Blog Topics...

3D plotting (1) Academic Life (2) ACE (18) Adaptive Behavior (2) Agglomeration (1) Aggregation Problems (1) Asset Pricing (1) Asymmetric Information (2) Behavioral Economics (1) Breakfast (4) Business Cycles (8) Business Theory (4) China (1) Cities (2) Clustering (1) Collective Intelligence (1) Community Structure (1) Complex Systems (42) Computational Complexity (1) Consumption (1) Contracting (1) Credit constraints (1) Credit Cycles (6) Daydreaming (2) Decision Making (1) Deflation (1) Diffusion (2) Disequilibrium Dynamics (6) DSGE (3) Dynamic Programming (6) Dynamical Systems (9) Econometrics (2) Economic Growth (5) Economic Policy (5) Economic Theory (1) Education (4) Emacs (1) Ergodic Theory (6) Euro Zone (1) Evolutionary Biology (1) EVT (1) Externalities (1) Finance (29) Fitness (6) Game Theory (3) General Equilibrium (8) Geopolitics (1) GitHub (1) Graph of the Day (11) Greatest Hits (1) Healthcare Economics (1) Heterogenous Agent Models (2) Heteroskedasticity (1) HFT (1) Housing Market (2) Income Inequality (2) Inflation (2) Institutions (2) Interesting reading material (2) IPython (1) IS-LM (1) Jerusalem (7) Keynes (1) Kronecker Graphs (3) Krussel-Smith (1) Labor Economics (1) Leverage (2) Liquidity (11) Logistics (6) Lucas Critique (2) Machine Learning (2) Macroeconomics (45) Macroprudential Regulation (1) Mathematics (23) matplotlib (10) Mayavi (1) Micro-foundations (10) Microeconomic of Banking (1) Modeling (8) Monetary Policy (4) Mountaineering (9) MSD (1) My Daily Show (3) NASA (1) Networks (46) Non-parametric Estimation (5) NumPy (2) Old Jaffa (9) Online Gaming (1) Optimal Growth (1) Oxford (4) Pakistan (1) Pandas (8) Penn World Tables (1) Physics (2) Pigouvian taxes (1) Politics (6) Power Laws (10) Prediction Markets (1) Prices (3) Prisoner's Dilemma (2) Producer Theory (2) Python (29) Quant (4) Quote of the Day (21) Ramsey model (1) Rational Expectations (1) RBC Models (2) Research Agenda (36) Santa Fe (6) SciPy (1) Shakshuka (1) Shiller (1) Social Dynamics (1) St. Andrews (1) Statistics (1) Stocks (2) Sugarscape (2) Summer Plans (2) Systemic Risk (13) Teaching (16) Theory of the Firm (4) Trade (4) Travel (3) Unemployment (9) Value iteration (2) Visualizations (1) wbdata (2) Web 2.0 (1) Yale (1)

Tuesday, September 7, 2010

What have I done today...

Well besides the generic new student paperwork, I did have sometime to think a bit about some of the issues that I am likely to encounter.  This is a summary of what I have come up with so far:

Question: Why do banks form credit networks?
Banks basically want to do two things:
  1. Make lots of money, and
  2. Generate liquidity
Addressing 1: Banks make money by lending money (i.e., by forming links with other banks, firms, etc).  Banks essentially trade money now for more money later.  This is my working justification for why the number of direct links should be included in the bank's pay-off function.  Addressing 2: Forming credit networks may be a strategy to generate liquidity.  This is my justification for including indirect links in the bank's pay-off function.  I am tempted to say that, all things equal, banks should exhibit some type of preference to link with banks that have lots of links already (either because number of links is viewed as a proxy for something, or because lots of links implies greater access to the rest of the credit network) but this may be getting ahead of myself...

Very abstractly...banks can be divided into three broad classes:
  1. Pure lenders
  2. Pure borrowers
  3. Banks that do both (i.e., lend and borrow)
In the graphic above blue arrows represent flow of money now, and red dashed arrows represent flow of money later.  Not sure this diagram is all that useful except that it helped formalize my intuition concerning how link formation might generate liquidity.  The basic idea is that suppose we have three banks:
Now suppose that Bank 1 is willing to lend to Bank 2 but not to Bank 3 (for whatever reason...perhaps Bank 3 is too risky), but Bank 2 is willing to lend to Bank 3 (because Bank 2 has different risk tolerances...I suppose I have introduced my first heterogenous parameter).  In this case the linkages generate liquidity because without them, Bank 3 would not have been able to borrow. 

Question: How should returns to bank i from a link with bank j be defined?
At this point I am playing with the idea that the value of the link to the lender is something like the discounted present value of the money later minus costs (yet to be defined), while the value to the borrower is the loan amount minus costs (i.e., interest).  How to set interest rate?  Starting point would be to take interest rate as exogenous, but at the moment I am toying with the idea of having banks bargain locally over the interest rate.  In the bargaining process the lender would have several outside options (i.e., either lending to another bank or parking his money in "risk-free" securities) the only outside options available to the borrower would be other banks.

All of this is highly specualtive at this point...but what should you expect on day one of a PhD career!

1 comment:

  1. What does a link represent in your model? A link could be either a loan from one bank to another, or a (formal or informal) credit line, i.e. the option to take out a loan if necessary. How a bank assesses the value of a link will depend on whether a link is a loan or a credit line.

    Endogenizing network formation is important, I gather that one shortcoming of the Bank of England literature on financial networks is that it largely takes network structure as exogenous - the only papers with endogenous network formation mentioned in this paper: http://www.bankofengland.co.uk/publications/workingpapers/wp383.pdf are Leitner, 'Financial Networks: Contagion, Commitment, and Private Sector Bailouts' and Castiglione & Navarro, 'Optimal Fragile Financial Networks'

    ReplyDelete