A political economy perspective on persistent inequality, inflation, and redistribution

In this paper we examine the dynamics of the link between inequality and inflation from a political economy perspective. We consider a simple dynamic general equilibrium model in which agents vote over the desired inflation rate in each period, and inequality is persistent. Inflation in our model is a mechanism of redistribution, and we find that the link between inequality and inflation within any period or over time depends on institutional and preference related parameters. Furthermore, we find that differences in the initial distributions of wealth can yield a diverse set of patterns for the evolution of the inflation and inequality link. Relative to existing literature, our model leads to more precise predictions about the inflation-inequality correlation. To that end, results in the extant empirical literature on the inflation and inequality link need to be interpreted with caution.

An examination of the predictors of blood donors' intentions to donate during two phases of an avian influenza outbreak

BACKGROUND: Data from prior health scares suggest that an avian influenza outbreak will impact on people’s intention to donate blood; however research exploring this is scarce. Using an augmented theory of planned behavior (TPB), incorporating threat perceptions alongside the rational decision-making components of the TPB, the current study sought to identify predictors of blood donors’ intentions to donate during two phases of an avian influenza outbreak. STUDY DESIGN AND METHODS: Blood donors (N = 172) completed an on-line survey assessing the standard TPB predictors as well as measures of threat perceptions from the health belief model (HBM; i.e., perceived susceptibility and severity). Path analyses examined the utility of the augmented TPB to predict donors’ intentions to donate during a low- and high-risk phase of an avian influenza outbreak. RESULTS: In both phases, the model provided a good fit to the data explaining 69% (low risk) and 72% (high risk) of the variance in intentions. Attitude, subjective norm, and perceived susceptibility significantly predicted donor intentions in both phases. Within the low-risk phase, gender was an additional significant predictor of intention, while in the high-risk phase, perceived behavioral control was significantly related to intentions. CONCLUSION: An augmented TPB model can be used to predict donors’ intentions to donate blood in a low-risk and a high-risk phase of an outbreak of avian influenza. As such, the results provide important insights into donors’ decision-making that can be used by blood agencies to maintain the blood supply in the context of an avian influenza outbreak.

Effects of wearing a pressure redistribution belt while lying in a hospital bed

Bedsores (ulcers) are caused by multiple factors which include, but are not limited to; pressure, shear force, friction, temperature, age and medication. Specialised support services, such as specialised mattresses, sheepskin coverings etc., are thought to decrease or relieve pressure, resulting in a lowering of pressure ulcer incidence [3]. The primary aim of this study was to compare the upper/central body pressure distribution between normal lying in a hospital bed versus the use of a pressure redistribution belt. The study involved 16 healthy voluntary subjects lying on a hospital bed with and without wearing the belt. Results showed that the use of a pressure redistribution belt results in reduced pressure peaks and prevents the pressure from increasing over time.

Four new avian mitochondrial genomes help get to basic evolutionary questions in the late cretaceous

Good phylogenetic trees are required to test hypotheses about evolutionary processes. We report four new avian mitochondrial genomes, which together with an improved method of phylogenetic analysis for vertebrate mt genomes give results for three questions in avian evolution. The new mt genomes are: magpie goose (Anseranas semipalmata), an owl (morepork, Ninox novaeseelandiae); a basal passerine (rifleman, or New Zealand wren, Acanthisitta chloris); and a parrot (kakapo or owl-parrot, Strigops habroptilus). The magpie goose provides an important new calibration point for avian evolution because the well-studied Presbyornis fossils are on the lineage to ducks and geese, after the separation of the magpie goose. We find, as with other animal mitochondrial genomes, that RY-coding is helpful in adjusting for biases between pyrimidines and between purines. When RY-coding is used at third positions of the codon, the root occurs between paleognath and neognath birds (as expected from morphological and nuclear data). In addition, passerines form a relatively old group in Neoaves, and many modern avian lineages diverged during the Cretaceous. Although many aspects of the avian tree are stable, additional taxon sampling is required.

Costly technology adoption, redistribution and growth

We study a political economy model which aims to understand the diversity in the growth and technology-adoption experiences in different economies. In this model the cost of technology adoption is endogenous and varies across heterogeneous agents. Agents in the model vote on the proportion of revenues allocated towards such expenditures. In the early stages of development, the political-economy outcome of the model ensures that a sub-optimal proportion of government revenue is used to finance adoption-cost reducing expenditures. This sub-optimality is due to the presence of inequality; agents at the lower end of the distribution favor a larger amount of revenue allocated towards redistribution in the form of lump-sum transfers. Eventually all individuals make the switch to the better technology and their incomes converge. The outcomes of the model therefore explain why public choice is more likely to be conservative in nature; it represents the majority choice given conflicting preferences among agents. Consequently, the transition path towards growth and technology adoption varies across countries depending on initial levels of inequality.

Beliefs underlying blood donors’ intentions to donate during two phases of an avian influenza outbreak

Using a Theory of Planned Behavior (TPB) framework the current study explored the beliefs of current blood donors (N=172) about donating during a low and high-risk phase of a potential avian influenza outbreak. While the majority of behavioral, normative, and control beliefs identified in preliminary research differed as a function of donors’ intentions to donate during both phases of an avian influenza outbreak, regression analyses suggested that the targeting of different specific beliefs during each phase of an outbreak would yield most benefit in bolstering donors’ intentions to remain donating. The findings provide insight in how to best motivate donors in different phases of an avian influenza outbreak.

