Risk-taking behavior in the presence of nonconvex asset dynamics

The growing literature on poverty traps emphasizes the links between multiple equilibria and risk avoidance. However, multiple equilibria may also foster risk-taking behavior by some poor people. We illustrate this idea with a simple analytical model in which people with different wealth and ability endowments make investment and risky activity choices in the presence of known nonconvex asset dynamics. This model underscores a crucial distinction between familiar static concepts of risk aversion and forward-looking dynamic risk responses to nonconvex asset dynamics. Even when unobservable preferences exhibit decreasing absolute risk aversion, observed behavior may suggest that risk aversion actually increases with wealth near perceived dynamic asset thresholds. Although high ability individuals are not immune from poverty traps, they can leverage their capital endowments more effectively than lower ability types and are therefore less likely to take seemingly excessive risks. In general, linkages between behavioral responses and wealth dynamics often seem to run in both directions. Both theoretical and empirical poverty trap research could benefit from making this two-way linkage more explicit.     

Computation of determinantal subset influence in regression

One of the important goals of regression diagnostics is the detection of cases or groups of cases which have an inordinate impact on the regression results. Such observations are generally described as influential. A number of influence measures have been proposed, each focusing on a different aspect of the regression. For single cases, these measures are relatively simple and inexpensive to calculate. However, the detection of multiple-case or joint influence is more difficult on two counts. First, calculation of influence for a single subset is more involved than for an individual case, and second, the sheer number of subsets of cases makes the computation overwhelming for all but the smallest data sets.Barrett and Gray (1992) described methods for efficiently examining subset influence for those measures that can be expressed as the trace of a product of positive semidefinite (psd) matrices. There are, however, other popular measures that do not take this form, but rather are expressible as the ratio of determinants of psd matrices. This article focuses on reducing the computation for the determinantal ratio measures by making use of upper and lower bounds on the influence to limit the number of subsets for which the actual influence must be explicitly determined.     

The Evolution of Coding in Signaling Games

Signaling games with reinforcement learning have been used to model the evolution of term languages (Lewis 1969, Convention. Cambridge, MA: Harvard University Press; Skyrms 2006, “Signals” Presidential Address. Philosophy of Science Association for PSA). In this article, syntactic games, extensions of David Lewis’s original sender–receiver game, are used to illustrate how a language that exploits available syntactic structure might evolve to code for states of the world. The evolution of a language occurs in the context of available vocabulary and syntax—the role played by each component is compared in the context of simple reinforcement learning.     

Integrating Entropy‐Based Naïve Bayes and GIS for Spatial Evaluation of Flood Hazard

Regional flood risk caused by intensive rainfall under extreme climate conditions has increasingly attracted global attention. Mapping and evaluation of flood hazard are vital parts in flood risk assessment. This study develops an integrated framework for estimating spatial likelihood of flood hazard by coupling weighted naïve Bayes (WNB), geographic information system, and remote sensing. The north part of Fitzroy River Basin in Queensland, Australia, was selected as a case study site. The environmental indices, including extreme rainfall, evapotranspiration, net‐water index, soil water retention, elevation, slope, drainage proximity, and density, were generated from spatial data representing climate, soil, vegetation, hydrology, and topography. These indices were weighted using the statistics‐based entropy method. The weighted indices were input into the WNB‐based model to delineate a regional flood risk map that indicates the likelihood of flood occurrence. The resultant map was validated by the maximum inundation extent extracted from moderate resolution imaging spectroradiometer (MODIS) imagery. The evaluation results, including mapping and evaluation of the distribution of flood hazard, are helpful in guiding flood inundation disaster responses for the region. The novel approach presented consists of weighted grid data, image‐based sampling and validation, cell‐by‐cell probability inferring and spatial mapping. It is superior to an existing spatial naive Bayes (NB) method for regional flood hazard assessment. It can also be extended to other likelihood‐related environmental hazard studies.     

De-individualising autobiography: a reconsideration of the role of autobiographical life writing within disability studies

This article pursues a reconsideration of the role of autobiographical life writing within the context of disability studies. I respond to concerns that this genre tends toward a problematic and politically limiting individualism that undermines the consideration of disability as a social phenomenon, reproduces the depiction of disabled people as isolated outcasts, and replicates the meritocratic myths of personal achievement that dominate contemporary western capitalism. While not rejecting these concerns in their entirety, I attempt to develop a particular set of reading practices that may be productively employed to strategically work against the individualising tendencies of autobiographical life writing. These strategies include a commitment to seeing the realm of the ‘private’ as social, reading auto/biographically, and seeking to deconstruct the narrative myth of the liberal humanist ‘choosing’ subject. In conclusion, I offer a brief discussion of the particular ethical and methodological opportunities created by the greater consideration of these texts within disability studies.     

Voyaging on the seas of spirit: an ongoing journey towards understanding disability and humanity

In an important article in Disability & Society Hughes argued that ontology is becoming a ‘live issue’ in disability studies. Different sources, including non‐western and aboriginal conceptions of disability and cosmology and the literature on philosophy, religion, palliative and healthcare, suggest that we are missing a critical aspect of humanity in our discussions – the spirit. Drawing upon collectively defined or interpreted experiences of disability identified in non‐Western and aboriginal communities we identify gaps in our ontological discussions which result from taken for granted assumptions that there is only individual experience. When we incorporate spirit in our thinking we become open to emerging ways of understanding disability and humanity. Spirit is a critical, although often intangible, aspect of being alive. Drawing on these sources, ontological discussions around disability leads us to explore how experiences of disability teach us about the multiple dimensions of being human.     

THE DYNAMIC EFFECTS OF U.S. FOOD AID

Although food aid may have important medium- to long-term effects, there is a glaring absence of empirical research on food aid dynamics. This paper applies vector autoregression methods to data from 18 countries over the period 1961–95. We find evidence that food aid has a pronounced J-curve effect on recipient country per capita commercial food imports but only negligible negative effects on recipient country per capita food production. The commercial export gains are primarily enjoyed, however, by the donors' competitors, revealing heretofore unrecognized positive pecuniary trade externalities associated with foreign assistance. ( JEL F14, O13, Q17, Q18)     

Assessment of the Regional Economic Impacts of Catastrophic Events: CGE Analysis of Resource Loss and Behavioral Effects of an RDD Attack Scenario

We investigate the regional economic consequences of a hypothetical catastrophic event—attack via radiological dispersal device (RDD)—centered on the downtown Los Angeles area. We distinguish two routes via which such an event might affect regional economic activity: (i) reduction in effective resource supply (the resource loss effect) and (ii) shifts in the perceptions of economic agents (the behavioral effect). The resource loss effect relates to the physical destructiveness of the event, while the behavioral effect relates to changes in fear and risk perception. Both affect the size of the regional economy. RDD detonation causes little capital damage and few casualties, but generates substantial short‐run resource loss via business interruption. Changes in fear and risk perception increase the supply cost of resources to the affected region, while simultaneously reducing demand for goods produced in the region. We use results from a nationwide survey, tailored to our RDD scenario, to inform our model values for behavioral effects. Survey results, supplemented by findings from previous research on stigmatized asset values, suggest that in the region affected by the RDD, households may require higher wages, investors may require higher returns, and customers may require price discounts. We show that because behavioral effects may have lingering long‐term deleterious impacts on both the supply‐cost of resources to a region and willingness to pay for regional output, they can generate changes in regional gross domestic product (GDP) much greater than those generated by resource loss effects. Implications for policies that have the potential to mitigate these effects are discussed.