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Dušan Munđar and Diana Šimić

References 1. Arabzad, A.C. (2014). Football Match Results Prediction Using Artificial eural Networks: The Case of Iran Pro League. International Journal of Applied Research on Industrial Engineering. Vol. 1, No. 3, pp 159-179. 2. Constantinou, A.C., Fenton, N.E., Neil, M. (2012). pi-football: A Bayesian network model for forecasting Association Football match outcomes. Knowledge-Based Systems, 36, pp. 322-339. 3. Dixon, M.J., Coles, S.G. (1997). Modelling Association Football Scores and Inefficiencies in the

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Diána Ivett Fürész

References 1. Dobson, S., Gerrard, B. (1999). The Determination of Player Transfer Fees in English Professional Soccer. Journal of Sport Management , Vol. 13, No. 4, pp. 259-279. 2. Galambosné Tiszberger, M. (2015). A hálózatkutatás módszertani vizsgálati lehetőségei – szakirodalmi összefoglalás . Irodalomkutatás eredményei. Pécs, Pécsi Tudományegyetem. 3. Kapanova, K. (2012). Football transfers looked from a social network analyses perspective . Available at https://docs.google.com/file/d/0B-oMeTFloljVNkJ0c25JbFpjSkk/edit [10 May 2018

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Gábor Rappai and Diána Ivett Fűrész

Abstract

Based on previous research it can be stated that modelling sport economics related demand curves (e.g. demand for sport events and athletes) is different from other types of modelling. The difference lies in the fact that some parts of the demand curves are nearly horizontal in case of sport goods and nearly vertical in case of athletes, because the price of sport events is inflexible and at the same time, salaries of top athletes are extremely flexible. This study investigates parameter estimation methods appropriate for the relevant demand functions of sport economics. In this cases the generally used ordinary least squares estimator is less robust, so the weighted least squares estimators are able to handle heteroskedasticity. If the distribution of the variables is known, the Newey-West heteroscedasticity corrected estimates give even stronger results. The empirical study analyses footballer transfer fees in top European leagues and identifies a threshold at which the traditional supply-demand functions are not appropriate. According to the results, word class athletes, in a way, can be considered prestige goods for which demand may be irrational.

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Jean-Claude Kaufmann

References Beck, U. (2001) La société du risque. Sur la voie d’une autre modernité . Paris: Aubier. Bromberger, C. (1998) (éd.) Passions ordinaires : du match de football au concours de dictée . Paris: Bayard. Dumont, L. (1983) Essais sur l’individualisme. Une perspective anthropologi que sur l’idéologie modern . Paris: Le Seuil. Ehrenberg, A. (1998) La fatigue d’être soi. Dépression et société . Paris: Odile Jacob. Giddens, A. (1987) La constitution de la société. Eléments de la théorie de la structuration . Paris: PUF

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Pierre-Emmanuel Sorignet

. Paris : Fayard. Peterson, Richard A. et Albert Simkus. 1992. How musical tastes mark occupational status groups. Pp. 152–186 in Cultivating Differences. Symbolic Boundaries and the Making of Inequality, édité par Michèle Lamont et Marcel Fournier. Chicago : The University of Chicago Press. Rannou, Janine et Ionela Roharic. 2006. Les danseurs, un métier d’engagement. Paris : La Documentation française. Renahy, Nicolas. 2001. Football et représentation territoriale : un club amateur dans un village ouvrier. Ethnologie française 31(4) : 707

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Blagica Novkovska, Irena Palić and Sabina Hodžić

References 1. Bucevska,V., Mojanoski, G. (2018). Identifying the determinants that cause the value movements of currencies Denar, Kuna and Dinar. Croatian Review of Economics, Business and Social Statistics, Vol. 4, No. 2, 2018 – This issue. 2. Fürész, D. I. (2018). Correlation between profitability and transfer activity in European football. Croatian Review of Economics, Business and Social Statistics , Vol. 4, No. 2, 2018 – This issue. 3. Gheno, G. (2018). A new link function for the prediction of binary variables. Croatian Review of