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Daniel Graham

This talk will provide an overview of the measurement of wider economic impacts in transport appraisal focusing in particular on the role of agglomeration economies. It will describe how agglomeration effects can be estimated and included within a standard Benefit Cost Analysis framework to assess the productivity benefits of investment. Examples from around the world will be used to illustrate the potential significance of agglomeration externalities. The talk will discuss limitation of the existing approach, particularly in relation to econometric modelling, and will suggest future areas for research.


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About the Speaker(s)

Speaker: Daniel Graham is a leader in Transport Economics and Statistics at the Centre for Transport Studies at Imperial College London.

He specialises in the statistical modelling of transport systems. His main research themes are concerned with the implications of transport investment for productivity and economic growth; modelling efficiency in public transport provision; and with the wider consequences of travel demand patterns particularly in relation to safety, congestion, and environmental impacts. His modelling of the impacts of accessibility on the real economy forms the basis for the assessment of wider economic impacts in transport appraisal internationally. He is currently engaged in projects on Bayesian inference for road traffic accident prediction, mixed model propensity score approaches for causal inference, and semiparametric double robust estimation for continuous treatment effects.

Dr Graham also holds the post of Research Director of the Railway and Transport Strategy Centre (RTSC), a research group incorporating 15 full-time staff members at Imperial College. He teaches Masters courses in Statistics for Advanced Transport Modelling and Microeconomic Theory. Dr Graham provides advice to UK government departments, including the Department for Transport and the Treasury and was appointed Specialist Advisor to the Parliamentary Select Committee on Transport.