C22 - Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion ProcessesReturn

The United Nations Sustainable Development Goals (SDGs) emphasize the importance of energy by making affordable and clean fuel access the focus of Goal 7. Energy poverty is a widespread issue globally, particularly in developing countries. Thus, this investigation inspects the drivers of energy poverty in Brazil using data from 1997Q1 to 2022Q4. The study introduces the wavelet Zivot-Andrews (WZA) unit root test, which modifies the traditional Zivot-Andrews (ZA) test by incorporating wavelet analysis, allowing decomposition of the time series into different time scales (short-term, medium-term and long-term). This enables the WZA test to capture structural breaks and unit roots more effectively across various time scales. In addition, the study employs wavelet quantile-on-quantile regression. The results show that across all quantiles and time scales, an increase in financial globalization and economic policy uncertainty increases energy poverty. The study also shows that female political participation increases energy poverty in the short and long term. In contrast, in the medium term and across all quantiles, female political participation decreases energy poverty. Lastly, an increase in financial development decreases energy poverty across all quantiles and periods. Based on these findings, policies are suggested.

This investigation explores the influence of remittances on economic growth in Algeria during the period 1970–2022 using the Fourier autoregressive distributed lags (FARDL) model. This study provides new insights by suggesting an N-shaped association between remittances and economic growth. The findings reveal a nonlinear relationship between remittances and growth in Algeria. Initially, the impact of remittances on income is positive, then becomes negative when they exceed a threshold of 1.2% of GDP, and later becomes positive again when remittances surpass a second threshold estimated at 1.894% of GDP. These results highlight the importance of increasing remittance inflows to promote development in Algeria and urge decision-makers to create conditions that encourage the inflow of these funds through official channels

Purpose: This paper aims to examine the real interest rate parity (RIP) theory for EU5 countries (France, Germany, Italy, Spain and the UK) versus the USA. Design/methodology/approach: Utilizing RALS-FADF and RALS-FKSS unit root tests, this study addresses non-normality, non-linearity and structural breaks in real interest rate differentials. Findings: The results confirm the RIP theory, indicating mean reversion of real interest rate differentials and highlighting impact of financial integration on monetary policy independence and arbitrage opportunities. The study notes that central banks' ability to influence domestic economies through interest rates is limited due to global financial interconnectedness. Originality/value: The paper offers a new test and bases its empirical setup on whether interest rate differentials are non-normally distributed. The test also considers real interest rate non-linearity and the non-normality in the analysis.

In this paper, we present the results of a study examining whether the European Union, where countries act in common on many issues such as monetary policy, abolition of borders and mobilization of labour and capital, also constitutes a union in terms of energy security. From this point of view, whether the energy security risk in the European Union has converged or not is tested by using various analysis methods covering the period 1980-2018 for 17 EU countries. The findings of the study not only reveal whether individual countries converge to the group average but also show whether the group as a whole forms a convergent outlook. The linear unit root analysis indicates that each country is in a stochastic convergence process towards the group average. In addition, time series beta convergence analysis, which takes into account country- -specific structural break periods, is applied and the convergent-divergent situation of each country before and after the break is revealed. Following this determination of individual countries, whether the sample as a whole constitutes a convergent process is tested with sigma and panel beta convergence models and it is determined that the 17 countries subject to the analysis form a convergent outlook as a whole. A robustness check is also made via a nonlinear time series analysis and the previous findings are confirmed.

This study investigates the asymmetric effects of political stability and corruption on ecological footprint using time series data from 1984 to 2021 for Pakistan. The paper uses the nonlinear autoregressive distributed lag (NARDL) method to get accurate results regarding the positive and negative shocks of political stability. Besides, the NARDL method is utilized to identify the cointegrating link between the parameters, with a particular focus on uncovering asymmetric consequences in the long term. In addition, this research also includes natural resources, urbanization and economic progress in the model. The study results show that (i) political instability in Pakistan reduces environmental quality in both shocks; (ii) control of corruption increases the air quality in the negative shock; (iii) natural resources and urban population positively affect environmental quality; and (iv) economic progress has a favourable effect on environmental worsening. Additionally, the findings of the NARDL estimates and the outcomes of the robustness check are consistent. Particularly noteworthy is the fact that the general policy recommendation highlights the need for policymakers to vigorously synchronize their efforts to contend with the severe environmental degradation and political risk in Pakistan.

