The Commission’s plan for reforming EU asylum policy is very ambitious. But can it work?

Note: A 3,000-word analysis of reform plans that are probably never gonna see the light of day anyways, based on simple arithmetics and not-so-simple simulations. Also, an excuse to do graphs. Re-posted from Eurosearch

 

The European Commission announced last Wednesday a new package of proposals designed to reform the EU asylum system. The proposals include compulsory redistribution of asylum applications among the EU member states. This is called ‘corrective allocation mechanism’ or ‘fairness mechanism’.

Countries would be allocated ‘reference shares’ of asylum applications, and the moment a country’s reference share is exceeded by 50%, an automatic system will set it that will send the excess asylum applicants to countries that have not attained their reference shares yet. If member states do not cooperate, they will have to pay a ‘solidarity contribution’ of €250,000 for every asylum application they refuse to process.

The proposal for compulsory redistribution backed by the threat of financial penalties (sorry, solidarity contributions) is very ambitious. But can it work? And I mean, can it work in a strictly technical sense, provided that the EU musters the political support to adopt the proposals[1], manages to make the member states comply with the rules, ensures that they don’t game the national asylum statistics, and so on – additional problems that are by no means trivial to solve. Let’s also leave aside for the moment the normative issue whether such a compulsory redistribution system is fair, to asylum seekers and to the EU member states. For now, the simpler question – can the system work even in the best of political and bureaucratic circumstances?

How is the system supposed to work?

This is how the system is supposed to work, or at least how I think it’s supposed to work, based on the available explanations (see here, here, here and the actual draft regulation here):

(1) Each country gets a ‘reference key’ based on the relative size of its population and the relative size of its GDP (the two factors weighted equally) compared to the EU totals. For example, in 2014 Germany had a population of 81,174,000 (16% of the EU population of 508,191,116) and a GDP of €2,915,650 million (21% of the EU GDP of €13,959,741 million[2]), which, when combined, make up for a reference key of 18.5%.

(2) This reference key is translated into reference shares (indicative shares of the total number of asylum applications[3] made in the EU that each member state is expected to receive) by multiplying the reference key with the total numbers of asylum applications registered in the EU in the preceding 12 months. For example, according to Eurostat[4], between 1 January 2014 and 31 December 2014 the total number of asylum applications received in the EU was 653,885, so Germany’s reference share for January 2015 (covering the period 1 February 2014 – 31 January 2015) would be 18.5% of 653,885 which equals 120,969 applications.

(3) If a member state receives a number of applications that exceeds by 50% its reference share, the excess applications are to be redistributed to member states that have not attained their reference shares yet. For example, Germany would have to receive more than 181,453 (150% of 120,969) applications during the current and preceding 11 months to trigger the relocation mechanism.

(4) The reference totals and references shares are updated constantly and automatically.

How would the system work if it had to be implemented at the end of 2015 already?

Let’s first do the simple arithmetics to see how the system would work if it had to enter into force in the last month of 2015. We can plug in the total number of asylum applications registered in the preceding 12 months (hence, between 1 December 2014 and 30 November 2015) to calculate the country’s reference shares. We can then see who did more and who did less than their fair (reference) share, and we can estimate the number of transfers that would be necessary to balance the system.

According to Eurostat, the total number of asylum applications received in the reference period was 1,281,560, so this number is used in the calculations that follow. The figure below shows the reference shares (in black), 150% of the reference shares (in grey) and the actual numbers of applications received during the entire 2015 (in red). We can see that Hungary, Sweden, Germany, Austria, Finland, Bulgaria, and Cyprus would have exceeded 150% of their reference shares. And between them they would have had 449,821 ‘excess’ applications for redistribution. All the other member states are potential recipients (with the exception of Belgium, Denmark, and Malta which have received numbers of applications exceeding their reference shares but with less than 50%). The total number of available ‘slots’ for transfer is 592,469. The UK has 145,750, France has 106,227, Spain has 91,589, Italy has 67,689, Poland has 54,456, and so on. Even Greece would have to accept 8,577 more applications to achieve its fair share of registered asylum applications[5].

asylum_application_and quotas12

To sum up, if the ‘fairness mechanism’ was to enter into force in December 2015, it would require the relocation of almost half a million asylum seekers across the continent, with some member states having to receive more than 100,000 additional applications to balance the system. More than one-third of all applications received in the EU during the preceding 12 months would have to be relocated.

If the UK[6], for example, would refuse to accept the additional asylum applications to fill up its reference share, it would be expected to pay ‘solidarity contributions’ to a maximum of €36,437,500,000 (more than 36 billion euros). (For comparison, the total gross UK contribution to the EU budget in 2015 was around €16 billion). The total pool of asylum applications to be relocated would be worth  €112,455,250,000 (that is, more than 112 billion euros)! For comparison, the total budget of the EU for 2015 was € 141.2 billion.

