1000 resultados para Dwellings - Prices - Australia


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The main objective of this study is to test the value relevance of financial and non-financial information in high-tech industries in Australia. Ninety-one companies were selected from the sectors of Pharmaceuticals, Biotechnology and Life Sciences; Technology, Hardware and Equipment; and Telecommunication Services of ASX for the analysis. Both financial and non-financial sections of annual reports were scrutinized in order to obtain data for the analysis. The unaudited sections of annual reports were particularly analysed using NVivo to obtain the word-count of intangible assets. Ohlson’s (1995) Equity Valuation Model (modified for the intangible assets disclosures) was explicitly applied to examine the value relevance of financial and non-financial information. The overall results provide evidence that book value is the most significant factor and earnings are the least significant factor in deciding share prices in high-tech industries in Australia. This finding supports the previous studies that showed value relevance declined in earnings but increased in book value. This research proved that voluntary disclosures of intangible assets are value relevant, providing support for the previous US and Australian studies and the conclusion that investors probably increasingly rely upon alternative information sources.

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Purpose: Studies into ripple effects have previously focused on the interconnections between house price movements across cities over space and time. These interconnections were widely investigated in previous research using vector autoregression models. However, the effects generated from spatial information could not be captured by conventional vector autoregression models. This research aimed to incorporate spatial lags into a vector autoregression model to illustrate spatial-temporal interconnections between house price movements across the Australian capital cities. Design/methodology/approach: Geographic and demographic correlations were captured by assessing geographic distances and demographic structures between each pair of cities, respectively. Development scales of the housing market were also used to adjust spatial weights. Impulse response functions based on the estimated SpVAR model were further carried out to illustrate the ripple effects. Findings: The results confirmed spatial correlations exist in housing price dynamics in the Australian capital cities. The spatial correlations are dependent more on the geographic rather than the demographic information. Originality/value: This research investigated the spatial heterogeneity and autocorrelations of regional house prices within the context of demographic and geographic information. A spatial vector autoregression model was developed based on the demographic and geographic distance. The temporal and spatial effects on house prices in Australian capital cities were then depicted.

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Long-run equilibrium of house prices has been investigated by researchers in multiple countries. The identification of this equilibrium not only provides references against contemporary house price levels, but also contributes to creation of stable-development policies and healthy investment strategies. However, there is little research investigating the factors that drive house prices away from the long-run equilibrium.
Based on a framework of the conventional stationarity test process, this research develops a panel regression model and a spatial regression model to investigate the roles of spatial heterogeneity and correlations on house prices preceding the long-run equilibrium, respectively. Housing data generated from the capital cities in Australia are used to illustrate the models. Spatial effects can have a strong influence in the long-run performance of house prices, while the short-run performance of house prices is not influenced by the spatial effects.

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Imprint varies.

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A dividend imputation tax system provides shareholders with a credit (for corporate tax paid) that can be used to offset personal tax on dividend income. This paper shows how to infer the value of imputation tax credits from the prices of derivative securities that are unique to Australian retail markets. We also test whether a tax law amendment that was designed to prevent the trading of imputation credits affected their economic value. Before the amendment, tax credits were worth up to 50% of face value in large, high-yielding companies, but Subsequently it is difficult to detect any value at all. (C) 2003 Elsevier B.V. All rights reserved.

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In 2014, the Australian Government implemented the Emissions Reduction Fund to offer incentives for businesses to reduce greenhouse gas (GHG) emissions by following approved methods. Beef cattle businesses in northern Australia can participate by applying the 'reducing GHG emissions by feeding nitrates to beef cattle' methodology and the 'beef cattle herd management' methods. The nitrate (NO3) method requires that each baseline area must demonstrate a history of urea use. Projects earn Australian carbon credit units (ACCU) for reducing enteric methane emissions by substituting NO3 for urea at the same amount of fed nitrogen. NO3 must be fed in the form of a lick block because most operations do not have labour or equipment to manage daily supplementation. NO3 concentrations, after a 2-week adaptation period, must not exceed 50 g NO3/adult animal equivalent per day or 7 g NO3/kg dry matter intake per day to reduce the risk of NO3 toxicity. There is also a 'beef cattle herd management' method, approved in 2015, that covers activities that improve the herd emission intensity (emissions per unit of product sold) through change in the diet or management. The present study was conducted to compare the required ACCU or supplement prices for a 2% return on capital when feeding a low or high supplement concentration to breeding stock of either (1) urea, (2) three different forms of NO3 or (3) cottonseed meal (CSM), at N concentrations equivalent to 25 or 50 g urea/animal equivalent, to fasten steer entry to a feedlot (backgrounding), in a typical breeder herd on the coastal speargrass land types in central Queensland. Monte Carlo simulations were run using the software @risk, with probability functions used for (1) urea, NO3 and CSM prices, (2) GHG mitigation, (3) livestock prices and (4) carbon price. Increasing the weight of steers at a set turnoff month by feeding CSM was found to be the most cost-effective option, with or without including the offset income. The required ACCU prices for a 2% return on capital were an order of magnitude higher than were indicative carbon prices in 2015 for the three forms of NO3. The likely costs of participating in ERF projects would reduce the return on capital for all mitigation options. © CSIRO 2016.

