Female unemployment and its determinants in Poland in 2016 from the spatial perspective

Main Article Content

Karolina Lewandowska-Gwarda

Abstract

Research background: Through the cultural progress and socio-economic development in Poland women have obtained the same rights as men in the labour market. Nevertheless, they continuously face discrimination and the difficulty, resulting from their traditional role, in finding or maintaining employment.


Purpose of the article: The main objective of this study was an analysis of female unemployment and its determinants in Poland in 2016 from the spatial perspective. The following research questions were also specified: Is female unemployment dependent on social factors (do they play the key role)? Are the factors determining the level of female unemployment spatially diversified? Is the GWR model an effective tool in analysis of female unemployment?


Methods: The research applied GIS and spatial analysis methods including Geographically Weighted Regression, which enables the identification of the variability of regression coefficients in the geographical space. The analysis was carried out based on statistical data presenting the share of unemployed women in the working age population for 380 Polish districts (NUTS 4, LAU 1) in 2016.


Findings & Value added: The research results showed that in the period 2003-2016 the female unemployment was getting lower, but it was still higher than men. It was also spatially diversified. Moreover, the determinants of female unemployment were diverse in the geographic space and did not have a significant impact on the variable in all spatial units. The existence of clusters of districts, characterised by similar interactions and its strength, was also confirmed. The results of this analysis proved that non-economic (social) factors largely affected the level of female unemployment in Poland in 2016. Using GWR enabled drawing detailed conclusions concerning the determinants of female unemployment in Poland, it proved to be an effective tool for the analysis of this phenomenon.

Article Details

How to Cite
Lewandowska-Gwarda, K. (2018). Female unemployment and its determinants in Poland in 2016 from the spatial perspective. Oeconomia Copernicana, 9(2), 183-204. https://doi.org/10.24136/oc.2018.010
Section
Articles

