140 resultados para Urban economics.


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This paper presents evidence from two survey's to help explain the poor ratings consistently given to the teaching of economics at Australian universities. The evidence suggests that the Poor ratings of economics teaching can be attributed to two related factors: inappropriate pedagogical practices and lack of rewards for allocating additional time to teaching. The survey data oil pedagogy, in economics consist of 205 responses from graduates from two Queensland universities. The time elapsed since graduation ranges from 1 to 10 years. The survey data on academics' time allocation consist of 290 responses from academic economists across a wide range of Australian universities.

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Despite growing attention to crop and property damage caused by the Asian elephant, uncertainty exists about the magnitude of this problem. This article explores the nature and, Magnitude of this problem in Sri Lanka. An economic analysis of individual farmers'. decisions to control elephants is provided. Government policies to assist farmers in coping with the elephant pest problem are assessed. Appropriate compensation schemes for farmers are seen as potentially more effective for conserving elephants in Sri Lanka than legal prohibitions on the killing of elephants. The issues raised here have wider relevance than merely to Sri Lanka or Asian elephants.

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The majority of the world's population now resides in urban environments and information on the internal composition and dynamics of these environments is essential to enable preservation of certain standards of living. Remotely sensed data, especially the global coverage of moderate spatial resolution satellites such as Landsat, Indian Resource Satellite and Systeme Pour I'Observation de la Terre (SPOT), offer a highly useful data source for mapping the composition of these cities and examining their changes over time. The utility and range of applications for remotely sensed data in urban environments could be improved with a more appropriate conceptual model relating urban environments to the sampling resolutions of imaging sensors and processing routines. Hence, the aim of this work was to take the Vegetation-Impervious surface-Soil (VIS) model of urban composition and match it with the most appropriate image processing methodology to deliver information on VIS composition for urban environments. Several approaches were evaluated for mapping the urban composition of Brisbane city (south-cast Queensland, Australia) using Landsat 5 Thematic Mapper data and 1:5000 aerial photographs. The methods evaluated were: image classification; interpretation of aerial photographs; and constrained linear mixture analysis. Over 900 reference sample points on four transects were extracted from the aerial photographs and used as a basis to check output of the classification and mixture analysis. Distinctive zonations of VIS related to urban composition were found in the per-pixel classification and aggregated air-photo interpretation; however, significant spectral confusion also resulted between classes. In contrast, the VIS fraction images produced from the mixture analysis enabled distinctive densities of commercial, industrial and residential zones within the city to be clearly defined, based on their relative amount of vegetation cover. The soil fraction image served as an index for areas being (re)developed. The logical match of a low (L)-resolution, spectral mixture analysis approach with the moderate spatial resolution image data, ensured the processing model matched the spectrally heterogeneous nature of the urban environments at the scale of Landsat Thematic Mapper data.

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This paper analyzes a dual economy consisting of urban market areas and less developed rural areas with or without local markets. Urban areas have better opportunities for earnings and education than rural areas. Rural families choose whether to move to urban areas at costs that differ from location to location. As per capita output grows relative to the moving cost, urbanization proceeds, leading to lower fertility, more investments in human and physical capital per child relative to output per worker, and faster economic growth. These impacts are stronger if rural areas have no access to markets.