Seminar: Exploring global travel data: methodological challenges and substantive insights

DATE
22-01-2019
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TIME
from: 11:00
to: 12:30

As part of the Migration Policy Centre seminar series, Ettore Recchi, MPC part-time professor and professor at Sciences Po, and Emanuel Deutschmann, MPC research associate for the Global Mobilities Project will present on global travel data.

Abstract
Human mobility across national borders is a key phenomenon of our time. At the global scale, however, we still know relatively little about the structure and nature of such transnational movements. In this presentation, we combine insights from two related papers. The first study uses a large dataset on monthly air passenger traffic between 239 countries worldwide from 2010 to 2018 to gain new insights into (a) mobility trends over time and (b) types of mobility. A time series decomposition is used to extract a trend and a seasonal component. The trend component permits (at a higher level of granularity than previous sources) to examine the development of mobility between countries and to test how it is affected by policy and infrastructural changes, economic developments, and violent conflict. The seasonal component allows, by measuring the lag between initial and return motion, to discern different types of mobility, from tourism to seasonal workers’ migration. The result is a unique classification of trends and types of mobility for a global set of country pairs.

In the second study, we create a global dataset of country-to-country cross-border mobility by integrating planet-scale data on tourism (i.e., cross-border travels that include at least an overnight stay) from yearly UN World Tourism Organization statistics and air passenger traffic, based on the data from the first study. The joint use of these two sources allows us to (a) test for their reliability by comparing them, and (b) correct for the weaknesses of both by combining them. The two sources are adjusted and merged following simple procedures. The resulting GMP travel dataset, which covers more than 15 billion estimated trips over the years 2011 to 2016, promises to be a systematic, comprehensive resource on transnational human mobility worldwide.