Using Econometrics: A Practical Guide, Global Edition

Höfundur: A. H. Studenmund (Útgáfa: 7)
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.

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Útgefandi
Pearson International Content
ISBN
9781787644281
Print ISBN
9781292154091
Format
ePub
Útgáfa
7
Höfundar
A. H. Studenmund
Tungumál
English
Útgefið
20190722
Prent takmörkun á líftíma
100
Prent takmörkun
2
Afritunar takmörkun
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