This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Bayesian Variants of Some Classical Semiparametric Regression Techniques

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Koop, G.
Poirier, D.

Additional information is available for the following registered author(s):

Abstract

This paper develops new Bayesian methods for semiparametric inference in the partial linear Normal regression model. These methodes draw solely on teh Normal linear regression model with natural conjugate prior. Hence, analytical finite sample results are available which do not suffer form problems of theoretical and computational complexity which plague the existing literature.

Download Info
To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.

Publisher Info
Paper provided by California Irvine - School of Social Sciences in its series Papers with number 00-01-22.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 30 pages
Date of creation: 2000
Date of revision:
Handle: RePEc:fth:calirv:00-01-22

Contact details of provider:
Postal: UNIVERSITY OF CALIFORNIA IRVINE, SCHOOL OF SOCIAL SCIENCES, IRVINECALIFORNIA 91717 U.S.A.

For technical questions regarding this item, or to correct its listing, contact: (Thomas Krichel).

Related research
Keywords: MODELS ; TESTS ; MATHEMATICAL ANALYSIS;

Other versions of this item:

Find related papers by JEL classification:
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Dorfman, Jeffrey H. & Patridge, Mark D. & Galloway, Hamilton, 2008. "Are High-Tech Employment and Natural Amenities Linked?: Answers from a Smoothed Bayesian Spatial Model," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6459, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association). [Downloadable!]
  2. Scott E. Atkinson & Jeffrey H. Dorfman, 2009. "Feasible estimation of firm-specific allocative inefficiency through Bayesian numerical methods," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 675-697. [Downloadable!]
  3. Dale J. Poirier & Gary Koop & Justin Tobias, 2005. "Semiparametric Bayesian inference in multiple equation models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(6), pages 723-747. [Downloadable!]
    Other versions:
  4. Brendan Kline & Justin L. Tobias, 2008. "The wages of BMI: Bayesian analysis of a skewed treatment-response model with nonparametric endogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(6), pages 767-793. [Downloadable!]
  5. Gianni Amisano & Maria Letizia Giorgetti, . "The Dynamics of Firms' Entry and Diversification: A Bayesian Panel Probit Approach. A Cross-country analysis," Working Papers ubs0408, University of Brescia, Department of Economics. [Downloadable!]
  6. Bacolod, Marigee & Tobias, Justin, 2005. "Schools, School Quality and Academic Achievement: Evidence from the Philippines," Staff General Research Papers 12249, Iowa State University, Department of Economics.
  7. Gianni Amisano & Maria Letizia Giorgetti, 2005. "Entry in Pharmaceutical submarkets: A Bayesian Panel Probit Approach," Working Papers ubs0511, University of Brescia, Department of Economics. [Downloadable!]
  8. Priya Ranjan & Justin L. Tobias, 2007. "Bayesian inference for the gravity model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 817-838. [Downloadable!]
Statistics
Access and download statistics

Did you know? The yearly budget of IDEAS is exactly $0: it relies entirely on volunteer work.

This page was last updated on 2009-11-20.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.