The main purpose of this study is to examine the impacts of GDP, trade openness, the freedom index and the internet on FDI in 54 countries, including developing, transition and developed countries, over the period 1995-2021. First, the variables affecting FDI are determined. Then, first- and second-generation unit root tests are conducted for panel data to investigate stationarity. Finally, long- and short-run relationships between variables that have an effect on FDI are exhibited with panel cointegration tests and panel ARDL analysis. Among 17 candidate variables, internet, GDP, the freedom index and trade openness are determined to affect FDI. GDP, the internet and the freedom index have a significant positive and trade openness has a significant negative relationship with FDI in the short run. Finally, there is a long-term equilibrium between FDI and all the variables. Trade openness also has negative coefficient in developing countries such as China, Brazil and Turkey. This is a unique study in which empirical findings are given for each country with the PMG model, which would aid the policy implications identified for the 54 countries, including developing, transition and developed countries.

This study aims to investigate whether clean energy exchange traded funds (ETFs) exhibit long-term memory properties and whether the efficient market hypothesis is valid for these assets. The results of the model established to test the dual long memory indicate the existence of long memory in both return and volatility of the ICLN, PBD, PBW series, while the long memory feature is found only in the volatility of the other variables. The results reveal that the selected clean energy ETFs do not exhibit weak efficient market characteristics and volatility has a predictable structure. These results mean that by using the past price movements of clean energy ETFs, future price movements can be predicted and thus above-normal returns can be obtained. In addition, it can be said that risks and uncertainties are effective on the price movements of clean energy ETFs. These results are important for portfolio managers, hedgers and individual and institutional investors aiming to direct their investments to the renewable energy market, as well as for policymakers.

The objective of this paper is to analyse the distribution of salaries in the public sector with a focus on employees receiving a salary at the level of minimum wages in the initial period of the COVID-19 pandemic. Among the methods used is the construction of salary distribution models by gender and educational attainment and the creation of predictions using exponential smoothing. The results of the analysis show the highest increase in real salaries among women with the lowest education. The results further show that the highest benefit in terms of the average real monthly salary of both men and women comes from changing the employee's educational attainment from secondary education without A-level examination to secondary education with A-level examination. On the other hand, for women originally with primary education, obtaining an apprenticeship certificate does not have a significant effect on their real salary on average.

With the advancement of machine learning tools, an increasing number of algorithms are being utilized for predicting not only traditional time series data related to financial markets but also those connected to cryptocurrencies. This paper aims to compare various machine learning algorithms used for prediction, in order to identify the one with the greatest practical potential for creating a prediction model of Bitcoin’s price as an investment asset. The analysis focuses on supervised learning algorithms, taking into account the nature of the task involving long time series datasets. The paper also describes the exact process of creating and setting up individual models and their parameters, explaining procedures for obtaining and editing datasets, and shows how to evaluate performance of these models. In addition to the analysis of the main subject of research, which is Bitcoin, the paper also uses an analysis of reference cryptocurrencies such as Ethereum, Litecoin and NEO to compare the resulting performances. The processes consisting of editing the analysed datasets, creating individual prediction models, training and testing the performance of models on historical data, and creating, debugging and implementing individual machine learning models were realised through coding in the Python program.

This paper aims to find the microeconomic and macroeconomic determinants of European bank profitability from 2012 to 2019 using the regression model with the multicollinearity condition as a matrix parameter, the multicollinearity below the defined value, ensuring regression model reliability. The bank sector profitability is measured by return of average equity, return of average assets and net interest margin as dependent variables. The research creates a set of independent variables based on a literature review. The model is built on a sample of 3,257 European commercial banks for all EU countries excluding Romania due to missing data, and the input data were obtained based on the Orbis Focus Bank and the World Bank Database. The results revealed that the cost to income ratio and loan loss reserves to gross loans are the most important determinants of profitability of European commercial banks as measured by return of average assets. The results also show that GDP growth rate, inflation measured by the consumer prices and loan loss reserves to gross loans are the most important determinants for the net interest margin indicator. We recommend that commercial banks optimize the cost structure, create sufficient reserves, monitor the process of digital transformation and monitor credit risk indicators.

