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Searching for a better life: Predicting international migration with online search keywords

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  • Böhme, Marcus H.
  • Gröger, André
  • Stöhr, Tobias

Abstract

Migration data remains scarce, particularly in the context of developing countries. We demonstrate how geo-referenced online search data can be used to measure migration intentions in origin countries and to predict bilateral migration flows. Our approach provides strong additional predictive power for international migration flows when compared to reference models from the migration and trade literature. We provide evidence, based on survey data, that our measures partly reflect genuine migration intentions and that they outperform any of the established predictors of migration flows in terms of predictive power, especially in the bilateral within dimension. Our findings contribute to the literature by (1) providing a novel way for the measurement of migration intentions, (2) allowing real-time predictions of current migration flows ahead of official statistics, and (3) improving the performance of conventional models of migration flows.

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  • Böhme, Marcus H. & Gröger, André & Stöhr, Tobias, 2020. "Searching for a better life: Predicting international migration with online search keywords," Journal of Development Economics, Elsevier, vol. 142(C).
    • Handle: RePEc:eee:deveco:v:142:y:2020:i:c:s0304387819304900
    DOI: 10.1016/j.jdeveco.2019.04.002
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    Cited by:

    1. Andreea Avramescu & Arkadiusz Wiśniowski, 2021. "Now-casting Romanian migration into the United Kingdom by using Google Search engine data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 45(40), pages 1219-1254.
    2. Karol Król & Dariusz Zdonek, 2023. "Cultural Heritage Topics in Online Queries: A Comparison between English- and Polish-Speaking Internet Users," Sustainability, MDPI, vol. 15(6), pages 1-20, March.
    3. Bert Leysen & Pieter-Paul Verhaeghe, 2023. "Searching for migration: estimating Japanese migration to Europe with Google Trends data," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(5), pages 4603-4631, October.
    4. David H. Kreitmeir & Paul A. Raschky, 2023. "The Unintended Consequences of Censoring Digital Technology - Evidence from Italy's ChatGPT Ban," SoDa Laboratories Working Paper Series 2023-01, Monash University, SoDa Laboratories.
    5. Fuchs, Andreas & Gröger, André & Heidland, Tobias & Wellner, Lukas, 2023. "The effect of foreign aid on migration: Global micro evidence from world bank projects," Kiel Working Papers 2257, Kiel Institute for the World Economy (IfW Kiel).
    6. Roland-Holst, David & Karymshakov, Kamalbek & Sulaimanova, Burulcha & Sultakeev, Kadyrbek, 2022. "ICT, Online Search Behavior, and Remittances: Evidence from the Kyrgyz Republic," ADBI Working Papers 1348, Asian Development Bank Institute.
    7. Konstantin Boss & Andre Groeger & Tobias Heidland & Finja Krueger & Conghan Zheng, 2023. "Forecasting Bilateral Refugee Flows with High-dimensional Data and Machine Learning Techniques," Working Papers 1387, Barcelona School of Economics.

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    More about this item

    Keywords

    International migration; Migration intention; Google trends;
    All these keywords.

    JEL classification:

    • F22 - International Economics - - International Factor Movements and International Business - - - International Migration
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • J61 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Geographic Labor Mobility; Immigrant Workers
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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