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Chancellor W.,Australian Bureau of Statistics | Abbott M.,Swinburne University of Technology
Construction Management and Economics | Year: 2015

Estimates of the size and change in the Australian construction industry shadow economy value over time are provided and applied as a quality adjustment to Australian construction industry productivity growth from 1985 to 2012. The results indicate that the Australian construction industry shadow economy is growing and that by adjusting for the shadow economy, distortion is removed from construction industry productivity growth estimates. The findings create significant scope for future research into the estimation and the effect of shadow economic activity on productivity growth, not just in Australia but in other countries as well. © 2015, © 2015 Taylor & Francis. Source

Stoneham G.,1 Macarthur St | O'Keefe A.,1 Macarthur St | Eigenraam M.,8 Nicholson St. | Bain D.,Australian Bureau of Statistics
Ecological Economics | Year: 2012

Recent developments in economics make it possible to design and create markets in sectors of the economy where they have previously been missing or inefficient. Although of interest from an economic efficiency perspective, market-based approaches to environmental management also reveal information and valuations that could have a role in environmental accounting. Using data from a pilot, involving the creation of a market (auction) for conservation contracts, we demonstrate a methodology to calculate the contribution of purchased ecosystem services to GDP, and create selected physical environmental asset accounts consistent with the System of Integrated Environmental and Economic Accounts. The paper also examines the role this information might play in developing monetary valuations for environmental assets. © 2012. Source

Pinter L.,Central European University | Hardi P.,CEU Business School | Martinuzzi A.,Vienna University of Economics and Business | Hall J.,Australian Bureau of Statistics
Ecological Indicators | Year: 2012

Revisiting the way society defines and measures progress has been identified as one of the key levers in tackling the root causes of unsustainable development. The recent economic and food crises exposed a critical weakness in the ability of currently mainstream indicators of progress to provide early warning and take adequate preventive action. Since the early 1990s a growing number of organizations have been involved in the development of indicator systems around the key socio-economic and environmental concerns of sustainable development within their own context. In order to provide guidance and promote best practice, in 1997 a global group of leading measurement and assessment experts developed the Bellagio Principles. The Bellagio Principles have become a widely quoted reference point for measuring sustainable development, but new developments in policy, science, civil society and technology have made their update necessary. The Bellagio Sustainability Assessment and Measurement Principles (BellagioSTAMP) have been developed through a similar expert group process, using the original Principles as a starting point. Intended to be used as a complete set, the new BellagioSTAMP includes eight principles: (1) Guiding vision; (2) Essential considerations; (3) Adequate scope; (4) Framework and indicators; (5) Transparency; (6) Effective communications; (7) Broad participation; and (8) Continuity and capacity. The paper provides the rationale for the revision of the principles, their detailed description and guidance for their application. © 2011 Elsevier Ltd. All rights reserved. Source

van Dijk A.,Australian National University | Mount R.,Bureau of Meteorology | Mount R.,University of Tasmania | Gibbons P.,Australian National University | And 2 more authors.
Science of the Total Environment | Year: 2014

Despite strong demand for information to support the sustainable use of Australia's natural resources and conserve environmental values and despite considerable effort and investment, nation-wide environmental data collection and analysis remains a substantially unmet challenge. We review progress in producing national environmental reports and accounts, identify challenges and opportunities, and analyse the potential role of research in addressing these. Australia's low and concentrated population density and the short history since European settlement contribute to the lack of environmental data. There are additional factors: highly diverse data requirements and standards, disagreement on information priorities, poorly measurable management objectives, lack of coordination, over-reliance on researchers and businesses for data collection, lack of business engagement, and short-term, project-based activities. New opportunities have arisen to overcome some of these challenges: enhanced monitoring networks, standardisation, data management and modelling, greater commitment to share and integrate data, community monitoring, increasing acceptance of environmental and sustainability indicators, and progress in environmental accounting practices. Successes in generating climate, water and greenhouse gas information appear to be attributable to an unambiguous data requirement, considerable investment, and legislative instruments that enhance data sharing and create a clearly defined role for operational agencies. Based on the analysis presented, we suggest six priorities for research: (1) common definitions and standards for information that address management objectives, (2) ecological measures that are scalable from local to national level, (3) promotion of long-term data collection and reporting by researchers, (4) efficient satellite and sensor network technologies and data analysis methods, (5) environmental modelling approaches that can reconcile multiple data sources, and (6) experimental accounting to pursue consistent, credible and relevant information structures and to identify new data requirements. Opportunities exist to make progress in each of these areas and help secure a more sustainable future. © 2013. Source

Marley J.K.,Australian Bureau of Statistics | Wand M.P.,University of Wollongong
Journal of Statistical Software | Year: 2010

We provide several illustrations of Bayesian semiparametric regression analyses in the BRugs package. BRugs facilitates use of the BUGS inference engine from the R computing environment and allows analyses to be managed using scripts. The examples are chosen to represent an array of non-standard situations, for which mixed model software is not viable. The situations include: the response variable being outside of the one-parameter exponential family, data subject to missingness, data subject to measurement error and parameters entering the model via an index. Source

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