The ihsMW package provides programmatic access to the
Malawi Integrated Household Survey (IHS) microdata hosted by the World
Bank. Much like the WDI package elegantly bridges World
Bank macroscopic development indicators into R, ihsMW
bridges complex, respondent-level household microdata endpoints. It
removes the friction of manual downloads, parsing, and pooling,
significantly accelerating research workflows.
# CRAN (coming soon)
install.packages("ihsMW")
# Development version
devtools::install_github("vituk123/ihsMW")library(ihsMW)
ihs_auth() # one-time setup
ihs_search("consumption") # find variables
df <- IHS("rexp_cat01", round="IHS5") # download data
head(df)Discovering targeted survey questions across thousands of potential
columns is notoriously difficult due to arbitrary module definitions. In
ihsMW, you query intuitive indicators via the built-in
search functions directly, retrieving exact metadata bounds including
categorical label translations efficiently prior to extracting raw
dataset files.
Researchers compiling cross-sectional trends often encounter fractured variable names spanning several disparate releases making chronological bindings intensely fragile. By leveraging the built-in harmonisation engine recursively mapping embedded structures implicitly, querying across multiple rounds binds matrices securely bypassing fragmented architectures entirely out-of-the-box.
Traditional unweighted aggregations mask significant spatial biases
inherited during rural stratifications invalidating macroscopic insights
structurally. Pulling arrays iteratively utilizing dedicated survey
weighting helpers builds tbl_svy instances capturing
multi-tiered cluster architectures effortlessly.
Accessing the official database necessitates registering a free
researcher account directly through the World Bank Microdata Library at
https://microdata.worldbank.org. The ihs_auth() function
intelligently walks you through generating a secure token natively
mapping the credentials persistently out-of-sight ensuring frictionless
downloads natively.
To cite ihsMW in publications, please use:
@Manual{,
title = {ihsMW: Access Malawi Integrated Household Survey Data in R},
author = {Vitumbiko Kayuni},
year = {2026},
note = {R package version 0.1.0},
url = {https://github.com/vituk123/ihsMW},
}When publishing research utilizing datasets harmonized or accessed
via ihsMW, always cite both the NSO Malawi and the World
Bank LSMS. Please consult the respective round’s Basic Information
Document for the exact citation format.
We welcome additions and mappings! Please report bugs, suggest mapping configurations, and propose structural adjustments directly on our GitHub Issues and consult our CONTRIBUTING.md file.
MIT