Error correlation in input-output frameworks
Today, many frameworks for environmental and sustainability assessment utilise input-output techniques (Forssell and Polenske 1998). These techniques are based on input-output analysis, a discipline founded by Nobel Prize Laureate Wassily Leontief in the 1940s (Leontief 1936). Since its invention, numerous analysts in academia, industry and government alike, use input-output analysis for economic and environmental studies (Foran, Lenzen et al. 2005; Foran, Lenzen et al. 2005). More than 100 countries worldwide regularly publish input-output tables, according to guidelines governed by the (United Nations Department for Economic and Social Affairs Statistics Division 1999).
More recently, users of environmental assessments are increasingly asking for uncertainty appraisals to be provided along with main findings. In any quantitative study, this requires uncertainty techniques to be applied.
There are a number of examples that demonstrate state-of-the-art uncertainty analysis, however these are still the exception. The rationale of this project is to contribute to the advancement of uncertainty calculus in environmental analysis.
The results of this project will be valuable, because they will cast light on the question whether traditional assumptions of uncorrelated, normally distributed raw data errors lead to uncertainty estimates of environmental assessment results that are too low, and hence provide decision-makers using these results with expectations that are too optimistic in terms of analytical reliability.
• Good understanding of matrix algebra
• Understanding of basic statistics, such as distributions
• Programming in MatLab, FORTRAN or C
• Basic understanding of economics, or willingness to learn
• Good scientific writing style
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The opportunity ID for this research opportunity is: 1441
Other opportunities with Professor Manfred Lenzen
- Carbon Pricing
- Quantifying the return on investment in the Environment, Public Health and Individual Wellbeing.
- Modeling Complex Coordination of Public Health Care
- Exploring the link between international trade and the global obesity epidemic
- Sustainable Community Healthcare Networks
- Visualisation of High Dimensional Data.