Title Using Econometrics: A Practical Guide (7th Edition) 11.2 MB 578
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Inside Front Cover
Title Page
Dedication
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
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 238
8.6. Summary and Exercises
8.7. Appendix: The SAT Interactive Regression Learning Exercise 244
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
11.6. 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