Essential Econometric Techniques: A Guide to Concepts and Applications, 3rd Edition
- Length: 176 pages
- Edition: 3
- Language: English
- Publisher: Routledge
- Publication Date: 2022-02-21
- ISBN-10: 1032101229
- ISBN-13: 9781032101224
- Sales Rank: #0 (See Top 100 Books)
Now in its third edition, Essential Econometric Techniques: A Guide to Concepts and Applications is a concise, student-friendly textbook which provides an introductory grounding in econometrics, with an emphasis on the proper application and interpretation of results.
Drawing on the author’s extensive teaching experience, this book offers intuitive explanations of concepts such as heteroskedasticity and serial correlation, and provides step-by-step overviews of each key topic.
This new edition contains more applications, brings in new material including a dedicated chapter on panel data techniques, and moves the theoretical proofs to appendices. After chapter seven, students will be able to design and conduct rudimentary econometric research. The next chapters cover multicollinearity, heteroskedasticity and autocorrelation, followed by techniques for time-series analysis and panel data.
Excel data sets for the end-of-chapter problems are available as a digital supplement. A solutions manual is also available for instructors, as well as PowerPoint slides for each chapter.
Essential Econometric Techniques shows students how economic hypotheses can be questioned and tested using real-world data, and is the ideal supplementary text for all introductory econometrics courses.
Cover Endorsements Half Title Title Page Copyright Page Contents 1. The Nature of Econometrics What Is Econometrics? The Econometric Methodology Many Applications Terms Chapter 1 Problems 2. Simple Regression Analysis The Basic Idea Notation The Ordinary Least Squares Technique Example: Economic Performance and Corruption A Note on Econometric Software Terms Chapter 2 Problems Appendix to Chapter Deriving the Ordinary Least Squares Estimators Algebra of Summation Signs 3. Residual Statistics Measures of Goodness-of-Fit The Standard Errors of βˆ0 and βˆ1 Repeated Sampling Terms Chapter 3 Problems 4. Hypothesis Testing Test of Significance Confidence Intervals Positive Sign Test Negative Sign Test A Review of the Decision Rules Specific Value Test Test for r2 = Probability Values Terms Chapter 4 Problems 5. Multivariate Regression Parameter Estimation in Multivariate Regression The Intuition of Multivariate Regression The Variance and Standard Errors of the Estimators Goodness-of-Fit in Multivariate Regression An Illustrative Example with Hypothesis Testing Interpretations Hypothesis Testing Model Specification Underspecification Overspecification Unbiased and Best Estimators An Example of Searching for an Appropriate Econometric Model Terms Chapter 5 Problems APPENDIX to Chapter Deriving the Ordinary Least Squares Estimators with Two Explanatory Variables Degrees of Freedom 6. Alternate Functional Forms Regression through the Origin Units of Measurement and Estimates The Double-Log Model The Log-Lin Model The Lin-Log Model The Reciprocal Model The Polynomial Model Mixing and Matching Alternate Forms Finding the Correct Functional Form Terms Chapter 6 Problems Appendix to Chapter Derivation of βˆ1 with Regression through the Origin 7. Dichotomous Variables Dichotomous Variables Interactive Terms Linear Probability Models Interpretations Logistic Models Interpretations Predicting with Logistic Models Terms Chapter 7 Problems 8. The Classical Linear Regression Model The Ordinary Least Squares Estimators Are BLUE Linear Unbiased Best The Classical Linear Regression Model Terms Chapter 8 Problems Appendix to Chapter Proof That βˆ1 Is Unbiased Proof That βˆ0 Is Unbiased Proof That βˆ1 Is Best Proof That βˆ0 Is Best 9. Multicollinearity The Nature of Multicollinearity Perfect Multicollinearity Multicollinearity Defined Consequences of Multicollinearity Detecting Multicollinearity Remedies for Multicollinearity Terms Chapter 9 Problems 10. Heteroskedasticity What Is Heteroskedasticity? Consequences of Heteroskedasticity Detection The Graphical Approach The Park Test The White Test Remedies Weighted Least Squares Newey-West Standard Errors Terms Chapter 10 Problems 11. Serial Correlation What Is Serial Correlation? Consequences of Serial Correlation Detection The Graphical Approach The Durbin-Watson Test The Breusch-Godfrey Test Testing for Second-Order Serial Correlation Remedies OLS Technique Cochrane-Orcutt Iterative Procedure Hildreth-Lu Scanning Procedure Maximum Likelihood Procedure Final Thoughts Terms Chapter 11 Problems 12. Time-Series Techniques Time-Series Econometrics Distributed Lag Models The Koyck Model Granger Tests Spurious Correlation, Nonstationarity, and Cointegration ARIMA Models Autoregressive Models Moving Average Models Autoregressive Moving Average Models ARIMA Models The Maximum Likelihood Procedure A Complete Example Terms Chapter 12 Problems 13. Panel Data Techniques Panel Data Cross-Sectional Fixed Effects Models Time Fixed Effects Models Random Effects Model Robust Standard Errors Hausman Test An Illustrative Example Terms Chapter 13 Problems Critical Values Tables Critical Values of the t-Distribution Critical Values of the F-Distribution (5%) Critical Values of the χ2-Distribution Cited Works Index
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