Nonparametric approach to evaluation of economic and social development in the EU28 member states by DEA efficiency

Data envelopment analysis (DEA) methodology is used in this study for a comparison of the dynamic efficiency of European countries over the last decade. Moreover, efficiency analysis is used to determine where resources are distributed efficiently and/or were used efficiently/inefficiently under factors of competitiveness extracted from factor analysis. DEA measures numerical grades of the efficiency of economic processes within evaluated countries and, therefore, it becomes a suitable tool for setting an efficient/inefficient position of each country. Most importantly, the DEA technique is applied to all (28) European Union (EU) countries to evaluate their technical and technological efficiency within the selected factors of competitiveness based on country competitiveness index in the 2000-2017 reference period. The main aim of the paper is to measure efficiency changes over the reference period and to analyze the level of productivity in individual countries based on the Malmquist productivity index (MPI). Empirical results confirm significant disparities among European countries and selected periods 2000-2007, 2008-2011, and 2012-2017. Finally, the study offers a comprehensive comparison and discussion of results obtained by MPI that indicate the EU countries in which policy-making authorities should aim to stimulate national development and provide more quality of life to the EU citizens.Web of Science122art. no. 7

Education Performance of Czech Public Higher Education Institutions Using Data Envelopment and Panel Regression Analysis

The priority goals of the development of Czech higher education include ensuring the quality of its activities, improving the availability and relevance of flexible forms of education, and increasing efficiency in teaching and research. Several professional articles evaluated educational efficiency, but the proposed models did not include unemployed graduate students. The paper assesses education efficiency at public universities in the Czech Republic in 2020-2021 using an extended Data envelopment model with undesirable outputs, non-proportional and non-radial measures of distance from the efficient frontier. The influence of selected economic, social, regional and institutional factors on education efficiency is estimated by a panel regression model using the Feasible generalized least squares method. The results document the level and development of education efficiency and find insufficient reduction of unemployed graduates as a critical problem of inefficiency. More prominent universities achieve higher education efficiency. The main statistically significant factors influencing changes in education efficiency are population density, the unemployment rate, the location of the university in larger urban centres and the number of students per university employee

Use of logistic regression for understanding and prediction of customer churn in telecommunications

Customer churn, loss of customers due to switch to another service provider or non-renewal of commitment, is very common in highly competitive and saturated markets such as telecommunications. Predictive models need to be implemented to identify customers who are at risk of churning and also to discover the key drivers of churn. The aim of this paper is to use demographic and service usage variables to estimate logistic regression model to predict customer churn in European Telecommunications provider and to find the factors influencing customer churn. An interesting findings came out of the estimated model - younger customers who are shorter time with company, who use mobile data and sms more than traditional calls, having occasional problem with paying bills, with students account and ending contract in the near future are typical representatives of customers who tend to leave the company. An interaction terms added as explanatory variables showed that effect of usage of data and voice vary depending on the year of birth. The quality of the logistic regression model was assessed by Hosmer-Lemeshow test and pseudo R squared measures. An independent testing data set was further used to evaluate the predictive ability of the model by computation of performance metrics such as the area under the ROC curve (AUC), sensitivity and precision. The resulting model was able to catch 94.8% of customers who in fact left the company. Quality of the model was confirmed also by high value of AUC metric equal to 0.9759. Logistic regression represents a very useful tool in prediction of customer churn not only thanks to its interpretability, but also for its predictive power.Web of Science99214112

Aplikace modelových přístupů pro řízení efektivních akciových portfolií

Prezenční výpůjčkaVŠB - Technická univerzita Ostrava. Ekonomická fakult

Econometric analysis of macroeconomic efficiency development in the EU15 and EU12 countries

The paper evaluates the macroeconomic efficiency development in the countries of the European Union by the Data Development Analysis (DEA). The aim of the paper is to measure and assess the efficiency potential of the “old” (EU15) and “new” EU countries (EU12) in 2000-2011. The DEA method is convenient because it is based on the ratio between input- and output-indicators thus measuring the efficiency with which the EU countries transform their inputs into outputs. DEA conveniently analyses effective/ineffective positions of each country providing numerical values describing the efficiency of economic processes in these countries. Efficiency can be thus considered as a “source” of competitiveness. When applying the DEA method, the indicators of the Country Competitiveness Index (CCI) are used. The following econometric development analysis of the macroeconomic efficiency is undertaken with the help of the dynamic panel model with fixed effects estimated by the pooled least squares method

Podpora rozhodování o nároku na hmotné zabezpečení v nezaměstnanosti prostřednictvím expertního systému

Import 20/04/2006Prezenční výpůjčkaVŠB - Technická univerzita Ostrava. Ekonomická fakult

Long-run relations in a small open economy of the Czech Republic and the Slovak Republic

A small open economy is highly dependent on foreign environments. This article investigates equilibrium relations between a small open economy and its foreign trade partners. Based on long-run relationships developed by Garratt et al. (2003) a structural model for the Czech Republic (CR) and Slovak Republic (SR) is constructed for period 2002Q1 to 2015Q4. As most of the macroeconomic variables are nonstationary, the Cointegrated Vector Autoregressive Approach (CVAR) is used for empirical analysis. The following five long-run equilibrium relations are examined: relative purchasing power parity, uncovered interest rate parity, Fisher inflation parity, money market equilibrium, and output relation. The estimation results of the long-run relations confirmed similarities between these economies.Web of Science65542540