Spatial Heterogeneity in Spillover Effects of Assisted and Unassisted Rental Housing

Three new contributions are added to the literature on subsidized rental housing impacts on nearby property values: 1) A primary focus on the spatial heterogeneity of these effects which warrants caution regarding citywide results; 2) an analysis by zoning area, and 3) a comparison of impacts with unsubsidized apartments. An adjusted-interrupted time series (difference-in-difference) model is estimated with a comprehensive dataset for Seattle, WA (1987-97). Contrary to NIMBY expectations, the predominant impact is an upgrading effect of lower-value areas. However, spillover effects are very sensitive to how data are pooled across space: The citywide upgrading effects are driven by poorer pockets adjacent to affluent areas with no or small effects in more diverse low- and medium income areas. They only occur in single-family, not multi-family zones. The only negative effects were associated with vouchers in one of the affluent areas. Impacts of unsubsidized rentals are very similar to those of subsidized ones, suggesting an independent effect beyond subsidy status. These findings are explained with Seattle's dispersion and good neighbor policies, with gentrification pressures as a possible alternative explanation. Site visits confirmed the location of subsidized sites in lower-value areas and the higher maintenance quality of subsidized vis-à-vis unsubsidized units.

Synthesis of highly alkylated functionalized cyclopentadienes

Tetra- and pentaalkylated cyclopentadienyl ketones and carboxylic acids are prepared by electrophilic allylation of enolizible 1,3-dicarbonyl compounds and successive acid catalyzed cyclisation

4. Wochenbericht FS Meteor Reise M147

GEOTRACES - Las Palmas, Kanarische Inseln - Belém, Brasilien, 07.05.2018-13.05.201

Does Context Matter for the Relationship between Deprivation and All-Cause Mortality? The West vs. the Rest of Scotland

Background A growing body of research emphasizes the importance of contextual factors on health outcomes. Using postcode data for Scotland (UK), this study tests the hypothesis of spatial heterogeneity in the relationship between area-level deprivation and mortality to determine if contextual differences in the West vs. the rest of Scotland influence this relationship. Research into health inequalities frequently fails to recognise spatial heterogeneity in the deprivation-health relationship, assuming that global relationships apply uniformly across geographical areas. In this study, exploratory spatial data analysis methods are used to assess local patterns in deprivation and mortality. Spatial regression models are then implemented to examine the relationship between deprivation and mortality more formally. Results The initial exploratory spatial data analysis reveals concentrations of high SMR and deprivation values (hotspots) in the West of Scotland and concentrations of low values (coldspots) for both variables in the rest of the country. The main spatial regression result is that deprivation is the only variable that is highly significantly correlated with all-cause mortality in all models. However, in contrast to the expected spatial heterogeneity in the deprivation-mortality relationship, this relation does not vary between regions in any of the models. This result is robust to a number of specifications, including weighing for population size, controlling for spatial autocorrelation and heteroskedasticity, assuming a non-linear relationship between mortality and deprivation, breaking the dependent variable into male and female SMRs, and distinguishing between West, North and Southeast regions. The rejection of the hypothesis of spatial heterogeneity in the relationship between deprivation and mortality complements prior research on the stability of the deprivation-mortality relationship over time. Conclusions The obtained homogeneity in the deprivation-mortality relationship across the regions of Scotland and the absence of a contextualized effect of region highlights the importance of taking a broader strategic policy that can combat the toxic impacts of deprivation on health. Focusing on a few specific places (e.g. 15% of the poorest areas) to concentrate resources might be a good start but the impacts of deprivation on mortality is not restricted to a few places. A comprehensive strategy that can be sustained over time might be needed to interrupt the linkages between poverty and mortality.

Improving the Multi-Dimensional Comparison of Simulation Results: A Spatial Visualization Approach

Results from simulation experiments are important in applied spatial econometrics to, for instance, assess the performance of spatial estimators and tests for finite samples. However, the traditional tabular and graphi- cal formats for displaying simulation results in the literature have several disadvantages. These include loss of results, lack of intuitive synthesis, and difficulty in comparing results across multiple dimensions. We pro- pose to address these challenges through a spatial visualization approach. This approach visualizes model precision and bias as well as the size and power of tests in map format. The advantage of this spatial approach is that these maps can display all results succinctly, enable an intuitive interpretation, and compare results efficiently across multiple dimensions of a simulation experiment. Due to the respective strengths of tables, graphs and maps, we propose this spatial approach as a supplement to traditional tabular and graphical display formats. To allow readers to generate maps such as the ones presented in this article, a package (written in Python) has been made available by the authors as free/libre software. The package includes an example as well as a short tutorial for researchers without programming experience and can be downloaded at: https://github.com/darribas/simVizMap.