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Analysis of microdata / Rainer Winkelmann, Stefan Boes.

By: Contributor(s): Material type: TextTextPublication details: Berlin : Springer Verlag, 2009.Edition: Second editionDescription: xiv, 343 páginas : ilustraciones, gráficas, tablas ; 24 cmContent type:
  • Texto
Media type:
  • Sin mediación
Carrier type:
  • Volumen
ISBN:
  • 9783540927471
Subject(s): DDC classification:
  • 330.015195  W45a  21
Other classification:
  • B23
Contents:
1. Introduction: 1.1. What are microdata? ; 1.2. Types of microdata ; 1.3. Why not linear regression? ; 1.4. Common elements of microdata models ; 1.5. Examples ; 1.6. Overview of the book -- 2. From regression to probability models: 2.1. Introduction ; 2.2. Conditional probability functions ; 2.3. Probability and probability distributions ; 2.4. Further exercises -- 3. Maximum likelihood estimation: 3.1. Introduction ; 3.2. Likelihood functions ; 3.3. Properties of the maximum likelihood estimator : 3.4. Normal linear model ; 3.5. Further aspects of maximum likelihood estimation ; 3.6. Testing ; 3.7. Pros and cons of maximum likelihood ; 3.8. Further exercises -- 4. Binary response models: 4.1. Introduction ; 4.2. Models for binary response variables ; 4.3. Discrete choice models ; 4.4. Estimation ; 4.5. Goodness-of-fit ; 4.6. Non-standard sampling schemes ; 4.7. Flexible specification of binary response models ; 4.8. Further exercises – 5. Multinomial response models: 5.1. Introduction ; 5.2. Multinomial logit model ; 5.3. Conditional logit model ; 5.4. Generalized multinomial response models ; 5.5. Further exercises -- 6. Ordered response models: 6.1. Introduction ; 6.2. Standard ordered response models ; 6.3. Generalized threshold models ; 6.4. Sequential models ; 6.5. Interval data ; 6.6. Further exercises -- 7. Limited dependent variables: 7.1. Introduction ; 7.2. Tobin’s corner solution model ; 7.3. Sample selection models ; 74. Treatment effect models ; 7.5. Further exercises -- 8. Event history models: 8.1. Introduction ; 8.2. Duration models ; 8.3. Count data models ; 8.4. Further exercises.
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Item type Home library Call number Vol info Status Notes Date due Barcode Item holds
LIBRO FISICO Biblioteca Principal 330.015195 W45a (Browse shelf(Opens below)) Ejemplar 1 Available Mantener en colección. 29004025666941
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Incluye referencias bibliográficas páginas 301-309) e índice.

1. Introduction: 1.1. What are microdata? ; 1.2. Types of microdata ; 1.3. Why not linear regression? ; 1.4. Common elements of microdata models ; 1.5. Examples ; 1.6. Overview of the book -- 2. From regression to probability models: 2.1. Introduction ; 2.2. Conditional probability functions ; 2.3. Probability and probability distributions ; 2.4. Further exercises -- 3. Maximum likelihood estimation: 3.1. Introduction ; 3.2. Likelihood functions ; 3.3. Properties of the maximum likelihood estimator : 3.4. Normal linear model ; 3.5. Further aspects of maximum likelihood estimation ; 3.6. Testing ; 3.7. Pros and cons of maximum likelihood ; 3.8. Further exercises -- 4. Binary response models: 4.1. Introduction ; 4.2. Models for binary response variables ; 4.3. Discrete choice models ; 4.4. Estimation ; 4.5. Goodness-of-fit ; 4.6. Non-standard sampling schemes ; 4.7. Flexible specification of binary response models ; 4.8. Further exercises – 5. Multinomial response models: 5.1. Introduction ; 5.2. Multinomial logit model ; 5.3. Conditional logit model ; 5.4. Generalized multinomial response models ; 5.5. Further exercises -- 6. Ordered response models: 6.1. Introduction ; 6.2. Standard ordered response models ; 6.3. Generalized threshold models ; 6.4. Sequential models ; 6.5. Interval data ; 6.6. Further exercises -- 7. Limited dependent variables: 7.1. Introduction ; 7.2. Tobin’s corner solution model ; 7.3. Sample selection models ; 74. Treatment effect models ; 7.5. Further exercises -- 8. Event history models: 8.1. Introduction ; 8.2. Duration models ; 8.3. Count data models ; 8.4. Further exercises.

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