Identification for prediction and decision:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cambridge, Mass. [u.a.]
Harvard Univ. Press
2007
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Inhaltsverzeichnis |
| Beschreibung: | Literaturverz. S. [321] - 337 |
| Beschreibung: | XIV, 348 S. |
| ISBN: | 0674026535 9780674026537 |
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| 650 | 4 | |a Toma de decisiones | |
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| adam_text | Contents
Preface xiii
Introduction 1
The Reflection Problem /
The Law of Decreasing Credibility 2
Identification and Statistical Inference 3
Prediction and Decisions 6
Coping with Ambiguity 6
Organization of the Book 8
The Developing Literature on Partial Identification //
I Prediction with Incomplete Data
1 Conditional Prediction 17
1.1 Predicting Criminality 17
1.2 Probabilistic Prediction 18
1.3 Estimation of Best Predictors from Random
Samples 22
1.4 Extrapolation 25
1.5 Predicting High School Graduation 28
Complement 1A. Best Predictors under Square and Absolute
Loss 30
Complement IB. Nonparametric Regression Analysis 32
Complement 1C. Word Problems 34
Contents
2 Missing Outcomes 36
2.1 Anatomy of the Problem 37
2.2 Bounding the Probability of Exiting Homelessness 40
2.3 Means of Functions of the Outcome 42
2.4 Parameters That Respect Stochastic Dominance 44
2.5 Distributional Assumptions 45
2.6 Wage Regressions and the Reservation Wage Model of
Labor Supply 48
2.7 Statistical Inference 5/
Complement 2A. Interval Measurement of Outcomes 54
Complement 2B. Jointly Missing Outcomes and
Covariates 56
Complement 2C. Convergence of Sets to Sets 60
3 Instrumental Variables 62
3.1 Distributional Assumptions and Credible Inference 62
3.2 Missingness at Random 64
3.3 Statistical Independence 66
3.4 Equality of Means 69
3.5 Inequality of Means 71
Complement 3A. Imputations and Nonresponse Weights 73
Complement 3B. Conditioning on the Propensity Score 75
Complement 3C. Word Problems 76
4 Parametric Prediction 83
4.1 The Normal Linear Model of Market and
Reservation Wages 83
4.2 Selection Models 87
4.3 Parametric Models for Best Predictors 89
Complement 4A. Minimum Distance Estimation of Partially
Identified Models 91
5 Decomposition of Mixtures 94
5.1 The Inferential Problem and Some Manifestations 94
5.2 Binary Mixing Covariates 98
5.3 Contamination through Imputation 102
5.4 Instrumental Variables 105
Complement 5A. Sharp Bounds on Parameters That Respect
Stochastic Dominance 107
6 Response Based Sampling 109
6.1 The Odds Ratio and Public Health 110
6.2 Bounds on Relative and Attributable Risk 114
Contents
6.3 Information on Marginal Distributions 118
6.4 Sampling from One Response Stratum 119
6.5 General Binary Stratifications 122
II Analysis of Treatment Response
7 The Selection Problem 127
7.1 Anatomy of the Problem 128
7.2 Sentencing and Recidivism 134
13 Randomized Experiments 136
1A Compliance with Treatment Assignment 140
7.5 Treatment by Choice 148
7.6 Treatment at Random in Nonexperimental Settings 151
7.7 Homogeneous Linear Response 153
Complement 7A. Perspectives on Treatment Comparison 157
Complement 7B. Word Problems 160
8 Linear Simultaneous Equations 167
8.1 Simultaneity in Competitive Markets 167
8.2 The Linear Market Model 170
8.3 Equilibrium in Games 174
8.4 The Reflection Problem 177
9 Monotone Treatment Response 183
9.1 Shape Restrictions 183
9.2 Bounds on Parameters That Respect Stochastic
Dominance 186
9.3 Bounds on Treatment Effects 189
9.4 Monotone Response and Selection 191
9.5 Bounding the Returns to Schooling 193
10 The Mixing Problem 198
10.1 Extrapolation from Experiments to Rules with Treatment
Variation 198
10.2 Extrapolation from the Perry Preschool Experiment 200
10.3 Identification of Event Probabilities with the Experimental
Evidence Alone 204
10.4 Treatment Response Assumptions 206
10.5 Treatment Rule Assumptions 207
10.6 Combining Assumptions 210
Contents
11 Planning under Ambiguity 211
11.1 Studying Treatment Response to Inform Treatment
Choice 211
11.2 Criteria for Choice under Ambiguity 214
11.3 Treatment Using Data from an Experiment with Partial
Compliance 218
11.4 An Additive Planning Problem 222
11.5 Planning with Partial Knowledge of Treatment
Response 226
11.6 Planning and the Selection Problem 229
11.7 The Ethics of Fractional Treatment Rules 233
11.8 Decentralized Treatment Choice 235
