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Pavlína Netrdová
Charles University, Faculty of Science, Department of Social Geography and Regional Development, Prague, Czechia

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Journal article
Published: 26 June 2021 in Geografie
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The aim of this paper is to gain insight into the dynamics of spatial differentiation of unemployment on the municipal and microregional levels in Czechia. The spatial patterns of unemployment are quantitatively evaluated; and, based on these results, two microregions are chosen as case studies (Karvinsko and Jablunkovsko). These microregions are spatially close but underwent a totally different evolution in regional unemployment. Factors that affect different dynamics of unemployment are identified based on the analysis of their historical development and interviews with local agents. Thus, potential causes of dissimilar trajectories are revealed. The theoretical framework of the research is based on a combination of evolutionary and institutional approaches in economic geography that emphasize the role of history, continuity, local specifics and informal norms and practices in local and regional development.

ACS Style

Filip Vrbík; Pavlína Netrdová. The development of spatial differentiation of unemployment in Czechia through evolutionary and institutional approaches: the example of the Karvinsko and Jablunkovsko regions. Geografie 2021, 126, 195 -220.

AMA Style

Filip Vrbík, Pavlína Netrdová. The development of spatial differentiation of unemployment in Czechia through evolutionary and institutional approaches: the example of the Karvinsko and Jablunkovsko regions. Geografie. 2021; 126 (2):195-220.

Chicago/Turabian Style

Filip Vrbík; Pavlína Netrdová. 2021. "The development of spatial differentiation of unemployment in Czechia through evolutionary and institutional approaches: the example of the Karvinsko and Jablunkovsko regions." Geografie 126, no. 2: 195-220.

Journal article
Published: 18 June 2020 in ISPRS International Journal of Geo-Information
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This paper focuses on the analysis of unemployment data in Czechia on a very detailed spatial structure and yearly, extended time series (2002–2019). The main goal of the study was to examine the spatial dimension of disparities in regional unemployment and its evolutionary tendencies on a municipal level. To achieve this goal, global and local spatial autocorrelation methods were used. Besides spatial and space-time analyses, special attention was given to spatial weight matrix selection. The spatial weights were created according to real-time accessibilities between the municipalities based on the Czech road network. The results of spatial autocorrelation analyses based on network spatial weights were compared to the traditional distance-based spatial weights. Despite significant methodological differences between applied spatial weights, the resulting spatial pattern of unemployment proved to be very similar. Empirically, relative stability of spatial patterns of unemployment with only slow shift of differentiation from macro- to microlevels could be observed.

ACS Style

Pavlína Netrdová; Vojtěch Nosek. Spatial Dimension of Unemployment: Space-Time Analysis Using Real-Time Accessibility in Czechia. ISPRS International Journal of Geo-Information 2020, 9, 401 .

AMA Style

Pavlína Netrdová, Vojtěch Nosek. Spatial Dimension of Unemployment: Space-Time Analysis Using Real-Time Accessibility in Czechia. ISPRS International Journal of Geo-Information. 2020; 9 (6):401.

Chicago/Turabian Style

Pavlína Netrdová; Vojtěch Nosek. 2020. "Spatial Dimension of Unemployment: Space-Time Analysis Using Real-Time Accessibility in Czechia." ISPRS International Journal of Geo-Information 9, no. 6: 401.

Journal article
Published: 22 February 2020 in ISPRS International Journal of Geo-Information
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When working with regional data from different countries, issues concerning data comparability need to be solved, including regional comparability. Differing regional unit size is a common issue which influences the results of socio-economic analyses. In this paper, we introduce a strategy to deal with the regional incomparability of administrative data in international research. We propose a methodological approach based on the areal interpolation method, which facilitates the usage of advanced spatial analyses. To illustrate, we analyze spatial patterns of unemployment in seven Central European countries. We use a very detailed spatial (municipal) level to reveal local tendencies. To have comparable units across the whole region, we apply the areal interpolation method, a process of projecting data from source administrative units to the target structure of a grid. After choosing the most suitable grid structure and projecting the data onto the grid, we perform a hot spot analysis to show the benefits of the grid structure for socio-economic analyses. The proposed approach has great potential in international research for its methodological correctness and the ability to interpret results.

