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In Matlab, execute the script "
main_create_env".-
If you have the Matlab Symbolic Math Toolbox and use version 2018b or earlier, leave the flag "
useJacobian" in line 43 on. Otherwise set to false to use numerical differentiation. -
Note: generating the analytic Jacobian for the benchmark model takes approximately 5 minutes with version 2018b, and can take longer for the other experiments.
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"
main_create_env" will create a file "env_bench_ini0" that contains the experiment definition for the benchmark economy. -
The code archive contains the pre-computed file.
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Execute script "
main_run_exper".-
You can set the number of parallel workers to be started in the separate script "
open_parpool" -
Set to zero if you want to run it with a single process.
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On a computer with sixteen cores (and 16 parallel workers) the benchmark model converges in about 3 hours.
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"
main_run_exper" creates a results file named "res_[current_date_time]" that contains the converged policy functions. -
The code archive contains the pre-computed file named "
res_20191112_bench".
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Simulate the model using "
sim_stationary" and "sim_trans_cluster".-
"
sim_stationary" simulates the model policies contained in "res_20191112_bench" for 10,000 periods and writes out the resulting time-series and several statistics. The main output is a file named "sim_res_20191112_bench". -
"
sim_trans_cluster" reads both "res_20191112_bench" and "sim_res_20191112_bench", and simulates generalized IRFs. -
To plot IRFs, run "
plot_trans".
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1: Greenwald: Massachussetts Institute of Technology Sloan School; email: dlg(at)mit.edu. Landvoigt: University of Pennsylvania Wharton School, NBER, and CEPR; email: timland(at)wharton.upenn.edu. Van Nieuwerburgh: Columbia University Graduate School of Business, NBER, and CEPR, 3022 Broadway, Uris Hall 809, New York, NY 10027; email: svnieuwe(at)gsb.columbia.edu.