Statistika: Statistics and Economy Journal - No. 3/2017

This paper studies the evolution of the relationship between households' and general government's expenditure on final consumption in the most recent 15 years; our data covers more than 30 countries. The most recent 15-year period has been characterised by variability in the worldwide economic development; hence this paper mainly focuses on the relationship to the rate of GDP growth. The mentioned relationship has also been assessed from the viewpoints of both the economic policy and the concepts that may be utilised by political representatives as the tools for controlling such economic policy.
This text aims at pointing out the importance of utilising the indicated issues, as related to the evolution of the relationship between the structure of the final consumption and the rate of economic growth, as well as the necessity of a proactive approach to the cognitive and behavioural activities, rather than in the modelling area, which has been visibly prevailing lately.

Keywords
Final consumption expenditure of households, government final consumption expenditure, GDP, economic crisis

This study aims at the research of the influence of unemployment rate (Un), exchange rate of CZK/USD (Ex), inflation rate (Inf), expenditures on research and development (RaD), size of wages and environmental pollution on inward foreign direct investment (FDI) into regions in the Czech Republic in the period 2002–2012. The study dealt with the whole period, then the pre-crisis and crisis period, altogether with the inclusion or elimination of Prague in or out of the group of Czech regions. Models without and with dynamic parameter were checked. For estimation of influence of the above mentioned parameters the fixed effects model, random effects model and pooled ordinary least squares (POLS) were used. For dynamic model the generalized method of moments and POLS were applied. The results showed that Wage, appreciation of Ex and RaD positively determined the inflow of FDI to Czech regions and no negative determinant of inward FDI has been found. On the other hand, results of dynamic model imply that inward FDI in preceding year, appreciation of Ex, RaD have positive impact on inward FDI in current year. However, negative impact of Un and Inf on inward FDI were detected. Results of this research enable the policy makers or decision makers try to focus their attention on specific factors and eliminate to consume scarce funding.

Keywords
Foreign direct investment, unemployment, inflation, expenditure on research and development, pollution, panel data

This paper aims to bridge the areas of credit risk and regional economic disparities, and investigates the relationship between credit risk and economic indicators in the Czech Republic at the regional (NUTS 3) level. This relationship is consecutively examined using graphical and correlation analysis, regression techniques, and different types of clustering methods. Regions are then clustered into three groups according to their economic similarities and disparities. Subsequently, it is shown on the real data that region-specific information has the potential to be utilizable in credit scoring and possibly other applications.

Keywords
Credit risk, regional disparities, cluster analysis, Bayesian information criterion, model selection, logistic regression

Public expenses are often evaluated in terms of their effectiveness. This is caused by the character of financial resources and by the fact that public activities are dependent on those resources. This paper addresses the evaluation of financial subsidies within the Operational Programme Environment 2007–2013. From the perspective of financial subsidies, the Operational Programme Environment was the second largest programme in the Czech Republic offering almost 4.92 billion EUR. Verifying the effectiveness of the management of these public funds is highly desirable, as the use of public funds is associated with a risk of over-exploitation. The main aim of the paper is to evaluate the supported projects and to offer new indicators. The assessment was based on the 3E survey. The results of the research confirmed that among the evaluated projects the desired outcomes are achieved at greater efficiency.

Keywords
Alley, efficiency of projects, forest ecosystem, landscape-related activities, operational programmes, recovery of landscape

Previous studies on the energy-environment-growth literature overlook the investigation of the most-visited countries. Since these countries do not only belong to the largest economies and the top carbon dioxide (CO₂) emitters in the world but are also listed in renewable energy country attractiveness index, this study analyzes the impacts of real GDP, renewable energy and tourism on the level of CO₂ emissions for the top 10 mostvisited countries. Applying several panel econometric approaches, we find out that renewable energy mitigates the pollution whereas real GDP and tourism contribute to the level of emissions. Thus, regulatory policies are necessary to increase the awareness of sustainable tourism. In addition, the use of renewable energy and the adoption of clean technologies in tourism sector as well as in producing goods and services play a significant role in CO₂ mitigation.

Keywords
Carbon dioxide emissions, tourism, renewable energy, real GDP, heterogeneity, cross-sectional dependence

The most important issues that national accounts have to solve today are the changes brought about by the globalization and the activity of multinational corporations on economic life. In June 2017, the 16^th Conference of the Association de Comptabilité Nationale was held in Paris to talk over these topical issues. The paper presents the most important discussion topics raised at the conference and reflects their importance for the further development of national accounts.

Keywords
National accounts, gross domestic product, Association de Comptabilité Nationale

Regional price level comparison in the Czech Republic was a topic not touched until recently. Then a team of researchers from the University of Economics in Prague pioneered the way for NUTS 3 regions for the year 2007 and repeatedly in 2012. Another step to establish more reliable results came together with a research team of the Technical University in Liberec, which brought qualitatively new and well advanced approaches. This article aims to discuss some aspects of the two attempts to establish regional price level comparison in the Czech Republic.

Keywords
Purchasing power parity, regional price level

Principal component analysis (PCA) is a popular dimensionality reduction and data visualization method. Sparse PCA (SPCA) is its extensively studied and NP-hard-to-solve modifcation. In the past decade, many diferent algorithms were proposed to perform SPCA. We build upon the work of Zou et al. (2006) who recast the SPCA problem into the regression framework and proposed to induce sparsity with the l₁ penalty. Instead, we propose to drop the l1 penalty and promote sparsity by re-weighting the l₂-norm. Our algorithm thus consists mainly of solving weighted ridge regression problems. We show that the algorithm basically attempts to fnd a solution to a penalized least squares problem with a non-convex penalty that resembles the l0-norm more closely. We also apply the algorithm to analyze the voting records of the Chamber of Deputies of the Parliament of the Czech Republic. We show not only why the SPCA is more appropriate to analyze this type of data, but we also discuss whether the variable selection property can be utilized as an additional piece of information, for example to create voting calculators automatically.

Keywords
Sparse principal components, IRLS, penalized least squares, roll-calldata

The focus of this paper is the nonparametric regression where the predictor is a functional random variable, and the response is a scalar. Functional kernel regression belongs to popular nonparametric methods used for this purpose. The two key problems in functional kernel regression are choosing an optimal smoothing parameter and selecting an appropriate semimetric as a distance measure. The former is the focus of this paper – several data-driven methods for optimal bandwidth selection are described and discussed. The performance of these methods is illustrated in a real data application. A conclusion is drawn that local bandwidth selection methods are more appropriate in the functional setting.

Keywords
Functional data, nonparametric regression, kernel methods, bandwidth selection