*! version 0.1.4 8 Nov 2022

mpitb -- Toolbox to estimate and analyze multidimensional poverty indices (MPI)

Syntax

mpitb subcommand ... [, options]

subcommand

Core tools
set specifies the deprivation indicators of a MPI

est estimates MPIs and their subindices

Cross-country tools
refsh creates or updates a reference sheet

ctyselect selects a subset or all of the available countries

Low-level tools
show shows details of a particular specification (e.g., weights)

setwgts sets indicator weights based on dimensional weights

gafvars generates variables for the Alkire-Foster framework

rframe prepares result frames

stores stores estimates into results frame

estcot estimates changes over time

Auxiliary tools
assoc calculates association measures for indicators

Description

mpitb is a toolbox that offers several commands to facilitate specification,
estimation, and analysis of multidimensional poverty indices (MPI) and supports the popular
Alkire-Foster (AF) framework to multidimensional poverty measurement. In particular
this toolbox supports M0, a member of the Alkire-Foster class of measures, several
of its subindices and related auxiliary measures, see Alkire and Foster (2011) and
Alkire et al. (2015).

mpitb has been developed to facilitate the production process of the
global multidimensional poverty index. Indeed, mpitb has been developed in tandem
with a particular workflow now underlying the global MPI estimations. This workflow
seeks to provide more efficient and flexible estimation routines with results that
are also easy to replicate (Suppa 2021).

Workflow

The generic workflow for a single country is follows:

use ...

svyset ...

mpitb set ...

mpitb est ...

The two-step procedure of set and est has several advantages. First,
overly long commands and unnecessary repetitions can be avoided. This is also useful
for more intense and comprehensive estimation, as the indicators have to be chosen
only once, whereas results can be conveniently allocated into different files.
Second, it also allows a more interactive analyses of MPIs.

The generic workflow for a cross-country analysis is as follows:

mpitb refsh ...

mpitb ctyselect ...

foreach cty in `r(ctylist)' {

use ...

svyset ...

mpitb set ...

mpitb est ... , addmeta(ccty=`cty') ...

}

See Suppa (2022) for further illustrations using synthetic data shipped with
this toolbox as ancillary files.

Remarks

(1) A careful folder structure is strongly recommended for the use of this toolbox,
in particular if used in a cross-country setting. This recommendation directly follows
from the desiderata of the global MPI workflow to allow flexible re-estimations and
avoid unnecessary ones. Storing results to disk and only replacing
them as needed does precisely that. Sloppy data management is anyhow discouraged
for replicable research, but may be particular detrimental in the present case.

(2) Low-level tools are subcommands called by core tools. Low-level tools may
be interesting for advanced users and programmers who wish to implement
additional types of analyses. Users who are exclusively interested in established
analyses can ignore these commands and should use mpitb set and
mpitb est instead which additionally perform plausibility checks on user
inputs. Low-level tools require correct user input.

(3) This toolbox is still under active development. Many tweaks and extensions
may be obvious and some of them are, in fact, already scheduled for the next round
of code revision. Likewise, bugs and other issues may still emerge despite thorough
testing in different settings. Therefore, feedback on (i) successes and failures in
using this software package, (ii) bugs and related issues as well as (iii) suggestions
for tweaks and extensions are highly welcome.

(4) mpitb issues warnings or errors in many instances when the user is about to
commit an error or provides implausible information. Additionally, mpitb is tested
in various ways and contexts. Using mpitb, by itself, however does not guarantee to
obtain meaningful, informative or even correct results. Ultimately, living up to this
expectation remains the responsibility of the user and requires a proper understanding
of data, methods and analysis.

References

Alkire, S., Foster, J.E., Seth, S., Santos, M.E., Roche, J.M., and Ballón, P. (2015):
Multidimensional Poverty Measurement and Analysis: A Counting Approach, Oxford
University Press. (website)

Alkire, S. and Foster, J.E. (2011): Counting and Multidimensional Poverty
Measurement. Journal of Public Economics, Vol. 95 (7-8), pp. 476-487.
(website)

Suppa (2022): mpitb: A toolbox for multidimensional poverty indices.
OPHI Research in Progress 62a, Oxford Poverty and Human Development
Initiative (OPHI), University of Oxford [download].

Suppa (2021): The production process of the global MPI, presentation at the
UK Stata Conference, virtual, UK. (zip)

Author

Nicolai Suppa, Centre for Demographic Studies, Autonomous University of Barcelona
(nsuppa@ced.uab.es) and Oxford Poverty and Human Development Initiative (OPHI),
University of Oxford.

Please report bugs and other issues (including incomprehensible parts of the
documentation) to the issue tracker
of the gitlab repository. Feature requests, other suggestions, and more generally
any kind of feedback is always highly welcome!

License

This software package is published under the MIT license, see
here for details.

Citation

If you publish results obtained using this software package please cite it as

Suppa, Nicolai (2022): "mpitb - A toolbox for multidimensional poverty
indices", OPHI Research in Progress 62a, Oxford Poverty and Human Development
Initiative (OPHI), University of Oxford.

Acknowledgements

As this toolbox was developed in the context of several releases of the global MPI
since 2018, its development benefited from many helpful discussions with the wider OPHI
team, ranging from specific aspects of the estimation to user needs.
Code, documentation or paper benefited in particular from comments made by Jakob Dirksen,
Stephen Jenkins, Ricardo Nogales and an anonymous reviewer for the Stata Journal.
Finally, countless discussions with Usha Kanagaratnam, who is leading the global MPI
since 2018, have been essential for both identifying the overall workflow and packaging
parts of the code into this toolbox.