Volume 45 - Article 40 | Pages 1219–1254  

Now-casting Romanian migration into the United Kingdom by using Google Search engine data

By Andreea Avramescu, Arkadiusz Wiśniowski

References

Abel, G.J. and Sander, N. (2014). Quantifying global international migration flows. Science 343(6178): 1520–1522.

Weblink:
Download reference:

Afkhami, M., Cormack, L., and Ghoddusi, H. (2017). Google search keywords that best predict energy price volatility. Energy Economics 67: 17–27.

Weblink:
Download reference:

Alexander, M., Polimis, K., and Zagheni, E. (2020). Combining social media and survey data to Nowcast migrant stocks in the United States. Population Research and Policy Review .

Weblink:
Download reference:

Alexander, M., Polimis, K., and Zagheni, E. (2019). The Impact of Hurricane Maria on Out-migration from Puerto Rico: Evidence from Facebook Data. Population and Development Review 45(3): 617–630.

Weblink:
Download reference:

Askitas, N. and Zimmermann, K.F. (2009). Google econometrics and unemployment forecasting. SSRN Electronic Journal .

Weblink:
Download reference:

Azose, J.J. and Raftery, A.E. (2015). Bayesian probabilistic projection of international migration. Demography 52(5): 1627–1650.

Weblink:
Download reference:

BBC (2012). Romania protests: PM Emil Boc calls for dialogue [electronic resource]. British Broadcasting Corporation.

Bijak, J. (2011). Forecasting international migration in Europe: A Bayesian view. The Springer Series on demographic methods and population analysis. Cham: Springer.

Weblink:
Download reference:

Bijak, J. and Czaika, M. (2020). Assessing uncertain migration futures – a typology of the unknown [electronic resource].

Bijak, J., Disney, G., Findlay, A.M., Forster, J.J., Smith, P.W., and Wiśniowski, A. (2019). Assessing time series models for forecasting international migration: Lessons from the United Kingdom. Journal of Forecasting 38(5): 470–487.

Weblink:
Download reference:

Bijak, J. and Wiśniowski, A. (2010). Bayesian forecasting of immigration to selected European countries by using expert knowledge. Journal of the Royal Statistical Society 173(4): 775–796.

Weblink:
Download reference:

Blake, A. (2020). Population and migration statistics system transformation - overview [electronic resource]. Office for National Statistics.

Weblink:
Download reference:

Böhme, M.H., Gröger, A., and Stöhr, T. (2020). Searching for a better life: Predicting international migration with online search keywords. Journal of Development Economics 142: 102347.

Weblink:
Download reference:

Borup, D. and Schütte, E.C.M. (2020). In search of a job: Forecasting employment growth using Google Trends. Journal of Business and Economic Statistics .

Weblink:
Download reference:

Boyd, D. and Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, communication and society 15(5): 662–679.

Weblink:
Download reference:

Cappelen, Å, Skjerpen, T., and Tønnessen, M. (2015). Forecasting immigration in official population projections using an econometric model. International Migration Review 49(4): 945–980.

Weblink:
Download reference:

Cesare, N., Lee, H., McCormick, T., Spiro, E., and Zagheni, E. (2018). Promises and pitfalls of using digital traces for demographic research. Demography 55(5): 1979–1999.

Weblink:
Download reference:

Chan, E.H., Sahai, V., Conrad, C., and Brownstein, J.S. (2011). Using web search query data to monitor Dengue epidemics: A new model for neglected tropical disease surveillance. PLoS Neglected Tropical Diseases 5(5).

Weblink:
Download reference:

Choi, H. and Varian, H. (2012). Predicting the present with Google trends. Economic Record 88: 2–9.

Weblink:
Download reference:

D’Amuri, F. and Marcucci, J. (2017). The predictive power of Google searches in forecasting US unemployment. International Journal of Forecasting 33(4): 801–816.

Weblink:
Download reference:

Dennison, J. and Geddes, A. (2018). Brexit and the perils of ‘Europeanised’ migration. Journal of European Public Policy 25(8): 1137–1153.

