Abstract
For a country to efficiently monitor international migration, quick access to information on migration flows is helpful. However, traditional data sources fail to provide immediate information on migration flows and do not facilitate the correct anticipation of these flows in the short term. To tackle this issue, this paper evaluates the predictive capacity of big data to estimate the current level or to predict short-term flows. The results show that Google Trends can provide information that reflects the attractiveness of Switzerland for to immigrants from different countries and predict, to some extent, current and future (short-term) migration flows of adults arriving from Spain or Italy. However, the predictions appear not to be satisfactory for other flows (from France and Germany). Additional studies based on alternative approaches are needed to validate or overturn our study results.
Highlights
The emergence of alternative data derived from the operations of internet companies or communication providers as well as individual data from scientific collections has introduced a new era of quantitative research in the social sciences
The objective of this study was to test the usefulness of Google Trends indexes to ‘‘nowcast’’ or forecast migration using a simple model in a context of regular migration
Google Trends provides an index of searches for information on the Swiss labour market, which may differ from actual intention to migrate to/work in Switzerland
Summary
The emergence of alternative data derived from the operations of internet companies or communication providers as well as individual data (or microdata) from scientific collections has introduced a new era of quantitative research in the social sciences. Researchers have progressively gained access to a large amount of data, allowing them to think outside the box, transcend traditional approaches and develop new tools. Individual data (or microdata) gathered using scientific standards are increasingly available (for instance, through the IPUMS project; see Ruggles 2014), which has facilitated the rapid development of (spatial or temporal) comparative studies. Researchers have begun to use other non-traditional or alternative data (mobile phone records, social media, satellite maps, internet-based platforms, commonly called ‘‘big data’’, IOM 2015), to understand migration and mobility in light of new methodological approaches. Scepticism and uncertainty remain regarding the feasibility of using alternative data
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