Consumption function in the context of cultural affinity zones

Consumers' purchasing behaviour is affected at the microeconomic level by personal, psychological, situational, social and cultural factors. Beside the political and economic factors, culture with its beliefs, values, attitudes and traditions plays a substantial role also at the macroeconomic level in affecting national aggregate consumption, despite the recent phenomenon of globalisation. There is an evidence of excess sensitivity in European countries, which confirms that income change is a good predictor of consumption change. Clusters of European countries constructed according to single consumption functions correspond to some extent to the cultural affinity zones. Reactions (marginal propensity to consume) vary among formed groups of European countries and average consumption response is the highest in wealthier Western, followed by Central Europe and is the lowest in the South Europe. The results of this paper suggest that a stabilization policy may be more effective in an individualistic, hedonistic, rather a decentralised culture.O

On Estimation and Testing for Pareto Tails

2010 Mathematics Subject Classification: 62F10, 62F12.The t-Hill estimator for independent data was introduced by Fabian and Stehlik (2009). It estimates the extreme value index of distribution function with regularly varying tail. This paper considers sampling of an infinite moving average model. We prove that in the discussed case the t-Hill estimator is weak consistent. However, in contrast to independent identically distributed case here it is shown that the t-Hill and the Hill estimator applied to the moving average model are not robust with respect to large observations

The New Oil Sector and the Dutch Disease: the Case of Ghana

This paper investigates the impact of the new oil sector on the economic performance of major traditional sectors of the Ghanaian economy. The discovery of resource booming sectors in most countries often comes with several opportunities as well as challenges. Ghana discovered oil in 2007 and started subsequent commercial production and export in 2010. The results from the study show that, there is no clear case of declining performance of sectors in terms of output, growth and export earnings as a result of the oil production. The study could also not establish a sustained appreciation in the real effective exchange rate since commercial oil production commenced which is an indicator of the presence of the Dutch Disease phenomenon. The real effective exchange rate was also found to be highly influenced by oil production, oil prices, total exports and remittances. The study applied an autoregressive distributed lag model due to differences in the level of integration of variables. The data was obtained from the Bank of Ghana, the Ministry of Finance in Ghana and the Energy Information Administration

Comparison of power of modified Jarque-Bera normality tests and selected tests of normality

The aim of this paper is to modify the classical Jarque-Bera test and the robust Jarque-Bera test of normality. We use the median as an estimator instead of the mean in the classical Jarque-Bera test and in the robust Jarque-Bera test. This leads to the modified Jarque-Bera test and the modified robust Jarque-Bera test. Paper also demonstrates results of simulation studies of power of such tests with the various alternatives – light tailed alternatives as exponential, lognormal and gamma distribution, heavy tailed alternatives as Cauchy, Laplace, t3, t5 and logistic distributions and short tailed alternatives as beta and uniform distributions. These tests of normality are also used for normality testing of selected datasets of financial time series. Source data include logarithmic returns of monthly ave­ra­ge prices of Prague stock exchange index PX and monthly average prices of CZK/EUR exchange rate in the period from 2000 to 2007

Robustní testy normality a jejich využití při ověřování slabé formy efektivnosti akciového trhu

Submitted dissertation is focused on methods of robust normality testing and applications of robust tests in verifying hypothesis of the weak form of efficiency in stock markets. In the dissertation, theory of efficient markets and approaches to verifying the weak form of market efficiency and normality assumption are being discussed. Novel robust testing procedures of testing normality are proposed in this work to overcome shortcomings of classical normality tests in the field of financial data, which are typical with occurrence of remote data points and additional types of deviations from normality. Results of power simulation study of classical and robust tests of normality against several types of alternative distributions, i.e. symmetric heavy-tailed, symmetric light-tailed, asymmetric heavy-tailed, asymmetric light-tailed, selected mixtures of normal distributions and outlier models, are presented. Based on outcome of the power simulation study, selected normality tests were consequently used to verify the weak form of efficiency in stock markets in the Czech Republic, Hungary, Austria, Germany, Slovakia, United States and Japan during years 2000-2009. In addition to selected classical and robust normality tests, Ljung-Box portmanteau test was also used. In conclusion, there is a discussion and comparison of results carried out and future trends of these markets are outlined

Analysis of power of the classical and robust normality tests against bimodal distribution

The aim of this paper is to compare the power of selected normality tests to detect a bimodal distribution. We use some classical normality tests (the Shapiro-Wilk test, the Lilliefors test, the Anderson-Darling test, the classical Jarque-Bera test and the Jarque-Bera-Urzua test), some robust normality tests (the robust Jarque-Bera test and the Medcouple test) and the modified Jarque-Bera tests, where the median instead of the mean is used in the classical Jarque-Bera test statistic. The results of simulation study show that the Anderson-Darling and the Shapiro-Wilk tests outperform the others, especially in small sample sizes. On the other hand the classical Jarque-Bera, the Jarque-Bera-Urzua and robust Jarque-Bera tests are biased, especially in small sample sizes again. Finally, the modification of the Jarque-Bera test leads to increase of power against bimodal distribution

Analysis of increasing trend of mortgage volume in the Czech Republic

The aim of this paper is an empirical analysis of mortgage volume in the Czech Republic and factors identification of the increasing trend of the mortgage volume in the period from 2001 to 2007. Firstly, analysis of quarterly time series of mortgage volume and average mortgage rate are performed. Consequently, causality between mortgage volume and average mortgage rate is analysed. The morgage rate is the most important factor for economic subjects decision of residential investment. Afterwards, it is analysed causality between mortgage volume and selected factors via multiple regression analysis. Based on this analysis, influencing factors for multiple regression analysis describing mortgage volume are selected. Our empirical analysis validate the causality between mortgage volume and mortgage rate, unemployment rate and price level of real estates. Part of this paper is also economic eduction of causality and estimation of expect progress of mortgage volume especially in connection with present economic and business recession

On normality assumptions for claims in insurance

The aim of this paper is to discuss effects of deviations from hypothetized normality. Two models are considered, one is the first pension pillar (and we consider here very small samples, which plays some role at start of some pension system or at early phases of it) and second one of modeling for IBNR (here we consider mid-samples). We will show that at early phases of 1st pension pillar in Slovakia the estimation of upper probability of oversizing of critical constant given by Potocký and Stehlík, 2005, fits well. For the case of IBNR reserves, the date given by Stelljes, 2006, are significantly more skewed and thus further research is needed for appropriate modelling of these reserves

Exploration into power of homogeneity and serial correlation tests

Verification of regression models is primarily based on analysis of error terms and constitutes one of the most important steps in applied regression analysis. In cross-sectional models, the error terms are typically heteroskedastic, while in time series regressions the errors are often affected by serial correlation. Consequently, in this paper, we focus on Monte Carlo simulations applied to explore the power of several tests of homogeneity and tests for presence of autocorrelation. In the past decades, the computational power has increased significantly to allow the benefit of simulation from exact distributions, which are not defined explicitly. We will discuss 1) testing of homogeneity for a given number of components in the exponential mixture approximated by subpopulations and 2) simulation of power in several commonly used tests of autocorrelation. For the first case, we consider exact likelihood ratio test (ELR) and exact likelihood ratio test against the alternative with two-component subpopulation (ELR2). In the second case, we consider the Durbin-Watson, Durbin h, Breusch-Godfrey, Box-Pierce and Ljung-Box tests of 1st order serial correlation and the runs test of randomness in two different types of linear regression models