Real stats: using econometrics for political science and public policy
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
New York ; Oxford
Oxford University Press
[2016]
|
| Ausgabe: | 1st edition |
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029405222&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Beschreibung: | Includes bibliographical references (pages 559-566) and index |
| Umfang: | xxxii, 592 Seiten Diagramme 24 cm |
| ISBN: | 9780199981946 |
Internformat
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| 100 | 1 | |a Bailey, Michael A. |d 1969- |0 (DE-588)1018150501 |4 aut | |
| 245 | 1 | 0 | |a Real stats |b using econometrics for political science and public policy |c Michael A. Bailey |
| 250 | |a 1st edition | ||
| 264 | 1 | |a New York ; Oxford |b Oxford University Press |c [2016] | |
| 300 | |a xxxii, 592 Seiten |b Diagramme |c 24 cm | ||
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| 500 | |a Includes bibliographical references (pages 559-566) and index | ||
| 650 | 4 | |a Wirtschaft | |
| 650 | 4 | |a Econometrics | |
| 650 | 4 | |a Economics |x Statistical methods | |
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Datensatz im Suchindex
| _version_ | 1819269487166226432 |
|---|---|
| adam_text | Real Stats
Using Econometrics for
Political Science and Publ
Policy
Michael A Bailey
ULB Darmstadt
llllllllllllllllll
19607380
New York Oxford
OXFORD UNIVERSITY PRESS
CONTENTS
List of Figures ix
List of Tables xiii
Useful Commands for Stata xviii
Useful Commands for R xx
Preface for Students: How This Book Can Help You Learn Statistics xxii
Preface for Instructors: How to Help Your Students Learn Statistics xxvi
Acknowledgments xxxii
1
The Quest for Causality 1
1 1 The Core Model
1 2 Two Challenges: Randomness and Endogeneity
1 3 Randomized Experiments as the Gold Standard
Conclusion 22 • Key Terms 23
2
7
18
2
Stats in the Wild: Good Data Practices
24
2 1 Know Our Data
2 2 Replication
2 3 Statistical Software
26
28
32
Conclusion 33 • Further Reading 33 • Key Terms 34 • Computing
Comer 34 • Exercises 39
THE OLS FRAMEWORK 43
Bivariate OLS: The Foundation of Statistical Analysis
45
31B ivariate Regres sion Model
47
hi
iv CONTENTS
3 2 Random Variation in Coefficient Estimates 53
3 3 Exogeneity and Unbiasedness 57
3 4 Precision of Estimates 61
3 5 Probability Limits and Consistency 65
3 6 Solvable Problems: Heteroscedasticity and Correlated Errors 67
3 7 Goodness of Fit 70
3 8 Outliers 76
Conclusion 79 • Further Reading 81 • Key Terms 81 • Computing
Comer 81 • Exercises 86
B Hypothesis Testing and Interval Estimation:
Answering Research Questions 91
4 1 Hypothesis Testing 92
42t Tests 98
43p Values 106
4 4 Power 109
4 5 Straight Talk about Hypothesis Testing 115
4 6 Confidence Intervals 117
Conclusion 120 • Further Reading 120 • Key Terms 121
• Computing Comer 121 • Exercises 123
5
5 1 Using Multivariate OLS to Fight Endogeneity 130
5 2 Omitted Variable Bias 138
5 3 Measurement Error 144
5 4 Precision and Goodness of Fit 147
5 5 Model Specification 156
Conclusion 158 • Further Reading 159 • Key Terms 160
• Computing Comer 160 • Exercises 161
6
6 1 Using Bivariate OLS to Assess Difference of Means 168
6 2 Dummy Independent Variables in Multivariate OLS 178
CONTENTS V
6 3 Transforming Categorical Variables to Multiple Dummy Variables 181
6 4 Interaction Variables 190
Conclusion 199 • Further Reading 200 • Key Terms 200
• Computing Corner 200 • Exercises 201
Transforming Variables, Comparing Variables 207
7 1 Quadratic and Polynomial Models
7 2 Logged Variables
7 3 Standardized Coefficients
7 4 Hypothesis Testing about Multiple Coefficients
Conclusion 234 • Further Reading 235 • Key Terms 235
• Computing Corner 235 • Exercises 239
208
218
223
226
II THE CONTEMPORARY STATISTICAL TOOLKIT 245
8
Using Fixed Effects Models to Fight Endogeneity
in Panel Data and Difference-in-Difference Models 247
8 1 The Problem with Pooling 248
8 2 Fixed Effects Models 253
8 3 Working with Fixed Effects Models 259
8 4 Two-Way Fixed Effects Model 263
8 5 Difference-in-Difference 268
Conclusion 274 • Further Reading 275 • Key Terms 276
• Computing Corner 276 • Exercises 280
9
Instrumental Variables: Using Exogenous Variation
to Fight Endogeneity 287
9 1 2SLS Example
9 2 Two-Stage Least Squares (2SLS)
9 3 Multiple Instruments
9 4 Weak Instruments
288
290
301
302
Vi CONTENTS
9 5 Precision of 2SLS 305
9 6 Simultaneous Equation Models 307
Conclusion 315 • Further Reading 316 • Key Terms 316