Complement 11 A. Minimax Regret Rules for Two Treatments
Are Fractional 237
Complement 1 IB. Reporting Observable Variation in Treatment
Response 239
Complement 11C. Word Problems 241
12 Planning with Sample Data 243
12.1 Statistical Induction 243
12.2 Wald s Development of Statistical Decision Theory 245
12.3 Using a Randomized Experiment to Evaluate an
Innovation 250
III Predicting Choice Behavior
13 Revealed Preference Analysis 259
13.1 Revealing the Preferences of an Individual 260
13.2 Random Utility Models of Population Choice
Behavior 263
13.3 College Choice in America 270
13.4 Random Expected Utility Models 274
Complement 13A. Prediction Assuming Strict
Preferences 278
Complement 13B. Axiomatic Decision Theory 282
14 Measuring Expectations 284
14.1 Elicitation of Expectations from Survey
Respondents 285
14.2 Illustrative Findings 290
Contents :
14.3 Using Expectations Data to Predict Choice
Behavior 295
14.4 Measuring Ambiguity 298
Complement 14A. The Predictive Power of Intentions Data: A
Best Case Analysis 300
Complement 14B. Measuring Expectations of Facts 305
15 Studying Human Decision Processes 308
15.1 As If Rationality and Bounded Rationality 309
15.2 Choice Experiments 312
15.3 Prospects for a Neuroscientific Synthesis 317
References 321
Author Index 339
Subject Index 343
|
| adam_txt |
Contents
Preface xiii
Introduction 1
The Reflection Problem /
The Law of Decreasing Credibility 2
Identification and Statistical Inference 3
Prediction and Decisions 6
Coping with Ambiguity 6
Organization of the Book 8
The Developing Literature on Partial Identification //
I Prediction with Incomplete Data
1 Conditional Prediction 17
1.1 Predicting Criminality 17
1.2 Probabilistic Prediction 18
1.3 Estimation of Best Predictors from Random
Samples 22
1.4 Extrapolation 25
1.5 Predicting High School Graduation 28
Complement 1A. Best Predictors under Square and Absolute
Loss 30
Complement IB. Nonparametric Regression Analysis 32
Complement 1C. Word Problems 34
Contents
2 Missing Outcomes 36
2.1 Anatomy of the Problem 37
2.2 Bounding the Probability of Exiting Homelessness 40
2.3 Means of Functions of the Outcome 42
2.4 Parameters That Respect Stochastic Dominance 44
2.5 Distributional Assumptions 45
2.6 Wage Regressions and the Reservation Wage Model of
Labor Supply 48
2.7 Statistical Inference 5/
Complement 2A. Interval Measurement of Outcomes 54
Complement 2B. Jointly Missing Outcomes and
Covariates 56
Complement 2C. Convergence of Sets to Sets 60
3 Instrumental Variables 62
3.1 Distributional Assumptions and Credible Inference 62
3.2 Missingness at Random 64
3.3 Statistical Independence 66
3.4 Equality of Means 69
3.5 Inequality of Means 71
Complement 3A. Imputations and Nonresponse Weights 73
Complement 3B. Conditioning on the Propensity Score 75
Complement 3C. Word Problems 76
4 Parametric Prediction 83
4.1 The Normal Linear Model of Market and
Reservation Wages 83
4.2 Selection Models 87
4.3 Parametric Models for Best Predictors 89
Complement 4A. Minimum Distance Estimation of Partially
Identified Models 91
5 Decomposition of Mixtures 94
5.1 The Inferential Problem and Some Manifestations 94
5.2 Binary Mixing Covariates 98
5.3 Contamination through Imputation 102
5.4 Instrumental Variables 105
Complement 5A. Sharp Bounds on Parameters That Respect
Stochastic Dominance 107
6 Response Based Sampling 109
6.1 The Odds Ratio and Public Health 110
6.2 Bounds on Relative and Attributable Risk 114
Contents
6.3 Information on Marginal Distributions 118
6.4 Sampling from One Response Stratum 119
6.5 General Binary Stratifications 122
II Analysis of Treatment Response
7 The Selection Problem 127
7.1 Anatomy of the Problem 128
7.2 Sentencing and Recidivism 134
13 Randomized Experiments 136
1A Compliance with Treatment Assignment 140
7.5 Treatment by Choice 148
7.6 Treatment at Random in Nonexperimental Settings 151
7.7 Homogeneous Linear Response 153
Complement 7A. Perspectives on Treatment Comparison 157
Complement 7B. Word Problems 160
8 Linear Simultaneous Equations 167
8.1 Simultaneity in Competitive Markets 167
8.2 The Linear Market Model 170
8.3 Equilibrium in Games 174
8.4 The Reflection Problem 177
9 Monotone Treatment Response 183
9.1 Shape Restrictions 183
9.2 Bounds on Parameters That Respect Stochastic
Dominance 186
9.3 Bounds on Treatment Effects 189
9.4 Monotone Response and Selection 191
9.5 Bounding the Returns to Schooling 193
