The Migration Policy Index

MPI values in 2013
Plot of the (overall) MPI values in 2014, with darker colors indicating a less restrictive policy
Source: Rayp, Ruyssen and Standaert, 2017


The Migration Policy Index is a composite index reflecting the de jure openness of migration policy. It summarizes all available indicators informative of economic migration, excluding those that apply strictly to asylum policy. Importantly, this index does not contain any de facto information, like the number of migrants received, as this would confuse  the outcome of a country’s immigration laws rather than their intended objectives. In addition to an overall index, we also composed three sub-indexes that track entry policies (including family reunification), stay policies (permanent as opposed to temporary migration); and integration policies (including migrant rights). For more information on the construction of the MPI, we refer to the paper listed below.


Please cite as: Glenn Rayp, Ilse Ruyssen and Samuel Standaert (2017), "Measuring and Explaining Cross-Country Immigration Policies", World Development, Vol. 95, pp. 141--163.


Click here to download the worldwide MPI indexes in csv format. This file contains the following variables:
  • id: a numerical country id
  • iso: the 3 digit ISO codes
  • name: the country names
  • year

The file also contains the following information for the overall index (MPI) and each of the sub-indexes: Entry (MPI_E), Stay (MPI_S) and Integration legislation (MPI_I).

  • MPI: the index values
  • stdDev: the standard deviation of each estimate
  • rank: ranking of countries per year, based on significant differences
  • nrVars: number of individual indicators available in that year used to compute the index
In order to correctly take the uncertainty of estimates into account (for example when studying changes over time), the extended MPI dataset contains all of the information above, as well as a sample of 200 randomly drawn values for each index. Each of these draws reflects the time-dependency of the corruption estimates and can be used such that any subsequent computations or (Bayesian) estimations completely take the inherent uncertainty of the corruption estimates into account.

The creation of the overall policy measure of immigration toughness is part of the ‘‘Economic and social consequences of immigration” project, supported by LEM, Universities of Lille. This project also received funding from the Research Foundation - Flanders (FWO), Ghent University (BOF) and the Belgian National Bank.
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