IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v36y2009i7p723-741.html
   My bibliography  Save this article

Departure from independence and stationarity in a handball match

Author

Listed:
  • Montezuma Dumangane
  • Nicoletta Rosati
  • Anna Volossovitch

Abstract

This paper analyses direct and indirect forms of dependence in the probability of scoring in a handball match, taking into account the mutual influence of both playing teams. Non-identical distribution (i.d.) and non-stationarity, which are commonly observed in sport games, are studied through the specification of time-varying parameters. The model accounts for the binary character of the dependent variable, and for unobserved heterogeneity. The parameter dynamics is specified by a first-order auto-regressive process. Data from the Handball World Championships 2001-2005 show that the dynamics of handball violate both independence and i.d., in some cases having a non-stationary behaviour.

Suggested Citation

  • Montezuma Dumangane & Nicoletta Rosati & Anna Volossovitch, 2009. "Departure from independence and stationarity in a handball match," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(7), pages 723-741.
    • Handle: RePEc:taf:japsta:v:36:y:2009:i:7:p:723-741
    DOI: 10.1080/02664760802499329
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/02664760802499329
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664760802499329?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. Kiviet, Jan F., 1995. "On bias, inconsistency, and efficiency of various estimators in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 68(1), pages 53-78, July.
    2. Xue, Liugen & Zhu, Lixing, 2007. "Empirical Likelihood for a Varying Coefficient Model With Longitudinal Data," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 642-654, June.
    3. Cooley, Thomas F & Prescott, Edward C, 1976. "Estimation in the Presence of Stochastic Parameter Variation," Econometrica, Econometric Society, vol. 44(1), pages 167-184, January.
    4. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
    5. Hsiao, Cheng, 1974. "Statistical Inference for a Model with Both Random Cross-Sectional and Time Effects," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 15(1), pages 12-30, February.
    6. Hsiao, Cheng, 1975. "Some Estimation Methods for a Random Coefficient Model," Econometrica, Econometric Society, vol. 43(2), pages 305-325, March.
    7. Ron C. Mittelhammer & Roger K. Conway, 1988. "Applying Mixed Estimation in Econometric Research," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 70(4), pages 859-866.
    8. Kim, Chang-Jin, 2006. "Time-varying parameter models with endogenous regressors," Economics Letters, Elsevier, vol. 91(1), pages 21-26, April.
    9. Klaassen F. J G M & Magnus J. R., 2001. "Are Points in Tennis Independent and Identically Distributed? Evidence From a Dynamic Binary Panel Data Model," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 500-509, June.
    10. Bo E. Honoré & Ekaterini Kyriazidou, 2000. "Panel Data Discrete Choice Models with Lagged Dependent Variables," Econometrica, Econometric Society, vol. 68(4), pages 839-874, 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. László Csató, 2020. "Optimal Tournament Design: Lessons From the Men’s Handball Champions League," Journal of Sports Economics, , vol. 21(8), pages 848-868, December.
    2. Leonardo Lamas & José Vitor Senatore & Gilbert Fellingham, 2020. "Two steps for scoring a point: Creating and converting opportunities in invasion team sports," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-16, October.
    3. Singh, Aaditya & Scarf, Phil & Baker, Rose, 2023. "A unified theory for bivariate scores in possessive ball-sports: The case of handball," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1099-1112.

    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. Cheng Hsiao & M. Hashem Pesaran, 2004. "Random Coefficient Panel Data Models," CESifo Working Paper Series 1233, CESifo.
    2. Timothy Neal, 2016. "Multidimensional Parameter Heterogeneity in Panel Data Models," Discussion Papers 2016-15, School of Economics, The University of New South Wales.
    3. Mariam Camarero & Juan Sapena & Cecilio Tamarit, 2020. "Modelling Time-Varying Parameters in Panel Data State-Space Frameworks: An Application to the Feldstein–Horioka Puzzle," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 87-114, June.
    4. Serge Coulombe, 2008. "Employment Adjustments in High-Trade-Exposed Manufacturing in Canada," Working Papers 0803E, University of Ottawa, Department of Economics.
    5. Abonazel, Mohamed R., 2016. "Bias Correction Methods for Dynamic Panel Data Models with Fixed Effects," MPRA Paper 70628, University Library of Munich, Germany.
    6. Geert Dhaene & Koen Jochmans, 2015. "Split-panel Jackknife Estimation of Fixed-effect Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(3), pages 991-1030.
    7. Cheng Hsiao, 2007. "Panel data analysis—advantages and challenges," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(1), pages 1-22, May.
    8. DELL'ANNO, Roberto & VILLA, Stefania, 2012. "Growth in Transition Countries: Big Bang versus Gradualism," CELPE Discussion Papers 122, CELPE - CEnter for Labor and Political Economics, University of Salerno, Italy.
    9. Bun, Maurice J.G. & Kiviet, Jan F., 2006. "The effects of dynamic feedbacks on LS and MM estimator accuracy in panel data models," Journal of Econometrics, Elsevier, vol. 132(2), pages 409-444, June.
    10. Giorgio Calzolari & Laura Magazzini, 2014. "Improving GMM efficiency in dynamic models for panel data with mean stationarity," Working Papers 12/2014, University of Verona, Department of Economics.
    11. Shiu, Ji-Liang & Hu, Yingyao, 2013. "Identification and estimation of nonlinear dynamic panel data models with unobserved covariates," Journal of Econometrics, Elsevier, vol. 175(2), pages 116-131.
    12. Michał Brzoza-Brzezina & Jacek Kotłowski & Kamil Wierus, 2015. "Can interest rate spreads stabilize the euro area?," Applied Economics, Taylor & Francis Journals, vol. 47(34-35), pages 3696-3709, July.
    13. Lionel WILNER, 2019. "The Dynamics of Individual Happiness," Working Papers 2019-18, Center for Research in Economics and Statistics.
    14. Carmela D'Avino, 2015. "Net Interoffice Accounts of Global Banks: The Role of Domestic Funding," IJFS, MDPI, vol. 3(3), pages 1-17, June.
    15. Dilla, Diana, 2017. "Staatsverschuldung und Verschuldungsmentalität [Public Debt and Debt Mentality]," MPRA Paper 79432, University Library of Munich, Germany.
    16. Georges Bresson & Cheng Hsiao & Alain Pirotte, 2011. "Assessing the contribution of R&D to total factor productivity—a Bayesian approach to account for heterogeneity and heteroskedasticity," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 435-452, December.
    17. Eoin Ó Broin & Jens Ewald & Franck Nadaud & Érika Mata & Magnus Hennlock & Louis-Gaëtan Giraudet & Thomas Sterner, 2019. "An ex post evaluation of energy-efficiency policies across the European Union," CIRED Working Papers hal-01985269, HAL.
    18. Dorothée Charlier & Mouez Fodha & Djamel Kirat, 2023. "Residential CO2 Emissions in Europe and Carbon Taxation: A Country-Level Assessment," Post-Print hal-03901487, HAL.
    19. Hsiao, Cheng & Hashem Pesaran, M. & Kamil Tahmiscioglu, A., 2002. "Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods," Journal of Econometrics, Elsevier, vol. 109(1), pages 107-150, July.
    20. Mahir Binici & Yin-Wong Cheung & Kon S. Lai, 2011. "Trade Openness, Market Competition, and Inflation: Some Sectoral Evidence from OECD Countries," CESifo Working Paper Series 3690, CESifo.

    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:36:y:2009:i:7:p:723-741. 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.