Spatial Autocorrelation Statistics of Areal Prevalence Rates under High Uncertainty in Denominator Data

We propose a new estimator of spatial autocorrelation of areal incidence or prevalence rates in small areas, such as crime and health indicators, for correcting spatially heterogeneous sampling errors in denominator data. The approach is dubbed the heteroscedasticity‐consistent empirical Bayes (HC‐EB) method. As American Community Survey (ACS) data have been released to the public for small census geographies, small‐area estimates now form the demographic landscape of neighborhoods. Meanwhile, there is growing awareness of the diminished statistical validity of global and local Moran’s I when such small‐area estimates are used in denominator data. Using teen birth rates by census tracts in Mecklenburg County, North Carolina, we present comparisons of conventional and new HC‐EB estimates of Global and Local Moran’s I statistics created on ACS data, along with estimates on ground truth values from the 2010 decennial census. Results show that the new adjustment method dramatically enhances the statistical validity of global and local spatial autocorrelation statistics.     

THE INFLUENCE OF ECONOMIC DIVERSITY ON UNEMPLOYMENT AND STABILITY*

ABSTRACT. For many years, regional scientists, economists, and geographers have been unable to clarify the influence of economic diversity on unemployment and instability in regional economies of the United States, the United Kingdom, and Canada. This article presents plausible theory, proper units of analysis, valid measures, and more inclusive models of the diversity-stability relationship. The findings are generalizable because the sample includes most metropolitan areas in the U.S. The empirical analysis estimates the influence of diversity, employment concentrated in unstable industries, population size, growth rate, and control variables on unemployment and employment instability during the 1972–88 period. The results indicate that metropolitan areas which are more diverse experience lower unemployment rates and less instability than areas which are less diverse.     

Statistical Network Analysis for Analyzing Policy Networks

To analyze social network data using standard statistical approaches is to risk incorrect inference. The dependencies among observations implied in a network conceptualization undermine standard assumptions of the usual general linear models. One of the most quickly expanding areas of social and policy network methodology is the development of statistical modeling approaches that can accommodate such dependent data. In this article, we review three network statistical methods commonly used in the current literature: quadratic assignment procedures, exponential random graph models (ERGMs), and stochastic actor‐oriented models. We focus most attention on ERGMs by providing an illustrative example of a model for a strategic information network within a local government. We draw inferences about the structural role played by individuals recognized as key innovators and conclude that such an approach has much to offer in analyzing the policy process.     

MEASURING THE IMPACT OF SEA‐LEVEL RISE ON COASTAL REAL ESTATE: A HEDONIC PROPERTY MODEL APPROACH*

ABSTRACT This study estimates the impact of sea‐level rise on coastal real estate in North Carolina using a unique integration of geospatial and hedonic property data. With rates of sea‐level rise approximately double the global average, North Carolina has one of the most vulnerable coastlines in the United States. A range of modest sea‐level rise scenarios based on the IPCC Fourth Assessment Report projections (2007) are considered for four counties of North Carolina—New Hanover, Dare, Carteret, and Bertie—which represent a cross‐section of the state's coastline in geographical distribution and economic development. High‐resolution topographic LIDAR (light detection and ranging) data are used to provide accurate inundation maps for the properties that will be at risk under six different sea‐level rise scenarios. A simulation approach based on spatial hedonic models is used to provide consistent estimates of the property value losses. Considering just four coastal counties in North Carolina, the value of residential property loss without discounting in 2030 (2080) is estimated to be about $179 ($526) million for the mid‐range sea‐level rise scenarios. Low‐lying and heavily developed areas in the northern coastline are comparatively more vulnerable to the effect of sea‐level rise than the other areas.     

Meteorological Sub‐divisional Scale Rainfall Monitoring Using Kalpana‐1 VHRR Measurements

