Download the notebook here! Interactive online version:

[1]:

import yaml
import sys
import os

import pandas as pd
import respy as rp

sys.path.insert(0, "python")
from auxiliary import plot_average_wages_over_time  # noqa: E402
from auxiliary import plot_choice_probabilities  # noqa: E402
from auxiliary import plot_distibution_wages  # noqa: E402

Robinson Crusoe economy

The respy package provides several example models that can be used to explore selected issues in the structural microeconometrics. We focus on the robinson example, which allows for quick iterations. All example models share the same interface so they can be easily swapped in and out of any analysis.

[2]:

options_base = yaml.safe_load(open(os.environ["ROBINSON_SPEC"] + "/robinson.yaml", "r"))

params_base = pd.read_csv(open(os.environ["ROBINSON_SPEC"] + "/robinson.csv", "r"))
params_base.set_index(["category", "name"], inplace=True)

Let’s look at the parameterization of the model, the specified options and a simulated dataset.

[3]:

params_base

[3]:

		value
category	name
delta	delta	0.950
wage_fishing	exp_fishing	0.070
nonpec_fishing	constant	-0.100
nonpec_hammock	constant	1.046
shocks_sdcorr	sd_fishing	0.010
	sd_hammock	0.010
	corr_hammock_fishing	0.000

[4]:

options_base

[4]:

{'estimation_draws': 100,
 'estimation_seed': 100,
 'estimation_tau': 0.001,
 'interpolation_points': -1,
 'n_periods': 5,
 'simulation_agents': 1000,
 'simulation_seed': 132,
 'solution_draws': 100,
 'solution_seed': 456,
 'covariates': {'constant': '1'}}

Now we are ready to simulate a sample.

[5]:

simulate = rp.get_simulate_func(params_base, options_base)
df = simulate(params_base)

We first look at the general structure of the data.

[6]:

df.head()

[6]:

		Experience_Fishing	Shock_Reward_Fishing	Meas_Error_Wage_Fishing	Shock_Reward_Hammock	Meas_Error_Wage_Hammock	Choice	Wage	Discount_Rate	Present_Bias	Nonpecuniary_Reward_Fishing	Wage_Fishing	Flow_Utility_Fishing	Value_Function_Fishing	Continuation_Value_Fishing	Nonpecuniary_Reward_Hammock	Wage_Hammock	Flow_Utility_Hammock	Value_Function_Hammock	Continuation_Value_Hammock
Identifier	Period
0	0	0	1.007197	1	0.010305	1	fishing	1.007197	0.95	1	-0.1	1.007197	0.907197	4.747606	4.042536	1.046	NaN	1.056305	4.742931	3.880659
	1	1	0.981015	1	0.010596	1	fishing	1.052147	0.95	1	-0.1	1.052147	0.952147	4.022193	3.231627	1.046	NaN	1.056596	3.903085	2.996304
	2	2	0.998980	1	-0.003797	1	fishing	1.149101	0.95	1	-0.1	1.149101	1.049101	3.230306	2.296006	1.046	NaN	1.042203	3.063422	2.127598
	3	3	0.989253	1	-0.011702	1	fishing	1.220419	0.95	1	-0.1	1.220419	1.120419	2.282845	1.223607	1.046	NaN	1.034298	2.111715	1.134123
	4	4	1.010431	1	-0.002176	1	fishing	1.336932	0.95	1	-0.1	1.336932	1.236932	1.236932	0.000000	1.046	NaN	1.043824	1.043824	0.000000