Synopses & Reviews
Advances in Econometrics and Quantitative Economics is a comprehensive guide to the statistical methods used in econometrics and quantitative economics. Bringing together contributions from those acknowledged to be amongst the world's leading econometricians and statisticians this volume covers topics such as:
* Semiparametric and non-parametric interference.
* Multivariate analysis.
* Diagnostic tests.
* Time series behavior of commodity prices.
* Applications of Edgeworth expansions and quantitative methods in development economics.
The book is dedicated to Professor C. R. Rao, whose unique contribution to the subject has influenced econometricians for many years.
Synopsis
A comprehensive guide to the statistical methods used in economics and quantitative economics. Acknowledged experts cover topics such as: * Semiparametic and non-parametic interference * Time series behaviour of commodity prices * Applications of Edgeworth expansions and quantitative methods in development economics.
About the Author
G. S. Maddala is a University Eminent Scholar at the Ohio State University.
Peter C. B. Phillips is Sterling Professor of Economics and Statistics at Yale University.
T. N. Srinivasan is Samuel C. Park Jr. Professor of Economics at Yale University, all USA.
Table of Contents
1. Specification Errors in Limited Dependent Variable Models: G. S. Maddala (Ohio State University).
2. The Optimality of Extended Score Tests With Applications to Testing for a Moving Average Unit Root: K. Tanaka (Hitotsubashi University).
3. Score Diagnostics for Linear Models Estimated by Two Stage Least Squares: J. M. Woolridge (Michigan State University).
4. Asymptotic Expansions in Statisics: A Review of Methods and Applications: R. N. Bhattacharya and M. L. Puri (Both Indiana University).
5. An Asymptotic Expansion for the Distribution of Test Criteria Which Are Asymptotically Distributed as Chi-Squared Under Contiguous Alternatives: A. Holly and L. Gardiol (Both Université de Lausanne).
6. Estimation in Semiparametric Models: O. Linton (Yale University).
7. Pooling Nonparametric Estimates of Regression Functions with a Similar Shape: C. A. P. Pinkse and P. M. Robinson (University of British Columbia and London School of Economics).
8. On the Theory of Testing Covariance Stationarity Under Moment Condition Failure: Peter C. B. Phillips and Mico Lorentan (Yale University and University of Wisconsin).
9. Pattern Identification of ARMA Models: T. W. Anderson (Stanford University).
10. Convergence Rates for Series Estimators: W. K. Newey (Massachusetts Institute of Technology).
11. Generalized Least Squares with Nonnormal Errors: C. L. Cavanagh and T. J. Rotherberg (Columbia University and University of California at Berkeley).
12. Factor Analysis Under More General Conditions with Reference to Heteroskedasticity of Unknown Form: John G. Cragg and Stephen G. Donald (University of British Columbia and Boston University).
13. Inference in Factor Models: Christian Gourieroux, A. Monfort and E. Renault (CRES, CREST, and Université des Sciences Sociales).
14. Expectations: Are They Rational, Adaptive or Naive?: Marc Nerlove and T. Schuerman (University of Maryland and AT & T Bell Laboratories).
15. Some Hypotheses About the Time Series Behaviour of Commodity Prices: P. K. Trivedi (Indiana University).
16. A Review of the Derivation and Calculation of Rao Distances with an Application to Portfolio Theory: U. Jensen (Christian-Albrechts Universitat).