Description

Book Synopsis
The first book to discuss the principles of the nonparametric approach to the topics covered in a first year graduate course in econometrics. The book will provide a new perspective on teaching and research in applied subjects in general and econometrics and statistics in particular.

Trade Review
'The authors of this well-produced volume merit high praise for their endeavours. This will be the most comprehensive summary of nonparametric statistics that we are likely to see for a long time. I can recommend it as a guide to recent work in an important area of mathematical statistics.' Short Book Reviews

Table of Contents
1. Introduction; 2. Methods of density estimation; 3. Conditional moment estimation; 4. Nonparametric estimation of derivatives; 5. Semiparametric estimation of single equation models; 6. Semi and nonparametric estimation of simultaneous equation models; 7. Semiparametric estimation of discrete choice models; 8. Semiparametric estimation of selectivity models; 9. Semiparametric estimation of censored regression models; 10. Retrospect and prospect.

Nonparametric Econometrics

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    £42.74

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    RRP £44.99 – you save £2.25 (5%)

    Order before 4pm tomorrow for delivery by Fri 26 Jun 2026.

    A Paperback by Adrian Pagan, Aman Ullah

    15 in stock


      View other formats and editions of Nonparametric Econometrics by Adrian Pagan

      Publisher: Cambridge University Press
      Publication Date: 6/13/1999 12:00:00 AM
      ISBN13: 9780521586115, 978-0521586115
      ISBN10: 0521586119

      Description

      Book Synopsis
      The first book to discuss the principles of the nonparametric approach to the topics covered in a first year graduate course in econometrics. The book will provide a new perspective on teaching and research in applied subjects in general and econometrics and statistics in particular.

      Trade Review
      'The authors of this well-produced volume merit high praise for their endeavours. This will be the most comprehensive summary of nonparametric statistics that we are likely to see for a long time. I can recommend it as a guide to recent work in an important area of mathematical statistics.' Short Book Reviews

      Table of Contents
      1. Introduction; 2. Methods of density estimation; 3. Conditional moment estimation; 4. Nonparametric estimation of derivatives; 5. Semiparametric estimation of single equation models; 6. Semi and nonparametric estimation of simultaneous equation models; 7. Semiparametric estimation of discrete choice models; 8. Semiparametric estimation of selectivity models; 9. Semiparametric estimation of censored regression models; 10. Retrospect and prospect.

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