Data on stocks and flows of international migration are necessary to understand migrant patterns and trends and to monitor and evaluate migration-relevant international development agendas. Many countries do not publish data on bilateral migration flows. At least six methods have been proposed recently to estimate bilateral migration flows between all origin-destination country pairs based on migrant stock data published by the World Bank and United Nations. We apply each of these methods to the latest available stock data to provide six estimates of five-year bilateral migration flows between 1990 and 2015. To assess the resulting estimates, we correlate estimates of six migration measures from each method with equivalent reported data where possible. Such systematic efforts at validation have largely been neglected thus far. We show that the correlation between the reported data and the estimates varies widely among different migration measures, over space, and over time. We find that the two methods using a closed demographic accounting approach perform consistently better than the four other estimation approaches.
This paper came out a day before the United Nations Population Division updated their World Population Prospects (WPP). As all the estimates were based on WPP2017 our claim for the estimates being based on the most up to date input data was only true for around 24 hours.
In order to keep the estimates a bit more current I have added new set based on the WPP2019 to the Figshare collection. Below is a quick summary of the changes in the updated estimates to those in the paper.
The plot below shows the relationship between the bilateral flow estimates based on WPP2017 and WPP2019 from each period and estimation method.
For the stock differencing methods there are no changes in the estimates. They do not rely on WPP data. The migration rates approach uses the total absolute net migration data from WPP. All bilateral flows from WPP2019 are slightly higher than their WPP2017 counterparts, though it is barely noticeable in the plot above. The demographic accounting methods use the birth, death and population estimates from the WPP. In each method there are some sizable differences for the flows generated by updated revisions to the WPP demographic data, in particular for those based on the closed demographic accounting approach.
These difference results in revisions to the overall totals of migration flows. Below is an animation of the changes to Figure 2 in the paper
From this plot it is easier to see the changes in the migration rates estimation method. I was surprised that the changes in the estimates were occurring in all periods, not just the most recent period (2010-2015). To investigate I took a look at the changes in the WPP data.
The countries where the largest changes in the bilateral estimates occured (from the closed demographic accounting methods) can be detected by looking at the revisions in net migration between WPP2017 and WPP2019. Net migration is the best measure to track their changes as it correlates perfectly with the net migration in the WPP and is the residual of the input data (births, deaths and population) for the estimates based on the demographic accounting methods. Below are the changes in the complete time series of net migration in nine countries where the largest absolute differences (in any period) between the two WPP versions occur.
At first I was a bit surprised by the scale of the changes. In some periods the revisions to net migration are greater than a million. I dug a little deeper into net migration in previous WPP revisions to find that similar revisions are not unusual. Below are the revisions of absolute net migration between past WPP versions that exceed one million (back to WPP2000, the earliest WPP data I can get my hands on).
The impact of the revision in WPP data on the validation exercise in the paper is minimal. Below is an update of Figure 4 in the paper.
The correlations change by few hundredths of a decimal. These small changes, despite what is shown in the first plot above, are due to the limited amount of reported migration flows statistics (at the global level) to carry out our validation exercise. In the 45 countries that we used (based on the United Nations Population Division collection) the revisions in the WPP data were relatively minor, hence only small changes in their estimates and the correlations with the reported data.