Download Using Econometrics: A Practical Guide (7th Edition) PDF

TitleUsing Econometrics: A Practical Guide (7th Edition)
File Size11.2 MB
Total Pages578
Table of Contents
Inside Front Cover
Title Page
Copyright Page
The Pearson Series in Economics
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 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
	11.1. 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

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