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In order to explore the long-run equilibrium in the house prices of different cities, studies on house price convergence have been conducted by a number of researchers. However, the majority of previous studies have neglected the effects of spatial heterogeneity and autocorrelation on house prices. This research improves on the investigation of house price convergence by developing a spatio-temporal autoregressive model based on a framework of panel regression methods. Both spatial heterogeneity and autocorrelation of house prices in different cities are taken into account. Geographical distance and the scale of development of the urban housing market are used to construct temporal varying spatial measurements. The spatio-temporal model is then applied to investigate the long-run equilibrium in the house prices of Australian capital cities. The results confirm that house prices in Sydney approach a steady state in the long run, whereas house prices in Brisbane, Canberra, Melbourne and Perth are able to do with lower confidence. However, little evidence supports the existence of long-run equilibrium in the house prices of Adelaide, Darwin and Hobart.

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OBJECTIVE: To determine the average price difference between foods and beverages in remote Indigenous community stores and capital city supermarkets and explore differences across products.

METHODS: A cross-sectional survey compared prices derived from point-of-sale data in 20 remote Northern Territory stores with supermarkets in capital cities of the Northern Territory and South Australia for groceries commonly purchased in remote stores. Average price differences for products, supply categories and food groups were examined.

RESULTS: The 443 products examined represented 63% of food and beverage expenditure in remote stores. Remote products were, on average, 60% and 68% more expensive than advertised prices for Darwin and Adelaide supermarkets, respectively. The average price difference for fresh products was half that of packaged groceries for Darwin supermarkets and more than 50% for food groups that contributed most to purchasing.

CONCLUSIONS: Strategies employed by manufacturers and supermarkets, such as promotional pricing, and supermarkets' generic products lead to lower prices. These opportunities are not equally available to remote customers and are a major driver of price disparity.

IMPLICATIONS: Food affordability for already disadvantaged residents of remote communities could be improved by policies targeted at manufacturers, wholesalers and/or major supermarket chains.

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1. Active engagement with practitioners is a crucial component of model-based decision-making in conservation management; it can assist with data acquisition, improve models and help narrow the 'knowing-doing' gap.
2. We worked with practitioners of one of the worst invasive species in Australia, the cane toad Rhinella marina, to revise a model that estimates the effectiveness of landscape barriers to contain spread. The original model predicted that the invasion could be contained by managing artificial watering points on pastoral properties, but was initially met with scepticism by practitioners, in part due to a lack of engagement during model development.
3. We held a workshop with practitioners and experts in cane toad biology. Using structured decision-making, we elicited concerns about the original model, revised its structure, updated relevant input data, added an economic component and found the most cost-effective location for a barrier across a range of fixed budgets and management scenarios. We then conducted scenario analyses to test the sensitivity of management decisions to model revisions.
4. We found that toad spread could be contained for all of the scenarios tested. Our modelling suggests a barrier could cost $4·5 M (2015 AUD) over 50 years for the most likely landscape scenario. The incorporation of practitioner knowledge into the model was crucial. As well as improving engagement, when we incorporated practitioner concerns (particularly regarding the effects of irrigation and dwellings on toad spread), we found a different location for the optimal barrier compared to a previously published study (Tingley et al. 2013).
5. Synthesis and applications. Through engagement with practitioners, we turned an academic modelling exercise into a decision-support tool that integrated local information, and considered more realistic scenarios and constraints. Active engagement with practitioners led to productive revisions of a model that estimates the effectiveness of a landscape barrier to contain spread of the invasive cane toad R. marina. Benefits also include greater confidence in model predictions, improving our assessment of the cost and feasibility of containing the spread of toads.

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Purpose – The process for examining the value of house prices in an urban city has given limited attention, if any, to demographic variables associated with urban geography. Although the disciplines of property/real estate and demography have moved closer, little progress has been made when modelling house prices using population-related data in the field of urban geography to explain the level of house prices.

Design/methodology/approach – This paper proposes an innovative model to examine the influence of population variables on the level of house prices. It used a two-stage approach as follows: principal components analysis (PCA) identified social dimensions from a range of demographic variables, which were then retained for further analysis. This information was sourced from two Australian Bureau of Statistics censuses undertaken involving all Melbourne residents during 1996, 2001, 2006 and 2011; multiple regression analysis examined the relationship between the retained factor scores from the PCA (as independent variables) and established residential house prices (as the dependent variable).

Findings – The findings confirm the demographic profile of each household, which is directly related to their decisions about housing location and house prices. Based on a case study of Melbourne, Victoria, it was demonstrated that households with specific demographic characteristics are closely related to a certain level of house prices at the suburban level.

Originality/value – This is an innovative study which has not been previously undertaken for an extended period of time to facilitate an analysis of change over time.