Linking policies for biodiversity conservation with advances in behavioural economics

Global biodiversity loss and its consequences for human welfare and sustainable development have become major concerns. Economists have, therefore, given increasing attention to the policy issues involved in the management of genetic resources. To do so, they often apply empirical methods developed in behavioral and experimental economics to estimate economic values placed on genetic resources. This trend away from almost exclusive dependence on axiomatic methods is welcomed. However, major valuation methods used in behavioral economics raise new scientific challenges. Possibly the most important of these include deficiencies in the knowledge of the public (and researchers) about genetic resources, implications for the formation of values of supplying information to focal individuals, and limits to rationality. These issues are explored for stated-preference techniques of valuation (e.g., contingent valuation) as well as revealed preference techniques, especially the travel cost method. They are illustrated by Australian and Asian examples. Taking into account behavioral and psychological models and empirical evidence, particular attention is given to how elicitation of preferences, and supply of information to individuals, influences their preferences about biodiversity. Policy consequences are outlined.

Estimating Income Inequality in China Using Grouped Data and the Generalized Beta Distribution

There are two main types of data sources of income distributions in China: household survey data and grouped data. Household survey data are typically available for isolated years and individual provinces. In comparison, aggregate or grouped data are typically available more frequently and usually have national coverage. In principle, grouped data allow investigation of the change of inequality over longer, continuous periods of time, and the identification of patterns of inequality across broader regions. Nevertheless, a major limitation of grouped data is that only mean (average) income and income shares of quintile or decile groups of the population are reported. Directly using grouped data reported in this format is equivalent to assuming that all individuals in a quintile or decile group have the same income. This potentially distorts the estimate of inequality within each region. The aim of this paper is to apply an improved econometric method designed to use grouped data to study income inequality in China. A generalized beta distribution is employed to model income inequality in China at various levels and periods of time. The generalized beta distribution is more general and flexible than the lognormal distribution that has been used in past research, and also relaxes the assumption of a uniform distribution of income within quintile and decile groups of populations. The paper studies the nature and extent of inequality in rural and urban China over the period 1978 to 2002. Income inequality in the whole of China is then modeled using a mixture of province-specific distributions. The estimated results are used to study the trends in national inequality, and to discuss the empirical findings in the light of economic reforms, regional policies, and globalization of the Chinese economy.

Domestic violence in the urban fringe

Police call data for domestic violence incidents in the city of Brisbane were used to further explore the locational disadvantage thesis. It was hypothesised that the supposed additional burdens and stresses on disadvantaged families living in the outer suburbs may be reflected in significantly higher rates of reported domestic violence. Using an index of relative socioeconomic disadvantage and employing Analysis of Variance (ANOVA), this research shows that significantly higher rates of reported domestic violence occur in the inner suburbs relative to the middle or outer suburbs of Brisbane. This finding adds further doubt as to the magnitude of locational disadvantage impacts on outer suburban low income family households.

Exploratory spatial data analysis techniques for examining urban crime

Regional planners, policy makers and policing agencies all recognize the importance of better understanding the dynamics of crime. Theoretical and application-oriented approaches which provide insights into why and where crimes take place are much sought after. Geographic information systems and spatial analysis techniques, in particular, are proving to be essential or studying criminal activity. However, the capabilities of these quantitative methods continue to evolve. This paper explores the use of geographic information systems and spatial analysis approaches for examining crime occurrence in Brisbane, Australia. The analysis highlights novel capabilities for the analysis of crime in urban regions.

Urban birth and migrant status as risk factors for psychosis: An Australian case-control study

Background Urban birth and migrant status have been identified as risk factors for psychosis in North American and European studies. The aim of this study was to explore these variables in an Australian case-control study. Method Country of birth of subjects and their parents, and place of birth of Australian-born subjects, were examined in individuals with psychosis drawn from a prevalence study (n = 310) and well controls recruited from the same catchment area (n = 303). Results Migrant status was associated with a significantly decreased odds of having a psychotic disorder. For those born in Australia, neither migrant status of parents nor urban birth was associated with having a psychotic disorder. Conclusions The lack of effect for urban birth and second-generation migrant status may help generate candidate environmental risk factors that operate in Europe but not in Australia.