Monitoring of inflation rate dynamics is one of the most important tasks in order to identify the current economic conditions of the observed countries. The aim of this study is to examine the unit root properties of inflation in the Western Balkan countries. It also investigates the existence of structural breaks and nonlinearity. The time horizon encompasses the period 2006Q1-2020Q2. The results suggest that the inflation in Albania and Montenegro manifests a nonstationary process and structural breaks. The macroeconomic shocks will have more persistent effects on the inflation rate if it is characterized by nonstationarity. The inflation rates of Serbia and Bosnia and Herzegovina are characterized by nonlinear mean reverting behaviour. This implies less costly implementation of the proclaimed monetary strategy.

This paper examines the development and comparison of competition and concentration in the banking and insurance sector in the Czech Republic during the 2007-2019 period using the Herfindahl-Hirschman index (HH index). In the empirical section we calculate the degree of concentration and indexes separately for the banking and insurance markets, where the main variable in relation to banks is the balance sheet and this variable is the gross written premium in relation to insurance companies. Subsequently, we compare the two examined sectors including the analysis of their long-term equilibrium. The result of this research confirms the determined hypotheses, whereas the oligopolic structure of both markets, which falls over time and aims towards a competitive market but does not achieve this goal during the monitored period. Throughout examination, the insurance market demonstrates higher HH index values and therefore lower competitiveness compared to the banking market.

The elasticity of substitution between labour and capital in the Slovak economy is estimated in the paper. We used an econometric specification of capital and labour demand and data from the National Bank of Slovakia's macroeconomic database. In order to filter the processes caused by short-term shocks, the data were adjusted using the frequency filter. Using the Breusch and Pagan test, we have shown that the stochastic terms of capital and labour demand are related. Therefore, we did not use only the least squares method to estimate both specifications, but we also estimated a system of two equations with seemingly unrelated regression. The paper is extended with a discussion showing that the relatively low value of the input substitution elasticity could theoretically be explained by the transitive nature of the Slovak economy during the studied period. The elasticity of substitution between labour and capital in the Slovak economy was relatively low in the period 1997-2014; we estimated its value in the range from 0.03 to 0.11 depending on the choice of the database version.

The aim of the article is to examine the relations between forward exchange rates (maturities of 3 and 6 months), spot exchange rates, interest rate differentials, expected spot exchange rates and risk premiums on the CZK/EUR and CZK/USD parities. A model of FX speculators and arbitrageurs is devised and subsequently empirically verified in order to provide an explanation for the dynamics of forward exchange rates. The estimations of parameters of explanatory variables, which enter the covered interest rate parity, are confirmed to be statistically significant for the time period preceding the application of the exchange rate commitment by the Czech National Bank. Though the estimated parameters of future spot rates are statistically significant, their low values suggest that their impact on the quotation of forward exchange rates is rather marginal. The statistically significant estimations of constants with negative signs are interpreted as risk premiums reflecting the higher credit risk for financial investments denominated in CZK. The relations within the time series of the CZK/EUR parity were found to be distorted during the period of exchange rate commitment on the parity level of 27 CZK/EUR and during foreign exchange interventions (i.e., the estimated parameters of interest rate differentials were not statistically significant).

The aim of the article is to construct a model for estimating the quarterly gross value added (GVA) of the national economy (GDP) based on the results of business surveys (so-called confidence indicators) in industry, construction, commerce and services (incl. banking sector), and to set the forecast for four quarters ahead. The suitability of the applied approach is assessed using pairwise dependencies for individual sectors. In the case of both pairwise and multidimensional dependencies, the authors proceed from a linear dynamic model, which is a combination of ARIMA models (or SARIMA models) in conjunction with regression analysis, where the variables explained are time-shifted. The quality of the estimated models is proven to be very high. The analysis shows a significant link between the sector's gross value added and sectoral confidence indicators. Significant predictors of the GVA of the national economy and GDP show explanatory variables of confidence indicators in industry and construction, whereas indicators of confidence in trade and services were statistically insignificant. Timely knowledge of these indicators in conjunction with linear dynamic models allows better and faster predictions of quarterly GVA and GDP than with conventional time series models.

