References
- ANSELIN, L. (1988): Spatial Econometrics: Methods and Models. Dordrecht, Kluwer.
- ANSELIN, L. (1995): Local Indicators of Spatial Association – LISA. Geographical Analysis, 27(2): 93–115.
- ANSELIN, L. (2003): An introduction to spatial autocorrelation analysis with Geoda. Spatial Analysis Laboratory, Department of Agricultural and Consumer Economics, University of Illinois, Urbana-Champaign, USA. [online]. [cit. 05.04.2013]. Available at: http://www.utdallas.edu/~briggs/poec6382/geoda_spauto.pdf
- ANSELIN, L., REY, S. J. (1991): Properties of tests for spatial dependence in linear-regression models. Geographical Analysis, 23(2): 112–131.
- ANSELIN, L., SYABRI, I. KHO, Y. (2004): GeoDa: An introduction to spatial data analysis. Spatial Analysis Laboratory, Department of Agricultural and Consumer Economics, University of Illinois, Urbana-Champaign, USA. [online]. [cit. 05.04.2013]. Available at: http://www.csiss.org/events/workshops/geodaGA.pdf
- ARBIA, G. (1989): Spatial Data Configuration in Statistical Analysis of Regional Economic and Related Problems. Boston, Kluwer.
- ARBIA, G. (2000): Some critique to statistical measures of spatial concentration and convergence. International Advances in Economic Research, 6(3): 590.
- ARBIA, G. (2001): The role of spatial effects in the empirical analysis of regional concentration. Journal of Geographical Systems, 3(3): 271–281.
- BLAŽEK, J., NETRDOVÁ, P. (2012): Aktuální tendence lokální diferenciace vybraných socioekonomických jevů v Česku: směřuje vývoj k větší mozaikovitosti prostorového uspořádání? Geografie, 117(3): 266–288.
- BOOTS, B., TIEFELSDORF, M. (2000): Global and local spatial autocorrelation in bounded regular tessellations. Journal of Geographical Systems, 2(4): 319–348.
- BRÜLHART, M., TRAEGER, R. (2005): An account of geographic concentration patterns in Europe. Regional Science and Urban Economics, 35(6): 597–624.
- CLIFF, A. D., ORD J. K. (1973): Spatial Autocorrelation. London, Pion.
- COWELL, F. A., FLACHAIRE, E. (2007): Income distribution and inequality measurement: The problem of extreme values. Journal of Econometrics, 141(2): 1044–1072.
- Czech Statistical Office (2014): Results of population censes 1980, 1991, 2001, and 2011 for municipalities in a regional structure in 2011. Prague, Czech Statistical Office.
- ELBERS, C., LAJOUW, P. F., MISTIAEN, J. A., ÖZLER, B. (2008): Reinterpreting between-group inequality. The Journal of Economic Inequality, 6(3): 231–245.
- FOTHERINGHAM, A. S. (1997): Trends in quantitative methods I: stressing the local. Progress in Human Geography, 21(1): 88–96.
- FOTHERINGHAM, A. S., BRUNSDON, C., CHARLTON, M. (2000): Quantitative geography – Perspectives on spatial data analysis. London, SAGE.
- GETIS, A. (2007): Reflections on spatial autocorrelation. Regional Science and Urban Economics, 37(4): 491–496.
- GETIS, A., ALDSTADT, J. (2004): Constructing the spatial weights matrix using a local statistic. Geographical Analysis, 36(2): 90–104.
- GUIMARAES, P., FIGUEIREDO, O., WOODWARD, D. (2011): Accounting for neighboring effects in measures of spatial concentration. Journal of Regional Science, 51(4): 678–693.
- HAMPL, M. [eds.] (1999): Geography of Societal Transformation in the Czech Republic. Prague, Department of Social Geography and Regional Development, Faculty of Science, Charles University in Prague.
- IMRE, A. R., NOVOTNÝ, J., ROCCHINI, D. (2012): The Korcak-exponent: a non-fractal descriptor for landscape patchiness. Ecological Complexity, 12: 70–74.
- KLADIVO, P., PTÁČEK, P., ROUBÍNEK, P., ZIENER, K. (2012): The Czech-Polish and Austrian-Slovenian borderlands – similarities and differences in the development and typology of regions. Moravian Geographical Reports, 20(3): 22–37.
- KLAPKA, P., HALÁS, M., NETRDOVÁ, P., NOSEK, V. (2016): The efficiency of areal units in spatial analysis: Assessing the performance of functional and administrative regions. Moravian Geographical Reports, 24(2): 47–59.
- KORČÁK, J. (1938): Deux types fondamentaux de distribution statistique. Bulletin de l'Institute International de Statistique, 30: 295–299.
- LAFOURCADE, M., MION, G. (2007): Concentration, agglomeration and the size of plants. Regional Science and Urban Economics, 37(1): 46–68.
- LAMBERT, P. J., ARONSON, J. R. (1993): Inequality decomposition analysis and the Gini coefficient revisited. The Economic Journal, 103(420): 1221–1227.