Weblink:
Download reference:

Department of Work and Pensions (2020). National insurance number allocations to adult overseas nationals entering the UK to June 2020 [electronic resource].

Weblink:
Download reference:

Dergiades, T., Mavragani, E., and Pan, B. (2018). Google trends and tourists arrivals: Emerging biases and proposed corrections. Tourism Management 66: 108–120.

Weblink:
Download reference:

digi24.ro (2019). Românii sunt uimiți de proiectul care i-ar obliga pe copii să plătească pensii părinților. ‘Chiar lege să dea?’ [electronic resource].

Weblink:
Download reference:

Escobar, A.M. (2012). Bilingualism in Latin America. In: Tej, K.B. and William, C.R. (eds.). The handbook of bilingualism and multilingualism. Hoboken: Blackwell Publishing: 725–744.

Weblink:
Download reference:

Ettredge, M., Gerdes, J., and Karuga, G. (2005). Using web-based search data to predict macroeconomic statistics. Communications of the ACM 48(11): 87–92.

Weblink:
Download reference:

Eurostat (2018). Archive: Internet access and use statistics - households and individuals [electronic resource].

Fatehkia, M., Kashyap, R., and Weber, I. (2018). Using Facebook ad data to track the global digital gender gap. World Development 107: 189–209.

Weblink:
Download reference:

Fiorio, L., Zagheni, E., Abel, G., Hill, J., Pestre, G., Letouzé, E., and Cai, J. (2021). Analyzing the effect of time in migration measurement using Georeferenced Digital Trace Data. Demography 58(1): 51–74.

Weblink:
Download reference:

Fodness, D. and Murray, B. (1998). A typology of tourist information search strategies. Journal of Travel Research 37(2): 108–119.

Weblink:
Download reference:

Fodness, D. and Murray, B. (1997). Tourist information search. Annals of Tourism Research 24(3): 503–523.

Weblink:
Download reference:

Fondeur, Y. and Karamé, F. (2013). Can Google data help predict French youth unemployment? Economic Modelling 30: 117–125.

Weblink:
Download reference:

Galgoczi, B., Leschke, J., and Watt, A. (2011). Intra-EU labour migration: Flows, effects and policy responses.

Weblink:
Download reference:

Gendronneau, C., Wiśniowski, A., Yildiz, D., Zagheni, E., Florio, L., Hsiao, Y., Stepanek, M., Weber, I., Abel, G., and Hoorens, S. (2019). Measuring labour mobility and migration using big data: Exploring the potential of social-media data for measuring EU mobility flows and stocks of EU movers.

Gerland, P., Raftery, A.E., Ševčíková, H., Li, N., Gu, D., Spoorenberg, T., Alkema, L., Fosdick, B.K., Chunn, J., and Lalic, N. (2014). World population stabilization unlikely this century. Science 346(6206): 234–237.

Weblink:
Download reference:

Ginsberg, J., Mohebbi, M.H., Patel, R.S., Brammer, L., Smolinski, M.S., and Brilliant, L. (2009). Detecting influenza epidemics using search engine query data. Nature 457(7232): 10121014.

Weblink:
Download reference:

Gower, M. and Hawkins, O. (2013). Ending of transitional restrictions for Bulgarian and Romanian workers [electronic resource].

Herm, A. (2010). Country report Romania. PROMINSTAT: Promoting Comparative Quantitative Research in the Field of Migration and Integration in Europe.

Hughes, C., Zagheni, E., Abel, G.J., Wiśniowski, A., Sorichetta, A., Weber, I., and Tatem, A. (2016). Inferring migrations: Traditional methods and new approaches based on mobile phone, social media, and other big data: Feasibility study on inferring (labour) mobility and migration in the European Union from big data and social media data. Tech. rep., European Commission.

James, M. (2014). International migration of Romania [electronic resource]. Office for National Statistics.

