I invite ideas for collaboration which push the frontiers of understanding how technology, innovation, and infrastructure impact the broader economy (e.g. inter-industry, inter-regional, and/or global effects). My core competency is representing technology, innovation, and infrastructure in techno-economic optimization models and computable general equilibrium (CGE) both in theory and in application. Below are some specific areas of interest related to my current projects.
GTAP-Power: an energy and electricity-detailed CGE model
I created the the GTAP-Power model, an energy-electricity detailed version of the GTAP model which includes transmission & distribution and 11 electricity generating technologies. The GTAP-Power (available with GTAP subscription) model is a built on the multi-sector, multi-region GTAP framework which includes inter-sectoral substitution, consumer demands, and bilateral trade. The PE-GE representation of electricity technology substitution captures both capacity factor adjustment ("short-term" response to relative prices with fixed capacity) as well as long-term capacity growth and decommissioning. This represents the cutting-edge of electricity modeling in CGE where many models have either a single electricity sector or a simple parametrization of substitution between technologies.
The model is newly developed, and I am currently working on some applications independently. I invite researchers interested in modeling electricity in CGE and learning more about how GTAP-Power may help their efforts to contact me and discuss further.
Introducing new sectors and technology in CGE modeling
I have in-depth experience integrating "bottom-up" technical detail into "top-down" CGE databases along with intimate knowledge of the GTAP database. This type of work allows researchers to model detailed technological or policy change in a very specific industry while simultaneously considering inter-industry, inter-regional, and the circular flow of the economy represented in CGE models. My experience stems from introducing electricity generating technologies in the GTAP model where I worked on the complete project life-cycle:
- "Bottom-up", "top-down" data reconciliation: using RAS, cross-entropy, and even creating novel problem-specific methods
- PE-to-GE modeling: GAMS and GEMPACK (GTAP and various versions)
- Validation: sensitivity analysis, calibration, and retrospective shocks
I'd be interested in discussing ideas which dive deeper into energy and electricity or new projects which require additional technological detail than CGE models typically offer.
Validation of large-scale models
The development of innovative CGE and IAM models typically outpaces the ability to collect data, construct meaningful databases, and set parameters required to drive them. I have experience using systematic sensitivity analysis to test the robustness of results to model parameters. Further, I have experience in moving from raw data to CGE databases and have shown that even alternate database construction methods (with same raw data) can lead to opposite and unintuitive modeling results. There are many sources of uncertainty that are largely under-appreciated. I am interested in:
- Identifying and understanding the sources of uncertainty in large-scale modeling
- Reducing uncertainty by creating methods to validate the large-scale models particularly ones that are not unique to a certain modeling frame work and can be applied across other frameworks
I find this of increasing importance due to the prevalence of these large-scale models in both academic literature and policy analysis which will only increase in quantity and scope with lower barriers to entry (e.g. cost of data, computational power).