Using Econometrics: A Practical Guide, Seventh Edition |
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Comment from the Stata technical groupUsing Econometrics, by A.H. Studenmund, provides an introduction to econometrics at the undergraduate level. The book covers classical linear regression and hypothesis testing, along with the complications involved with multicollinearity, serial correlation, and heteroskedasticity. Topic-specific chapters introduce time-series models, limited dependent variables, simultaneous equations, forecasting, and panel-data methods. This book distinguishes itself from others at this level by extensively covering model specification. The book contains numerous exercises, many with answers and hints, and most chapters conclude with an extended applied exercise that students work through using Stata. The book is accompanied by an online guide, "Using Stata," that mirrors the book chapter-by-chapter and explains the Stata commands needed to reproduce the examples described in the text. The online guide provides a bridge between the concepts described in Using Econometrics and the applied exercises that accompany each chapter. |
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Table of contentsView table of 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 \(\overline{R}^2\) 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 \(\hat{\beta}\) 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
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