1. The Future of International Migration: A Scenario Approach 14 September 2011 1 International Migration Institute Oxford Department of International Development Oxford Martin School University of Oxford Simona Vezzoli Simona.vezzoli@qeh.ox.ac.uk

2. International migration in the present Despite being a “top issue”, debates and policies on migration o Tend to be short-term and reactive to political concerns and perceived ‘migration crises’ o Reveal a limited understanding of the complex drivers of migration processes Symptom: Potentially unintended and perverse effects of migration policies. 14 September 20112

3. International migration in the future We cannot just assume continuation of current trends (e.g., forecasting) Future social, economic and political change will fundamentally affect global migration, but how? Both research and policy are ill-prepared Overall lack of long-term vision and imagination on how the future of migration might look like 14 September 20113

4. Global Migration Futures project Aims: o To gain insights in possible future (regional and global) migration trends and their effects on receiving, transit and sending countries... o... through the elaboration of scenarios, taking into account future social, economic, political, demographic, technological and environmental change that might affect migration 14 September 20114

5. Studying the future 5 14 September 2011 Reliance on data and statistical analysis Models helps us understand the ‘chaos’ that surrounds us A model which has been tested in the past is extended to predict the future

6. Using forecasting models: an example Dustmann et al. (2003), a report commissioned by the Home Office to forecast net immigration from the AC10 to the UK after the enlargement of the EU: o Estimations were based on rather high population growth rates in the AC10 o Net immigration to the UK from the AC10 will be ‘relatively small at between 5,000 and 13,000 immigrants per year up to 2010.’ Two baseline projections: baseline model 1 = 4,872; baseline model 2 = 12,568 o The UK opened its labour markets to the AC10 countries on May 1, 2004 6 14 September 2011

7. Flows estimates to September 2009 14 September 20117 Even with a relatively sound estimation they missed the actual number dramatically

8. Why can a sound model deliver poor estimates? 14 September 20118 Five main reasons: o The same structure is applied across countries o The same structure is applied across time o Explanatory variables must themselves be forecasted o Complex levels of impacts and feedback o Even when data are not a problem, there are uncertainties, which models are unable to incorporate

9. Structures across countries In many cases the data don’t exist and the parameters of the model must be estimated using historical migration data for other countries This implies the assumption that we can apply the same structure across countries 14 September 20119 Country A Country B

10. Structures across time We assume that the structure of our model remains the same across time. However, will the relationship between migration and its main determinants be the same in the future? 14 September 201110 Country A 201019602050

11. Explanatory variables in sending and receiving countries 14 September 201111 Models require explanatory variables, which are not always available When available, these variables must be forecasted for the entire prediction period

12. Complex levels of impacts and feedback 14 September 201112 Contextual Environment (‘external factors’) Demographics Macroeconomic policies of the host countries Global economy Oil prices Social values Technology Geo-political trendsEnvironmental change Local policies Development Migration flows ‘internal factors’ Interest groups Media Migration policies

13. Two major uncertainties: Migration = f (y host, y home, networks, policy, natural disasters…) Model uncertainties, which are comprised of the insufficient understanding of the mechanisms that operate in the migration process. Contextual uncertainties, which are found in the constantly changing environment in which migration occurs. Even with certain data, when we look at the future we have uncertainties Uncertainties

14. Known facts 14 September 201114 Forecasting assumes that it is possible to predict the future Yet, data are limited, severely constraining the usefulness of models Model uncertainties are numerous o What are the determinants of migration today? What will they be in the future? Non-migration (contextual) uncertainties abound o What will the world look like in the future? How will the determinants of migration change in the future?

15. The power of numbers 14 September 201115 Diverging Scenarios Converging Scenarios

16. Scenarios: what are they NOT? A forecast or projection of today into the future An alternative specification of the forecasting model RATHER, THEY ARE visualisations of possible futures that we do not necessarily expect to come true 14 September 201116

17. Scenarios’ characteristics Stories created using multiple perspectives on: o What has happened in the past o What we know today o What could possibly develop in the future The stories must be: o Plausible o Coherent o Challenging our expectations Scenarios neither represent a perfect world, nor an apocalyptic world – they are a mix of positive and negative events and outcomes that do not simply reproduce the status quo 14 September 201117

18. Benefits of scenarios Scenarios offer techniques to develop a better understanding of migration processes o Intuitive method that encourages the ‘break down of mental barriers’ and promotes a stimulating and creative process o Identification of the ‘germs of change’ or ‘weak signals’ Key role of multiple stakeholders o Awareness that knowledge of migration is available in many segments of society o Multiple stakeholders bring various experiences and perspectives from different sectors (i.e. business, government, academia and civil society), disciplines and backgrounds The process is as important as the outcome 14 September 201118

19. Creating a new framework Uncover assumptions that shape our way of thinking (mental maps) RELATIVE CERTAINTIES o Factors that we strongly believe will not change and be relevant in our scenarios E.g. French will be the official language in France in 2020; Mexico and the US will share a border in 2035 RELATIVE UNCERTAINTIES o Factors for which we have more than one possible outcome and which are relevant to our scenarios E.g. The EU will have a common immigration policy in 2025; in 2035 Spain and Morocco will share a land border (Ceuta and Melilla) 14 September 201119

20. Overview of scenario production framework 14 September 201120 Time Present situation of the context Past events & forces shaping the present Plausible scenarios Slide’s author: Rafael Ramirez

21. Scenarios and feedback processes Evolution of the story over time Forces and events influence each other Using logic and intuition, scenarios are tested for coherence and consistency 14 September 201121 Increased mobility within North Africa and from Sub-Saharan Africa Xenophobia increases Introduction of point-system immigration policy Investment in various economic sectors, need for high-skilled workers High economic grown in North Africa (oil resources) is accompanied with high political instability North Africa is a destination of highly-skilled + Increased inequality in society Continuing emigration to Europe and the Gulf