Using E-Mail Data to Estimate International Migration Rates

As is well known, “estimates of demographic flows are inexistent, outdated, or largely inconsistent, for most countries.” I would add costly to that list as well. So my QCRI colleague Ingmar Weber co-authored a very interesting study on the use of e-mail data to estimate international migration rates.

The study analyzes a large sample of Yahoo! emails sent by 43 million users between September 2009 and June 2011. “For each message, we know the date when it was sent and the geographic location from where it was sent. In addition, we could link the message with the person who sent it, and with the user’s demographic information (date of birth and gender), that was self reported when he or she signed up for a Yahoo! account. We estimated the geographic location from where each email message was sent using the IP address of the user.”

The authors used data on existing migration rates for a dozen countries and international statistics on Internet diffusion rates by age and gender in order to correct for selection bias. For example, “estimated number of migrants, by age group and gender, is multiplied by a correction factor to adjust for over-representation of more educated and mobile people in groups for which the Internet penetration is low.” The graphs below are estimates of age and gender-specific immigration rates for the Philippines. “The gray area represents the size of the bias correction.” This means that “without any correction for bias, the point estimates would be at the upper end of the gray area.” These methods “correct for the fact that the group of users in the sample, although very large, is not representative of the entire population.”

The results? Ingmar and his co-author Emilio Zagheni were able to “estimate migration rates that are consistent with the ones published by those few countries that compile migration statistics. By using the same method for all geographic regions, we obtained country statistics in a consistent way, and we generated new information for those countries that do not have registration systems in place (e.g., developing countries), or that do not collect data on out-migration (e.g., the United States).” Overall, the study documented a “global trend of increasing mobility,” which is “growing at a faster pace for females than males. The rate of increase for different age groups varies across countries.”

The authors argue that this approach could also be used in the context of “natural” disasters and man-made disasters. In terms of future research, they are interested in evaluating “whether sending a high proportion of e-mail messages to a particular country (which is a proxy for having a strong social network in the country) is related to the decision of actually moving to the country.” Naturally, they are also interested in analyzing Twitter data. “In addition to mobility or migration rates, we could evaluate sentiments pro or against migration for different geographic areas. This would help us understand how sentiments change near an international border or in regions with different migration rates and economic conditions.”

I’m very excited to have Ingmar at QCRI so we can explore these ideas further and in the context of humanitarian and development challenges. I’ve been dis-cussing similar research ideas with my colleagues at UN Global Pulse and there may be a real sweet spot for collaboration here, particularly with the recently launched Pulse Lab in Jakarta.” The possibility of collaborating with my collea-gues at Flowminder could also be really interesting given their important study of population movement following the Haiti Earthquake. In conclusion, I fully share the authors’ sentiment when they highlight the fact that it is “more and more important to develop models for data sharing between private com-panies and the academic world, that allow for both protection of users’ privacy & private companies’ interests, as well as reproducibility in scientific publishing.”

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