References

Akinwande, M. O., Dikko, H. G., & Samson, A. (2015). Variance inflation factor: as a condition for the inclusion of suppressor variable(s) in regression analysis. Open Journal of Statistics, 5(7). doi: 10.4236/ojs.2015.57075.
ASM Centrum Badań i Analiz Rynku Sp. z o.o. (2006). Diagnosis of the situation of women on the labor market in Poland. Women's professional activation system: Working woman). Retrieved from www.kobietapracujaca.org (06.03.2017).
Auleytner, J. (Ed.). (2008). Multifaceted diagnosis of the situation of women in the labor market. Warszawa: MPiPS.
Bieszk-Stolorz, B. (2017). The impact of gender on routes for registered unemployment exit in Poland. Equilibrium. Quarterly Journal of Economics and Economic Policy, 12(4). doi: 10.24136/eq.v12i4.38.
Bremond, J., Couet, J. F., & Salort, M. M. (1997). Dictionnaire De L'Essentiel En Economie. LIRIS.
Brunsdon, C., Fotheringham, S., & Charlton, M. (1996). Geographically weighted regression: a method for exploring spatial nonstationarity. Geographical Analysis, 28(4). doi: 10.1111/j.1538-4632.1996.tb00936.x.
Charlton, M., & Fotheringham, A.S. (2009). Geographically weighted regression. White paper. National Centre for Geocomputation National University of Ireland Maynooth. Retrieved from http://gwr.nuim.ie /downloads/GWR_White Paper.pdf (15.03.2017).
Drela K. (2014). Discrimination against women on the Polish labor market? Ekonomiczne problem usług, 114.
Elhorst, J. P. (2003). The mystery of regional unemployment differentials. Theoretical and empirical explanations. Journal of Economic Surve, 17(5). doi: 10.1046/j.1467-6419.2003.00211.x.
Fotheringham, A. S., Charlton, M., & Brunsdon, C. (1997). Measuring spatial variations in relationships with geographically weighted regression. In M. Fischer & A. Getis (Eds.). Recent developments in spatial analysis. London: Springer Verlag.
Golinowska, S., Gwarońska-Nowak, B., & Zarzycka, A. (2004). Work from a gender perspective. In S. Golinowska (Ed.). For the sake of work. Report on social development Poland. Warszawa: CeDeWu.
Haponiuk, M. (2013). The situation of women on the labor market in Poland. In M. Kiełkowska (Ed.). Labor market in the face of demographic changes. Warszawa: Instytut Obywatelski.
Instytut Badań Strukturalnych. (2015). Pay inequalities of women and men. Measurement, trends, explanations. Retrieved from http://ibs.org.pl/app/ uploads/2016 /05/ IBS_Nierownosc_Placowa _raport.pdf (06.03.2017).
Kalinowska-Nawrotek, B. (2004). Forms of discrimination against women on the Polish labor market. Ruch Prawniczy, Ekonomiczny i Socjologiczny, 2.
Kantar, Y. M., & Aktaş, S. G. (2016). Spatial correlation analysis of unemployment rates in Turkey. Journal of Eastern Europe Research in Business and Economics, 1(9). doi: 10.5171/2016.136996.
Khamis, F.G. (2012). Measuring the spatial correlation of unemployment in Iraq-2007. Modern Applied Science, 6(1). doi: 10.5539/mas.v6n1p17.
Kołaczek, B. (2009). Discrimination against women in employment. Polityka Społeczna, 5(6).
Kopycińska, D., & Kryńska, E. (2016). Wage inequalities between men and women in Poland – a justified differentiation or accepted wage discrimination of women? Economics and Sociology, 9(4). doi: 10.14254/2071789X.2016/9-4/14.
Kotowska, I. E. (1995). Discrimination against women in the labor market in Poland during the transition to a market economy. Social Politics: International Studies in Gender, State & Society, 2(1). doi: 10.1093/sp/2.1.76.
Kwiatkowska, W. (2012). Unemployment in problem groups on the labor market in Poland. Acta Universitatis Lodziensis, Folia Oeconomica, 268.
Le Gallo, J., & Ertur, C. (2003). Exploratory spatial data analysis of the distribution of regional per capita GDP in Europe, 1980–1995. Papers in Regional Science, 82(2). doi: 10.1111/j.1435-5597.2003.tb00010.x.
Lewandowska-Gwarda, K. (2012). Spatio-temporal analysis of unemployment rate in Poland. Comparative Economic Research. Central and Eastern Europe, 15(4). doi: 10.2478/v10103-012-0031-9.
Lewandowska-Gwarda K. (2018). Geographically weighted regression in analysis of unemployment in Poland. International Journal of Geo-Information, 17(1). doi: 10.3390/ijgi701001.
Ludera-Ruszel, A. (2016). The situation of women in the labor market in Poland in the light of existing labor law provisions concerning the working time. Przegląd Politologiczny, 4. doi: 10.14746/pp.2016.21.4.11.
Musiał-Karg, M. (2017). Women on the labor market - analysis of conditions. Czasopismo Naukowe Instytutu Studiów Kobiecych, 2(3).
McMillen, D. (1996). One hundred fifty years of land values in Chicago: a nonparametric approach. Journal of Urban Economics, 40(1). doi: 10.1006/juec. 1996.0025.
Netrdová, P., & Nosek, V. (2016). Spatial patterns of unemployment in Central Europe: emerging development axes beyond the Blue Banana. Journal of Maps, 12(4). doi: 10.1080/17445647.2015.1063467.
Oczki, J. (2016). Gender pay gap in Poland. Ekonomia Międzynarodowa, 14. doi: 10.18778/2082-4440.14.01.
Rękas, M. (2013). Mothers and their return to the labor market after childbirth in research results. Studia Ekonomiczne Uniwersytet Ekonomiczny w Katowicach, 161.
Salvati, L. (2015). Space matters: reconstructing local-scale Okun’s law for Italy. International Journal of Latest Trends in Finance and Economic Sciences, 5(1).
Siemieńska, R. (1996). Gendered perceptions: women in the labour market in Poland. Women's History Review, 5(4). doi: 10.1080/09612029600200 130.
Tracz-Dral, J. (2013). Discrimination in employment due to gender. Warszawa: Kancelaria Senatu.
Wheeler, D. (2007). Diagnostic tools and a remedial method for collinearity in geographically weighted regression. Environment and Planning A, 39(10). doi: 10.1068/a38325.
Witkowska, D. (2016). Comparison of women’s situation in the labour market in the former GDR and Poland. Comparative Economic Research, 19(2). doi: 10.1515/cer-2016-0017.
Yu, D-L. (2006). Spatially varying development mechanisms in the Greater Beijing area: a geographically weighted regression investigation. Annals of Regional Science, 40(1). doi: 10.1007/s00168-005-0038-2.