Geostationary satellites provide measurements over a wider geographical area with high temporal sampling, while microwave measurements are more accurate but sparse. For continuous monitoring of the Indian monsoon, geostationary platform would be ideal. In this study, INSAT (Indian National Satellite) Multi‐spectral Rainfall Algorithm (IMSRA) has been used for the estimation of rainfall from Kalpana‐1 very high resolution radiometer (VHRR) measurements. IMSRA benefits from the relative advantages of infrared and microwave sensors and is operational at the India Meteorological Department (IMD). In this paper, rainfall is estimated over India at meteorological sub‐divisional scale during the south‐west monsoon season of 2009 using Kalpana‐1 satellite measurements. This is the first experimental attempt to generate meteorological sub‐divisional scale rainfall maps using Kalpana‐1 satellite measurements. The rainfall maps for the south‐west monsoon season over the Indian land region are successfully utilised as a space input for the drought monitoring of the year 2009. The results have been compared with the IMD gauge‐based accumulated rainfall maps at monthly and seasonal time scales. The qualitative comparison suggests that rainfall maps generated using the present methodology is in good agreement with the IMD rainfall maps. The quantitative comparison of the sub‐divisional monthly accumulated rainfall shows a correlation of 0.77 and standard error of 71 mm over the non‐orographic regions, whereas a correlation of 0.60 and standard error of 117 mm is observed over the orographic regions. The present study shows that Kalpana‐1 satellite‐based rainfall estimates (IMSRA technique) can act as a complementary tool for the monsoon monitoring over the Indian meteorological sub‐divisions and can be used for various meteorological and hydrological applications.     

SUFFICIENT CONDITIONS FOR NEGATIVE EXPONENTIAL DENSITIES A FURTHER ANALYSIS

ABSTRACT Brueckner correctly pointed out that one of the sufficient conditions for negative exponential densities is a unitary price elasticity of the compensated, not the uncompensated, demand for housing. This note shows that the Brueckner condition implies a zero income elasticity of housing demand when income and price elasticities are constrained to be constants. It also derives the utility function that gives rise to negative exponential densities in this case, given that other standard assumptions are satisfied. In light of empirical evidence, justification for the popular negative exponential functional form seems rather weak.     

Urban and Rural Estimates of Poverty: Recent Advances in Spatial Microsimulation in Australia

This paper reports on the calculation of poverty rates for small areas in Australia using a spatial microsimulation model. The spatial microsimulation methodology used involves reweighting data from confidentialised unit record files (CURFs) from surveys conducted by the Australian Bureau of Statistics (ABS) to small area census data, also from the ABS. The method is described in this paper, and then maps of poverty using poverty rates derived from this small area estimation method are shown for the eastern coast of Australia and its capital cities. Further analysis of poverty rates in capital cities is then conducted. We find that areas of higher poverty risk can be clearly identified within Sydney, Melbourne, Canberra and Brisbane. We also find that areas of high poverty are frequently ‘buffered’ by areas of moderate poverty. This is not always the case since, in some areas, we find a high poverty area neighbouring a low poverty area but, generally, there appears to be a moderate poverty ‘buffer’ in most capital cities.     

Comments on a paper entitled “sudden neutral sodium layers: A strong link to sporadic e layers” by U. Von Zahn and T. L. Hansen

Observations of thin, enhanced, layers within the atmospheric sodium layer have recently been interpreted in the literature as resulting from the liberation of sodium from dust particles by the effect of auroral particle precipitation. In this note we point out that one of the assumptions on which the argument for this mechanism is based is incorrect, and that direct deposition of meteoric material is more likely to be the cause of the observed enhancements.     

Changing mental maps of the Baltic Sea and Mediterranean regions

ABSTRACT

Little empirical research has considered the way in which macro-regions are perceived outside academic and political circles. Such studies alone can determine what regional narratives mean for the wider public, and the extent to which they coincide with region-building images produced by elites. This article examines the mental maps of high school seniors in 10 cities in the Baltic Sea and Mediterranean regions, focusing upon their perception and knowledge of other countries in those areas. Despite efforts at region building since the Cold War, the two regions remain divided on mental maps. Students have little knowledge of countries across the sea from their own, although such knowledge is generally greater among those from coastal (and particularly island) locations. A comparison with maps constructed by Gould in 1966 reveals that the perception of countries within one's own region among Italian and Swedish students has become more negative over the last 50 years.     

Mental maps of global regions: identifying and characterizing “hard” and “soft” regions

ABSTRACT

This article presents the quantitative synthesis of mental maps that identify different types of world regions. It is the result of a large-scale survey conducted in 18 countries, based on a sketch map approach. The number, shape, and extension of these vernacular world regions vary according to countries, cultures, and the personal styles of respondents who drew the maps. However, when we collectively analyze the regions identified by respondents, we observe that the figures of global regions are more or less recurrent. While the most commonly used division of the world is into “continents”, we can identify “hard” and “soft” regions of the world. Whereas a “hard” region, such as Africa, can be recognized relatively unambiguously as a continent, “soft” regions may include numerous regional distinctions such as East Asia, Russia, South East Asia, and the Middle East. Our methodology involves defining a set of characteristics that discriminate between “hard” and “soft” regions (measuring spatial uncertainty and the relative vagueness of limits and fringes), then accounting for the correlation of these areas on the world map.     

