Contemporary Economics Quarterly of University of Finance and Management in Warsaw Volume 9 Issue 4 November 2015 SOCIAL DIAGNOSIS 2015 OBJECTIVE AND SUBJECTIVE QUALITY OF LIFE IN POLAND DIAGNOZA SPOŁECZNA 2015 WARUNKI I JAKOŚĆ ŻYCIA POLAKÓW Edited by: Janusz Czapiński Tomasz Panek Raport Diagnoza Społeczna 2015 finansowany przez: Warszawa: Rada Monitoringu Społecznego listopad 2015
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Social Diagnosis 2015 119 Please use the following citation when referring to this chapter: Panek, T. (2015). Household living conditions. Analysis of households living conditions by Voivodship. Social Diagnosis 2015, The Objective and Subjective Quality Of Life In Poland. Contemporary Economics, 9/4, 119-122. DOI:10.5709/ce.1897-9254.186 4.8. Analysis of households living conditions by Voivodship Tomasz Panek 1 1 Warsaw School of Economics, Institute of Statistics and Demography Abstract Comparison of conditions of life in households according to the voivodship was done on the basis of a taxonomic measure of conditions of life. Living conditions in households were measured in terms of financial possibilities of satisfying their needs. Five groups of voivodships were indicated. 4.8.1. Comparison of households living conditions Households living condition levels by voivodship were compared on the basis of a taxonomic measure of living conditions 35. The living conditions of the households were measured in terms of financial possibilities of satisfying their needs. The taxonomic measure of living conditions is a composite indicator being the product of the influence of all the variables (indicators) describing the financial need-fulfilment capacity for all living condition types selected in the research and arranged according to voivodship. Household living conditions in each Voivodship are estimated by comparing selected variable values for each Voivodship with values of these variables for a hypothetical model voivodship. The variables used in the construction of taxonomic measure of living condition are different in nature, namely: Stimulant variables, for which the rising value indicates improvement in household living conditions in a Voivodship. Destimulant variables, for which the rising value indicates deterioration in household living conditions in a Voivodship. The starting point for building up a taxonomic measure of living conditions is selecting variable values for the model voivodship. These are the optimal values of each variable describing household s living conditions in the voivodships - with the stimulant variables at maximum observed values and the destimulants at minimum observed values from all compared Voivodships. When the comparative analysis refers to a number of periods at the same time, optimal values are set as the maximum or minimum among all compared Voivodships in all analysed periods. The model voivodship therefore is an ideal model against which each voivodships is compared. In formal terms, compared voivodships and the model voivodship are represented by points in the space of variables that describe them. The number of dimensions of this space (the number of axes defining the dimension) is equal to the number of variables describing living conditions in the voivodships. The next step of the procedure is to standardise the values of the selected variables. This makes it possible to both eliminate the units of measurement and the prevalence in share of high-value variables in the living condition numerical values. Values of synthetic measure of living conditions (like group measures of living conditions in each of their categories) are obtained by calculating the distance between individual points representing voivodships in relation to the point representing the model voivodship. The better the households living conditions in a given Voivodship the smaller the distance between its point and that of the model. Thanks to appropriate normalisation, both group measures of living conditions in each of their categories and the synthetic measure of living conditions always appear as values from interval [0; 1]. The