Weblink:
Download reference:

James, M. (2021). International migration: developing our approach for producing admin-based migration estimates, April 2021 release. Office for National Statistics .

Weblink:
Download reference:

James, M. (2020). Long-term international migration estimates methodology [electronic resource]. Office for National Statistics.

Weblink:
Download reference:

Jansen, B.J., Ciamacca, C.C., and Spink, A. (2008). An analysis of travel information searching on the web. Information Technology and Tourism 10(2): 101–118.

Weblink:
Download reference:

Jordan, B. (2019). Mobility and Migration. In: Jordan, B. (ed.). Authoritarianism and how to counter it. Cham: Palgrave Macmillan: 51–62.

Weblink:
Download reference:

Klugman, J. (2009). Human development report. Tech. rep., United Nations Development Programme.

Weblink:
Download reference:

Kristoufek, L. (2013). BitCoin meets Google trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era. Scientific Reports 3(1).

Weblink:
Download reference:

Lazer, D., Kennedy, R., King, G., and Vespignani, A. (2014). The parable of Google flu: Traps in big data analysis. Science 343(6176): 1203–1205.

Weblink:
Download reference:

Li, X., Pan, B., Law, R., and Huang, X. (2017). Forecasting tourism demand with composite search index. Tourism Management 59: 57–66.

Weblink:
Download reference:

Maitland, C. and Xu, Y. (2015). A social informatics analysis of refugee mobile phone use: a case study of Zaaatari Syrian refugee camp. SSRN Electronic Journal .

Weblink:
Download reference:

Massey, D.S. (2003). Patterns and processes of international migration in the 21st century. Paper presented at the Conference on African Migration in Comparative Perspective, Johannesburg, South Africa.

Weblink:
Download reference:

Massicotte, P. and Eddelbuettel, D. (2020). gtrendsR: Perform and display Google trends queries [electronic resource].

Weblink:
Download reference:

McAuliffe, M. (2018). The link between migration and technology is not what you think [electronic resource].

Mohebbi, M., Vanderkam, D., Kodysh, J., Schonberger, R., Choi, H., and Kumar, S. (2011). Google Correlate Whitepaper [electronic resource].

Onder, I. and Gunter, U. (2016). Forecasting tourism demand with Google trends for a major European city destination. Tourism Analysis 21(2–3): 203–220.

Weblink:
Download reference:

Palotti, J., Adler, N., Morales-Guzman, A., Villaveces, J., Sekara, V., Garcia Herranz, M., Al-Asad, M., and Weber, I. (2020). Monitoring of the Venezuelan exodus through Facebook’s advertising platform. Plos One 15(2): 0229175.

Weblink:
Download reference:

Parkins, N.C. (2010). Push and pull factors of migration. American Review of Political Economy 8(2): 6–24 (Accessed 14/09/2021.).

Download reference:

Popa, D. (2019). Legea recunoştinţei între generaţii: În ce țări mai există și cum funcționează [electronic resource].

Weblink:
Download reference:

Preis, T., Moat, H.S., and Stanley, H.E. (2013). Quantifying trading behavior in financial markets using Google trends. Scientific Reports 3(1).

Weblink:
Download reference:

R. Core Team (2020). R: A Language and Environment for Statistical Computing [electronic resource]. Vienna: R Foundation for Statistical Computing.

Weblink:
Download reference:

Rango, M. and Vespe, M. (2017). Big data and alternative data sources on migration: From case-studies to policy support. Joint Research Centre (JRC), Summary report, European Commission.

Raymer, J., Rees, P., and Blake, A. (2015). Frameworks for guiding the development and improvement of population statistics in the United Kingdom. Journal of Official Statistics 31(4): 699–722.

Weblink:
Download reference:

Raymer, J., Wiśniowski, A., Forster, J.J., Smith, P.W., and Bijak, J. (2013). Integrated modeling of European migration. Journal of the American Statistical Association 108(503): 801–819.

Weblink:
Download reference:

Righi, A. (2019). Assessing migration through social media: a review. Mathematical Population Studies 26(2): 80–91.

