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1 Download the MICS Data

This chapter shows how to download official MICS microdata from UNICEF and unpack it into a clean folder tree. MICS datasets are released as SPSS (.sav) files. They already carry variable and value labels, so you can open them directly in R or Stata without separate label codebooks or scripts, or a format conversion.

1.1 Download from UNICEF

Official MICS microdata are published on the UNICEF MICS surveys page.

  1. Open https://mics.unicef.org/surveys.
  2. Log in if the site asks you to (dataset downloads often require an account).
  3. Set the filters to match the surveys you want, for example, round (MICS6), region or countries, data type (MICS), and status (Completed).
  4. Click Download MICS datasets. The site packages every survey that matches your filters into one bulk zip (often named MICS_Datasets.zip).

Save the zip somewhere easy to find, such as your Downloads folder.

1.2 Messy nested survey archives

UNICEF’s bulk zip packs each survey in its own folder, and each folder usually holds another zip of SPSS files. Unpacking that by hand across many countries wastes time and invites path errors.

What you want instead is a flat tree: one folder per survey, with the .sav files and readme sitting directly inside it.

data/MICS_Datasets/
├── BEN_2021_MICS6_v01_M/
│   ├── bh.sav
│   ├── ch.sav
│   ├── fs.sav      # children aged 5–17 (foundation skills / FS module)
│   ├── hh.sav
│   ├── hl.sav
│   ├── mn.sav
│   ├── tn.sav
│   ├── wm.sav
│   └── Readme_....rtf   # or "Read me_....txt" — name varies by survey
├── GHA_2017_MICS6_v01_M/
│   └── ...
└── ...

Each country-year folder keeps all SPSS modules from that release, plus the readme. The prepare script below produces this layout from whatever surveys sit inside your bulk zip.

1.3 Prepare the folders with prepare-mics-fs.R

AFLEARN’s prepare-mics-fs.R turns UNICEF’s messy nested survey archives into that clean folder tree. The script finds MICS_Datasets.zip in your working directory, project, or Downloads; extracts the .sav files and readmes; strips nested archives and wrapper folders; and writes data/MICS_Datasets/{SURVEY}/. It needs only base R, and it runs beside the zip in any folder—Downloads, Desktop, a USB drive, or a project directory.

Download the script, copy it next to MICS_Datasets.zip, set that folder as the working directory in R, and run:

setwd("C:/path/to/folder/with/zip/and/script")
source("prepare-mics-fs.R")

The script writes path-ready survey files to data/MICS_Datasets/ under that folder. The original bulk zip is kept by default. To delete it after a successful run:

prepare_mics_data(remove_zip = TRUE)

If the zip lives elsewhere, source the script once to load the functions, then call:

prepare_mics_data(zip = "C:/path/to/MICS_Datasets.zip")

1.4 Quality checks

Before you analyse, check that:

  1. data/MICS_Datasets/ exists under the folder you used as the output root (for this guide, the project folder).
  2. At least one survey folder is present (for example data/MICS_Datasets/BEN_2021_MICS6_v01_M/).
  3. That folder contains .sav files (including fs.sav when the survey fielded the children 5–17 module) and usually a readme.
  4. You can open a .sav file in R (haven::read_sav()) or Stata (import spss).
dir.exists("data/MICS_Datasets")     # 1
list.files("data/MICS_Datasets")     # 2
file.exists("data/MICS_Datasets/BEN_2021_MICS6_v01_M/fs.sav")  # 3

1.5 Next steps

Once data/MICS_Datasets/ is in place—and especially once the supported surveys have fs.sav (and hl.sav for parent education)—continue with Harmonising MICS6 reading outcomes and Harmonising MICS6 FS background themes. For survey design and file structure, see Understanding MICS Data.