The transfer market of European football can be classified as a system. In this system, the effectiveness of participant teams can depend on the activity in players’ transfers. This article assesses the utility of network analysis in analysing connections between the mentioned concepts. The hypothesis is that there is causality between a club’s activity in the transfer market and its profit from transfers. This research is based on empirical transfer data of major soccer teams, which have had a significant role in the last 12 years in Europe. It is assumed that the most active clubs in the transfer system have more financial power in the transfer market, while teams which are not active in transfers have less profit from transfers. In the network analysis, the teams can be defined as a set of nodes and connected by edges (interactions). The thickness of the edges and the size of the nodes depend on the volume of transfers among clubs. The number of interactions and the amount of the transfer price can measure this volume also. Considering the results of network indices, the relationships between the two phenomena were reviewed. In order to explore these relationships, the correlations among all of the relevant variables in the transfer market were also measured.
The aim of this paper is to present a comparative study of trade credit indicators and the possible determinants of trade credit for firms acting in the construction sector, using a sample of 958 medium and large firms for the period 2004-2013. The objective of the study is to identify and examine selected variables that may determine trade credit used and provided by selected firms. The sample is derived from the Amadeus database. The examined firms were ones that have sold and bought on credit. The data was organised as panel- data and quantitative analyses were performed. This study demonstrates results that firms with higher trade receivables are less profitable; a positive correlation was found between trade receivables and liquidity, whereas a negative correlation was detected between trade receivables and gearing; larger firms provide and obtain more trade credit than medium firms; more profitable firms use less gearing; firms with higher profit margin are more liquid and more liquid firms use less gearing; based on an average and overall terms, there is not such a clear distinction between Western and Eastern European countries from viewpoint of net trade credit and net trade period.
The economy of Georgia had corruptive characteristics at the end of the last century and that has largely contributed to the existence of high-scaled shadow economy. Tax avoidance by entrepreneurs is considered to be the main cause of shadow economy1 (Gabidzashvili, Kbiladze, 2010). The methodological measurement and assessment of the shadow economy is characterized by certain peculiarities; therefore, we have aimed to examine and assess the scale of shadow economy and its impact on the overall economy of Georgia. The research shows several differences between real indicators, obtained by interviewers using hidden chronometry, and those indicators declared by entrepreneurs (the non-traditional method of research). The differences reveal unregistered micro-level economy, and provide the basis for determining the scale of shadow economy on the macroeconomic level. This problem was discussed several times by the president of Georgia. The research uses methods of average values, time series and the correlation-regression analysis of data. The study allowed us to identify the pattern of shadow economy reduction in Georgia during recent years and its shifting from the illegal to legal sectors, also, the maintenance of same trends before 2020.
The humankind is ageing rapidly, and as a result, there is an increasing need for old people’s homes. The nursing homes face different problems in financing and recruiting the labour force and management. Lack of resources causes the situation, when managers have to find possibilities to accomplish services and to provide quality care with the limited funds. This situation has an additional impact on the nursing professionals, who have to deal with many psychosocial risk factors in their work. The aim of the paper is to explore the work-related psychosocial risk factors and their relationships with mental health problems (MHPs) amongst care workers. A cross-sectional survey was undertaken amongst the care workers in nine Estonian nursing homes. Psychosocial work factors and MHPs (stress, somatic symptoms, depressive symptoms, burnout, cognitive symptoms, and sleep disorders) were analysed using the second version of the Copenhagen Psychosocial Questionnaire (COPSOQ II). Descriptive statistics and Pearson’s r correlation were used to analyse the data. The analysis was based on 340 care worker surveys. The highest mean scores for the studied work-related psychosocial factors were recorded for the quantitative demands, influence, rewards, role conflicts, trust, insecurity and work-family balance. Low mean scores were recorded for the meaning of work, role clarity, social relationships at work. The lowest score was followed by burnout and the highest - by cognitive symptoms.
., Dhesi, G. (2010). Volatility spillover and time varying conditional correlation between the European and US stock markets. Global Economy and Finance Journal, (3), 148-164.
