Additional Information
Book Details
Abstract
For courses in Econometrics.
A Clear, Practical Introduction to Econometrics
Using Econometrics: A Practical Guide offers students an innovative introduction to elementary econometrics. Through real-world examples and exercises, the book covers the topic of single-equation linear regression analysis in an easily understandable format.
The Seventh Edition is appropriate for all levels: beginner econometric students, regression users seeking a refresher, and experienced practitioners who want a convenient reference. Praised as one of the most important texts in the last 30 years, the book retains its clarity and practicality in previous editions with a number of substantial improvements throughout.
Table of Contents
| Section Title | Page | Action | Price |
|---|---|---|---|
| Cover | Cover | ||
| Title Page | 3 | ||
| Copyright Page | 4 | ||
| The Pearson Series in Economics | 6 | ||
| Contents | 9 | ||
| Preface | 13 | ||
| Chapter 1: An Overview of Regression Analysis | 19 | ||
| 1.1. What Is Econometrics? | 19 | ||
| 1.2. What Is Regression Analysis? | 23 | ||
| 1.3. The Estimated Regression Equation | 32 | ||
| 1.4. A Simple Example of Regression Analysis | 35 | ||
| 1.5. Using Regression Analysis to Explain Housing Prices | 38 | ||
| 1.6. Summary and Exercises | 41 | ||
| 1.7. Appendix: Using Stata | 48 | ||
| Chapter 2: Ordinary Least Squares | 53 | ||
| 2.1. Estimating Single-Independent-Variable Models with OLS | 53 | ||
| 2.2. Estimating Multivariate Regression Models with OLS | 58 | ||
| 2.3. Evaluating the Quality of a Regression Equation | 67 | ||
| 2.4. Describing the Overall Fit of the Estimated Model | 68 | ||
| 2.5. An Example of the Misuse of R 2 | 73 | ||
| 2.6. Summary and Exercises | 75 | ||
| 2.7. Appendix: Econometric Lab | 81 | ||
| Chapter 3: Learning to Use Regression Analysis | 83 | ||
| 3.1. Steps in Applied Regression Analysis | 84 | ||
| 3.2. Using Regression Analysis to Pick Restaurant Locations | 91 | ||
| 3.3. Dummy Variables | 97 | ||
| 3.4. Summary and Exercises | 101 | ||
| 3.5. Appendix: Econometric Lab | 107 | ||
| Chapter 4: The Classical Model | 110 | ||
| 4.1. The Classical Assumptions | 110 | ||
| 4.2. The Sampling Distribution of | 118 | ||
| 4.3. The Gauss–Markov Theorem and the Properties of OLS Estimators | 124 | ||
| 4.4. Standard Econometric Notation | 125 | ||
| 4.5. Summary and Exercises | 126 | ||
| Chapter 5: Hypothesis Testing and Statistical Inference | 133 | ||
| 5.1. What Is Hypothesis Testing? | 134 | ||
| 5.2. The t-Test | 139 | ||
| 5.3. Examples of t-Tests | 147 | ||
| 5.4. Limitations of the t-Test | 155 | ||
| 5.5. Confidence Intervals | 157 | ||
| 5.6. The F-Test | 160 | ||
| 5.7. Summary and Exercises | 165 | ||
| 5.8. Appendix: Econometric Lab | 173 | ||
| Chapter 6: Specification: Choosing the Independent Variables | 175 | ||
| 6.1. Omitted Variables | 176 | ||
| 6.2. Irrelevant Variables | 183 | ||
| 6.3. An Illustration of the Misuse of Specification Criteria | 185 | ||
| 6.4. Specification Searches | 187 | ||
| 6.5. An Example of Choosing Independent Variables | 192 | ||
| 6.6. Summary and Exercises | 195 | ||
| 6.7. Appendix: Additional Specification Criteria | 202 | ||
| Chapter 7: Specification: Choosing a Functional Form | 207 | ||
| 7.1. The Use and Interpretation of the Constant Term | 208 | ||