ACS Style

Pavlína Netrdová; Vojtěch Nosek; Pavol Hurbánek. Using Areal Interpolation to Deal with Differing Regional Structures in International Research. ISPRS International Journal of Geo-Information 2020, 9, 126 .

AMA Style

Pavlína Netrdová, Vojtěch Nosek, Pavol Hurbánek. Using Areal Interpolation to Deal with Differing Regional Structures in International Research. ISPRS International Journal of Geo-Information. 2020; 9 (2):126.

Chicago/Turabian Style

Pavlína Netrdová; Vojtěch Nosek; Pavol Hurbánek. 2020. "Using Areal Interpolation to Deal with Differing Regional Structures in International Research." ISPRS International Journal of Geo-Information 9, no. 2: 126.

Social science
Published: 02 January 2019 in Journal of Maps
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This study presents an analysis and visualisation of the evolutionary dynamics of unemployment at the municipal level in Czechia during the global economic crisis. The analysis is based on a monthly time series of unemployment data at a detailed territorial level. Namely, there are 6,258 municipalities in Czechia, which makes it particularly suitable for a detailed investigation of the unfolding and evolution of the recent crisis. Our focus is on analysing and mapping the spatiotemporal patterns of unemployment using variability and autocorrelation measures. Given the detailed territorial level of our analysis, large-scale maps will be presented to assist with interpretation and analytical conclusions. The Main Map (1:600 000) shows the categories of municipalities according to the rate of unemployment and its evolutionary dynamics. Three additional maps (1:1 400 000) visualise the results of spatiotemporal analyses.

ACS Style

Pavlína Netrdová; Jiří Blažek. Soaring unemployment in Czechia during the global economic crisis. Journal of Maps 2019, 15, 69 -76.

AMA Style

Pavlína Netrdová, Jiří Blažek. Soaring unemployment in Czechia during the global economic crisis. Journal of Maps. 2019; 15 (1):69-76.

Chicago/Turabian Style

Pavlína Netrdová; Jiří Blažek. 2019. "Soaring unemployment in Czechia during the global economic crisis." Journal of Maps 15, no. 1: 69-76.

Journal article
Published: 01 January 2018 in Geografie
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The paper is focused on the geographical differentiation of the population in Czechia between the years 1980 and 2011. Data from population censuses were adjusted in all years to the municipal structure in 2011, so an analysis of evolution on a municipal level could be undertaken. Besides analyzing geographical differentiation of the population for different types of phenomena (demographic, social, and economic) and its evolution, we study underlying processes (such as concentration/deconcentration, convergence/divergence) and conditional factors and mechanisms. When studying geographical differentiation, we distinguish between simple regional differentiation measured by standard statistical measures, relative regional differentiation measured by Theil index decomposition, and spatial differentiation quantified by Moran’s I. The empirical results show that the geographical differentiation of the population in the transformation period and beyond has been steadily decreasing in a majority of studied variables. Variables with increasing geographical differentiation of the population are always connected with specific conditional factors and mechanisms. Moreover, the geographical differentiation of the population has shixed to lower geographical levels.

ACS Style

Pavlína Netrdová; Vojtěch Nosek. Development regularities and specific features of geographic differentiation of population and its structure on the level of Czechia’s municipalities in transformation period. Geografie 2018, 123, 225 -251.

AMA Style

Pavlína Netrdová, Vojtěch Nosek. Development regularities and specific features of geographic differentiation of population and its structure on the level of Czechia’s municipalities in transformation period. Geografie. 2018; 123 (2):225-251.

