1st Year of my PhD (A Rough Outline)...

As my PhD studies approach I have been thinking about how best to structure my first year to make sure that it is in line with my overall PhD agenda.  Here is my first attempt:

1st Year Topic of Focus: Formation of Credit Networks

Need to build at least two small-scale, analytically tractable models (i.e., solvable via pen & paper)of credit network formation.  Goal is to build intution and gain a deeper understanding of how credit effects network incentives.  There are two main approaches to explore:

• Traditional utility-based approach to credit network formation.  Analysis will rely heavily on game threory.  Equilibrum concept will be some version refinement of Nash.  Work will rely heavily on previous research by Jackson, Goyal, Vega-Redondo, et al.
• Random network approach to credit network formation.  Relies heavily on research done by Jackson, Barabasi and Albert, et al.  Analytical techniques borrow heavily from statistical physics.

Need to begin building simple agent-based computational models of credit network formation.  Starting point will be Axtell and Epstein's model of emerging credit networks from Growing Artificial Societies.  Other more advanced models will be considered for year's two and three.

• I will need to establish relationships with the School of Informatics in order to develop my programming skills to the point where I can write and compile my own code.  Programming is especially important as I will be applying to the Sante Fe Institute's Summer School in 2011.
• Also I need to continue to develop my EVT skills.  Much of this can actually be done in conjunction with my responsibilities as a QM tutor and TA.

These 1st-year objectives fit nicely into my overall PhD agenda which starts with network formation, then moves to diffusion of credit/liquidity over the networks, and then finishes (ideally) with a detailed dynamic computational model that ties everything together.  In addition to increasing my understanding of economic theory, I want to finish my PhD with significant computer programming skills.  These skills should be sufficient to build complex computational models of network formation that could be used to address policy issues.