computational methods for macroeconomics (spring 2007)

makoto nakajima (@wh452, makoto[at]uiuc[dot]edu)

tue and thu, 12:30-13:50 @ 174 wh

wed, 10:00-12:00 or by appointment (email me)

click here

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[note] dynamic programming.

[note] numerical methods: approximation of normal and ar(1).

[note] numerical methods: chebyshev regression.

[note] numerical methods: one-dimensional optimziation.

[note] numerical methods: numerical differentiation.

[note] solving neoclassical growth model: introduction.

[note] solving neoclassical growth model: value function iteration + discretization.

[note] solving neoclassical growth model: value function iteration + finite element method.

[note] solving neoclassical growth model: value function iteration + chebyshev regression.

[note] solving rbc model: linear-quadratic approximation.

[note] solving rbc model: blanchard-kahn.

[note] solving rbc model: undetermined coefficients.

[note] solving heterogeneous agent model: handling type distribution.

[note] solving heterogeneous agent model: aiyagari (1994).

[note] solving heterogeneous agent model: aiyagari (1994) with some extensions.

[note] solving heterogeneous agent model: krusell and smith (1998).

[note: access restricted] solving heterogeneous agent model: krusell and smith (1998) with labor supply decision.

[note: access restricted] solving heterogeneous agent model: krusell and smith (1997), with two types of assets.

[note: access restricted] solving heterogeneous agent model: limited commitment

[note: access restricted] solving heterogeneous agent model: equilibrium bankruptcy

[pronlem set 1]: due feb 13. you need this earnings data.

[pronlem set 2]: due feb 27.

[pronlem set 3]: due mar 27.

[pronlem set 4]: due apr 17. you need this individual productivity proces.

[pronlem set 5]: due may 13. you need this discretized stochastic process for tfp.

[pronlem set 6]: due xxx xx. only for super-motivated. you need this discretized stochastic process.