Improved world-wide maps of monthly median foF2

New global maps of monthly median values of foF2 have been prepared using over 45,000 station months of foF2 observations, semi-empirical model values of foF2 in the mid-latitude ocean areas and empirical model values for the equatorial and high latitude regions. These observations have been carefully screened and mapped, using the Jones-Galley technique, to produce monthly median maps of foF2 for each hour, each month and for high and low levels of solar activity.     

Assessing the reliability of criteria used to identify mandibles and mandibular teeth in sheep, Ovis, and goats, Capra

Criteria developed to distinguish between the mandibles and mandibular teeth of sheep and goats are evaluated using modern specimens from the collections of the National Museum of Natural History and the Field Museum of Natural History. Certain teeth prove to be quite reliable in this regard (dP3, P3, P4). Other dental elements, however, are not reliable and should not be used in dental based identifications of these closely related species (dP4, M1, and mandibular bones). Overall, the identification of sheep dentition using these criteria is more reliable than it is for goats. However, the generally greater likelihood of incorrect identification of goat teeth and mandibles means that specimens identified as sheep are likely to contain high proportion of misidentified goats. Both the proportion of remains that can only be classified as ‘Ovis-Capra’ and the proportion of incorrectly identified teeth and mandibular bones varies with age, with identifications of younger and older animals less reliable than those of animals in the 1.5–6 year age range. Reliability of identifications increases when more criteria and more elements are used. Identifications based on whole mandibles with complete tooth rows are quite reliable. However, the proportion of specimens likely to be classified as ‘Ovis-Capra’ also increases in whole mandible identifications, especially in goats. Systematic differences in the proportions of indeterminate and incorrect identifications have a significant impact on species-level dentition-based harvest profiles. Recommendations are made for the use of dentition and long bone based harvest profiles in the study of sheep and goat exploitation strategies.     

Spatial variation in cervical cancer screening participation and outcomes among Indigenous and non‐Indigenous Australians in Queensland

Indigenous women continue to experience a disproportionately higher burden of cervical cancer than non‐Indigenous women in Australia. The National Indigenous Cervical Screening Project used probabilistic record linkage to combine population‐based administrative databases and identify Indigenous women on Pap Smear Registers. This study aimed to quantify the spatial variation by local government areas (LGAs) for Indigenous and non‐Indigenous women in Queensland in cervical screening participation rates and related outcomes. Empirical Bayes local geostatistical smoothing was performed to reduce the likelihood of spurious variation between small areas. The cohort included 1,091,260 women (2 per cent Indigenous) aged 20 to 69 with 2,393,708 Pap smears between 2006 and 2011. Indigenous women had smoothed LGA‐specific 5‐year participation rates (interquartile range (IQR) 38.9–53.3 per 100 eligible women) consistently lower than non‐Indigenous women (IQR 80.7–85.3). The non‐overlapping confidence intervals of these rates suggest that the Indigenous differential was significant. Compared with Indigenous women, non‐Indigenous women had consistently lower and more stable prevalence rates of histologically confirmed high grade abnormalities (IQR 8.0–10.1 versus 15.0–21.3 per 1,000 screened women). Although the LGA‐specific rates also suggest that a higher proportion of non‐Indigenous women were followed‐up within two months of an abnormal screening result, the wide confidence intervals for these estimates limit our ability to draw definitive conclusions about spatial patterns for this outcome. These findings highlight the importance of continued monitoring and ongoing efforts to identify drivers of these patterns and develop effective strategies to improve participation and potentially reduce the cervical cancer burden among Indigenous women.     

Critical Issues on Probabilistic Earthquake Loss Assessment

Probabilistic loss modeling can be used to develop risk reduction measures, such as the identification of regions more prone to human and economic losses, or to develop financial mechanisms to transfer the earthquake risk from local governments to the private sector. This study addresses several critical issues in probabilistic loss modeling, and provides recommendations depending on the intended final use of the risk results. Modeling issues related to convergence in probabilistic event-based analysis; consideration of epistemic uncertainties within a logic tree; generation of different types of loss exceedance curves; and derivation of risk maps are thoroughly investigated. The Metropolitan Area of Lisbon is used to explore these issues, and it is demonstrated that different assumptions in the loss modeling process can lead to considerably different risk results. Furthermore, the findings and recommendations of this study are also relevant for institutions that promote the assessment of earthquake hazard and risk, such as the Global Earthquake Model Foundation.     