Temperature redistribution modelling during intermittent microwave convective heating

Microwave power is used for heating and drying processes because of its faster and volumetric heating capability. Non-uniform temperature distribution during microwave application is a major drawback of these processes. Intermittent application of microwave potentially reduces the impact of non-uniformity and improves energy efficiency by redistributing the temperature. However, temperature re-distribution during intermittent microwave heating has not been investigated adequately. Consequently, in this study, a coupled electromagnetic with heat and mass transfer model was developed using the finite element method embedded in COMSOL-Multyphysics software. Particularly, the temperature redistribution due to intermittent heating was investigated. A series of experiments were performed to validate the simulation. The test specimen was an apple and the temperature distribution was closely monitored by a TIC (Thermal Imaging Camera). The simulated temperature profile matched closely with thermal images obtained from experiments.

Redistribution and technology adoption under uncertainty : a political economy perspective

We examine the role of politico-economic influences on macroeconomic performance within the framework of an endogenous growth model with costly technology adoption and uncertainty. The model is aimed at understanding the diversity in growth and inequality experiences across countries. Agents adopt either of two risky technologies, one of which is only available through financial intermediaries, who are able to alleviate some of this risk. The entry cost of financial intermediation depends on the proportion of government revenue that is allocated towards cost-reducing financial development expenditure, and agents vote on this proportion. The results show that agents at the top and bottom ends of the distribution prefer alternative means of re-distribution, thereby effectively blocking the allocation of resources towards cost-reducing financial development expenditure. Thus political factors have a role in delaying financial and capital deepening and economic development. Furthermore, the model provides a political-economy perspective on the Kuznets curve; uncertainty interacts with the political economy mechanism to produce transitional inequality patterns that, depending on initial conditions, can unearth the Kuznets-curve experience. Finally, the political outcomes are inefficient relative to policies aimed at maximizing the collective welfare of agents in the economy.

The use of acoustic indices to determine avian species richness in audio-recordings of the environment

Interpreting acoustic recordings of the natural environment is an increasingly important technique for ecologists wishing to monitor terrestrial ecosystems. Technological advances make it possible to accumulate many more recordings than can be listened to or interpreted, thereby necessitating automated assistance to identify elements in the soundscape. In this paper we examine the problem of estimating avian species richness by sampling from very long acoustic recordings. We work with data recorded under natural conditions and with all the attendant problems of undefined and unconstrained acoustic content (such as wind, rain, traffic, etc.) which can mask content of interest (in our case, bird calls). We describe 14 acoustic indices calculated at one minute resolution for the duration of a 24 hour recording. An acoustic index is a statistic that summarizes some aspect of the structure and distribution of acoustic energy and information in a recording. Some of the indices we calculate are standard (e.g. signal-to-noise ratio), some have been reported useful for the detection of bioacoustic activity (e.g. temporal and spectral entropies) and some are directed to avian sources (spectral persistence of whistles). We rank the one minute segments of a 24 hour recording in descending order according to an "acoustic richness" score which is derived from a single index or a weighted combination of two or more. We describe combinations of indices which lead to more efficient estimates of species richness than random sampling from the same recording, where efficiency is defined as total species identified for given listening effort. Using random sampling, we achieve a 53% increase in species recognized over traditional field surveys and an increase of 87% using combinations of indices to direct the sampling. We also demonstrate how combinations of the same indices can be used to detect long duration acoustic events (such as heavy rain and cicada chorus) and to construct long duration (24 h) spectrograms.

Regional avian species declines estimated from volunteer-collected long-term data using List Length Analysis

Long-term systematic population monitoring data sets are rare but are essential in identifying changes in species abundance. In contrast, community groups and natural history organizations have collected many species lists. These represent a large, untapped source of information on changes in abundance but are generally considered of little value. The major problem with using species lists to detect population changes is that the amount of effort used to obtain the list is often uncontrolled and usually unknown. It has been suggested that using the number of species on the list, the "list length," can be a measure of effort. This paper significantly extends the utility of Franklin's approach using Bayesian logistic regression. We demonstrate the value of List Length Analysis to model changes in species prevalence (i.e., the proportion of lists on which the species occurs) using bird lists collected by a local bird club over 40 years around Brisbane, southeast Queensland, Australia. We estimate the magnitude and certainty of change for 269 bird species and calculate the probabilities that there have been declines and increases of given magnitudes. List Length Analysis confirmed suspected species declines and increases. This method is an important complement to systematically designed intensive monitoring schemes and provides a means of utilizing data that may otherwise be deemed useless. The results of List Length Analysis can be used for targeting species of conservation concern for listing purposes or for more intensive monitoring. While Bayesian methods are not essential for List Length Analysis, they can offer more flexibility in interrogating the data and are able to provide a range of parameters that are easy to interpret and can facilitate conservation listing and prioritization. © 2010 by the Ecological Society of America.

Acoustic sensing: Roles and applications in monitoring avian biodiversity

This thesis examined the use of acoustic sensors for monitoring avian biodiversity. Acoustic sensors have the potential to significantly increase the spatial and temporal scale of ecological observations, however acoustic recordings of the environment can be opaque and complex. This thesis developed methods for analysing large volumes of acoustic data to maximise the detection of bird species, and compared the results of acoustic sensor biodiversity surveys with traditional bird survey techniques.

Assistive classification for improving the efficiency of avian species richness surveys

Avian species richness surveys, which measure the total number of unique avian species, can be conducted via remote acoustic sensors. An immense quantity of data can be collected, which, although rich in useful information, places a great workload on the scientists who manually inspect the audio. To deal with this big data problem, we calculated acoustic indices from audio data at a one-minute resolution and used them to classify one-minute recordings into five classes. By filtering out the non-avian minutes, we can reduce the amount of data by about 50% and improve the efficiency of determining avian species richness. The experimental results show that, given 60 one-minute samples, our approach enables to direct ecologists to find about 10% more avian species.