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The goal of this paper is to specify the trends of money supply in Czech Republic. This will allow us evaluate the current approach taken by the Czech National Bank in its monetary policy. To determine money's endogeneity, we have analyzed time series for the M3 monetary aggregate, the monetary base, GDP, and loans. As part of the analysis, we have worked with quarterly data from the 1 st quarter of 1996 to the 2 nd quarter of 2017. We determined the optimal lag time for the time series using the Hannan-Quinn information criterion. Next, we have analyzed the stationarity of the time series using the Dickey-Fuller test. We have further tested the stationary time series with the Engle-Granger test. Testing long-term relationships using the Engle-Granger cointegration test between the money supply (expressed by the M3 monetary aggregate) and both GDP and loans, and then between the money base and loans did not confirm long-term relationships between the values examined. Therefore, we can consider the money supply in Czech Republic to be endogenous. Two-way causal relationships between M3 and both GDP and loans as well as between the monetary base and loans was confirmed using the results of Granger causality testing as a basis.

The purpose of this paper is to analyze the impact of negative interest rates on economic activity in a selected group of countries, in particular Sweden, Denmark, and Switzerland, for the period 2009–2018. The central banks of these countries were among the first to implement negative interest rates to revive the economic growth. Therefore, this study analyzed long- and short-term relationships between interest rates announced by central banks and gross domestic product and blue chip stock indices. Time series analysis was conducted using Engle-Granger cointegration analysis and Granger causality testing to identify long- and short-term relationship. The first step, using the Akaike criteria, was to determine the optimal delay of the entire time interval for the analyzed periods. Time series that seem to be stationary were excluded based on the results of the Dickey-Fuller test. Further testing continued with the Engle-Granger test if the conditions were met. It was designed to identify co-integration relationships that would show correlation between the selected variables. These tests showed that at a significance level of 0.05, there is no co-integration between any time series in the countries analyzed. On the basis of these analyses, it was determined that there were no long-term relationships between interest rates and GDP or stock indices for these countries during the monitored time period. Using Granger causality, the study only confirmed short-term relationship between interest rates and GDP for all examined countries, though not between interest rates and the stock indices. Acknowledgment The paper has been created with the financial support of The Czech Science Foundation GACR 18-05244S – Innovative Approaches to Credit Risk Management.

The aim of this paper is to analyse the influence of monetary aggregate on economic indicators in the Eurozone. Cointegration, this selected indicator monetary aggregate M3, is demonstrated in relation to the development of Harmonised Index of Consumer Prices (HICP), gross domestic product (GDP), commodity prices and credits using Granger causality. Quarterly data between the years 1996 and 2017 are included in the analysis. Because we did not confirm the long-term relationship of the selected indicators, we continue with Granger causality. We found causal relationships between monetary aggregate M3 and GDP, HICP, commodity prices and credits. In all cases, the selected indicators have the opposite effect in Granger causality too. We also cannot definitely evaluate the effectiveness of the European Central Bank’s monetary policy and cannot confirm the use of monetary aggregate M3 as an economic indicator of future economic development in the Eurozone.Keywords: Eurozone, GDP, Granger causality, HICP, M3, monetary aggregate.

The article examines the comparative performance of Banks for the Visegrad group (V4) of four Central European States for the period 2009-2013. We study the technical effi ciency as well as the total factor of productivity changes differences between countries by employing the Data Envelopment Analysis. The effi ciency scores are calculated with an output-oriented model. Specifi cation of inputs and outputs is one of the major problems for measurement of bank's effi ciency and productivity changes. To determine inputs and outputs, we made use of assets approach that treats banks as classical intermediators between depositors and borrowers. We have determined three inputs (personnel, physical capital, purchased funds) and two outputs: net loans, total securities. Our results showed that average technical effi ciency (for all banks) trended upward during the study period. This increase effi ciency is not common for all banks in the Czech Republic, Poland, Hungary and Slovak. We found that effi ciency for Czech, Polish and Slovak banks increase during research time. Development of effi ciency Hungarian banks has on the contrary a downward trend from 0.882 in 2009 to 0.856 in 2013. We also founded that the Total Factor of Productivity (TFP) changes across all countries was relatively stable in 3 of the 4 observation periods. However, there was a substantial decline in TFP in 2011-2012. Examination of the trends for each of the countries showed that Hungary overly infl uenced the sample mean. The TFP remained stable during this period for all Poland and Czech Republic, declined slightly for Slovakia, but declined precipitously for Hungary in 2011-2012.