---
id: engines/simpop
about:
  label: simPop
  description: >-
    R package by Matthias Templ and colleagues that simulates a full synthetic
    population from a survey sample and census totals, developed with support
    from the World Bank and the IHSN.
  tags:
    - synthetic population
    - survey data
    - census
    - microdata
    - R
tool:
  form: open-source R package (CRAN)
  group: People and populations
  homepage: 'https://github.com/statistikat/simPop'
  licence: GPL-2 or GPL-3
  cost: free
domains:
  - people
open:
  source: open
  data: unknown
  api: unknown
  participation: open
  licence: GPL-2 or GPL-3
relations:
  - predicate: alternative_to
    target: engines/populationsim
provenance:
  origin: agent
  sources:
    - title: statistikat/simPop (README)
      url: 'https://github.com/statistikat/simPop'
    - title: 'CRAN: Package simPop'
      url: 'https://cran.r-project.org/package=simPop'
    - title: Synthetic Populations | IHSN
      url: 'https://www.ihsn.org/projects/synthetic-populations'
    - title: >-
        Simulation of Synthetic Complex Data: The R Package simPop (Crossref
        record)
      url: 'https://api.crossref.org/works/10.18637/jss.v079.i10'
  created: '2026-10-23'
  reviewed: '2026-10-23'
  reviewed_by: 'Claude, from the sources listed'
  status: draft
---
simPop is an R package that turns a household survey into a synthetic population: a complete, invented set of people and households that keeps the statistical shape of the survey and of known census totals.[^2,3] Researchers use this kind of file when they want to run an agent-based or micro-level model of a country or region but cannot release, or do not have, a record for every resident.[^3]

The main authors are Matthias Templ, Alexander Kowarik, Bernhard Meindl and Andreas Alfons; the code is kept on GitHub under the statistikat account.[^1,2] The International Household Survey Network (IHSN) and the World Bank's Development Data Group backed its development to encourage the use of existing survey and census microdata for agent-based simulation, funded through a DFID trust fund administered by the World Bank.[^2,3] The IHSN describes synthetic data as largely solving the risk of disclosing real respondents, and as a way to fuse data from several sources.[^3]

The package combines model-based methods, calibration and combinatorial optimisation.[^2,3] You install it from CRAN and work in R.[^2] The method is described in a 2017 paper in the Journal of Statistical Software by Templ, Meindl, Kowarik and Olivier Dupriez.[^4]

It is licensed GPL-2 or GPL-3.[^2] The CRAN release is 2.1.3 from January 2024; the GitHub repository carries a slightly newer 2.1.4 and its last commit was in January 2026, so it is maintained but quiet.[^1,2] The IHSN project page marks the World Bank project itself as closed, with follow-up activities.[^3]