- LITCHFIELD, J. A. (1999): Inequality: Methods and Tools. World’s Bank Web Site on Inequality, Poverty, and Socio-economic Performance. [online]. [cit. 30.05.2013]. Available at: http://siteresources.worldbank.org/INTPGI/Resources/Inequality/litchfie.pdf
- LONGFORD, N. T., PITTAU, M. G., ZELLI, R., MASSARI, R. (2012): Poverty and inequality in European regions. Journal of Applied Statistics, 39(7): 1557–1576.
- MARCON, E., PUECH, F. (2003): Evaluating the geographic concentration of industries using distance-based methods. Journal of Economic Geography 3: 409–428.
- MILLS, J. A., ZANDVAKILI, S. (1997): Statistical inference via bootstrapping for measures of inequality. Journal of Applied Econometrics, 12(2): 133–150.
- MUSSARD, S., SEYTE, F., TERRAZA, M. (2003): Decomposition of Gini and the generalized entropy inequality measures. Economics Bulletin, 4(7): 1–6.
- NETRDOVÁ, P., NOSEK, V. (2009): Approaches to measuring the significance of geographical dimension of societal inequality. Geografie, 114(1): 52–65.
- NOSEK, V., NETRDOVÁ, P. (2010): Regional and spatial concentration of socio-economic phenomena: empirical evidence from the Czech Republic. Ekonomický časopis/Journal of Economics, 58(4): 344–359.
- NOSEK, V., NETRDOVÁ, P. (2014): Measuring Spatial Aspects of Variability. Comparing Spatial Autocorrelation with Regional Decomposition in International Unemployment Research. Historical Social Research, 39(2): 292–314.
- NOVOTNÝ, J., NOSEK, V. (2009): Nomothetic geography revisited: statistical distributions, basic generative mechanisms, and inequality measures. Geografie, 114(4): 282–297.
- NOVOTNÝ, J., NOSEK, V. (2012): Comparison of regional inequality in unemployment among four Central European countries: an inferential approach. Letters in Spatial and Resource Sciences, 5(2): 95–101.
- NOVOTNÝ, J., NOSEK, V., JELÍNEK, K. (2014): EasyStat 1.0. Prague, Faculty of Science, Charles University. [cit. 19.05.2015]. Available at: https://web.natur.cuni.cz/~pepino/EasyStat.zip
- OKAMOTO, M. (2009): Decomposition of gini and multivariate gini indices. The Journal of Economic Inequality, 7(2): 153–177.
- OPENSHAW, S. (1984): Concepts and Techniques in Modern Geography. Volume 37: The Modifiable Areal Unit Problem. Norwich, Geo Books.
- ORD, J. K., GETIS, A. (2012): Local spatial heteroscedasticity (LOSH). The Annals of Regional Science, 48(2): 529–539.
- REY, S. J. (2004): Spatial analysis of regional income inequality. In: Goodchild, M., Janelle, D. [eds.]: Spatially Integrated Social Science: Examples in Best Practice 1 (pp. 280–299). Oxford, Oxford University Press.
- REY, S. J., JANIKAS, M. V. (2005): Regional convergence, inequality, and space. Journal of Economic Geography, 5(2): 155–176.
- REY, S. J., MONTOURI, B. D. (1999): US regional income convergence: a spatial econometric perspective. Regional Studies, 33(2): 143–156.
- REY, S. J., SMITH, R. J. (2013): A spatial decomposition of the Gini coefficient. Letters in Spatial and Resource Sciences, 6(2): 55–70.
- SEN, A. (1972): On economic inequality. Oxford, Claredon Press.
- SHORROCKS, A., WAN, G. (2005): Spatial decomposition of inequality. Journal of Economic Geography, 5(1): 59–81.
- STINE, R. (1989): An introduction to bootstrap methods: examples and ideas. Sociological Methods Research, 18(2–3): 243–291.
- STAKHOVYCH, S., BIJMOLT, T. H. A. (2009): Specification of spatial models: A simulation study on weights matrices. Papers in Regional Science, 88(2): 389–408.
- SUBRAMANIAN, S. (2004): Indicators of inequality and poverty. Research Paper No. 2004/25, World Institute for Development Economics Research. [online]. [cit. 30.05.2013]. Available at: https://www.wider.unu.edu/sites/default/files/rp2004-025.pdf
- SUN, W., JONES, B. (2013): Using multi-scale spatial and statistical analysis to assess the effects of brownfield redevelopment on surrounding residential property values in Milwaukee County, USA. Moravian Geographical Reports, 21(2): 56–64.
- UNWIN, A., UNWIN, D. (1998): Exploratory spatial data analysis with local statistics. Journal of the Royal Statistical Society: Series D (The Statistician), 47(3): 415–421.
- WONG, D. (2009): The Modifiable Areal Unit Problem (MAUP). In: Fotheringham, A. S., Rogerson, P. A. [eds.]: The SAGE Handbook of Spatial Analysis (pp. 105–125). London, SAGE.