IDEAS home Printed from https://ideas.repec.org/p/ems/eureir/21723.html

A Trinomial Test for Paired Data When There are Many Ties

Author

Listed:
  • Bian, G.
  • McAleer, M.J.
  • Wong, W.-K.

Abstract

This paper develops a new test, the trinomial test, for pairwise ordinal data samples to improve the power of the sign test by modifying its treatment of zero di®erences between observations, thereby increasing the use of sample information. Simulations demonstrate the power superiority of the proposed trinomial test statis- tic over the sign test in small samples in the presence of tie observations. We also show that the proposed trinomial test has substantially higher power than the sign test in large samples and also in the presence of tie observations, as the sign test ignores information from observations resulting in ties.

Suggested Citation

  • Bian, G. & McAleer, M.J. & Wong, W.-K., 2010. "A Trinomial Test for Paired Data When There are Many Ties," Econometric Institute Research Papers EI 2010-66, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:21723
    as

    Download full text from publisher

    File URL: https://repub.eur.nl/pub/21723/EI2010-66.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    2. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    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. is not listed on IDEAS
    2. Nguyen Huu Hau & Tran Trung Tinh & Hoa Anh Tuong & Wing-Keung Wong, 2020. "Review of Matrix Theory with Applications in Education and Decision Sciences," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(1), pages 28-69, March.
    3. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections," JRFM, MDPI, vol. 11(1), pages 1-29, March.
    4. Kim-Hung Pho & Thi Diem-Chinh Ho & Tuan-Kiet Tran & Wing-Keung Wong, 2019. "Moment Generating Function, Expectation And Variance Of Ubiquitous Distributions With Applications In Decision Sciences: A Review," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(2), pages 65-150, June.
    5. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Decision Sciences, Economics, Finance, Business, Computing, and Big Data: Connections," Tinbergen Institute Discussion Papers 18-024/III, Tinbergen Institute.
    6. Kai-Yin Woo & Chulin Mai & Michael McAleer & Wing-Keung Wong, 2020. "Review on Efficiency and Anomalies in Stock Markets," Economies, MDPI, vol. 8(1), pages 1-51, March.
    7. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Decision Sciences, Economics, Finance, Business, Computing, And Big Data: Connections," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 36-94, December.
    8. Kim-Hung Pho & Tuan-Kiet Tran & Thi Diem-Chinh Ho & Wing-Keung Wong, 2019. "Optimal Solution Techniques in Decision Sciences A Review," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(1), pages 114-161, March.
    9. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 11(1), pages 1-29, March.
    10. Kai-Yin Woo & Hassan Zada & Shin-Hung Pan, 2026. "A Review of Behavioral Finance and Econometrics: Theories and Applications," Advances in Decision Sciences, Asia University, Taiwan, vol. 30(2), pages 302-331, June.

    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. Albert J.F. Yang & William N. Trumbull & Chin Wei Yang & Bwo‐Nung Huang, 2011. "On The Relationship Between Military Expenditure, Threat, And Economic Growth: A Nonlinear Approach," Defence and Peace Economics, Taylor & Francis Journals, vol. 22(4), pages 449-457, April.
    2. Philip Hans Franses & Dick van Dijk, 2006. "A simple test for PPP among traded goods," Applied Financial Economics, Taylor & Francis Journals, vol. 16(1-2), pages 19-27.
    3. Li, Kunpeng & Lin, Wei, 2024. "Threshold spatial autoregressive model," Journal of Econometrics, Elsevier, vol. 244(1).
    4. Houda Haffoudhi & Rihab Bellakhal, 2020. "Threshold Effect of Globalization on Democracy: the Role of Demography," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 11(4), pages 1690-1707, December.
    5. Po, Wan-Chen & Huang, Bwo-Nung, 2008. "Tourism development and economic growth–a nonlinear approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(22), pages 5535-5542.
    6. van Dijk, Dick & Franses, Philip Hans & Paap, Richard, 2002. "A nonlinear long memory model, with an application to US unemployment," Journal of Econometrics, Elsevier, vol. 110(2), pages 135-165, October.
    7. Alexander Mayer & Davide Raggi, 2025. "Estimation and inference in models with multiple behavioural equilibria," Papers 2512.04541, arXiv.org, revised Sep 2026.
    8. Corradi, Valentina & Swanson, Norman R., 2002. "A consistent test for nonlinear out of sample predictive accuracy," Journal of Econometrics, Elsevier, vol. 110(2), pages 353-381, October.
    9. Dang, Viet Anh & Kim, Minjoo & Shin, Yongcheol, 2014. "Asymmetric adjustment toward optimal capital structure: Evidence from a crisis," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 226-242.
    10. Lanouar Charfeddine & Dominique Guegan, 2008. "Is it possible to discriminate between different switching regressions models? An empirical investigation," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00368358, HAL.
    11. Chung‐Hua Shen & Hsing‐Hua Hsu, 2022. "The determinants of Asian banking crises—Application of the panel threshold logit model," International Review of Finance, International Review of Finance Ltd., vol. 22(1), pages 248-277, March.
    12. Lütkepohl, Helmut & Milunovich, George & Yang, Minxian, 2020. "Inference in partially identified heteroskedastic simultaneous equations models," Journal of Econometrics, Elsevier, vol. 218(2), pages 317-345.
    13. Lahiani, A. & Scaillet, O., 2009. "Testing for threshold effect in ARFIMA models: Application to US unemployment rate data," International Journal of Forecasting, Elsevier, vol. 25(2), pages 418-428.
    14. Munehisa Kasuya, 2003. "Regime-Switching Approach to Monetary Policy Effects: Empirical Studies using a Smooth Transition Vector Autoregressive Model," Bank of Japan Working Paper Series Research and Statistics D, Bank of Japan.
    15. Che, Chou Ming, 2013. "Panel threshold analysis of Taiwan's outbound visitors," Economic Modelling, Elsevier, vol. 33(C), pages 787-793.
    16. Sergio Da Silva & Mauricio Nunes, 2008. "Explosive and periodically collapsing bubbles in emerging stockmarkets," Economics Bulletin, AccessEcon, vol. 3(46), pages 1-18.
    17. Thomas Giroux & Julien Royer & Olivier David Zerbib, 2024. "Empirical Asset Pricing with Score-Driven Conditional Betas," Post-Print hal-05415058, HAL.
    18. Jesus Crespo Cuaresma & Doris Ritzberger-Grunwald & Maria Antoinette Silgoner, 2008. "Growth, convergence and EU membership," Applied Economics, Taylor & Francis Journals, vol. 40(5), pages 643-656.
    19. Rafael Gonz�lez-Val & Jose Olmo, 2015. "Growth in a Cross-section of Cities: Location, Increasing Returns or Random Growth?," Spatial Economic Analysis, Taylor & Francis Journals, vol. 10(2), pages 230-261, June.
    20. Öğünç, Fethi & Akdoğan, Kurmaş & Başer, Selen & Chadwick, Meltem Gülenay & Ertuğ, Dilara & Hülagü, Timur & Kösem, Sevim & Özmen, Mustafa Utku & Tekatlı, Necati, 2013. "Short-term inflation forecasting models for Turkey and a forecast combination analysis," Economic Modelling, Elsevier, vol. 33(C), pages 312-325.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

    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:ems:eureir:21723. 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: RePub The email address of this maintainer does not seem to be valid anymore. Please ask RePub to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/feeurnl.html .

    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.