---
license: gpl-3.0
language:
- en
pretty_name: 'Deep learning four decades of human migration: datasets'
tags:
- arXiv:2506.22821
---
Deep learning four decades of human migration: datasets
---

This repository contains all migration flow estimates associated with the paper [_"Deep learning four decades of human migration."_](https://arxiv.org/abs/2506.22821) Evaluation code, training data, trained neural networks, and smaller flow datasets are available in the [main GitHub repository](https://github.com/ThGaskin/Migration_flows), which also provides detailed instructions on data sourcing. Due to file size limits, the larger datasets are archived here.
The repository contains three folders:

# Estimates
This folder contains all the migration estimates. Data is available in both NetCDF (`.nc`) and CSV (`.csv`) formats. The NetCDF format is more compact and pre-indexed, making it suitable for large files. In Python, datasets can be opened as [`xarray.Dataset`](https://docs.xarray.dev/en/stable/generated/xarray.Dataset.html) objects, enabling coordinate-based data selection.

Each dataset uses the following coordinate conventions:

*   **Year**: 1990–2023
*   **Birth ISO**: Country of birth (UN ISO3)
*   **Origin ISO**: Country of origin (UN ISO3)
*   **Destination ISO**: Destination country (UN ISO3)
*   **Country ISO**: Used for net migration data (UN ISO3)

The following data files are provided:

*   **T.nc**: Full table of flows disaggregated by country of birth. Dimensions: Year, Birth ISO, Origin ISO, Destination ISO
*   **flows.nc**: Total origin-destination flows (equivalent to `T` summed over Birth ISO). Dimensions: Year, Origin ISO, Destination ISO
*   **net\_migration.nc**: Net migration data by country. Dimensions: Year, Country ISO
*   **stocks.nc**: Stock estimates for each country pair. Dimensions: Year, Origin ISO (corresponding to Birth ISO), Destination ISO
*   **test\_flows.nc**: Flow estimates on a randomly selected set of test edges, used for model validation

Additionally, two CSV files are provided for convenience:

*   **mig\_unilateral.csv**: Unilateral migration estimates per country, comprising:
    *   `imm`: Total immigration flows
    *   `emi`: Total emigration flows
    *   `net`: Net migration
    *   `imm_pop`: Total immigrant population (non-native-born)
    *   `emi_pop`: Total emigrant population (living abroad)
*   **mig\_bilateral.csv**: Bilateral flow data, comprising:
    *   `mig_prev`: Total origin-destination flows
    *   `mig_brth`: Total birth-destination flows, where `Origin ISO` reflects place of birth

Each dataset includes a `mean` variable (mean estimate) and a `std` variable (standard deviation of the estimate).

An ISO3 conversion table is also provided.

# Data
The `Data` contains all the data used to train, evaluate, and test the neural network.
It is stored thematically in different folders, and most folders again contains its own `README` file to further
explain the specific sources and imputation methods. All data is given *both* as a `.csv` file and a `.nc` file, and 
follows the ISO3-naming convention outlined in the main README.

## Training_data
This folder contains all the tensors used to train the neural network. All data is given as a PyTorch
tensor (`.pt`) and can be loaded using `torch.load()`. The folder contains targets, weights, masks, input covariates (scaled
and unscaled), and the edge indices of each input. See the folder README for further details.

## Net migration (`Net_migration`)
This folder contains net migration data, sourced from national statistical offices, together with a list of sources 
and the UN WPP net migration figures.

## GDP indicators (`GDP_data`)
This folder contains data on GDP/capita, GDP growth, nominal GDP, and other GDP-related indicators for all countries and
years included in the training period.

## Gravity covariates (`Gravity_datasets`)

## Demographic indicators (`UN_WPP_data`)

## Migrant stocks (`UN_stock_data`)

## Refugee figures (`UNHCR_data`)
Total number of refugees, asylum-seekers, and other people in need of international protection, taken from the 
[UNHCR dataset](https://www.unhcr.org/refugee-statistics/download).

## Conflict deaths (`UCDP_data`)
This folder contains data on deaths in conflict provided by
[UCDP Georeferenced Event](https://ucdp.uu.se/downloads/index.html#ged_global) dataset.
NaN values are filled with 0.

## Bilateral flows (`Flow_data`)

# Trained networks
Contains the ensemble of trained neural networks