The research database consists of the OECD countries except Iceland, Latvia and Turkey, which were excluded because of insufficient data. The primary objective of the study is to group the countries according to their average wage, GDP per capita, minimum wage and unemployment rate. Another objective, of no less importance, is to determine which of the three remaining above variables significantly affect the average wage, while defining the type and strength of this relationship. Yet another important goal is to develop forecasts of the wage level and GDP per capita for each OECD country by 2020. In terms of clustering OECD countries by the four variables, the Czech Republic always ranks alongside Chile and three post-communist countries, Estonia, Hungary and Poland. GDP per capita is the only explanatory variable significantly affecting the average wage. The dependence of these two variables is represented by a second-order polynomial (concave parabola), the selected regression parabola explaining approximately 88 percent of the variability in the observed levels of the average annual wage. The conversion of the average wage, GDP per capita and minimum wage to purchasing power parity allows consideration of different price levels and thus comparison of purchasing power parity of the population in different countries.

This article analyses wages development in the Czech Republic since 2000 to 2014. Analysis is principal focused on ICT Professional's (this group of employees in the economy is split into two sub groups ICT Specialists and ICT technicians) wages and its comparison to the wages in the whole Czech economy. Used data sources were collected by Ministry of Labour and Social Affairs of the Czech Republic, in the "Information System of Average Earnings" which is harmonized with the "Structure of Earnings Survey" provided by Europen Union. Analysis is provided by ICT sub groups and by gender. For more detail analysis, is also the percentile analysis of ICT job groups in comparison to the whole Czech economy presented. Contribution of ICT Professional's average wage to the average wage of the Czech economy increased from 0.43% in 2000 to 1.32% in 2014. The long term trend in wages of ICT Professionals in permanently increasing. Wages for ICT Specialists are significant higher then wages of ICT Technicians. The non-equality in wages is analysed by method of Gini index. This method is demonstrated by the development of GINI index for ICT Professionals and its comparison to Gini index of the whole Czech economy. Comparison shows that non equality is lower by ICT Professionals then in the Czech economy and from two job groups in ICT is the lower non equality for ICT Technicians group then for ICT Specialists.

Having regard to the importance of the compensation effect between output and unemployment known as Okun's law for both contemporary economic theory and for practical economic policy, the intent of the paper is to examine the empirical validity of Okun's law for the four Visegrad Group countries with consideration given to possible asymmetry. Using the quarterly data for the period from Q1/1998 and Q2/2014 and its gap version, Okun's law is verifi ed for each investigated country and some specifi cs of labour markets are highlighted so as to explain the magnitude of the estimated Okun's coeffi cients. The contribution of the paper is two-fold. First, this empirical relationship is confi rmed in validity with attention directed to the foursome of countries. Second, the analysis utilizes the non-linear ARDL model proposed in the paper to accommodate possible nonlinearity and asymmetry in Okun's law. Asymmetry is found and economically reasoned by the specifi cs of the labour market only for Slovakia since there appears to be a different reaction of the unemployment gap to positive output gap and to negative one.

The article presents an alternative method to growth accounting. It makes it possible to express the effect of change in the quantity of inputs as well as the effect of the productivity of inputs (i.e. technological changes) on the change of GDP for all possible typologies of input/output changes. Unlike the growth accounting, this method is universal and also accurate; it may be applied not only to small growth rates. Dynamic parameters of intensity and extensity could be delivered as the output of the method. The first one captures the effect of change in the summary productivity of factors, while the latter captures changes in the input quantity. The dynamic parameters were calculated for the development of GDP in the United States and China for a period of fifty years (1960-2011). In case of the United States, it was also calculated how the development of labor and the development of capital contribute to the change in inputs. The calculated values verify that the method can reliably capture significant changes that took place in the given countries in individual years. The growth rate of the summary productivity of factors calculated on the basis of our method only differs slightly from the growth rate of the summary productivity of factors calculated on the basis of growth accounting. For all the aforementioned reasons, the method appears to be a suitable instrument for analyzing the GDP development.

This article presents the methodology to extend the traditional employment-unemployment flows model with a third sector: long-term unemployment. This enables a new range of decompositions of various labour market aggregates which allows for a deeper understanding of the structure and dynamics of a particular labour market. One of possible analyses is conducted in the case of selected EU Member States. Finally, it is shown that transition probabilities into and from long-term unemployment depend on the business cycle in most EU countries.

