Disagreement in Australian partners’ reports of financial difficulty

We use unique data in which both partners report about household finances to demonstrate that there is often disagreement about whether the household has experienced financial difficulty in the past year. Four alternative explanations for this disagreement are tested using the data. The results indicate that disagreement may be related to the severity of the underlying material hardship rather than to gender differences or individual (as opposed to household) views of financial difficulty. We find limited evidence that for some couples information asymmetries contribute to explaining disagreement about financial difficulty. This implies that standard surveys which collect information about the household’s financial position from a representative individual may fail to completely characterize the nature of material hardship.      

The impact of wives’ earnings on income inequality: Issues and estimates

We estimate the extent to which rising family income inequality can be explained by changes in the earnings of married women. We develop a decomposition equation that separates single persons from married couples (decomposition by population group) and, for married couples, distinguishes the impact of wives' earnings from other sources of income (decomposition by income source). Despite the rising correlation between husbands' and wives' earnings, changes in wives' earnings do not explain a substantial portion of the increase in family income inequality. Our results contradict those of some previous analyses. The inconsistency of recent estimates can be traced to the use of a variety of conceptually different approaches in the previous literature. We clarify these approaches by explicitly distinguishing the conceptual issues, analyzing the empirical components, and providing comprehensive estimates.     

Village on the Border, anthropology at the crossroads: the significance of a classic British ethnography

Village on the Border was the seminal anthropological study of a mainland British rural community. It was written and published during a period of unsurpassed scholarship and creativity in British social science. To explain the impact it had on social anthropology, British studies and public discourse at the time, I look at the influences on Ronnie Frankenberg and his work of the then state of social anthropology; of the particular academic environment in which he was trained and worked; and of his personal background and political convictions. This analysis shows that although the book clearly bears particular historical and intellectual influences, it was explicitly set within comparative ethnographic frameworks, and in due course greatly influenced work elsewhere. Both methodologically and substantively, it should be seen as a significant contribution to the comparative study of local‐level politics, gender relations and the role of the ‘stranger’, as well as the authentic origin of modern anthropological studies of rural Britain.     

Shape analysis for automated sulcal classification and parcellation of MRI data

We describe geometric invariants that characterize the shape of curves and surfaces in 3D space: curvature, Gauss integrals and moments. We apply these invariants to neuroimaging data to determine if they have application for automatically classifying and parcellating cortical data. The curves of sulci and gyri on the cortical surface can be obtained by reconstructing cortical surface representations of the human brain from magnetic resonance imaging (MRI) data. We reconstructed gray matter surfaces for 15 subjects, traced 10 sulcal curves on each surface and computed geometric invariants for each curve. These geometric features were used classify the curves into sulcal and hemispheric classes. The best classification results were obtained when moment-based features were computed on the sulcal curves in native space. Gauss integral measures showed that they were useful for differentiating the hemispheric location of a single sulcus. These promising results may indicate that moment invariants are useful for characterizing shape on a global scale. Gauss integral invariants are potentially useful measures for characterizing cortical shape on a local, rather than global scale. Gauss integrals have found biological significance in characterizing proteins so it is worthwhile to consider their possible application to neuroscientific data.     

Evacuation from Natural Disasters: A Systematic Review of the Literature

Research on evacuation from natural disasters has been published across the peer‐reviewed literature among several disparate disciplinary outlets and has suggested a wide variety of predictors of evacuation behavior. We conducted a systematic review to summarize and evaluate the current literature on demographic, storm‐related, and psychosocial correlates of natural disaster evacuation behavior. Eighty‐three eligible papers utilizing 83 independent samples were identified. Risk perception was a consistent positive predictor of evacuation, as were several demographic indicators, prior evacuation behavior, and having an evacuation plan. The influence of prior experiences, self‐efficacy, personality, and links between expected and actual behavior were examined less frequently. Prospective, longitudinal designs are relatively uncommon. Although difficult to conduct in postdisaster settings, more prospective, methodologically rigorous studies would bolster inferences. Results synthesize the current body of literature on evacuation behavior and can help inform the design of more effective predisaster evacuation warnings and procedures.     

Determinants of International Migration Flows to and from Industrialized Countries: A Panel Data Approach Beyond Gravity1

We quantified determinants of international migratory inflows to 17 Western countries and outflows from 13 of these countries between 1950 and 2007 in 77,658 observations from multiple sources using panel-data analysis techniques. To construct a quantitative model that could be useful for demographic projection, we analyzed the logarithm of the number of migrants (inflows and outflows separately) as dependent variables in relation to demographic, geographic, and social independent variables. The independent variables most influential on log inflows were demographic [log population of origin and destination and log infant mortality rate (IMR) of origin and destination] and geographic (log distance between capitals and log land area of the destination). Social and historical determinants were less influential. For log outflows from the 13 countries, the most influential independent variables were log population of origin and destination, log IMR of destination, and log distance between capitals. A young age structure in the destination was associated with lower inflows while a young age structure in the origin was associated with higher inflows. Urbanization in destination and origin increased international migration. IMR affected inflows and outflows significantly but oppositely. Being landlocked, having a common border, having the same official language, sharing a minority language, and colonial links also had statistically significant but quantitatively smaller effects on international migration. Comparisons of models with different assumed correlation structures of residuals indicated that independence was the best assumption, supporting the use of ordinary-least-squares estimation techniques to obtain point estimates of coefficients.     

Modeling distances between humans using Taylor’s law and geometric probability

Taylor’s law states that the variance of the distribution of distance between two randomly chosen individuals is a power function of the mean distance. It applies to the distances between two randomly chosen points in various geometric shapes, subject to a few conditions. In Réunion Island and metropolitan France, at some spatial scales, the empirical frequency distributions of inter-individual distances are predicted accurately by the theoretical frequency distributions of inter-point distances in models of geometric probability under a uniform distribution of points. When these models fail to predict the empirical frequency distributions of inter-individual distances, they provide baselines against which to highlight the spatial distribution of population concentrations.