Weblink:
Download reference:

Sagiroglu, S. and Sinanc, D. (2013). Big data: A review. Paper presented at the 2013 International Conference on Collaboration Technologies and Systems (CTS).

Weblink:
Download reference:

Sarigul, S. and Rui, H. (2014). Nowcasting obesity in the US using Google search volume data. Western Coordinating Committee on Agribusiness, Tech. Rep. 327-2016-12719.

Weblink:
Download reference:

Sides, J. and Citrin, J. (2007). European opinion about immigration: The role of identities, interests and information. British Journal of Political Science 37(3): 477–504.

Weblink:
Download reference:

Siliverstovs, B. and Wochner, D.S. (2018). Google trends and reality: Do the proportions match? Appraising the informational value of online search behavior: Evidence from Swiss tourism regions. Journal of Economic Behavior and Organization 145: 1–23.

Weblink:
Download reference:

Sjaastad, L.A. (1962). The costs and returns of human migration. Journal of Political Economy 70(5, Part 2): 80–93.

Weblink:
Download reference:

Stan Development Team (2020). Stan modeling language users guide and reference manual, 2.25 [electronic resource].

Weblink:
Download reference:

StatCounter (2019). Search engine market share Romania [electronic resource].

StatCounter (2019). Search engine market share Worldwide [electronic resource].

Taylor, L. (2016). The ethics of big data as a public good: Which public? Whose good? SSRN Electronic Journal .

Weblink:
Download reference:

Thorvaldsen, G. (2019). Censuses and census takers: A global history. Oxon: Routledge.

Download reference:

Tirosh, N. and Schejter, A. (2017). Information is like your daily bread’: The role of media and telecommunications in the life of refugees in Israel. Hagira—Israel Journal of Migration 7: 1–25 (Accessed 10/01/2021.).

Download reference:

UN (2014). Estimating migration flows using online search data - UN Global Pulse. Global Pulse Project Series 4 (Accessed 09/09/2021.).

Download reference:

Vargas-Silva, C. and Rienzo, C. (2020). Migrants in the UK: An overview. Migration Observatory Briefing .

Weblink:
Download reference:

Vlastakis, N. and Markellos, R.N. (2012). Information demand and stock market volatility. SSRN Electronic Journal .

Weblink:
Download reference:

Wanner, P. (2020). How well can we estimate immigration trends using Google data? Quality and Quantity 55: 1181–1202.

Weblink:
Download reference:

Wilde, J., Chen, W., and Lohmann, S. (2020). COVID-19 and the future of US fertility: What can we learn from Google? IZA Discussion Paper Series 13776.

Weblink:
Download reference:

Willekens, F. (2019). Evidence-based monitoring of international migration flows in Europe. Journal of Official Statistics 35(1): 231–277.

Weblink:
Download reference:

Willekens, F. (1994). Monitoring international migration flows in Europe. European Journal of Population/Revue européenne de Démographie 10(1): 1–42.

Download reference:

Willekens, F., Massey, D., Raymer, J., and Beauchemin, C. (2016). International migration under the microscope. Science 352(6288): 897–899.

Weblink:
Download reference:

Wladyka, D. (2017). Queries to Google search as predictors of migration flows from Latin America to Spain. Journal of Population and Social Studies 25(4): 312–327.

Weblink:
Download reference:

Yu, L., Zhao, Y., Tang, L., and Yang, Z. (2019). Online big data-driven oil consumption forecasting with Google trends. International Journal of Forecasting 35(1): 213–223.

Weblink:
Download reference:

Zagheni, E. and Weber, I. (2012). You are where you e-mail. Paper presented at the Proceedings of the 3rd Annual ACM Web Science Conference on - WebSci 12.

Weblink:
Download reference:

Zagheni, E., Weber, I., and Gummadi, K. (2017). Leveraging Facebook advertising platform to monitor stocks of migrants. Population and Development Review 43(4): 721–734.

Weblink:
Download reference:

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