IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v43y2016i10p1892-1905.html
   My bibliography  Save this article

A new modified Jackknifed estimator for the Poisson regression model

Author

Listed:
  • Semra Türkan
  • Gamze Özel

Abstract

The Poisson regression is very popular in applied researches when analyzing the count data. However, multicollinearity problem arises for the Poisson regression model when the independent variables are highly intercorrelated. Shrinkage estimator is a commonly applied solution to the general problem caused by multicollinearity. Recently, the ridge regression (RR) estimators and some methods for estimating the ridge parameter k in the Poisson regression have been proposed. It has been found that some estimators are better than the commonly used maximum-likelihood (ML) estimator and some other RR estimators. In this study, the modified Jackknifed Poisson ridge regression (MJPR) estimator is proposed to remedy the multicollinearity. A simulation study and a real data example are provided to evaluate the performance of estimators. Both mean-squared error and the percentage relative error are considered as the performance criteria. The simulation study and the real data example results show that the proposed MJPR method outperforms the Poisson ridge regression, Jackknifed Poisson ridge regression and the ML in all of the different situations evaluated in this paper.

Suggested Citation

  • Semra Türkan & Gamze Özel, 2016. "A new modified Jackknifed estimator for the Poisson regression model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(10), pages 1892-1905, August.
    • Handle: RePEc:taf:japsta:v:43:y:2016:i:10:p:1892-1905
    DOI: 10.1080/02664763.2015.1125861
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2015.1125861
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664763.2015.1125861?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. Gruber, Marvin H. J., 1991. "The efficiency of jack-knifed and usual ridge type estimators: A comparison," Statistics & Probability Letters, Elsevier, vol. 11(1), pages 49-51, January.
    2. Nyquist, Hans, 1988. "Applications of the jackknife procedure in ridge regression," Computational Statistics & Data Analysis, Elsevier, vol. 6(2), pages 177-183, March.
    3. Urban Gråsjö, 2009. "Accessibility to R&D and Patent Production," Chapters, in: Charlie Karlsson & Börje Johansson & Roger R. Stough (ed.), Innovation, Agglomeration and Regional Competition, chapter 10, Edward Elgar Publishing.
    4. Mansi Khurana & Yogendra P. Chaubey & Shalini Chandra, 2014. "Jackknifing the Ridge Regression Estimator: A Revisit," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 43(24), pages 5249-5262, December.
    5. Månsson, Kristofer & Shukur, Ghazi, 2011. "A Poisson ridge regression estimator," Economic Modelling, Elsevier, vol. 28(4), pages 1475-1481, July.
    6. J. M. C. Santos Silva & Silvana Tenreyro, 2006. "The Log of Gravity," The Review of Economics and Statistics, MIT Press, vol. 88(4), pages 641-658, November.
    7. Manning, Willard G. & Mullahy, John, 2001. "Estimating log models: to transform or not to transform?," Journal of Health Economics, Elsevier, vol. 20(4), pages 461-494, July.
    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. Sheng Li & Wei Wang & Menghan Yao & Junyu Wang & Qianqian Du & Xuelin Li & Xinyue Tian & Jing Zeng & Ying Deng & Tao Zhang & Fei Yin & Yue Ma, 2024. "Poisson average maximum likelihood‐centered penalized estimator: A new estimator to better address multicollinearity in Poisson regression," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 78(1), pages 208-227, February.