• Computing Comer 317 • Exercises 318
10
10 1 Randomization and Balance 327
10 2 Compliance and Intention-to-Treat Models 332
10 3 Using 2SLS to Deal with Non-compliance 338
10 4 Attrition 346
10 5 Natural Experiments 352
Conclusion 355 • Further Reading 357 • Key Terms 357
• Computing Corner 357 • Exercises 358
Regression Discontinuity: Looking for Jumps in Data 365
11 1 Basic RD Model 367
11 2 More Flexible RD Models 372
11 3 Windows and Bins 378
11 4 Limitations and Diagnostics 383
Conclusion 389 • Further Reading 390 • Key Terms 390
• Computing Corner 391 • Exercises 392
III LIMITED DEPENDENT VARIABLES 399
12
12 1 Linear Probability Model 402
12 2 Using Latent Variables to Explain Observed Variables 406
12 3 Probit and Logit Models 410
12 4 Estimation 415
12 5 Interpreting Probit and Logit Coefficients 418
12 6 Hypothesis Testing about Multiple Coefficients 427
CONTENTS VM
Conclusion 433 • Further Reading 434 • Key Terms 434
• Computing Corner 435 • Exercises 439
IV ADVANCED MATERIAL 447
13
Time Series: Dealing with Stickiness over Time 449
13 1 Modeling Autocorrelation
13 2 Detecting Autocorrelation
13 3 Fixing Autocorrelation
13 4 Dynamic Models
13 5 Stationarity
Conclusion 475 • Further Reading 476 • Key Terms 477
• Computing Corner 477 • Exercises 479
450
453
457
462
465
14
Advanced OLS
481
14 1 How to Derive the OLS Estimator and Prove Unbiasedness
14 2 How to Derive the Equation for the Variance of ß
14 3 How to Derive the Omitted Variable Bias Conditions
14 4 Anticipating the Sign of Omitted Variable Bias
14 5 Omitted Variable Bias with Multiple Variables
14 6 Omitted Variable Bias due to Measurement Error
Conclusion 497 • Further Reading 497 • Key Term 498
• Computing Comer 498 • Exercises 498
481
487
489
491
494
495
15
Advanced Panel Data 501
15 1 Panel Data Models with Serially Correlated Errors
15 2 Temporal Dependence with a Lagged Dependent Variable
15 3 Random Effects Models
Conclusion 509 • Further Reading 509 • Key Term 510
• Computing Corner 510 • Exercises 513
501
503
507
VÜi CONTENTS
16
Conclusion: How to Be a Statistical Realist
516
Further Reading 520
APPENDICES
Math and Probability Background 521
A Summation 521
B Expectation 521
C Variance 522
D Covariance 523
E Correlation 524
F Probability Density Functions 524
G Normal Distributions 526
H Other Useful Distributions 532
I Sampling 534
Further Reading 537 • Key Terms 537 • Computing Comer 537
Citations and Additional Notes 539
Guide to Review Questions 549
Bibliography/Credits 559
Glossary 568
|
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| discipline | Politologie Wirtschaftswissenschaften |
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| indexdate | 2024-12-20T17:50:49Z |
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| isbn | 9780199981946 |
| language | English |
| lccn | 015032221 |
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| physical | xxxii, 592 Seiten Diagramme 24 cm |
| publishDate | 2016 |
| publishDateSearch | 2016 |
| publishDateSort | 2016 |
| publisher | Oxford University Press |
| record_format | marc |
| spellingShingle | Bailey, Michael A. 1969- Real stats using econometrics for political science and public policy Wirtschaft Econometrics Economics Statistical methods Statistik (DE-588)4056995-0 gnd Politische Wissenschaft (DE-588)4076229-4 gnd |
| subject_GND | (DE-588)4056995-0 (DE-588)4076229-4 (DE-588)4123623-3 |
| title | Real stats using econometrics for political science and public policy |
| title_auth | Real stats using econometrics for political science and public policy |
| title_exact_search | Real stats using econometrics for political science and public policy |
| title_full | Real stats using econometrics for political science and public policy Michael A. Bailey |
| title_fullStr | Real stats using econometrics for political science and public policy Michael A. Bailey |
| title_full_unstemmed | Real stats using econometrics for political science and public policy Michael A. Bailey |
| title_short | Real stats |
| title_sort | real stats using econometrics for political science and public policy |
| title_sub | using econometrics for political science and public policy |
| topic | Wirtschaft Econometrics Economics Statistical methods Statistik (DE-588)4056995-0 gnd Politische Wissenschaft (DE-588)4076229-4 gnd |
| topic_facet | Wirtschaft Econometrics Economics Statistical methods Statistik Politische Wissenschaft Lehrbuch |
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