C38 - Multiple or Simultaneous Equation Models: Classification Methods; Cluster Analysis; Principal Components; Factor ModelsReturn

There is no consensus on the key drivers of financial inclusion due to variation in the socioeconomic features of countries, use of indicators and research methods. The main objective of this study is, therefore, to empirically examine the key drivers of financial inclusion across 26 selected Sub-Saharan African (SSA) economies for the period between 2000 and 2019, using a system generalized method of moments (GMM). A principal component analysis (PCA) is applied to construct a composite index of financial inclusion to address the multi-dimensional nature of the variable. The findings of the study indicate that both the macroeconomic and microeconomic factors influence the level of financial inclusion of the SSA countries. Specifically, the lag effect, economic growth, financial stability, inflation, financial deepening, liquidity, profitability, and bank efficiency are important drivers of financial inclusion in the SSA region. It is therefore important for policy makers and regulators to consider these factors while developing policies and strategies that foster access to financial products and services and ensure financial inclusion in the region.

We investigate commonality and heterogeneity of inflationary processes in ten Central and Eastern European (CEE) countries over the period 2001-2013. The research is important for the analysis of monetary policy as it helps understand the origin of price formation from both sectoral and country perspective. With a multi-level factor model we decompose product-level inflation rates into the CEE region-wide, sector, country, country-sector, and idiosyncratic components. The outcomes indicate that CEE region-wide and country specific components are more persistent than sector and product-level components, which is in line with similar studies for core EU countries. Regional factors explain about 17% of variance in monthly price changes, which is more than any other factors (below 10% each). This result is at odds with the assumptions of many sectoral DSGE models and empirical evidence on the importance of sectoral price shocks in developed economies. The difference may be related to the conclusion that the first regional factor is associated with common disinflationary process that occurred in CEE economies in the 2000s, whereas the second one reveals significant correlations with global factors, especially commodity prices and euro area price developments.

The paper analyses the evolution of the retail network of the capital city of Slovakia Bratislava affecting buying behaviour and lifestyle of its consumers. From the marketing point of view, it characterizes the space behaviour of the consumers and presents the behaviour of consumers living in single districts of Bratislava. It shows, on the one hand, how the importance of consumer behaviour rises in the declining economic prosperity during last years, while on the other hand, the concentration in retail declines the chances for success of small independent food retail stores during last recent years. The authors used different methods, e.g. GIS, cluster analysis, for testing they asses the significance of market segments on the sample involving 11,389 respondents interviewed.

Income, expenditure and similar variables in monetary units tend to have distributions similar to log-normal. Description of such variables after logarithmic transformation by the normal model is often not accurate enough, especially for multivariate data. Deviations of their empirical distributions from the theoretical lognormal distribution often require more sophisticated analysis. Mixtures represent a very flexible way of reconstructing complex distributions with irregular features and are suitable for detailed modelling. Multivariate mixture models are applied to the Czech longitudinal survey of household income in the European Union Statistics on Income and Living Conditions (EU-SILC) in 2005-2008. The analysis identifies distinct patterns of progression of income, with a high percentage of households having steady annual increases over the four years (three transitions). Graphical presentation of the results is emphasised.

Composite indicators as a tool for a ranking become more and more popular, because they illustrate a comprehensive view on a phenomenon that cannot be captured by only one single indicator. Indicators for Europe 2020 are set of indicators used for monitoring targets defined by the European Commission in the Strategy of Smart, Sustainable and Inclusive Growth. The main objective of this paper is the comparison of performance of the EU Member States using the composite indicator principles. Within constructing composite indicators several steps have to be made and corresponding methods have to be chosen. There is not only one correct method how to develop a composite indicator. Of course, the choice of the methods manipulates the results. Primarily, normalisation methods, weighting schemes and aggregation formulas are fundamental but very subjective. This paper deals with two types of normalisation (z-score and min-max) and four weighting and aggregation schemes (equal weighting with linear aggregation, principal components analysis, benefit of doubt method and multi-criteria analysis). European countries ranking is provided according to the seven different scenarios.

The swap market is key segment of the fixed income market due to its liquidity and tight links to other market segments. In our paper we estimate basic parameters of the swap curve and we test the stability of these parameters during the crises period. Our estimate confirms that the Czech swap curve may be represented by three components that track its level, slope and curvature. These parameters were stable during the crises period that culminated in the autumn 2008. On contrary, the basic swap curve characteristics are showing most abnormal behaviour during periods of relative calm development. The traditional determinants of the Czech swap curve remain monetary policy, euro swap rates and risk premiums. Although risk premiums are low in the swap market, the large increase in risk premium in the Czech money market rates had significant impact on the swap curve slope during the crises period.