The interconnections within food, biofuel and fossil fuel markets are first described in the context of biofuels technologies and economic policy framework. Consequently, the econometric analysis consisting of Johansen cointegration, error correction model, vector autoregression and Granger causality is applied to price series of 12 biofuel related commodities. While a number of equilibrium relationships are found across the examined markets suggesting their interconnection, we do not obtain a persuasive confirmation of the thesis that biofuels clearly lead to food shortages via the increase in prices of basic food commodities used in the production of biofuels.

The aim of our paper is to formulate and empirically verify the simple backward looking econometric model of the monetary rule, which would be able to describe the development of CNB repo rate, namely only on the basis of statistically measured and in the given time available information. We focus on the period after 1998, when the CNB's inflation targeting policy is implemented and the repo rate (14 days) plays the role of the monetary policy rate. In the paper we discuss some methodological problems associated with the "ex post" empirical verification of the central bank monetary rule. We construct an empirical model of the monetary rule, justify the choice and the inclusion of explanatory variables, we analyze the statistical properties of time series and verify the alternative forms of econometric models. Our analysis showed that the development of CNB repo rate in the reporting period can be explained by the past and present evolution of three explanatory variables: the yearly inflation rate, the exchange rate and the ECB repo rate. The annualized inflation rate proved to be statistically insignificant in the model. We find interesting that the statistical quality of the estimated model was further increased after a six-month delay of the yearly inflation rate. The obtained results indicate that in determining the CNB repo rate the expected future level of the yearly inflation rate does not play important role and the last yearly inflation rate is more important than its present level.

In various fields of macroeconomic modelling, researchers often face the problem of decomposing time series into trend component and cycle fluctuations. While there are several potentially useful methods to perform the task in question, Hodrick-Prescott (HP) fi lter seems to have remained (despite some serious criticism) the most popular approach over the past decade. In this article I propose a straightforward and easy-to-implement bootstrap procedure for building pointwise and simultaneous confidence intervals around "point estimates" produced by HP filter. The principle of proposed method can be described as follows: first, we use maximum entropy bootstrap (Vinod, 2004, 2006) to approximate ensemble from which original time series is drawn and then apply the HP filter directly to each bootstrap replication. If necessary, the proposed method can be adapted to allow for uncertainty in the smoothing parameter. Practical usefulness of our approach is demonstrated with an application to the GDP data. Results are encouraging - obtained confi dence intervals for the trend and cyclical component are overall plausible thus supplying a researcher with some measure of uncertainty related to HP filtering. Finally, we demonstrate that a former approach to build confidence intervals for HP filter (Gallego and Johnson, 2005) leads to erratic inference for cycle due to the shape-destroying block bootstrap sampling.

The paper is concerned with the use of several methods that can be useful from the point of view of trend reversal in financial time series. These methods are demonstrated on PX index time series during 2002-2009. The research itself is subdivided into four parts corresponding to individual analytical methods used. The first group contains the use of moving EGARCH(1,1) model to daily relative returns of PX index. The results obtained are indicative of the importance of negative parameter values, which can be considered as precursors of the trend reversal. The second group contains different moving characteristics that are able to signalize regime changes in certain time intervals. Particularly, the information related to intraday price variations proved to be useful. Third, selected price indicators from technical analysis were employed. Among them, Simple Moving Averages, Bollinger Bands, Relative Strength Index and Stochastic led to acceptable predictions. Last, the predictive ability of Artificial Neural Networks was tested with respect to different network structure and number of delayed values of explanatory variable. The results obtained here are promising, but further research in this direction is necessary.

The exchange rate cannot significantly diverge from a (real) long-term equilibrium level consistent with the macroeconomic picture of an economy for a long period of time; otherwise, the economy suffers from macroeconomic imbalances such as below-potential growth and below natural employment, or on the other hand faces overheating of the economy with rising inflation. The paper focuses on different methods of how to measure the long-term equilibrium exchange rate. After a brief discussion of different approaches, the NATREX one was theoretically developed for the case of an open economy and empirically validated for the Czech economy. The NATREX concept represents a macroeconomic model based on stock-flow interaction. After the estimation of the NATREX model for the CZK, we have been able to answer such questions as: What are the pace and main determinants of the current long-term equilibrium appreciation? What is the current value of the equilibrium exchange rate and the misalignment of the current exchange rate? And, how fast is the exchange rate likely to revert to its equilibrium value?

