Extending Stochastic Growth Model


Is there a simple way of extending the Stochastic Growth Model with one extra control variable?
The brent_max optimizer only takes in one free variable?

Would be interesting to add variable which represent the decision of having capital placed in risky-asset vs capital in fixed income.

Guess, the first change will be to set the Cobb-Douglas function to a linear production function.
And just optimize the value function with respect to consumption and asset-share?

Hi @VSB.

The brent_max optimizer is only univariate, as you say.

There’s also multivariate optimization in quantecon.py: see https://quanteconpy.readthedocs.io/en/latest/optimize/nelder_mead.html.

I haven’t tested that routine much myself.

But note that we use these kinds of routines because they work in jit-compiled functions (those with @jit at the start), which helps with execution speed.

If you don’t mind a little bit more execution time, you can drop the jit-compilation and then pick any optimization routine from SciPy — there are lots.

Good luck with your project.

Thanks for you’re comment John.

Also, big thanks for coding examples and the lecture :slight_smile:

my pleasure :wink::+1:

I just updated the optimal growth lecture on the Python side to use @jitclass, which was fun. The code is a bit cleaner now. But it still needs to be checked for typos, so apologies in advance if you find some.

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