Negative choice set eliminates option(s) completely under some cirumstances and induces missing data columns

[amageh]

• respy version used, if any: 2.0.0
• Python version, if any: any
• Operating System: any

Describe the bug

The bug concerns the negative choice sets. The observed behavior is the following: restricting work choices based on minimum experience requirements in other choice alternatives sometimes eliminates the choice for which the negative choice set is specified. Not sure whether I am just not specifying things correctly, but some parts seem weird to me:

Behavior

In the example models kw_94_* setting options["negative_choice_set"] = {'b': ['exp_edu < 12']} seems to partially eliminate option b. The option is never chosen and more importantly, the simulated dataset then only contains columns Experience_B, Shock_Reward_B, Meas_Error_Wage_B.

The following columns will be missing: Nonpecuniary_Reward_B, Wage_B , Flow_Utility_B, Value_Function_B, Continuation_Value_B.

Some additional info:

• In the above example, edu is also never chosen, but it is not missing data columns.
• This occurs for all kw_94_* example data sets and for both working options when exp_edu < 12 is set as the negative choice condition.
• It also sometimes occurs when the negative choice set is based on the experience in another occupation (for instance for kw_94_one option a when options["negative_choice_set"] = {'a': ['exp_b < 2']}) but not always (e.g. for the same model options["negative_choice_set"] = {'b': ['exp_a < 2']} does not create the issue for b).
• Eliminating a choice using a covariate like options["negative_choice_set"] = {'b': ['at_least_twelve_exp_edu == False']} also creates the issue.
• Eliminating the option using periods for example like options["negative_choice_set"] = {'b': ['period < 2']} does not eliminate the data columns in any case I tested.
• For the home option, the issue doesn't arise.
• Also tested this for kw_97_basic- same issues.

To reproduce

Steps to reproduce the behavior:

import respy as rp
params, options, df = rp.get_example_model("kw_94_one")
options["negative_choice_set"] = {'b': ['exp_edu < 12']}
simulate = rp.get_simulate_func(params, options)
data = simulate(params)

Then check out data columns and choice patterns.

[amageh]

@mo2561057 and @SofiaBadini tagging you, since I briefly discussed this with both of you :) Let me know if you have any ideas or additional input on this!