Bayesian Inference for Partially Identified Models

Bayesian Inference for Partially Identified Models

by Paul Gustafson
Released April 2015
Publisher(s): Chapman and Hall/CRC
ISBN: 9781439869406

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Book description

Bayesian Inference for Partially Identified Models: Exploring the Limits of Limited Data shows how the Bayesian approach to inference is applicable to partially identified models (PIMs) and examines the performance of Bayesian procedures in partially identified contexts. Drawing on his many years of research in this area, the author presents a thorough overview of the statistical theory, properties, and applications of PIMs.

The book first describes how reparameterization can assist in computing posterior quantities and providing insight into the properties of Bayesian estimators. It next compares partial identification and model misspecification, discussing which is the lesser of the two evils. The author then works through PIM examples in depth, examining the ramifications of partial identification in terms of how inferences change and the extent to which they sharpen as more data accumulate. He also explains how to characterize the value of information obtained from data in a partially identified context and explores some recent applications of PIMs. In the final chapter, the author shares his thoughts on the past and present state of research on partial identification.

This book helps readers understand how to use Bayesian methods for analyzing PIMs. Readers will recognize under what circumstances a posterior distribution on a target parameter will be usefully narrow versus uselessly wide.

Table of contents

  1. Cover (1/2)
  2. Cover (2/2)
  3. Dedication
  4. Contents
  5. List of Figures
  6. List of Tables
  7. Preface
  8. Guide to Notation
  9. Chapter 1: Introduction (1/3)
  10. Chapter 1: Introduction (2/3)
  11. Chapter 1: Introduction (3/3)
  12. Chapter 2: The Structure of Inference in Partially Identified Models (1/8)
  13. Chapter 2: The Structure of Inference in Partially Identified Models (2/8)
  14. Chapter 2: The Structure of Inference in Partially Identified Models (3/8)
  15. Chapter 2: The Structure of Inference in Partially Identified Models (4/8)
  16. Chapter 2: The Structure of Inference in Partially Identified Models (5/8)
  17. Chapter 2: The Structure of Inference in Partially Identified Models (6/8)
  18. Chapter 2: The Structure of Inference in Partially Identified Models (7/8)
  19. Chapter 2: The Structure of Inference in Partially Identified Models (8/8)
  20. Chapter 3: Partial Identification versus Model Misspecification: Is Honesty Best? (1/6)
  21. Chapter 3: Partial Identification versus Model Misspecification: Is Honesty Best? (2/6)
  22. Chapter 3: Partial Identification versus Model Misspecification: Is Honesty Best? (3/6)
  23. Chapter 3: Partial Identification versus Model Misspecification: Is Honesty Best? (4/6)
  24. Chapter 3: Partial Identification versus Model Misspecification: Is Honesty Best? (5/6)
  25. Chapter 3: Partial Identification versus Model Misspecification: Is Honesty Best? (6/6)
  26. Chapter 4: Further Examples: Models Involving Misclassification (1/6)
  27. Chapter 4: Further Examples: Models Involving Misclassification (2/6)
  28. Chapter 4: Further Examples: Models Involving Misclassification (3/6)
  29. Chapter 4: Further Examples: Models Involving Misclassification (4/6)
  30. Chapter 4: Further Examples: Models Involving Misclassification (5/6)
  31. Chapter 4: Further Examples: Models Involving Misclassification (6/6)
  32. Chapter 5: Further Examples: Models Involving Instrumental Variables (1/4)
  33. Chapter 5: Further Examples: Models Involving Instrumental Variables (2/4)
  34. Chapter 5: Further Examples: Models Involving Instrumental Variables (3/4)
  35. Chapter 5: Further Examples: Models Involving Instrumental Variables (4/4)
  36. Chapter 6: Further Examples (1/4)
  37. Chapter 6: Further Examples (2/4)
  38. Chapter 6: Further Examples (3/4)
  39. Chapter 6: Further Examples (4/4)
  40. Chapter 7: Further Topics (1/4)
  41. Chapter 7: Further Topics (2/4)
  42. Chapter 7: Further Topics (3/4)
  43. Chapter 7: Further Topics (4/4)
  44. Chapter 8: Concluding Thoughts (1/2)
  45. Chapter 8: Concluding Thoughts (2/2)
  46. Bibliography (1/3)
  47. Bibliography (2/3)
  48. Bibliography (3/3)

Product information

  • Title: Bayesian Inference for Partially Identified Models
  • Author(s): Paul Gustafson
  • Release date: April 2015
  • Publisher(s): Chapman and Hall/CRC
  • ISBN: 9781439869406