Monthly and yearly inflation rates can be understood as rates of dynamics of the basic inflation indicator i.e. the consumer price index. These indicators modify the original inflation information. It is important to analyze the difference of the consumer price index, monthly and yearly inflation rates, from the viewpoint of their frequency content, time lag and deformations. The theory of linear filtration and its representation in the frequency domain is used. Under particular assumptions, in the time series of yearly inflation rate there can be spurious cycles and high-frequency motions. The time series of yearly inflation rate lags behind the time series of instantaneous inflation rate about six months in low frequencies and the time series of monthly inflation rate lags behind the time series of instantaneous inflation rate about half of the month in all frequencies.

This study thoroughly analyzes the stock market efficiency hypothesis - its weak form - in the Czech Republic, Poland and Hungary in 1995-2005. It aims to reveal whether trading on historical information about stock prices or indices may lead to economically significant abnormal profits and whether the analyzed markets are comparably efficient. It also tests relative efficiency of the Central European markets compared to developed capital markets that are considered the most effective - the American NYSE, German and Netherlands stock exchanges. Complexity of the results is enhanced by analyzing daily, weekly and monthly returns of both the major regional indices - the Czech PX-50 and PX-D, Hungarian BUX and Polish WIG20 - and individual shares that constitute the indices. Moreover, consequences of the non-synchronous trading for autocorrelations are discussed. In conclusion, the Central European region must be considered as a heterogeneous market. While the Hungarian market generally complies with the hypothesis and behaves weakly efficient, significant linear dependences are typical for the Czech stock market. Some unsystematic departures from the random walk model persist in Poland and the efficiency market hypothesis can not be validated there. Any abnormally profitable investment strategy that exploits technical analysis should thus avoid Hungarian stocks and exploit short-term dependences on the Czech and, to a lesser extant, Polish stock market.

Panel data are increasingly being used in both macro- and micro-level studies of economic problems. Macro-panel data (i denotes countries) are characteristic by sufficiently long time series to be able to analyze panel spurious regression and panel cointegration. According to the main stream of the economic theory the budget deficits leads to deterioration in the current account balance. The panel long-run causal relation is examined in the case of the four groups of countries. For the Granger causality test the panel cointegration analysis is needed. The panel cointegration relationships were not found in any case. Some similarities in the panels were found in the case of Latin America countries but they are not significant.

In this paper historical performance of eleven approaches for estimation of one-day 95% value-at-risk is evaluated. Random sample of 1000 foreign exchange portfolios consisting of positions in EUR and USD with CZK as a base currency was considered. Since foreign exchange portfolio consists of linear instruments, historical simulation and the variance-covariance method for VaR estimation were investigated. Performance of all approaches was evaluated using seven performance criteria. With minimal degree of simplification we can say that variance-covariance method using exponentially weighted averages with is the best approach. This approach produces risk estimates which are systematically lowest ones and with high time volatility. It also achieves perfect coverage (95 %) and the highest correlation between risk measure and absolute value of the outcome. RiskMetrics variance-covariance approach was dominant in spite of violation of normality assumption.

New concepts have been presented in modelling of inflation dynamics recently, among others the New Keynesian Phillips curve (NKPC). There are several traditional ways of NKPC model validity testing, but none of them seems to be practically applicable in conditions of the Czech Republic. We tried to test the validity of the NKPC model by the untraditional method proposed by Demery and Duck (2002). This method does not rely on direct estimation of NKPC parameters, but relatively easy tests based on the cointegration analysis of time series are employed. Its application indicates that the NKPC model cannot be considered as effective in conditions of the Czech Republic; this model does not describe the inflation process sufficiently and it is not a suitable model for inflation prediction or for the choice of appropriate monetary (anti-inflation) policy.

Since 1980's many central banks have been changing their monetary strategy to explicit inflation targeting. This new monetary concept is based on management of short-term interest rates in the context of relation between inflation prediction and central bank inflation target. Therefore we try to analyze the crucial problems of efficiency of the inflation targeting strategy - the causality and sensitivity between interest rates on Prague interbank market (PRIBOR) and Czech National Bank repo rate. For this purpose we use the framework of expectation theory with the term premium and simple deterministic regression models. We found out that as repo rate was sticky it led to higher volatility of PRIBOR before repo rate change and when the maturity of PRIBOR was increasing the sensitivity of PRIBOR to repo rate changes was strongly decreasing. In our opinion it's the result of at least partial adjustment of PRIBOR before repo rate changes.