Concluding Remarks: Developing Spatial Demography

Howell, Frank M.; Porter, Jeremy R.; Matthews, Stephen A.

doi:10.1007/978-3-319-22810-5_18

Cited by 6 publications

(6 citation statements)

References 20 publications

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“…Our approach to studying the recession’s spatially differentiated impact on county labor markets is premised on the ideas that, first, space and place are key arenas in which social inequality emerges, operates, and changes over time; and second, that middle-range spatial scales and subnational inequality are important foci for research (Lobao 2004; Howell, Porter, and Matthews 2016; Tickamyer 2000). Social scientists have found significant between-place differences in many indicators of wellbeing in the U.S., including employment (Smith and Glauber 2013), income (Peters 2013), education (Roscigno, Tomaskovic-Devey, and Crowley 2006), poverty (Cotter, Hermsen, and Vanneman 2007; Curtis, Voss, and Long 2012), program participation (Slack and Myers 2014), health and mortality (Burton et al 2013; Sparks and Sparks 2010), and residential segregation (Downey 2003).…”

Section: Conceptual Frameworkmentioning

confidence: 99%

The Great Recession and America’s geography of unemployment

Thiede

Monnat

2016

DemRes

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BACKGROUNDThe Great Recession of [2007][2008][2009] was the most severe and lengthy economic crisis in the US since the Great Depression of the 1930s. The impacts on the population were multi-dimensional, but operated largely through local labor markets. OBJECTIVETo examine differences in recession-related changes in county unemployment rates and assess how population and place characteristics shaped these patterns. METHODSWe calculate and decompose Theil Indexes to describe recession-related changes in the distribution of unemployment rates between counties and states. We use exploratory spatial statistics to identify geographic clusters of counties that experienced similar changes in unemployment. We use spatial regression to evaluate associations between county-level recession impacts on unemployment and demographic composition, industrial structure, and state context. RESULTSThe recession was associated with increased inequality between county labor markets within states, but declining between-state differences. Counties that experienced disproportionate recession-related increases in unemployment were spatially clustered and characterized by large shares of historically disadvantaged racial and ethnic minority populations, low educational attainment, and heavy reliance on pro-cyclical industries. Associations between these sources of vulnerability were partially explained by unobserved state-level factors. CONCLUSIONSThe local consequences of macroeconomic trends are associated with county population characteristics, and the structural contexts and policy environments in which they are embedded. The recession placed upward pressure on within-state disparities in local labor market conditions. CONTRIBUTIONTo present new estimates of the recession's impact on local labor markets, quantify how heterogeneous impacts affected the distribution of unemployment prevalence, and identify county characteristics associated with disproportionately large recession-related increases in unemployment.

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Section: Conceptual Frameworkmentioning

confidence: 99%

The Great Recession and America’s geography of unemployment

Thiede

Monnat

2016

DemRes

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“…In the analysis and explanation of demographic dynamics, the influence of space and territorial context is both relevant and useful, especially in the study of small administrative territorial units, such as NUTS 3 and LAUs (see Note 1) (e.g., De Castro, 2007; Howell et al, 2016; Thiede & Monnat, 2016; Yu et al, 2020). All demographic phenomena occur in specific spaces and places (Chi & Zhu, 2008) thus space can have a relevant role in influencing the context in which the demographic events take place and the variables closely connected with these events.…”

Section: Methodsmentioning

confidence: 99%

The impact of the L'Aquila earthquake on demographic changes

Miccoli

Reynaud

Ambrosetti

et al. 2023

Population Space and Place

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This paper analyses the consequences on demographic changes observed in the municipalities of Abruzzo region after the earthquake of L'Aquila in 2009. Relying on Italian National Institute of Statistics (Istat) data on the population in the municipalities, we aim to understand how population growth changed after the earthquake, analysing population dynamics both in the municipalities affected by the earthquake and in the other municipalities of the Abruzzo region. We apply a spatial regression model to understand the associations between population growth, the earthquake, and some demographic and economic variables, taking into account the spatial autocorrelation. Our findings confirm the importance of space and the close association of the population dynamics after the earthquake with the population age structure, both in the pre‐existing situation and in the subsequent dynamics. Population trends in the Abruzzo region were closely associated with the pre‐existing vulnerabilities. The effect of the earthquake was strong in the crater municipalities in the period immediately after the shock, while it petered out over time. A destructive earthquake implies a tremendous shock, however, in places that are already suffering from demographic, social, and economic fragility, pre‐existing factors can act equally or even more strongly on the population dynamics in the medium term. Hence, in the medium period, the characteristics of the population and socio‐economic context are stronger than in the short one, and also the effect that space and territorial contiguities have on these and other nonobservable variables is stronger than in the short period.

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“…Based on the extensive development regarding segregation measures (see Tivadar, 2019; Wong, 2016; Yao et al, 2019 for a review), this work uses the Mutual Information Index ( M ), a multi-group measure based on the entropy, introduced by Theil, 1972; Theil and Finizza, 1971) and developed by Mora and Ruiz-Castillo (2003, 2009, 2011) and Frankel and Volij (2011). 3 Due to its margin-dependent property in both directions (groups and units), this index is ‘highly decomposable’, which is why some studies have used it in recent years to analyse segregation at the local level and between groups (e.g.…”

Section: Methodsmentioning

confidence: 99%

School and residential segregation in the reproduction of urban segregation: A case study in Buenos Aires

Serrati

2023

Urban Studies

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The link between residential and school segregation is widely recognised as a key to explaining urban inequalities. However, most studies have focused on countries of the Global North. This paper attempts to identify to what extent socio-economic residential segregation explains secondary school segregation in Buenos Aires (Argentina). Based on a linear programming method, the study proposes a hypothetical pupil allocation model that takes into account the capacity of schools and is used as an ideal typus to compare with the real socio-economic school composition. Using a ‘decompose method’ of segregation differences to analyse the differences in segregation indices and a local segregation analysis, this paper finds that in a residential context with low segregation but high social inequalities, school segregation is a social mechanism that allows maintaining spaces of differentiation and distancing between groups. In discussion with the idea of a ‘vicious circle of segregation’, this article argues for the potential of a multi-domain approach to segregation, to understand how different domains work in articulated and complex ways to reinforce urban segregation.

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Concluding Remarks: Developing Spatial Demography

Cited by 6 publications

References 20 publications

The Great Recession and America’s geography of unemployment

The Great Recession and America’s geography of unemployment

The impact of the L'Aquila earthquake on demographic changes

School and residential segregation in the reproduction of urban segregation: A case study in Buenos Aires

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