Nekhili, R., Aslihan A-S. & Gençay, R. (2002). Exploring exchange rate returns at different time horizons. Physica A, 313, 671-682.
Nikkinen, J., Piljak, V., Äijö, J. (2012). Baltic stock markets and the financial crisis of 2008–2009. Research in International Business and Finance, (26), 398-409.
Maneschiöld, P. O. (2006). Integration between the Baltic and international
Pablo de Pedraza, Stefano Visintin, Kea Tijdens and Gábor Kismihók
autocorrelation, cross-correlation patterns, and their synchronization by means of cross-spectral analyses.
With respect to the total number of vacancies in the economy, we find that the web and the CBS vacancy data present similar time series properties. Our results suggest that, in both cases, the time series for vacancy data could have been generated by the same underlying phenomenon: the real number of new vacancies appearing in the Dutch labor market every quarter. We arrive at this conclusion studying both, original and transformed (first difference), time series. This
In scientific literature, there aren’t clearly enough formulated reasons behind causing the solvency component elements changes that would help all companies to prepare for possible insolvency changes. Methods of analysis evaluate following variables: corporate income flows, liabilities amounts, short-term and long-term changes in assets, capital amount, their relative indicators. However, little attention is given to external environmental factors affecting the development of these indicators. The aim of this research is to establish the impact of business environmental factors for companies’ solvency indicators. The business environmental impact assessment seeks to determine just the external - macroeconomic business environment influence for companies’ solvency changes. After identifying the key changes of business environment factors and basic companies’ solvency trends, variables were calculated the dependency was expressed in Pearson correlation coefficients. The evaluation of environmental factors, the main solvency indicators in the sector of warehousing and transport services companies and of the correlation relation determined a statistically significant relationship between companies’ solvency and gross domestic product, inflation, the tax burden, shadow economy, corruption control, number of companies in the sector and interest rate changes. The study identified following dependencies: interest rates, the growth of inflation reduces the debt-to equity ratio, the decrease of the extent of shadow economy and the growth of corruption control increases companies’ debt ratio value, an increased number of companies reduces companies’ debt ratio values. The received statistical relationships and their evaluation of the reliability confirmed the study hypothesis about the statistical significance of the business environment economic factor effect for companies’ solvency changes.
Abdullah Saeed S Alqahtani, Hongbing Ouyang and Adam Ali
Moves Sovereign Bond Markets? The Effects of Economic News on US and German Yields. Current Issues in Economics and Finance, 9(9), 1-7. Retrieved from https://www.newyorkfed.org/medialibrary/media/research/current_issues/ci9-9.pdf
Hamao, Y., Masulis, R.W., & Ng, V. (1990). Correlations in Price Changes and Volatility Across International Stock Markets. Review of Financial Studies, 3(2), 281-307. https://doi.org/10.1093/rfs/3.2.281
Hassett, K. A., & Metcalf, G. E. (1999). Investment with Uncertain Tax Policy: Does Random Tax Policy
Pablo de Pedraza, Marcos Álvarez-Díaz and Marcos Domínguez-Torreiro
( EMCO, 2009 ), which draws upon four main flexicurity principles: flexible and reliable contractual agreements (FRCA), lifelong learning (LLL), ALMP, and modern social security (MSS). However, according to previous statistical assessments ( Nardo and Rossetti, 2013 ; Domínguez-Torreiro and Casubolo, 2017 ), the correlation structure among the variables included in each of these four groups is neither sound nor robust. These results do not support the use of composite indicators to summarize the four principles outlined above.
Very often in the existing literature
Effrosyni Adamopoulou, Emmanuele Bobbio, Marta De Philippis and Federico Giorgi
et al., 2016 , for the US and Calligaris et al., 2018 , and Linarello and Petrella, 2017 , for Italy), we are the first to quantify the role of this reallocation for aggregate wages.
Through the OP decomposition, we decompose aggregate wages into the simple unweighted average of the wage across firms ( within component) and a correlation term between wage and employment across firms (the OP component). The first term captures changes in aggregate wages that are due to changes in firms’ average wages common to all firms – due to inflation, aggregate shocks