameter Vector. 4.5 LR, W, and LM Statistics. 4.6 Bootstrapping. General Notes. Technical Notes. 5. Specification. 5.1 Introduction. 5.2 Three Methodologies. 5.3 General Principles for Specification. 5.4 Misspecification Tests/Diagnostics. 5.5 R2 Again. General Notes. Technical Notes. 6. Violating Assumption One: Wrong Regressors, Nonlinearities, and Parameter Inconstancy. 6.1 Introduction. 6.2 Incorrect Set of Independent Variables. 6.3 Nonlinearity. 6.4 Changing Parameter Values. General Notes. Technical Notes. 7. Violating Assumption Two: Nonzero Expected Disturbance . General Notes. 8. Violating Assumption Three: Nonspherical Disturbances . 8.1 Introduction. 8.2 Consequences of Violation. 8.3 Heteroskedasticity. 8.4 Autocorrelated Disturbances. 8.5 Generalized Method of Moments. General Notes. Technical Notes. 9. Violating Assumption Four: Instrumental Variable Estimation . 9.1 Introduction. 9.2 The IV Estimator. 9.3 IV Issues. General Notes. Technical Notes. 10. Violating Assumption Four: Measurement Errors and Autoregression . 10.1 Errors in Variables. 10.2 Autoregression. General Notes. Technical Notes. 11. Violating Assumption Four: Simultaneous Equations . 11.1 Introduction. 11.2...
