Space–Time Patterns of Rank Concordance: Local Indicators of Mobility Association with Application to Spatial Income Inequality Dynamics

Rey, Sergio J.

doi:10.1080/24694452.2016.1151336

Cited by 27 publications

(34 citation statements)

References 36 publications

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“…The idea of a local test for spatial autocorrelation has been extended in multiple directions, such as applications to categorical data (Boots 2003(Boots , 2006, points on networks (Yamada and Thill 2007), the construction of optimal spatial weights (Getis and Aldstadt 2004;Aldstadt and Getis 2006), as well as space-time and income mobility (Rey 2016). Considerable attention has been paid to problems of statistical inference, both exact and asymptotic, as well as more fundamental issues of multiple comparisons and correlated tests.…”

Section: Introductionmentioning

confidence: 99%

A Local Indicator of Multivariate Spatial Association: Extending Geary's c

Anselin

2018

Geographical Analysis

181

112

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This paper extends the application of the Local Geary c statistic to a multivariate context. The statistic is conceptualized as a weighted distance in multivariate attribute space between an observation and its geographical neighbors. Inference is based on a conditional permutation approach. The interpretation of significant univariate Local Geary statistics is clarified and the differences with a multivariate case outlined. An empirical illustration uses Guerry's classic data on moral statistics in 1830s France.

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Section: Introductionmentioning

confidence: 99%

A Local Indicator of Multivariate Spatial Association: Extending Geary's c

Anselin

2018

Geographical Analysis

181

112

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“…When the nearby locations have similar values as the observed location, there is an indication of interaction and a positive spatial autocorrelation exists [35]. When interactions seem to be competitive and nearby locations have largely different values relative to the observed location, then negative spatial autocorrelation exists [36]. Finally, in cases where no association seems to exist between a location and nearby locations, the data exhibit zero spatial autocorrelation.…”

Section: Methodsmentioning

confidence: 92%

“…Local spatial autocorrelation tests are more informative compared to global tests as they can map clusters and analyze spatial patterns. In this respect, they reveal whether autocorrelation or local spatial heterogeneity exists as a result of different processes crossing space and time, which is why they have been used extensively in geographical applications [36,38].…”

Section: Methodsmentioning

confidence: 99%

Further Widening or Bridging the Gap? A Cross-Regional Study of Unemployment across the EU Amid Economic Crisis

Grekousis

2018

Sustainability

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Abstract:The 2008 global economic crisis led to a sharp increase in unemployment with an estimated 210 million people being unemployed worldwide by 2010. This study analyzes the spatio-temporal distribution of unemployment in the European Union (EU) at a cross-regional level between 2008 and 2013 to identify if spatio-temporal patterns of unemployment exist, and if the European regions have suffered similarly during the study period. Various local spatial autocorrelation techniques are applied and results show that unemployment is highly polarized across the EU regions. Portugal, Spain, Italy, and Greece are experiencing high rates of unemployment forming clusters in space and time. By contrast, Germany, Austria, and nearby regions are more resilient to the economic crisis strains thus creating spatial clusters of low rates of unemployment. Spatial autocorrelation increased considerably in 2013 compared to 2008, indicating further polarization of unemployment and a widening gap between the south and the central-north, showcasing that the severe austerity measures imposed in the beginning of the crisis on some countries did not have any positive effect on unemployment mitigation. The paper also discusses interesting cross-regional patterns to assist policymakers and planners to better understand how high rates of unemployment are spreading geographically and thus take preventive measures to alleviate the implications of the phenomenon. The proposed analysis delves deeper into comprehending geographies of change, and related findings can support spatial planning for achieving society's sustainability.

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“…The decomposition in Equation (3) allows to determine to what extent the classic general rank correlation coefficient measure is silent about the correlation patterns between neighboring and non-neighboring regions. This can be inferred based on random spatial permutations of the attributes to develop a distribution for τ W under the null hypothesis of spatial homogeneity (Rey, 2016). The mobility index (M )…”

Section: Distribution Dynamics and Spatial Pattern: A Global Assessmentmentioning

confidence: 99%

Beyond GDP: an analysis of the socio-economic diversity of European regions

2019

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This paper aims to analyze the socioeconomic diversity of European Union (EU-28) regions from a dynamic perspective. For that purpose, we combine a series of exploratory space-time analysis approaches to multiple Factor Analysis (MFA) applied to a large range of indicators collected at the NUTS-2 level for the period 2000-2015 for the EU-28. First, we find that the first factor of MFA, interpreted as economic development (ECO-DEV), is spatially clustered and that a moderate convergence process is at work between European regions from 2000 to 2015.Second, when comparing these results with those obtained for GDP per capita, we show that the convergence pattern detected with GDP per capita is more pronounced: ECO-DEV adjusts slower over time compared to GDP per capita. Third, pictures provided by the remaining interesting factors, capturing educational attainment, population dynamics and employment, are very different.

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Space–Time Patterns of Rank Concordance: Local Indicators of Mobility Association with Application to Spatial Income Inequality Dynamics

Cited by 27 publications

References 36 publications

A Local Indicator of Multivariate Spatial Association: Extending Geary's c

A Local Indicator of Multivariate Spatial Association: Extending Geary's c

Further Widening or Bridging the Gap? A Cross-Regional Study of Unemployment across the EU Amid Economic Crisis

Beyond GDP: an analysis of the socio-economic diversity of European regions

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