Massively Parallel Algorithms for Bayesian Inference and Decision Making

Funding: 2013: $249,234
2014: $265,410
2015: $268,913

Funding or Partner Organisation: University of New South Wales (The University of New South Wales)
Australian Research Council (ARC Discovery Projects)
University of Colorado
University of Montreal

Start year: 2013

Summary: The primary aims of the project are to develop generic algorithms for econometric and economic analysis suited to graphical processing units, to use them in new and more realistic models of economic behaviour, and to incorporate them in readily accessible software. In accomplishing these aims the project will make fundamental advances in the quantitative and computational infrastructure of economic science and will improve public and private sector decision-making. The principal outcomes of the project will be a reorientation of quantitative economic modeling and statistical inference and higher standards for the realism and reliability of policy recommendations made by economists.

Keywords: Bayesian inference,optimization algorithms

FOR Codes: Mathematical Economics, Economic Framework not elsewhere classified, Econometric and Statistical Methods, Management, Economic Models and Forecasting, Public Sector Productivity, Mathematical economics , Other economic framework not elsewhere classified

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.