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Klappentext Fundamentals of Applied Econometrics is designed for an applied, undergraduate econometrics course providing students with an understanding of the most fundamental econometric ideas and tools. The texts serves both the student whose interest is in understanding how one can use sample data to illuminate economic theory and the student who wants and needs a solid intellectual foundation on which to build practical experiential expertise. Starting with a unique Statistics review to start the book, students will learn by doing. Ashley provides students with integrated, hands-on exercises, and the text is supplemented with Active Learning Exercises. Zusammenfassung Fundamentals of Applied Econometrics is designed for an applied! undergraduate econometrics course providing students with an understanding of the most fundamental econometric ideas and tools. The texts serves both the student whose interest is in understanding how one can use sample data to illuminate economic theory and the student who wants and needs a solid intellectual foundation on which to build practical experiential expertise. Starting with a unique Statistics review to start the book! students will learn by doing. Ashley provides students with integrated! hands-on exercises! and the text is supplemented with Active Learning Exercises. Inhaltsverzeichnis 1. Introduction2. A Review of Probability Theory3. Estimating the Mean of a Normally Distributed Random Variable4. Statistical Inference on the Mean of a Normally Distributed RandomVariable5. The Bivariate Regression Model:(Introduction, Assumptions, and Parameter Estimates)6. The Bivariate Regression Model:(Sampling Distributions and Estimator Properties)7. The Bivariate Regression Model: Inference on ß8. The Bivariate Regression Model: R2 and Prediction9. The Multiple Regression Model10. Diagnostically Checking and Re-Specifying the Multiple RegressionModel: Dealing With Potential Outliers and Heteroscedasticity in theCross-Sectional Data Case11. Stochastic Regressors and Endogeneity12. Instrumental Variables Estimation13. Diagnostically Checking and Re-Specifying the Multiple Regression14. Diagnostically Checking and Re-Specifying the Multiple Regression15. Regression Modeling with Panel Data (Part A)16. Regression Modeling with Panel Data (Part B)17. A Concise Introduction to Time-Series Analysis and Forecasting18. A Concise Introduction to Time-Series Analysis and Forecasting19. Parameter Estimation Beyond Curve-Fitting: MLE (with an Applicationto Binary-Choice Models) and GMM (with an Application to IVRegression)20. Concluding Comments...
