Description

Book Synopsis
This book deals with methods and models of microeconometrics, the statistical modeling of behavioral relationships based on data from sample surveys or actual or quasi-social experiments. The book is oriented to the graduate student and researcher using such data. The level of the book is post-first year PhD economics.

Trade Review
'This book presents an elegant and accessible treatment of the broad range of rapidly expanding topics currently being studied by microeconometricians. Thoughtful, intuitive, and careful in laying out central concepts of sophisticated econometric methodologies, it is not only an excellent textbook for students, but also an invaluable reference text for practitioners and researchers.' Cheng Hsiao, University of Southern California
'I wish Microeconometrics was available when I was a student! Here, in one place - and in clear and readable prose - you can find all of the tools that are necessary to do cutting-edge applied economic analysis, and with many helpful examples.' Alan Krueger, Princeton University
'Cameron and Trivedi have written a remarkably thorough and up-to-date treatment of microeconometric methods. This is not a superficial cookbook; the early chapters carefully lay the theoretical foundations on which the authors build their discussion of methods for discrete and limited dependent variables and for analysis of longitudinal data. A distinctive feature of the book is its attention to cutting-edge topics like semiparametric regression, bootstrap methods, simulation-based estimation, and empirical likelihood estimation. A highly valuable book.' Gary Solon, University of Michigan
'The empirical analysis of micro data is more widespread than ever before. The book by Cameron and Trivedi contains a superb treatment of all the methods that economists like to apply to such data. What is more, it fully integrates a number of exciting new methods that have become applicable due to recent advances in computer technology. The text is in perfect balance between econometric theory and empirical intuition, and it contains many insightful examples.' Gerard J. van den Berg, Free University, Amsterdam, The Netherlands
'… it is well organised and well written … the authors are to be congratulated on this sure-footed addition to the econometrics literature.' The Times Higher Education Supplement

Table of Contents
1. Introduction; 2. Causal and non-causal models; 3. Microeconomic data structures; 4. Linear models; 5. ML and NLS estimation; 6. GMM and systems estimation; 7. Hypothesis tests; 8. Specification tests and model selection; 9. Semiparametric methods; 10. Numerical optimization; 11. Bootstrap methods; 12. Simulation-based methods; 13. Bayesian methods; 14. Binary outcome models; 15. Multinomial models; 16. Tobit and selection models; 17. Transition data: survival analysis; 18. Mixture models and unobserved heterogeneity; 19. Models of multiple hazards; 20. Models of count data; 21. Linear panel models: basics; 22. Linear panel models: extensions; 23. Nonlinear panel models; 24. Stratified and clustered samples; 25. Treatment evaluation; 26. Measurement error models; 27. Missing data and imputation; A. Asymptotic theory; B. Making pseudo-random draw.

Microeconometrics

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A Hardback by A. Colin Cameron, Pravin K. Trivedi

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    View other formats and editions of Microeconometrics by A. Colin Cameron

    Publisher: Cambridge University Press
    Publication Date: 09/05/2005
    ISBN13: 9780521848053, 978-0521848053
    ISBN10: 0521848059

    Description

    Book Synopsis
    This book deals with methods and models of microeconometrics, the statistical modeling of behavioral relationships based on data from sample surveys or actual or quasi-social experiments. The book is oriented to the graduate student and researcher using such data. The level of the book is post-first year PhD economics.

    Trade Review
    'This book presents an elegant and accessible treatment of the broad range of rapidly expanding topics currently being studied by microeconometricians. Thoughtful, intuitive, and careful in laying out central concepts of sophisticated econometric methodologies, it is not only an excellent textbook for students, but also an invaluable reference text for practitioners and researchers.' Cheng Hsiao, University of Southern California
    'I wish Microeconometrics was available when I was a student! Here, in one place - and in clear and readable prose - you can find all of the tools that are necessary to do cutting-edge applied economic analysis, and with many helpful examples.' Alan Krueger, Princeton University
    'Cameron and Trivedi have written a remarkably thorough and up-to-date treatment of microeconometric methods. This is not a superficial cookbook; the early chapters carefully lay the theoretical foundations on which the authors build their discussion of methods for discrete and limited dependent variables and for analysis of longitudinal data. A distinctive feature of the book is its attention to cutting-edge topics like semiparametric regression, bootstrap methods, simulation-based estimation, and empirical likelihood estimation. A highly valuable book.' Gary Solon, University of Michigan
    'The empirical analysis of micro data is more widespread than ever before. The book by Cameron and Trivedi contains a superb treatment of all the methods that economists like to apply to such data. What is more, it fully integrates a number of exciting new methods that have become applicable due to recent advances in computer technology. The text is in perfect balance between econometric theory and empirical intuition, and it contains many insightful examples.' Gerard J. van den Berg, Free University, Amsterdam, The Netherlands
    '… it is well organised and well written … the authors are to be congratulated on this sure-footed addition to the econometrics literature.' The Times Higher Education Supplement

    Table of Contents
    1. Introduction; 2. Causal and non-causal models; 3. Microeconomic data structures; 4. Linear models; 5. ML and NLS estimation; 6. GMM and systems estimation; 7. Hypothesis tests; 8. Specification tests and model selection; 9. Semiparametric methods; 10. Numerical optimization; 11. Bootstrap methods; 12. Simulation-based methods; 13. Bayesian methods; 14. Binary outcome models; 15. Multinomial models; 16. Tobit and selection models; 17. Transition data: survival analysis; 18. Mixture models and unobserved heterogeneity; 19. Models of multiple hazards; 20. Models of count data; 21. Linear panel models: basics; 22. Linear panel models: extensions; 23. Nonlinear panel models; 24. Stratified and clustered samples; 25. Treatment evaluation; 26. Measurement error models; 27. Missing data and imputation; A. Asymptotic theory; B. Making pseudo-random draw.

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