Statistika: Statistics and Economy Journal - No. 4/2016

The Human development index is one of the most frequently used indicators of living conditions of population. We can find three dimensions in its structure – education, health and living standard. Since HDI represents a composite indicator combining three different indicators it is necessary to measure the sensitivity of each of its components. HDI is widely used to compare countries from any part of the world and therefore the variability of the indicators is high. The aim of this article is to show the dependency and mutual influence of individual imputed indicators to HDI. The construction of HDI and theoretical methods of sensitivity are also covered. Results show that the influence of individual inputs on the final HDI and its robustness differ among individual types of input and the strongest correlation of HDI occurs with the dimension of living standard. The influence of other indicators is affected by some other technical parameters of HDI construction.

Keywords
Human Development Index, Sensitivity Analysis, Gross National Income, Education, Health

Business and Consumer surveys are designed to signal turning points and provide in advance the informatik about potential changes in the economic cycle. The authors, using advanced methods of time series analysis, especially Granger causality and vector autoregressive models, deal with the question of to what extent the results of the surveys in the form of confidence indicators are able to outpace the development of the Czech economy represented by gross value added. In addition, the authors, experimenting with the structure of surveyed questions and used weights, propose some modifications in the construction of confidence indicators as stipulated by the European Commission with the aim to improve their forecasting abilities.

Keywords
Business and consumer survey, gross value added, vector autoregressive model, Granger causality, economic sentiment indicator, stationarity test of variables

This paper uses an estimated DSGE model with an explicit housing sector to analyse the role of the housing sector and housing collateral for business cycle fluctuations in the Czech economy. The baseline results show that the development in the housing market has negligible effect on the rest of the economy. Counterfactual experiments indicate that the spill-overs increases with looser credit standards, if banks provide loans for higher value of houses. Similarly, with the higher loan-to-value ratios the transmission mechanism of monetary policy also seems to strengthen, with the key rates having bigger influence on the consumption and output. Looking at the development in house prices, the recent boom and bust is found to have been caused primarily by housing preference shocks (demand side shocks). Supply shocks are also found to have been significant, but to a much lesser extent.

Keywords
Housing, loan-to-value ratio, DSGE model, collateral constraint, Bayesian estimation

The aim of this article is to suggest and to apply a method for estimation of the regional price levels in Czech districts. Its purpose is to enable an assessment of spatial differences in the regional price levels and thereby to provide an instrument for more precise and more realistic comparison of standard of living of households across the regions of the Czech Republic. Authors use data from the extensive price surveys carried out by the Czech Statistical Office and regionalize them by an original approach derived from the Eurostat-OECD International Comparison Program and certified by the Ministry of Regional Development of the Czech Republic. The results reflect regional differences in market prices of goods, services, as well as housing and rentals. The findings underpin the need of a more accurate specification of economic and social disparities on a regional level originating in the recent shifts of regional policies from localities-and-areas-centered to local-people-centered.

Keywords
Consumer Behavior, Household Expenditure, Price Level, Regionalization, Törnqvist Index

FIS (Faculty of Informatics and Statistics) of the University of Economics in Prague, was founded in 1991. Since 2001, so for 15 years, master’s degree survey is performed at the graduation ceremonies of all the faculties of University of Economics in Prague. Its aim is to explore some of the circumstances of their studies, their jobs during the study, but especially their likely future labor involvement, their salary expectations and their satisfaction with studies at the university. Paper presents some data about students and graduates of the faculty from this survey, but also the information about the students and graduates from the project Reflex 2013. This survey was conducted in 2013 for the third time in a row by SVP PedF of Charles University in Prague with the aim to map out the exercise of university graduates in the labor market shortly after obtaining a diploma. Therein respondents rated their university studies, characterized his professional history, and expressed their professional competencies in relation to the requirements of their employment.

Keywords
Faculty of informatics and statistics, a survey of new graduates, Reflex 2013

Algeria is planning to carry out its sixth General Census of Population and Housing (RGPH) in 2018. This paper mainly concentrates on ONS’ vision of census data collection through the use of mobile technology, namely 3G and 4G LTE technologies. A challenge in this method is the accuracy of data entered: the mobile applications environment has a multitude of particularities. This requires an adaptable approach for performance analysis in terms of total quality management for software projects. Thus, our paper will address the issues related to the implementation of this mobile solution through a mobile application quality estimation model that requires the identification of features (e.g. interaction time, volume of provided information, error management, data security, transaction security, …). The paper proposes to look at a set of indicators normalized on the [0; 1] interval as to measure the application quality level.

Keywords
Census Mobile Application, Total Quality Management, Aggregate Indicator