Chicago/Turabian Style

Pavlína Netrdová; Vojtěch Nosek. 2018. "Development regularities and specific features of geographic differentiation of population and its structure on the level of Czechia’s municipalities in transformation period." Geografie 123, no. 2: 225-251.

Journal article
Published: 01 June 2017 in Moravian Geographical Reports
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The variability and geographical patterns of population characteristics are key topics in Human Geography. There are many approaches to exploring and quantitatively measuring this issue. Besides standard aspatial statistical methods, there is no universal framework for incorporating regional and spatial aspects into the analysis of areal data. This is mainly because complications, such as the Modifiable Areal Unit Problem or the checkerboard problem, hinder analysis. In this paper, we use two approaches which uniquely combine regional and spatial perspectives of the analysis of variability. This combination brings new insights into the exploration of the variability and geographical patterns of population characteristics. The relationship between regional and spatial approaches is studied with models in a regular grid, using variability decomposition (Theil index) as an example of the regional approach, and spatial autocorrelation (Moran’s I) as an example of the spatial approach. When applied to empirical data based on the Czech censuses between 1980 and 2011, the combination of these two approaches enables us to categorise the studied phenomena according to the regional and spatial nature of their variability. This is a useful advance, especially for assessing evolution over time or comparisons between different phenomena.

ACS Style

Pavlína Netrdová; Vojtěch Nosek. Exploring the variability and geographical patterns of population characteristics: Regional and spatial perspectives. Moravian Geographical Reports 2017, 25, 85 -94.

AMA Style

Pavlína Netrdová, Vojtěch Nosek. Exploring the variability and geographical patterns of population characteristics: Regional and spatial perspectives. Moravian Geographical Reports. 2017; 25 (2):85-94.

Chicago/Turabian Style

Pavlína Netrdová; Vojtěch Nosek. 2017. "Exploring the variability and geographical patterns of population characteristics: Regional and spatial perspectives." Moravian Geographical Reports 25, no. 2: 85-94.

Original paper
Published: 12 October 2016 in Letters in Spatial and Resource Sciences
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In recent decades, improved methodological apparatuses and increased data availability have enhanced data analyses in social sciences. Moreover, complex analyses using sophisticated methods take just a matter of seconds nowadays thanks to highly powerful software. However, such methods are often poorly understood from a methodological point of view despite the fact that knowledge of their specific properties is crucial to accurately interpreting the results. In this paper we study methods of spatial aspects of variability and examine a specific property of such methods to demonstrate how it can affect the final interpretation. By modelling data in a regular 100 by 100 grid as well as empirical examples from Czechia based on data from the 2011 Czech census, this paper presents possible interpretation-biases and recommendations for how to avoid them. We use the example of spatial autocorrelation (measured by Moran’s I) and variability decomposition (measured by the Theil index); two basic methods which enable us to measure variability in regions and in space.

ACS Style

Vojtěch Nosek; Pavlína Netrdová. What values of Moran’s I and Theil index decomposition really mean under different conditions: on the issue of interpretation. Letters in Spatial and Resource Sciences 2016, 10, 149 -159.

AMA Style

Vojtěch Nosek, Pavlína Netrdová. What values of Moran’s I and Theil index decomposition really mean under different conditions: on the issue of interpretation. Letters in Spatial and Resource Sciences. 2016; 10 (2):149-159.

Chicago/Turabian Style

Vojtěch Nosek; Pavlína Netrdová. 2016. "What values of Moran’s I and Theil index decomposition really mean under different conditions: on the issue of interpretation." Letters in Spatial and Resource Sciences 10, no. 2: 149-159.

