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Croatian First Football League: Teams' performance in the championship

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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Cost Efficiency of Banks in Croatia


Foreign and larger banks in Croatia are generally considered to be more cost efficient compared with domestic and smaller banks. However, those views are often based on data from financial statements that can be misleading due to simultaneous consolidation process on the market and the existence of economies of scale. To contribute to the Croatian banking efficiency literature, we construct a panel of individual bank data for 1994-2014 period and conduct a frontier analysis to calculate bank specific X-efficiency. Our results suggest that efficiency scores depend on the cost definition as domestic and smaller banks are more efficient in managing administrative costs compared with foreign and larger banks but equally efficient in managing total costs. Results indicate that average bank relative efficiency increased on two occasions: one in the late 90s in the period of banking crisis and subsequent “market cleansing” and to a lesser extent in the period marked with financial crisis. Although the differences between bank cost efficiencies seem small, we conclude that the area is worth further research as significant gains in bank earnings could be achieved by increasing efficiency.

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A new link function for the prediction of binary variables

. (2018). Development of predictive scoring model for risk stratification of no-show at a public hospital specialist outpatient clinic . Available at [10 June 2018]. 5. Daggy, J., Lawley, M., Willis, D., Thayer, D., Suelzer, C., DeLaurentis, P. C., Turkcan, A., Chakraborty, S., Sands, L. (2010). Using no-show modeling to improve clinic performance. Health Informatics Journal , Vol. 16, No. 4, pp. 246-259. 6. Davies, M. L., Goffman, R. M., May, J. H., Monte, R. J., Rodriguez, K. L., Tjader, Y

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