Partial Identification of Probability Distributions, 2003
Springer Series in Statistics Series

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Language: English

137.14 €

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179 p. · 15.5x23.5 cm · Hardback

The book presents in a rigorous and thorough manner the main elements of Charles Manski's research on partial identification of probability distributions. The approach to inference that runs throughout the book is deliberately conservative and thoroughly nonparametric. There is an enormous scope for fruitful inference using data and assumptions that partially identify population parameters.

Missing Outcomes * Instrumental Variables * Conditional Prediction with Missing Data * Contaminated Outcomes * Regressions, Short and Long * Response-Based Sampling * Analysis of Treatment Response * Monotone Treatment Response * Monotone Instrumental Variables * The Mixing Problem

 Charles F. Manski is Board of Trustees Professor at Northwestern University. He is author of Identification Problems in the Social Sciences and Analog Estimation Methods in Econometrics. He is a Fellow of the American Academy of Arts and Sciences, the American Association for the Advancement of Science, and the Econometric Society.