Journal article
Published: 01 June 2016 in Moravian Geographical Reports
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An attempt to provide a procedure for the assessment of the efficiency of various regional systems for the purposes of spatial analysis is presented in this paper. Functional regions as well as approximated functional regions and the existing administrative regions in the Czech Republic are evaluated, as examples of regional systems to be compared and assessed. Functional regions and approximated functional regions are defined according to the adjusted third variant of the CURDS regionalisation algorithm, using the latest knowledge on the operation of the constraint function. The comparisons of individual regional systems are based on LISA maps and particularly on the assessment of regional variability, including the measures of internal homogeneity and external variability in the regional systems.

ACS Style

Pavel Klapka; Marián Halás; Pavlína Netrdová; Vojtěch Nosek. The efficiency of areal units in spatial analysis: Assessing the performance of functional and administrative regions. Moravian Geographical Reports 2016, 24, 47 -59.

AMA Style

Pavel Klapka, Marián Halás, Pavlína Netrdová, Vojtěch Nosek. The efficiency of areal units in spatial analysis: Assessing the performance of functional and administrative regions. Moravian Geographical Reports. 2016; 24 (2):47-59.

Chicago/Turabian Style

Pavel Klapka; Marián Halás; Pavlína Netrdová; Vojtěch Nosek. 2016. "The efficiency of areal units in spatial analysis: Assessing the performance of functional and administrative regions." Moravian Geographical Reports 24, no. 2: 47-59.

Social science
Published: 15 July 2015 in Journal of Maps
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In this paper, we focus on mapping and analysing the spatial patterns of unemployment in four Central European countries – Austria, Czechia, Germany, and Poland, on municipal level in 2010. Specifically, based on the geo-social differentiation patterns, we are searching for secondary axes stretching from the Blue Banana (the major European economic development axis running from London to Milan) towards Eastern Europe. Unemployment is supposed to approximate economic development, thanks to its close relation to GDP and other economic indicators. To study spatial patterns and development axes on a micro scale, we use the concept of spatial autocorrelation, specifically Moran's I and LISA analysis. While we analyse more than 44,000 units, the resulting maps are very detailed and difficult to interpret on small scales. In this paper, we take advantage of the opportunity to present large-scale maps (1:2,500,000 and 1:6,000,000), which are also more suitable for the analytical conclusions that follow.

ACS Style

Pavlína Netrdová; Vojtěch Nosek. Spatial patterns of unemployment in Central Europe: emerging development axes beyond the Blue Banana. Journal of Maps 2015, 12, 701 -706.

AMA Style

Pavlína Netrdová, Vojtěch Nosek. Spatial patterns of unemployment in Central Europe: emerging development axes beyond the Blue Banana. Journal of Maps. 2015; 12 (4):701-706.

Chicago/Turabian Style

Pavlína Netrdová; Vojtěch Nosek. 2015. "Spatial patterns of unemployment in Central Europe: emerging development axes beyond the Blue Banana." Journal of Maps 12, no. 4: 701-706.

Journal article
Published: 17 January 2012 in European Urban and Regional Studies
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The article analyses changes in the regional variability of unemployment rates resulting from the global crisis, at the NUTS 3 and LAU 1 levels in the new member states of the European Union in Central and Eastern Europe. Although the coefficient of variation, the Gini coefficient and the Theil index each show a clear tendency towards convergence, in all of the states and at both of the scale levels observed, the range of variation has increased throughout the region, with the exception of the LAU 1 level in Hungary. The analysis therefore shows the ambiguous nature of the relationship between an economic crisis and the intensity of micro-regional differences or, rather, their dependence, owing to the nature and severity of the crisis as well as the statistical measures of variability. We found a number of mutual and contradictory tendencies concerning regional development during the global economic crisis in the observed countries. Based upon these findings, several groups of countries with similar changes in their regional pattern during the crisis have been identified.

ACS Style

Jiří Blažek; Pavlína Netrdová. Regional unemployment impacts of the global financial crisis in the new member states of the EU in Central and Eastern Europe. European Urban and Regional Studies 2012, 19, 42 -61.

