Efnisyfirlit

• 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

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