There are many factors influencing the level and changes of the labour productivity. One of the useful methods of identifying these factors is shift-share approach. It makes it possible to determine if the sectoral structure or the level of competitiveness of the economy affects the dynamics and differentiation of labour productivity. The research concerned countries of the European Union, covered the period of 1999-2006 and was conducted for six main economic sectors. All examined countries were characterized by constant growth of labour productivity which was mainly caused by the increasing productivity in market financial services. The basic reason of productivity diversification was a country's competitiveness. The positive relation between sectoral structure and regional component also occurred.

BOOK REVIEWSMariusz E. Sokołowicz, Rozwój terytorialny w świetle dorobku ekonomii instytucjonalnej. Przestrzeń -bliskość - ....................................................................................................................... 118 Application of correspondence analysis to the identification of the influence of features of unemployed persons on the unemployment duration 1 Jacek Batóg 2 , Barbara Batóg 2 Abstract : The paper presents the analysis of the influence of selected features of unemployed persons on unemployment duration. Theoretical considerations go along with an empirical study based on individual data from Local Labour Office in Szczecin. The research hypothesis states that features of unemployed persons such as the level of education, sex, work seniority or age have a meaningful influence on unemployment duration. Recent studies usually used event history analysis, inflow-outflow analysis of the labour market or logit models. This research is unique because of the application of one of the methods of multidimensional analysis -correspondence analysis. This method allows analysis of multidimensional relationships between categories of nominal variables. From the results obtained it could be stated that strong relationships between unemployment duration and features of unemployed persons exist (apart from sex).

Accurate revenue prediction is a key factor for the reliable determination of the investment part of entire regional and local budgets, particularly during economic downturns and fiscal uncertainty. An unexpected decline in revenue requires the reduction in capital expenditures and forces the regional government to find additional sources to close the budget gaps. Current studies indicate that budget forecasts often underpredict revenue and use the available information inefficiently. In this article, the authors examine chosen methods of forecasting regional government revenue. In addition to classical forecasting models based on time series and causal models, an original structural forecasting procedure was proposed, which is effective especially in case of data delay. The reliability of applied methods was assessed using data from the Polish area of Zachodniopomorskie over the period 2000–2018. The found evidence supported results that were obtained by many other researchers, which indicated that less comprehensive methods of forecasting can provide reasonably accurate estimates.

The creation of an effective growth policy requires the identification of its key determinants. The study used one of the methods of multidimensional analysis-discriminant analysis. It is widely used on a microeconomic scale, especially in the area of forecasting bankruptcy of enterprises, but in the area of economic growth, it has not been used in practice so far. In addition to the main objective of identifying the most important economic growth factors of the European Union countries in 2000-2016, the impact of the crisis and accession to the EU was examined. The statistical data sources were the databases of Eurostat and the Conference Board (Total Economy Database). The results obtained allowed us to conclude that the rate of Gross Domestic Product growth in the EU countries was determined by consumption, investment, export and labour productivity, and in periods of economic slowdown also public debt. The enlargement of the EU resulted in an increase in the importance of export.

Due to limited resources, effective urban development policies require the identification of key development areas and priorities. The existing development strategies or results of statistical analyses can be used for this purpose. In the latter case, one of methods of multidimensional analysis can be used – discriminant analysis. Although it is applied to many areas on a microeconomic scale, e.g. in predicting the bankruptcy of enterprises, it was rarely used to assess the competitive position or the dynamics of development of cities. The main aim of the paper is to identify the most important factors of development of Polish cities with powiat status and to analyse changes of these factors in time. Apart from typical areas, such as investment, income, employment, debt, or migration, the analysis uses qualitative variables which allow us to assess whether the size of the city and its location determine the dynamics of city development. The authors have found that the key factors determining the development of the largest Polish cities are related to the situation on the labour market and investments incurred by companies as well as by the cities themselves.

Financial performance of companies and their groups is of major interest to all stakeholders. As a result, they assess categories such as profitability, financial liquidity, financial independence, and risk. Separate analyses carried out for each of those elements alone do not always deliver conclusive findings, which is where synthetic methods are helpful. A ranking based on the taxonomic measure of development is one of such methods. The aim of the paper is, firstly, to present opportunities for using a dynamic version of the taxonomic measure of development in a comparative and complex assessment of financial performance in PKD divisions (Polish Classification of Activity), and, secondly, to evaluate changes in this area in the years 2014–2016. The data used for developing the ranking were sourced from the joint publication of industry indicators by the Financial Analysis Commission at the Research Council of the Accountants Association in Poland and InfoCredit, and from the Statistics Poland.

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