AMA Style

Jiří Blažek, Pavlína Netrdová. Regional unemployment impacts of the global financial crisis in the new member states of the EU in Central and Eastern Europe. European Urban and Regional Studies. 2012; 19 (1):42-61.

Chicago/Turabian Style

Jiří Blažek; Pavlína Netrdová. 2012. "Regional unemployment impacts of the global financial crisis in the new member states of the EU in Central and Eastern Europe." European Urban and Regional Studies 19, no. 1: 42-61.

Journal article
Published: 01 January 2012 in Geografie
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The aim of this article is to contribute to the existing body of literature on regional development in two main spheres. First, due to limited availability of data, most of the existing studies dealt with regional development trends only upon regional level. However, regions can hide important intraregional differences. Therefore, the first aim of this study was to analyze the development trends of spatial pattern on local level. Secondly, the authors argue that analyses of development trends on local and regional level should not rely exclusively on various measures of variability, but these measures should be accompanied by an application of measures of spatial autocorrelation, which are able to capture the character of spatial pattern and its changes. Combination of these two types of statistics allows a more comprehensive analysis of development trends, especially at the local level. The results show that despite unclear trends of variability on local level, the spatial pattern has become much more fragmented, during the investigated 10 years period.

ACS Style

Jiří Blažek; Pavlína Netrdová. Contemporary tendencies of the development of spatial pattern on the local level in Czechia: towards higher fragmentation of the spatial pattern? Geografie 2012, 117, 266 -288.

AMA Style

Jiří Blažek, Pavlína Netrdová. Contemporary tendencies of the development of spatial pattern on the local level in Czechia: towards higher fragmentation of the spatial pattern? Geografie. 2012; 117 (3):266-288.

Chicago/Turabian Style

Jiří Blažek; Pavlína Netrdová. 2012. "Contemporary tendencies of the development of spatial pattern on the local level in Czechia: towards higher fragmentation of the spatial pattern?" Geografie 117, no. 3: 266-288.

Journal article
Published: 01 August 2011 in Czech Sociological Review
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The contemporary socio-spatial differentiation of the Czech Republic is the focus of this article. The main aim is (1) to identify spatial clusters of municipalities formed by similar structural and developmental socioeconomic characteristics,... The contemporary socio-spatial differentiation of the Czech Republic is the focus of this article. The main aim is (1) to identify spatial clusters of municipalities formed by similar structural and developmental socioeconomic characteristics,...

ACS Style

Jakub Novák; Pavlína Netrdová. Spatial Patterns of Socioeconomic Differentiation in the Czech Republic at the Level of Municipalities. Czech Sociological Review 2011, 47, 717 -744.

AMA Style

Jakub Novák, Pavlína Netrdová. Spatial Patterns of Socioeconomic Differentiation in the Czech Republic at the Level of Municipalities. Czech Sociological Review. 2011; 47 (4):717-744.

Chicago/Turabian Style

Jakub Novák; Pavlína Netrdová. 2011. "Spatial Patterns of Socioeconomic Differentiation in the Czech Republic at the Level of Municipalities." Czech Sociological Review 47, no. 4: 717-744.

Journal article
Published: 01 January 2009 in Geografie
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The article focuses on geographical dimension of societal inequalities, especially on approaches to its analysing. Two distinct methods of analysing the relative geographical inequality are utilized: Theil index decomposition and spatial autocorrelation measured by Moran’s I coefficient. Both employed methods should bring, in theory, very similar information. This fact is explored empirically by comparing both methods and by their application on detailed economic, social and demographic data on municipalities in Czechia. Conclusions, predominantly of epistemological nature, are intended to assess advantages and limitations of individual methods and their possible application in practice.

ACS Style

Pavlína Netrdová; Vojtěch Nosek. Approaches to measuring the relevance of geographical dimension of societa inequalities. Geografie 2009, 114, 52 -65.

AMA Style

Pavlína Netrdová, Vojtěch Nosek. Approaches to measuring the relevance of geographical dimension of societa inequalities. Geografie. 2009; 114 (1):52-65.