    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. Head, Keith & Mayer, Thierry, 2014. "Gravity Equations: Workhorse,Toolkit, and Cookbook," Handbook of International Economics, in: Gopinath, G. & Helpman, . & Rogoff, K. (ed.), Handbook of International Economics, edition 1, volume 4, chapter 0, pages 131-195, Elsevier.
    2. Santos Silva, J.M.C. & Tenreyro, Silvana, 2010. "On the existence of the maximum likelihood estimates in Poisson regression," Economics Letters, Elsevier, vol. 107(2), pages 310-312, May.
    3. Kai Sun & Daniel J. Henderson & Subal C. Kumbhakar, 2011. "Biases in approximating log production," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(4), pages 708-714, June.
    4. Kareem, Fatima Olanike & Martinez-Zarzoso, Inmaculada & Brümmer, Bernhard, 2016. "Fitting the Gravity Model when Zero Trade Flows are Frequent: a Comparison of Estimation Techniques using Africa's Trade Data," GlobalFood Discussion Papers 230588, Georg-August-Universitaet Goettingen, GlobalFood, Department of Agricultural Economics and Rural Development.
    5. de Melo, Jaime & Solleder, Jean-Marc, 2020. "Barriers to trade in environmental goods: How important they are and what should developing countries expect from their removal," World Development, Elsevier, vol. 130(C).
    6. Romano, Joseph P. & Wolf, Michael, 2017. "Resurrecting weighted least squares," Journal of Econometrics, Elsevier, vol. 197(1), pages 1-19.
    7. Fabbri, D & Robone, S, 2008. "The geography of hospital admission in a National Health Service with patient choice: evidence from Italy," Health, Econometrics and Data Group (HEDG) Working Papers 08/29, HEDG, c/o Department of Economics, University of York.
    8. Ciani Emanuele & Fisher Paul, 2019. "Dif-in-Dif Estimators of Multiplicative Treatment Effects," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-10, January.
    9. Wameq A. Raza & Ellen van de Poel & Arjun Bedi & Frans Rutten, 2016. "Impact of Community‐based Health Insurance on Access and Financial Protection: Evidence from Three Randomized Control Trials in Rural India," Health Economics, John Wiley & Sons, Ltd., vol. 25(6), pages 675-687, June.
    10. Inmaculada Martínez-Zarzoso, 2013. "The log of gravity revisited," Applied Economics, Taylor & Francis Journals, vol. 45(3), pages 311-327, January.
    11. Head, Keith & Mayer, Thierry & Ries, John, 2009. "How remote is the offshoring threat?," European Economic Review, Elsevier, vol. 53(4), pages 429-444, May.
    12. Max Brüning & Josselin Thuilliez, 2019. "Mortality and Macroeconomic Conditions: What Can We Learn From France?," Demography, Springer;Population Association of America (PAA), vol. 56(5), pages 1747-1764, October.
    13. Siyu Huang & Wensha Gou & Hongbo Cai & Xiaomeng Li & Qinghua Chen, 2020. "Effects of Regional Trade Agreement to Local and Global Trade Purity Relationships," Papers 2006.07329, arXiv.org.
    14. Guillaume Daudin & Elizaveta Archanskaia, 2012. "Heterogeneity and distance puzzle," Working Papers hal-01073683, HAL.
    15. Fracasso, Andrea, 2014. "A gravity model of virtual water trade," Ecological Economics, Elsevier, vol. 108(C), pages 215-228.
    16. repec:hal:spmain:info:hdl:2441/dambferfb7dfprc9m01g1j1k2 is not listed on IDEAS
    17. MORI Tomoya & Jens WRONA, 2021. "Centrality Bias in Inter-city Trade," Discussion papers 21035, Research Institute of Economy, Trade and Industry (RIETI).
    18. Clément Bosquet & Hervé Boulhol, 2015. "What is really puzzling about the “distance puzzle”," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 151(1), pages 1-21, February.
    19. Limwattananon, Supon & Neelsen, Sven & O'Donnell, Owen & Prakongsai, Phusit & Tangcharoensathien, Viroj & van Doorslaer, Eddy & Vongmongkol, Vuthiphan, 2015. "Universal coverage with supply-side reform: The impact on medical expenditure risk and utilization in Thailand," Journal of Public Economics, Elsevier, vol. 121(C), pages 79-94.
    20. Clément Bosquet & Hervé Boulhol, 2014. "Applying the GLM Variance Assumption to Overcome the Scale-Dependence of the Negative Binomial QGPML Estimator," Econometric Reviews, Taylor & Francis Journals, vol. 33(7), pages 772-784, October.
    21. Boris Kaiser, 2016. "Decomposing differences in arithmetic means: a doubly robust estimation approach," Empirical Economics, Springer, vol. 50(3), pages 873-899, May.

    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:japsta:v:43:y:2016:i:10:p:1892-1905. 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/CJAS20 .

    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.