better the living conditions, the closer the appropriate measure of living conditions is to 0; the worse the conditions, the higher the value (i.e. closer to 1). The comparative analysis of living conditions by voivodships was conducted, as already mentioned, from the point of view of households financial means of fulfilling needs in selected areas. This means that on assessment of the level of certain needs fulfilment, especially in terms of culture and recreation may also affect a lack of feeling these needs, which then causes a lack of financial problems in this respect. Małopolskie, Opolskie, Lubuskie and Wielkopolskie Voivodships reported the highest quality of living conditions (column 10 in Table 4.8.1.) in 2015 with the lowest recorded for Warmińsko-Mazurskie, Lubelskie, Łódzkie and Kujawsko-Pomorskie. The hierarchy of Voivodships was varied in terms of needs fulfilment levels in each area of living conditions. In the case of income, the best situation was noted in Mazowieckie, Pomorskie and Dolnośląskie and the worst in Podkarpackie, Lubelskie and Kujawsko-Pomorskie. As far as nutrition was concerned, the highest needs fulfilment was recorded in Wielkopolskie, Małopolskie and Opolskie and the lowest in Warmińsko-Mazurskie, Podkarpackie and Kujawsko-Pomorskie. Needs in terms of material affluence were most fulfilled in Podlaskie, Opolskie and Małopolskie, and least in Warmińsko-Mazurskie and Kujawsko-Pomorskie. In terms of housing conditions, the highest level of need fulfilment was recorded in Śląskie, Małopolskie and Podkarpackie, and the lowest in Lubelskie, Łódzkie and Warmińsko-Mazurskie. 35 35 The algorithm for estimation of taxonomic measure of living conditions is a modified taxonomic measure of development (vide e.g. Hellwig, The algorithm for estimation of taxonomic measure of living conditions is modified taxonomic measure of development (vide e.g. Hellwig, 1968; Panek 2009). 1968; Panek 2009). Rada Monitoringu Społecznego
Social Diagnosis 2015 120 In terms of children s education, the situation was the best in Lubuskie, Świętokrzyskie and Opolskie and the worst in Warmińsko-Mazurskie and Lubelskie. The healthcare needs were fulfilled the most in Opolskie and Małopolskie, and the least in Dolnośląskie, Podkarpackie and Warmińsko-Mazurskie. The highest level of need fulfilment in terms of participation in culture was reported in Opolskie, Wielkopolskie and Lubuskie, while the lowest in Dolnośląskie, Łódzkie and Śląskie. In terms of recreation, the best situation was observed in Mazowieckie, Wielkopolskie and Lubuskie, while it was the worst in Podkarpackie and Świętokrzyskie. Table 4.8.1. Household living conditions by voivodship in 2015 from best to worst in the last column Voivodship income nutrition material affluence Living condition dimensions housing conditions children's education healthcare participation in culture recreation Małopolskie 0.374 0.193 0.477 0.332 0.337 0.257 0.268 0.200 0.248 Opolskie 0.571 0.275 0.430 0.567 0.271 0.234 0.213 0.201 0.364 Lubuskie 0.363 0.385 0.696 0.501 0.239 0.418 0.245 0.195 0.375 Wielkopolskie 0.473 0.075 0.591 0.611 0.445 0.460 0.234 0.179 0.396 Mazowieckie 0.000 0.421 0.618 0.343 0.645 0.576 0.257 0.145 0.420 Pomorskie 0.313 0.474 0.668 0.388 0.502 0.375 0.291 0.525 0.467 Śląskie 0.383 0.355 0.713 0.304 0.570 0.493 0.668 0.588 0.585 Podlaskie 0.563 0.408 0.297 0.639 0.327 0.652 0.598 0.625 0.593 Zachodniopomorskie 0.425 0.458 0.502 0.401 0.654 0.649 0.560 0.431 0.608 Dolnośląskie 0.361 0.628 0.653 0.433 0.622 0.728 0.684 0.201 0.640 Podkarpackie 0.747 0.667 0.494 0.332 0.319 0.723 0.317 0.649 0.641 Świętokrzyskie 0.607 0.429 0.469 0.701 0.251 0.636 0.655 0.648 0.642 Kujawsko-pomorskie 0.653 0.658 0.819 0.705 0.436 0.458 0.586 0.244 0.699 Łódzkie 0.538 0.364 0.625 0.720 0.713 0.678 0.678 0.632 0.718 Lubelskie 0.660 0.605 0.524 0.724 0.704 0.439 0.567 0.578 0.727 Warmińsko-mazurskie 0.582 0.809 0.819 0.716 0.715 0.712 0.274 0.505 0.743 total The underlying aim of grouping voivodships was to define most homogenous groups in terms of living conditions structure as described by variables representing assessment