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• Title Page
• Copyright Page
• The Pearson Series in Economics
• Contents
• Preface
• Chapter 1: An Overview of Regression Analysis
• 1.1. What Is Econometrics?
• 1.2. What Is Regression Analysis?
• 1.3. The Estimated Regression Equation
• 1.4. A Simple Example of Regression Analysis
• 1.5. Using Regression Analysis to Explain Housing Prices
• 1.6. Summary and Exercises
• 1.7. Appendix: Using Stata
• Chapter 2: Ordinary Least Squares
• 2.1. Estimating Single-Independent-Variable Models with OLS
• 2.2. Estimating Multivariate Regression Models with OLS
• 2.3. Evaluating the Quality of a Regression Equation
• 2.4. Describing the Overall Fit of the Estimated Model
• 2.5. An Example of the Misuse of R 2
• 2.6. Summary and Exercises
• 2.7. Appendix: Econometric Lab #1
• Chapter 3: Learning to Use Regression Analysis
• 3.1. Steps in Applied Regression Analysis
• 3.2. Using Regression Analysis to Pick Restaurant Locations
• 3.3. Dummy Variables
• 3.4. Summary and Exercises
• 3.5. Appendix: Econometric Lab #2
• Chapter 4: The Classical Model
• 4.1. The Classical Assumptions
• 4.2. The Sampling Distribution of
• 4.3. The Gauss–Markov Theorem and the Properties of OLS Estimators
• 4.4. Standard Econometric Notation
• 4.5. Summary and Exercises
• Chapter 5: Hypothesis Testing and Statistical Inference
• 5.1. What Is Hypothesis Testing?
• 5.2. The t-Test
• 5.3. Examples of t-Tests
• 5.4. Limitations of the t-Test
• 5.5. Confidence Intervals
• 5.6. The F-Test
• 5.7. Summary and Exercises
• 5.8. Appendix: Econometric Lab #3
• Chapter 6: Specification: Choosing the Independent Variables
• 6.1. Omitted Variables
• 6.2. Irrelevant Variables
• 6.3. An Illustration of the Misuse of Specification Criteria
• 6.4. Specification Searches
• 6.5. An Example of Choosing Independent Variables
• 6.6. Summary and Exercises
• 6.7. Appendix: Additional Specification Criteria
• Chapter 7: Specification: Choosing a Functional Form
• 7.1. The Use and Interpretation of the Constant Term
• 7.2. Alternative Functional Forms
• 7.3. Lagged Independent Variables
• 7.4. Slope Dummy Variables
• 7.5. Problems with Incorrect Functional Forms
• 7.6. Summary and Exercises
• 7.7. Appendix: Econometric Lab #4
• Chapter 8: Multicollinearity
• 8.1. Perfect versus Imperfect Multicollinearity
• 8.2. The Consequences of Multicollinearity
• 8.3. The Detection of Multicollinearity
• 8.4. Remedies for Multicollinearity
• 8.5. An Example of Why Multicollinearity Often Is Best Left Unadjusted
• 8.6. Summary and Exercises
• 8.7. Appendix: The SAT Interactive Regression Learning Exercise
• Chapter 9: Serial Correlation
• 9.1. Time Series
• 9.2. Pure versus Impure Serial Correlation
• 9.3. The Consequences of Serial Correlation
• 9.4. The Detection of Serial Correlation
• 9.5. Remedies for Serial Correlation
• 9.6. Summary and Exercises
• 9.7. Appendix: Econometric Lab #5
• Chapter 10: Heteroskedasticity
• 10.1. Pure versus Impure Heteroskedasticity
• 10.2. The Consequences of Heteroskedasticity
• 10.3. Testing for Heteroskedasticity
• 10.4. Remedies for Heteroskedasticity
• 10.5. A More Complete Example
• 10.6. Summary and Exercises
• 10.7. Appendix: Econometric Lab #6
• Chapter 11: Running Your Own Regression Project
• 11.1. Choosing Your Topic
• 11.2. Collecting Your Data
• 11.3. Advanced Data Sources
• 11.4. Practical Advice for Your Project
• 11.5. Writing Your Research Report
• 11.6. A Regression User’s Checklist and Guide
• 11.7. Summary
• 11.8. Appendix: The Housing Price Interactive Exercise
• Chapter 12: Time-Series Models
• 12.1. Distributed Lag Models
• 12.2. Dynamic Models
• 12.3. Serial Correlation and Dynamic Models
• 12.4. Granger Causality
• 12.5. Spurious Correlation and Nonstationarity
• 12.6. Summary and Exercises
• Chapter 13: Dummy Dependent Variable Techniques
• 13.1. The Linear Probability Model
• 13.2. The Binomial Logit Model
• 13.3. Other Dummy Dependent Variable Techniques
• 13.4. Summary and Exercises
• Chapter 14: Simultaneous Equations
• 14.1. Structural and Reduced-Form Equations
• 14.2. The Bias of Ordinary Least Squares
• 14.3. Two-Stage Least Squares (2SLS)
• 14.4. The Identification Problem
• 14.5. Summary and Exercises
• 14.6. Appendix: Errors in the Variables
• Chapter 15: Forecasting
• 15.1. What Is Forecasting?
• 15.2. More Complex Forecasting Problems
• 15.3. ARIMA Models
• 15.4. Summary and Exercises
• Chapter 16: Experimental and Panel Data
• 16.1. Experimental Methods in Economics
• 16.2. Panel Data
• 16.3. Fixed versus Random Effects
• 16.4. Summary and Exercises
• Appendix A: Answers
• Appendix B: Statistical Tables
• Index
• Back Cover