Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 Methods of Density Estimation
- 3 Conditional Moment Estimation
- 4 Nonparametric Estimation of Derivatives
- 5 Semiparametric Estimation of Single-Equation Models
- 6 Semiparametric 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
- A Statistical Methods
- References
- Index
Preface
Published online by Cambridge University Press: 03 December 2009
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 Methods of Density Estimation
- 3 Conditional Moment Estimation
- 4 Nonparametric Estimation of Derivatives
- 5 Semiparametric Estimation of Single-Equation Models
- 6 Semiparametric 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
- A Statistical Methods
- References
- Index
Summary
It took almost a decade to complete the work on this book. During this period Pagan moved from the University of Rochester to the Australian National University while Ullah moved to the University of California, Riverside from the University of Western Ontario. Such moves are always difficult and are made more so when the protagonists were trying to write about a field that at time seemed to be growing at an exponential rate. All of this disruption caused the book to be typed and retyped several times on two continents as well as ensured that the idea of completing it died and was reborn more than once. In the end our desire to see a completed text won out.
As anyone who performs applied work knows, many assumptions are made in coming up with answers. Mostly these involve assertions about the distributional features of variables and functional relations among them. It is not unusual for one to feel a little uncomfortable with some of these assumptions and to wonder what would happen if they could be relaxed. We were therefore rather intrigued to come across a literature in mathematical statistics that provided tools for doing some of the applied work with a minimal number of assumptions. This “nonparametrics” literature was found to be very useful in some of our early work on the risk premium, and that experience suggested that these methods could be quite useful more generally and that they should be more widely known to econometricians. Hence our objective became one of bringing this literature together in a systematic and integrated way within a single source.
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- Nonparametric Econometrics , pp. xvii - xviiiPublisher: Cambridge University PressPrint publication year: 1999
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