of need fulfilment levels in certain areas of living conditions gained from the taxonomic measure of living conditions (Table 4.8.1.). The Voivodships were grouped using the k-means method 36 (Panek, 2009), which maximises inter-group variation and minimises variation inside the groups. The starting point of the k-means method is a decision on the number by which to divide the population of Voivodships. In this research, we decided to divide the Voivodships into four groups. The groups of Voivodships with a similar structure of living conditions as of 2015 were as follows: Group 1: Dolnośląskie, Mazowieckie, Pomorskie, Śląskie and Zachodniopomorskie, Group 2: Kujawsko-Pomorskie, Lubelskie, Łódzkie and Warmińsko-Mazurskie, Group 3: Podkarpackie, Podlaskie and Świętokrzyskie, Group 4: Lubuskie, Małopolskie, Opolskie and Wielkopolskie. 36 The k-means method is described in Annex 3.2
Level the lack of satisfaction of needs Social Diagnosis 2015 121 0,8 0,7 Group 1 Group 2 Group 3 Group 4 0,6 0,5 0,4 0,3 0,2 0,1 0 income nutrition material affluence housing conditions children education health care culture recreation Household living condition dimensions Figure 4.8.1. Household living conditions by voivodship groups in 2015. Group 1 is characterised by relatively the highest average need fulfilment level in terms of income and housing conditions. The fulfilment of needs in all the other groups is on average level. In Group 2, we observe the lowest average need fulfilment level in terms of nutrition, housing, children s education and cultural participation. In the remaining living condition areas the average need fulfilment is also relatively low. Group 3 was, in 2015, relatively the weakest at fulfilling needs in the areas of income, healthcare, and recreation, while they were the strongest on average in comparison to other Voivodships in terms of material affluence and children s education. Finally, in Group 4, need fulfilment was relatively the strongest in terms of nutrition, healthcare, culture participation and recreation. Table 4.8.2. Results of one-way analysis of variance. Dimension BSS df1 WSS df2 F Income 0.315 3 0.173 12 7.277 Nutrition 0.301 3 0.236 12 5.095 Material affluence 0.147 3 0.156 12 3.773 Housing conditions 0.266 3 0.134 12 7.940 Children education 0.372 3 0.101 12 14.772 Health care 0.213 3 0.179 12 4.749 Culture 0.223 3 0.327 12 2.741 Recreation 0.376 3 0.243 12 6.217 In order to evaluate the discriminatory power of specific areas of living conditions in groups (their significance in grouping voivodships), one-way variable analyses were conducted (Panek, 2009). On the basis of the value of statistic F, the ratio of inter-group diversity (BSS) to intra-group diversity (WSS) was established, weighted with appropriate degrees of freedom (df1 and df2). Dimensions can be grouped due to their importance in voivodship grouping. The higher the value, the bigger the discriminatory power of that particular area of living conditions. The highest discriminatory power in the grouping was that of children education and income 37. References Helliwig Z. (1968). Zastosowanie metody taksonomicznej do typologicznego podziału krajów ze względu na poziom ich rozwoju i strukturę wykwalifikowanych kadr. Przegląd Statystyczny, nr 4. [English: Application of the taxonomic method in the typological division of countries in terms of development and the structure of qualified personnel] 37 These findings relate to the results of one-dimensional analysis of discriminatory power of areas of living conditions and do not take into account the multidimensional effects (Panek i Zwierzchowski, 2013, 339-344).
Social Diagnosis 2015 122 Panek T. (2009). Statystyczne metody wielowymiarowej analizy porównawczej. Warszawa: Oficyna Wydawnicza Szkoły Głównej Handlowej. [English: Statistical methods of multi-dimensional comparative analysis] Panek T., Zwierzchowski J. (2013). Statystyczne metody wielowymiarowej analizy porównawczej, Teoria i zastosowania, Oficyna Wydawnicza SGH, Warszawa. [English: Statistical methods of multi-dimensional comparative analysis. Theory and application]