Using econometrics: a practical guide

✍ Scribed by Studenmund, Arnold H

• Publisher: Pearson
• Year: 2016;2017
• Tongue: English
• Leaves: 578
• Edition: Seventh edition, global edition
• Category: Library

✦ Synopsis

Using Econometrics: A Practical Guideoffers readers 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.
TheSeventh Editionis appropriate for all levels: beginner econometric readers, regression users seeking a refresher, and experienced practitioners who want a convenient reference. Praised as one of the most important texts in the last 30 years, the book retains its clarity and practicality in previous editions with a number of substantial improvements throughout.KEY TOPICS:An Overview of Regression Analysis; Ordinary Least Squares; Learning to Use Regression Analysis; The Classical Model; Hypothesis Testing and Statistical Inference; Specification: Choosing the Independent Variables; Specification: Choosing a Functional Form; Multicollinearity; Serial Correlation; Heteroskedasticity; Running Your Own Regression Project; Time-Series Models; Dummy Dependent Variable Techniques; Simultaneous Equations; Forecasting; Experimental and Panel DataMARKET:For anyone interested in econometrics.

✦ Table of Contents

Cover......Page 1
Title Page......Page 4
Copyright Page......Page 5
The Pearson Series in Economics......Page 7
Contents......Page 10
Preface......Page 14
1.1. What Is Econometrics?......Page 20
1.2. What Is Regression Analysis?......Page 24
1.3. The Estimated Regression Equation......Page 33
1.4. A Simple Example of Regression Analysis......Page 36
1.5. Using Regression Analysis to Explain Housing Prices......Page 39
1.6. Summary and Exercises......Page 42
1.7. Appendix: Using Stata......Page 49
2.1. Estimating Single-Independent-Variable Models with OLS......Page 54
2.2. Estimating Multivariate Regression Models with OLS......Page 59
2.3. Evaluating the Quality of a Regression Equation......Page 68
2.4. Describing the Overall Fit of the Estimated Model......Page 69
2.5. An Example of the Misuse of R 2......Page 74
2.6. Summary and Exercises......Page 76
2.7. Appendix: Econometric Lab #1......Page 82
Chapter 3: Learning to Use Regression Analysis......Page 84
3.1. Steps in Applied Regression Analysis......Page 85
3.2. Using Regression Analysis to Pick Restaurant Locations......Page 92
3.3. Dummy Variables......Page 98
3.4. Summary and Exercises......Page 102
3.5. Appendix: Econometric Lab #2......Page 108
4.1. The Classical Assumptions......Page 111
4.2. The Sampling Distribution of......Page 119
4.3. The Gauss–Markov Theorem and the Properties of OLS Estimators......Page 125
4.4. Standard Econometric Notation......Page 126
4.5. Summary and Exercises......Page 127
Chapter 5: Hypothesis Testing and Statistical Inference......Page 134
5.1. What Is Hypothesis Testing?......Page 135
5.2. The t-Test......Page 140
5.3. Examples of t-Tests......Page 148
5.4. Limitations of the t-Test......Page 156
5.5. Confidence Intervals......Page 158
5.6. The F-Test......Page 161
5.7. Summary and Exercises......Page 166
5.8. Appendix: Econometric Lab #3......Page 174
Chapter 6: Specification: Choosing the Independent Variables......Page 176
6.1. Omitted Variables......Page 177
6.2. Irrelevant Variables......Page 184
6.3. An Illustration of the Misuse of Specification Criteria......Page 186
6.4. Specification Searches......Page 188
6.5. An Example of Choosing Independent Variables......Page 193
6.6. Summary and Exercises......Page 196
6.7. Appendix: Additional Specification Criteria......Page 203
Chapter 7: Specification: Choosing a Functional Form......Page 208
7.1. The Use and Interpretation of the Constant Term......Page 209
7.2. Alternative Functional Forms......Page 211
7.3. Lagged Independent Variables......Page 221
7.4. Slope Dummy Variables......Page 222
7.5. Problems with Incorrect Functional Forms......Page 225
7.6. Summary and Exercises......Page 228
7.7. Appendix: Econometric Lab #4......Page 236
Chapter 8: Multicollinearity......Page 240
8.1. Perfect versus Imperfect Multicollinearity......Page 241
8.2. The Consequences of Multicollinearity......Page 245
8.3. The Detection of Multicollinearity......Page 251
8.4. Remedies for Multicollinearity......Page 254
8.5. An Example of Why Multicollinearity Often Is Best Left Unadjusted......Page 257
8.6. Summary and Exercises......Page 259
8.7. Appendix: The SAT Interactive Regression Learning Exercise......Page 264
Chapter 9: Serial Correlation......Page 292
9.1. Time Series......Page 293
9.2. Pure versus Impure Serial Correlation......Page 294
9.3. The Consequences of Serial Correlation......Page 300
9.4. The Detection of Serial Correlation......Page 303
9.5. Remedies for Serial Correlation......Page 310
9.6. Summary and Exercises......Page 315
9.7. Appendix: Econometric Lab #5......Page 322
Chapter 10: Heteroskedasticity......Page 325
10.1. Pure versus Impure Heteroskedasticity......Page 326
10.2. The Consequences of Heteroskedasticity......Page 331
10.3. Testing for Heteroskedasticity......Page 333
10.4. Remedies for Heteroskedasticity......Page 339
10.5. A More Complete Example......Page 343
10.6. Summary and Exercises......Page 349
10.7. Appendix: Econometric Lab #6......Page 357
Chapter 11: Running Your Own Regression Project......Page 359
11.1. Choosing Your Topic......Page 360
11.2. Collecting Your Data......Page 361
11.3. Advanced Data Sources......Page 365
11.4. Practical Advice for Your Project......Page 367
11.5. Writing Your Research Report......Page 371
11.6. A Regression User’s Checklist and Guide......Page 372
11.7. Summary......Page 376
11.8. Appendix: The Housing Price Interactive Exercise......Page 377
Chapter 12: Time-Series Models......Page 383
12.1. Distributed Lag Models......Page 384
12.2. Dynamic Models......Page 386
12.3. Serial Correlation and Dynamic Models......Page 390
12.4. Granger Causality......Page 393
12.5. Spurious Correlation and Nonstationarity......Page 395
12.6. Summary and Exercises......Page 404
13.1. The Linear Probability Model......Page 409
13.2. The Binomial Logit Model......Page 416
13.3. Other Dummy Dependent Variable Techniques......Page 423
13.4. Summary and Exercises......Page 425
Chapter 14: Simultaneous Equations......Page 430
14.1. Structural and Reduced-Form Equations......Page 431
14.2. The Bias of Ordinary Least Squares......Page 437
14.3. Two-Stage Least Squares (2SLS)......Page 440
14.4. The Identification Problem......Page 449
14.5. Summary and Exercises......Page 454
14.6. Appendix: Errors in the Variables......Page 459
Chapter 15: Forecasting......Page 462
15.1. What Is Forecasting?......Page 463
15.2. More Complex Forecasting Problems......Page 468
15.3. ARIMA Models......Page 475
15.4. Summary and Exercises......Page 478
Chapter 16: Experimental and Panel Data......Page 484
16.1. Experimental Methods in Economics......Page 485
16.2. Panel Data......Page 492
16.3. Fixed versus Random Effects......Page 502
16.4. Summary and Exercises......Page 503
Appendix A: Answers......Page 510
Appendix B: Statistical Tables......Page 536
Index......Page 550
Back Cover......Page 578

✦ Subjects

Economics;Academic;School;Nonfiction