| 7.2. Alternative Functional Forms | 210 | ||
| 7.3. Lagged Independent Variables | 220 | ||
| 7.4. Slope Dummy Variables | 221 | ||
| 7.5. Problems with Incorrect Functional Forms | 224 | ||
| 7.6. Summary and Exercises | 227 | ||
| 7.7. Appendix: Econometric Lab | 235 | ||
| Chapter 8: Multicollinearity | 239 | ||
| 8.1. Perfect versus Imperfect Multicollinearity | 240 | ||
| 8.2. The Consequences of Multicollinearity | 244 | ||
| 8.3. The Detection of Multicollinearity | 250 | ||
| 8.4. Remedies for Multicollinearity | 253 | ||
| 8.5. An Example of Why Multicollinearity Often Is Best Left Unadjusted | 256 | ||
| 8.6. Summary and Exercises | 258 | ||
| 8.7. Appendix: The SAT Interactive Regression Learning Exercise | 263 | ||
| Chapter 9: Serial Correlation | 291 | ||
| 9.1. Time Series | 292 | ||
| 9.2. Pure versus Impure Serial Correlation | 293 | ||
| 9.3. The Consequences of Serial Correlation | 299 | ||
| 9.4. The Detection of Serial Correlation | 302 | ||
| 9.5. Remedies for Serial Correlation | 309 | ||
| 9.6. Summary and Exercises | 314 | ||
| 9.7. Appendix: Econometric Lab | 321 | ||
| Chapter 10: Heteroskedasticity | 324 | ||
| 10.1. Pure versus Impure Heteroskedasticity | 325 | ||
| 10.2. The Consequences of Heteroskedasticity | 330 | ||
| 10.3. Testing for Heteroskedasticity | 332 | ||
| 10.4. Remedies for Heteroskedasticity | 338 | ||
| 10.5. A More Complete Example | 342 | ||
| 10.6. Summary and Exercises | 348 | ||
| 10.7. Appendix: Econometric Lab | 356 | ||
| Chapter 11: Running Your Own Regression Project | 358 | ||
| 11.1. Choosing Your Topic | 359 | ||
| 11.2. Collecting Your Data | 360 | ||
| 11.3. Advanced Data Sources | 364 | ||
| 11.4. Practical Advice for Your Project | 366 | ||
| 11.5. Writing Your Research Report | 370 | ||
| 11.6. A Regression User’s Checklist and Guide | 371 | ||
| 11.7. Summary | 375 | ||
| 11.8. Appendix: The Housing Price Interactive Exercise | 376 | ||
| Chapter 12: Time-Series Models | 382 | ||
| 12.1. Distributed Lag Models | 383 | ||
| 12.2. Dynamic Models | 385 | ||
| 12.3. Serial Correlation and Dynamic Models | 389 | ||
| 12.4. Granger Causality | 392 | ||
| 12.5. Spurious Correlation and Nonstationarity | 394 | ||
| 12.6. Summary and Exercises | 403 | ||
| Chapter 13: Dummy Dependent Variable Techniques | 408 | ||
| 13.1. The Linear Probability Model | 408 | ||
| 13.2. The Binomial Logit Model | 415 | ||
| 13.3. Other Dummy Dependent Variable Techniques | 422 | ||
| 13.4. Summary and Exercises | 424 | ||
| Chapter 14: Simultaneous Equations | 429 | ||
| 14.1. Structural and Reduced-Form Equations | 430 | ||
| 14.2. The Bias of Ordinary Least Squares | 436 | ||
| 14.3. Two-Stage Least Squares (2SLS) | 439 | ||
| 14.4. The Identification Problem | 448 | ||
| 14.5. Summary and Exercises | 453 | ||
| 14.6. Appendix: Errors in the Variables | 458 | ||
| Chapter 15: Forecasting | 461 | ||
| 15.1. What Is Forecasting? | 462 | ||
| 15.2. More Complex Forecasting Problems | 467 | ||
| 15.3. ARIMA Models | 474 | ||
| 15.4. Summary and Exercises | 477 | ||
| Chapter 16: Experimental and Panel Data | 483 | ||
| 16.1. Experimental Methods in Economics | 484 | ||
| 16.2. Panel Data | 491 | ||
| 16.3. Fixed versus Random Effects | 501 | ||
| 16.4. Summary and Exercises | 502 | ||
| Appendix A: Answers | 509 | ||
| Appendix B: Statistical Tables | 535 | ||
| Index | 549 | ||
| Back Cover | Back Cover |