do_custom.py

"""
This module runs a custom model specification, with all options specified by the user.
"""

import code.calibration as parameters
from code.estimation import estimate

param_name = "DiscFac"  # Which parameter to introduce heterogeneity in
dist_type = "uniform"  # Which type of distribution to use
do_param_dist = False  # Do param-dist version if True, param-point if False

do_lifecycle = False  # Use lifecycle model if True, perpetual youth if False
do_agg_shocks = False  # Solve the FBS aggregate shocks version of the model
do_liquid = False  # Matches liquid assets data when True, net worth data when False

run_estimation = True  # Runs the estimation if True
# Choose which sensitivity analyses to run: rho, xi_sigma, psi_sigma, mu, urate, mortality, g, R
run_sensitivity = [False, False, False, False, False, False, False, False]
# Computes K/Y ratio for a wide range of beta; should have do_beta_dist = False
find_beta_vs_KY = False
# Uses a "tractable consumer" rather than solving full model when True
do_tractable = False


options = {
    "param_name": param_name,
    "dist_type": dist_type,
    "run_estimation": run_estimation,
    "run_sensitivity": run_sensitivity,
    "find_beta_vs_KY": find_beta_vs_KY,
    "do_tractable": do_tractable,
    "do_param_dist": do_param_dist,
    "do_lifecycle": do_lifecycle,
    "do_agg_shocks": do_agg_shocks,
    "do_liquid": do_liquid,
}

# Run the custom model
estimate(options, parameters)