Analyzing the Relationship Between Smoking and Coronary Heart Disease at the Small Area Level: A Bayesian Approach to Spatial Modeling

We model the relationship between coronary heart disease and smoking prevalence and deprivation at the small area level using the Poisson log-linear model with and without random effects. Extra-Poisson variability (overdispersion) is handled through the addition of spatially structured and unstructured random effects in a Bayesian framework. In addition, four different measures of smoking prevalence are assessed because the smoking data are obtained from a survey that resulted in quite large differences in the size of the sample across the census tracts. Two of the methods use Bayes adjustments of standardized smoking ratios (local and global adjustments), and one uses a nonparametric spatial averaging technique. A preferred model is identified based on the deviance information criterion. Both smoking and deprivation are found to be statistically significant risk factors, but the effect of the smoking variable is reduced once the confounding effects of deprivation are taken into account. Maps of the spatial variability in relative risk, and the importance of the underlying covariates and random effects terms, are produced. We also identify areas with excess relative risk.     

Fitting Constrained Poisson Regression Models to Interurban Migration Flows

This paper demonstrates the effects of fitting singly and doubly constrained spatial interaction models using the Poisson regression approach. A large data set containing migration flows between labor market areas in Great Britain in 1970–71 is used. The results of fitting unconstrained, singly constrained, and doubly constrained models are compared with respect to goodness of fit and the interpretability of parameter estimates. The addition of other explanatory variables to the model is also explored.     

DELINEATING METROPOLITAN AREAS USING LAND PRICES*

ABSTRACT This paper proposes an approach to delineating metropolitan areas that is more general than the standard approaches in three respects: First, it uses the fraction of land prices attributable to economies of urban agglomeration instead of using commuting intensities as an indicator of economic integration between metropolitan centers and their hinterlands. Second, it identifies metropolitan centers endogenously instead of determining them exogenously. And third, it takes metropolitan subcenters explicitly into account. An empirical illustration is used to show that the approach tends to delineate fewer but larger metropolitan areas in densely populated regions, and smaller metropolitan areas in sparsely populated regions.     

From Big Noise to Big Data: Toward the Verification of Large Data sets for Understanding Regional Retail Flows

There has been much excitement among quantitative geographers about newly available data sets, characterized by high volume, velocity, and variety. This phenomenon is often labeled as “Big Data” and has contributed to methodological and empirical advances, particularly in the areas of visualization and analysis of social networks. However, a fourth v—veracity (or lack thereof)—has been conspicuously lacking from the literature. This article sets out to test the potential for verifying large data sets. It does this by cross‐comparing three unrelated estimates of retail flows—human movements from home locations to shopping centers—derived from the following geo‐coded sources: (1) a major mobile telephone service provider; (2) a commercial consumer survey; and (3) geotagged Twitter messages. Three spatial interaction models also provided estimates of flow: constrained and unconstrained versions of the “gravity model” and the recently developed “radiation model.” We found positive relationships between all data‐based and theoretical sources of estimated retail flows. Based on the analysis, the mobile telephone data fitted the modeled flows and consumer survey data closely, while flows obtained directly from the Twitter data diverged from other sources. The research highlights the importance of verification in flow data derived from new sources and demonstrates methods for achieving this.     

Differences in cancer incidence between men and women in the province of Québec, Canada, 1984–1993

This research concerns variation in incidence rates of cancer for males and females aged 35 to 69 in Québec for the period 1984 to 1993. In analysing the data, the Island of Montréal (health region 06) was distinguished from the rest of the province of Québec (excluding Nunavik and the James Bay regions). Relative rate index and the ratio of standardised incidence rates of cancer for males and females showed similar tendencies in all regions studied, with the risk of non–sex‐specific cancer higher in men than in women (excess ranged from 5 or 20 to 240 percent according to the study region). However, this higher risk was not consistent across lifespan and cancer site in the Montréal area. We suggest some general points that could explain the differences in cancer incidence between males and females.     

THE EFFECT OF PROPERTY TAX RATE DIFFERENTIALS ON SINGLE-FAMILY HOUSING STARTS IN WISCONSIN, 1978–1989*

ABSTRACT. A pooled cross-section time-series approach is used to test the hypothesis that differences in property tax rates between and across regions exert an excise-tax impact on housing starts. Synthesizing the research regarding property tax incidence on housing markets and residential location with that of regional housing studies, an empirical model that allows for inter- and intraregional influences on housing starts is developed. Using county data from Wisconsin over a twelve-year span, I find that property tax rate differentials have a negative effect on the construction of single-family houses.