10 The Mixing Problem 198
10.1 Extrapolation from Experiments to Rules with Treatment
Variation 198
10.2 Extrapolation from the Perry Preschool Experiment 200
10.3 Identification of Event Probabilities with the Experimental
Evidence Alone 204
10.4 Treatment Response Assumptions 206
10.5 Treatment Rule Assumptions 207
10.6 Combining Assumptions 210
Contents
11 Planning under Ambiguity 211
11.1 Studying Treatment Response to Inform Treatment
Choice 211
11.2 Criteria for Choice under Ambiguity 214
11.3 Treatment Using Data from an Experiment with Partial
Compliance 218
11.4 An Additive Planning Problem 222
11.5 Planning with Partial Knowledge of Treatment
Response 226
11.6 Planning and the Selection Problem 229
11.7 The Ethics of Fractional Treatment Rules 233
11.8 Decentralized Treatment Choice 235
Complement 11 A. Minimax Regret Rules for Two Treatments
Are Fractional 237
Complement 1 IB. Reporting Observable Variation in Treatment
Response 239
Complement 11C. Word Problems 241
12 Planning with Sample Data 243
12.1 Statistical Induction 243
12.2 Wald's Development of Statistical Decision Theory 245
12.3 Using a Randomized Experiment to Evaluate an
Innovation 250
III Predicting Choice Behavior
13 Revealed Preference Analysis 259
13.1 Revealing the Preferences of an Individual 260
13.2 Random Utility Models of Population Choice
Behavior 263
13.3 College Choice in America 270
13.4 Random Expected Utility Models 274
Complement 13A. Prediction Assuming Strict
Preferences 278
Complement 13B. Axiomatic Decision Theory 282
14 Measuring Expectations 284
14.1 Elicitation of Expectations from Survey
Respondents 285
14.2 Illustrative Findings 290
Contents :
14.3 Using Expectations Data to Predict Choice
Behavior 295
14.4 Measuring Ambiguity 298
Complement 14A. The Predictive Power of Intentions Data: A
Best Case Analysis 300
Complement 14B. Measuring Expectations of Facts 305
15 Studying Human Decision Processes 308
15.1 As If Rationality and Bounded Rationality 309
15.2 Choice Experiments 312
15.3 Prospects for a Neuroscientific Synthesis 317
References 321
Author Index 339
Subject Index 343 |
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| illustrated | Not Illustrated |
| index_date | 2024-07-02T18:48:33Z |
| indexdate | 2024-07-09T21:07:29Z |
| institution | BVB |
| isbn | 0674026535 9780674026537 |
| language | English |
| lccn | 2007006086 |
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| spelling | Manski, Charles F. 1948- Verfasser (DE-588)128388447 aut Identification for prediction and decision Charles F. Manski Cambridge, Mass. [u.a.] Harvard Univ. Press 2007 XIV, 348 S. txt rdacontent n rdamedia nc rdacarrier Literaturverz. S. [321] - 337 Predicciones sociales Predicción - Metodología Toma de decisiones Forecasting Methodology Social prediction Decision making Vorhersagetheorie (DE-588)4188671-9 gnd rswk-swf Vorhersagetheorie (DE-588)4188671-9 s DE-604 http://swbplus.bsz-bw.de/bsz275447634inh.pdf Inhaltsverzeichnis HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016079568&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Manski, Charles F. 1948- Identification for prediction and decision Predicciones sociales Predicción - Metodología Toma de decisiones Forecasting Methodology Social prediction Decision making Vorhersagetheorie (DE-588)4188671-9 gnd |
| subject_GND | (DE-588)4188671-9 |
| title | Identification for prediction and decision |
| title_auth | Identification for prediction and decision |
| title_exact_search | Identification for prediction and decision |
| title_exact_search_txtP | Identification for prediction and decision |
| title_full | Identification for prediction and decision Charles F. Manski |
| title_fullStr | Identification for prediction and decision Charles F. Manski |
| title_full_unstemmed | Identification for prediction and decision Charles F. Manski |
| title_short | Identification for prediction and decision |
| title_sort | identification for prediction and decision |
| topic | Predicciones sociales Predicción - Metodología Toma de decisiones Forecasting Methodology Social prediction Decision making Vorhersagetheorie (DE-588)4188671-9 gnd |
| topic_facet | Predicciones sociales Predicción - Metodología Toma de decisiones Forecasting Methodology Social prediction Decision making Vorhersagetheorie |
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