Using Econometrics: A Practical Guide, Global Edition
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Using Econometrics: A Practical Guide veitir nemendum nýstárlega og hagnýta kynningu á grunnatriðum hagrannsókna. Með raunverulegum dæmum og verkefnum fjallar bókin á aðgengilegan hátt um línulega aðhvarfsgreiningu með einni jöfnu. Sjöunda útgáfan hentar byrjendum í hagrannsóknum, þeim sem vilja rifja upp aðhvarfsgreiningu og reyndum sérfræðingum sem þurfa handhæga uppflettibók.
For courses in Econometrics. A Clear, Practical Introduction to EconometricsUsing 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.
Nánar um bókina
- Pearson International Content
- 9781787644281
- 9781292154091
- ePub
- 7
- A. H. Studenmund
- English
- 20190722
- 100
- 2
- 2
Kaflar
- Cover
- Title
- Copyright
- 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 R2
- 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