IDEAS home Printed from https://ideas.repec.org/a/taf/apeclt/v10y2003i9p541-543.html
   My bibliography  Save this article

Pre-test estimation in Poisson regression model

Author

Listed:
  • S. K. Sapra

Abstract

Pre-test estimation has been studied extensively for linear regression and simultaneous equation models. Recently attention has turned to pre-test estimation in non-linear models. This article studies pre-test maximum likelihood estimation in Poisson regression model. It presents its risk characteristics and compare them with those of restricted and unrestricted maximum likelihood estimators based on squared error loss function in a Monte Carlo experiment.

Suggested Citation

  • S. K. Sapra, 2003. "Pre-test estimation in Poisson regression model," Applied Economics Letters, Taylor & Francis Journals, vol. 10(9), pages 541-543.
    • Handle: RePEc:taf:apeclt:v:10:y:2003:i:9:p:541-543
    DOI: 10.1080/1350485032000100215
    as

    Download full text from publisher

    File URL: http://www.informaworld.com/openurl?genre=article&doi=10.1080/1350485032000100215&magic=repec&7C&7C8674ECAB8BB840C6AD35DC6213A474B5
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/1350485032000100215?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Adkins, Lee C. & Hill, R. Carter, 1989. "Risk characteristics of a stein-like estimator for the probit regression model," Economics Letters, Elsevier, vol. 30(1), pages 19-26.
    2. Giles, Judith A & Giles, David E A, 1993. "Pre-test Estimation and Testing in Econometrics: Recent Developments," Journal of Economic Surveys, Wiley Blackwell, vol. 7(2), pages 145-197, June.
    3. Kim, Minbo & CarterHill, R., 1995. "Shrinkage estimation in nonlinear regression The Box-Cox transformation," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 1-33.
    4. Judge, G.G. & Bock, M.E., 1983. "Biased estimation," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 10, pages 599-649, Elsevier.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ahmed, S. Ejaz & Nicol, Christopher J., 2012. "An application of shrinkage estimation to the nonlinear regression model," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3309-3321.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Danilov, D.L. & Magnus, J.R., 2002. "Estimation of the Mean of a Univariate Normal Distribution When the Variance is not Known," Discussion Paper 2002-77, Tilburg University, Center for Economic Research.
    2. Danilov, D.L. & Magnus, J.R., 2001. "On the Harm that Pretesting Does," Other publications TiSEM f131c709-4db4-468d-9ae8-9, Tilburg University, School of Economics and Management.
    3. Adkins, Lee C & Krehbiel, Timothy & Hill, R Carter, 2000. "Using Cointegration Restrictions to Improve Inference in Vector Autoregressive Systems," Review of Quantitative Finance and Accounting, Springer, vol. 14(2), pages 193-208, March.
    4. Čížek, Pavel, 2004. "(Non) Linear Regression Modeling," Papers 2004,11, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    5. Clarke, Judith A., 2008. "On weighted estimation in linear regression in the presence of parameter uncertainty," Economics Letters, Elsevier, vol. 100(1), pages 1-3, July.
    6. Badi H. Baltagi & Peter Egger & Michael Pfaffermayr, 2007. "A Monte Carlo Study for Pure and Pretest Estimators of a Panel Data Model with Spatially Autocorrelated Disturbances," Annals of Economics and Statistics, GENES, issue 87-88, pages 11-38.
    7. Ashok Bansal & Priyanka Aggarwa, 2012. "Bayes pre-test estimation for the change point of the changing one parameter exponential family," METRON, Springer;Sapienza Università di Roma, vol. 70(1), pages 41-57, April.
    8. Peter M. Mphekgwana & Yehenew G. Kifle & Chioneso S. Marange, 2024. "Shrinkage Testimator for the Common Mean of Several Univariate Normal Populations," Mathematics, MDPI, vol. 12(7), pages 1-18, April.
    9. S. Hossain & S. Ejaz Ahmed & Grace Y. Yi & B. Chen, 2016. "Shrinkage and pretest estimators for longitudinal data analysis under partially linear models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(3), pages 531-549, September.
    10. Wan, Alan T. K. & Chaturvedi, Anoop, 2001. "Double k-Class Estimators in Regression Models with Non-spherical Disturbances," Journal of Multivariate Analysis, Elsevier, vol. 79(2), pages 226-250, November.
    11. Bodo E. Steiner, 2004. "Australian wines in the British wine market: A hedonic price analysis," Agribusiness, John Wiley & Sons, Ltd., vol. 20(3), pages 287-307.
    12. Mittelhammer, Ron C & Judge, George G. & Schoenberg, Ron, 2003. "Empirical Evidence Concerning the Finite Sample Performance of EL-Type Structural Equation Estimation and Inference Methods," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt2xm0n02g, Department of Agricultural & Resource Economics, UC Berkeley.
    13. Reif, Jiri & Vlcek, Karel, 2002. "Optimal pre-test estimators in regression," Journal of Econometrics, Elsevier, vol. 110(1), pages 91-102, September.
    14. Matei Demetrescu & Uwe Hassler & Vladimir Kuzin, 2011. "Pitfalls of post-model-selection testing: experimental quantification," Empirical Economics, Springer, vol. 40(2), pages 359-372, April.
    15. Yannick Hoga, 2022. "Quantifying the data-dredging bias in structural break tests," Statistical Papers, Springer, vol. 63(1), pages 143-155, February.
    16. Dette, Holger & Hetzler, Benjamin, 2006. "A simple test for the parametric form of the variance function in nonparametric regression," Technical Reports 2006,07, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    17. Burt, Oscar R. & Frank, Michael D. & Beattie, Bruce R., 1987. "Prior Information And Heuristic Ridge Regression For Production Function Estimation," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 12(2), pages 1-9, December.
    18. Kim, Minbo & CarterHill, R., 1995. "Shrinkage estimation in nonlinear regression The Box-Cox transformation," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 1-33.
    19. Adkins, Lee C. & Eells, James B., 1995. "Improved estimators of energy models," Energy Economics, Elsevier, vol. 17(1), pages 15-25, January.
    20. Xianyi Wu & Xian Zhou, 2019. "On Hodges’ superefficiency and merits of oracle property in model selection," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(5), pages 1093-1119, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:apeclt:v:10:y:2003:i:9:p:541-543. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEL20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.