Chicago/Turabian Style

Pavlína Netrdová; Vojtěch Nosek. 2009. "Approaches to measuring the relevance of geographical dimension of societa inequalities." Geografie 114, no. 1: 52-65.

Journal article
Published: 01 January 2009 in Geografie
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This article aims to contribute to existing analyses of regional development in the post-socialist countries of Central and Eastern Europe (CEE) by conducting a detailed regional analysis at the municipal (LAU II) level in Czechia. The focus on such a detailed regional level allows for the testing of several hypotheses, for which traditional regional analyses based on NUTS II – NUTS III data were insufficient. First, we investigate whether development axes, as used in planning documents, manifest themselves at a higher level of socioeconomic development. Second, we expect the formation of clusters, exhibiting a higher level of socioeconomic development, around strong growth centres, such as the city of Mladá Boleslav. Third, we explore whether increasing differentiation has shifted from the regional level to the microregional/local level during the past 15 years of the post-socialist transformation. To address these hypotheses, we analyze a set of socioeconomic variables with the help of the spatial autocorrelation method, which allows us to generalize the inevitably, highly fragmented patterns found at the local level.

ACS Style

Jiří Blažek; Pavlína Netrdová. Can development axes be identified by socio-economic variables? The case of Czechia. Geografie 2009, 114, 245 -262.

AMA Style

Jiří Blažek, Pavlína Netrdová. Can development axes be identified by socio-economic variables? The case of Czechia. Geografie. 2009; 114 (4):245-262.

Chicago/Turabian Style

Jiří Blažek; Pavlína Netrdová. 2009. "Can development axes be identified by socio-economic variables? The case of Czechia." Geografie 114, no. 4: 245-262.

Zeitschriftenaufsatzjournal article
Published: 01 September 2021 in Historical Social Research
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This paper focuses on spatial aspects of variability and specifically on the relationship between regional decomposition and spatial autocorrelation. These characteristics are often supposed to be interconnected, but the subject has not yet been studied in sufficient detail and spatial methods are often neglected in regional analysis. We start with a brief discussion of a methodology suitable for identifying and quantifying spatial aspects of variability. The key part of the paper focuses on methodological reflections on measuring spatial aspects of variability and the advantages and disadvantages of our chosen methods. We use the Theil index, which is decomposable without residuum, to assess the relative importance of the regional organization of our studied phenomena. To measure spatial autocorrelation, which enables us to quantify the level of spatial concentration of the studied phenomena and reveal spatial clustering, we use Moran’s I (global scale) and LISA (local scale). We explain in depth the properties of these methods, advantages/disadvantages, behaviour in different situations and the potential for them to be combined and used jointly. These methodological findings help to better understand and interpret the results of the subsequent empirical research. We apply the methods in international unemployment research with highly detailed data from Austria, Czechia, Germany, and Poland. Specifically, we are interested in the importance of socio-spatial (regional) organization in relation to unemployment rates, and we present noteworthy results concerning the spatial differentiation of unemployment in the Central European region.

ACS Style

Vojtěch Nosek; Pavlína Netrdová. Measuring Spatial Aspects of Variability. Comparing Spatial Autocorrelation with Regional Decomposition in International Unemployment Research. Historical Social Research 2021, 39, 292-314 .

AMA Style

Vojtěch Nosek, Pavlína Netrdová. Measuring Spatial Aspects of Variability. Comparing Spatial Autocorrelation with Regional Decomposition in International Unemployment Research. Historical Social Research. 2021; 39 (2):292-314.

Chicago/Turabian Style

Vojtěch Nosek; Pavlína Netrdová. 2021. "Measuring Spatial Aspects of Variability. Comparing Spatial Autocorrelation with Regional Decomposition in International Unemployment Research." Historical Social Research 39, no. 2: 292-314.