opl_dt_max_choice

Function that allows the user to select a row of maximum welfare among the rows with maximum welfare constrained. The function prints out the result and requires user input to select the row.

Provides functions for optimal policy learning in socioeconomic applications helping users to learn the most effective policies based
on data in order to maximize empirical welfare. Specifically, 'OPL' allows to find "treatment assignment rules" that maximize the overall
welfare, defined as the sum of the policy effects estimated over all the policy beneficiaries. Documentation about 'OPL' is provided by
several international articles via Athey et al (2021, <doi:10.3982/ECTA15732>), Kitagawa et al (2018, <doi:10.3982/ECTA13288>),
Cerulli (2022, <doi:10.1080/13504851.2022.2032577>), the paper by Cerulli (2021, <doi:10.1080/13504851.2020.1820939>)
and the book by Gareth et al (2013, <doi:10.1007/978-1-4614-7138-7>).

Federico Brogi

Optimal Policy Learning

Barbara Guardabascio

Giovanni Cerulli

opl_dt_max_choice function

<dl><dt>nc</dt>
<dd>Numeber of max welfare.</dd>
<dt>col_max</dt>
<dd>Row index for max constrained welfare.</dd>
<dt>verbose</dt>
<dd>Set TRUE to print the output on the console.</dd></dl>

Arguments

User selection on multiple choice — opl_dt_max_choice

<dl>

<dt>nc</dt>
<dd>Numeber of max welfare.</dd>


<dt>col_max</dt>
<dd>Row index for max constrained welfare.</dd>


<dt>verbose</dt>
<dd>Set TRUE to print the output on the console.</dd>

</dl>

opl_dt_max_choice: User selection on multiple choice

Description

Usage

Value

Arguments