To my mind, the scale of the potential fines (sorry, ‘solidarity contributions’) is so big as to make their application totally unrealistic. Of course, it is the threat of fines that is supposed to make the member states cooperate, but to do their work, fines still have to realistic enough.

To sum up the argument so far, things don’t look very bright for the solidarity mechanism. But one might object that 2015 was exceptional, and that it is precisely this type of imbalances observed at the end of 2015 that the fairness mechanism is designed to avoid. Yet, unless the system starts with a clean slate[7], the existing imbalances accumulated over the past months would have to be corrected somehow. The analysis above shows the enormous scale of the corrections needed, if the system would have entered into force five months ago.

How would the system handle the 2015 flow of asylum applications?

We can also try to simulate how the fairness mechanism with compulsory reallocation would have handled the flow of asylum applications that the EU experienced during 2015 (provided that the member states cooperated fully). That is, we start with the situation as observed in January 2015, we calculate the reference shares and apply the necessary transfers to balance the system, and then we move forward to February 2015 observing the actual numbers of applications received in reality, balance the system again with the necessary transfers, and so on until the end of the year. (The script for the analysis and the simulation (in R) is available upon request.)

Running the simulation for the entire course of 2015 delivers good news and bad news (for the architects of the proposed mechanism). The good news is that the redistribution system does not get ‘choked up’ – that is, it does not run out of capacity to redistribute asylum applications received by some member states in excess of 150% of their reference shares to member states that have yet to reach their reference shares. The bad news is that in order to get and stay balanced, the system applying the ‘fairness mechanism’ needs to make approximately 500,000 transfers (that makes 37% of all asylum applications received in the EU during the year).

The figure below shows the number of transfers (in black) that need to be made per month, together with the actual number of asylum applications received in the EU as a whole during this period (in grey). Approximately 157,000 transfers must be made in the first month of the simulation (January 2015) to balance the system initially, and the remaining 343,000 are needed to keep it in balance for the rest of the year. The peak is in August, when more than 50,000 transfers must be made. (The bars are not stacked upon each other but overlap).

asylum_application_transfersmonthly2015

The next figure shows the distribution of transfers per member state. The blue bars that go below the horizontal line at zero indicate that the member state is a net ‘exporter’ of asylum applications, and the red ones that rise above the zero line indicate that the member state is a net receiver of transferred applications during the year, according to the simulation. (The parts of the bars colored in light blue and light red show the transfers made in the first month of the simulation.)

It is clear from the figure that Hungary, Sweden, Germany and Austria export the greatest number of applications, while Poland, Italy, Spain, France and the UK are expected to receive the most transfers. Some countries actually change their status in the course of the year from exporters to receivers of additional asylum applications (Denmark) and vice versa (Finland). Even Sweden and Hungary – countries that are big net exporters for most of the year have to receive additional applications during one or two months (see here the detailed plot of the experience of individual countries over the 12 months of the simulation).asylum_application_transfers2015

Despite the huge amount of transfers, not all member states handle a completely proportional burden of the total EU pool of asylum applications throughout the year. While the monthly transfers correct for gross imbalances and ensure that no country deals with more than 150% of its reference share, the system still leaves potential for significant differences across the member states. The figure below demonstrates this fact by showing the simulated number of asylum applications in red (actual applications received and simulated transfers) and the references shares (in black and grey). While the two sets of bars are much closer now, and the red one does not exceed the grey one for any country, member states still vary from fulfilling 70% of their reference shares (for example, Croatia, Portugal, Romania, and Slovakia) to fulfilling close to 150% of their reference shares (Germany, Belgium and Austria).[8]

asylum_application_sims_and quotas

Conclusions

To sum up, the proposed compulsory redistribution of asylum applications among the EU member states can reduce the current imbalances, but only at the price of a huge amount of transfers between the member states. With the proposed parameters, the mechanism would be able to handle even a great influx of asylum seekers as the one observed during 2015. However, under the 2015 scenario, half a million applications would have to be redistributed to make it work. An enormous amount of transfers between member states would be necessary to balance the system initially (unless the mechanism starts with a clean slate), and as many as 50,000 applications per month might have to be redistributed later (under a scenario similar to the one that actually occurred in 2015).

The reference period of 12 months used for calculating the countries’ reference shares must be updated and moved forward every month to ensure that the system retains enough capacity for redistribution. Otherwise, the ‘cushion’ provided by the fact that countries only export applications once they receive 50% more than their reference shares might not be enough to guarantee that there are enough ‘free slots’ in other member states. For the reference period to be updated fast, reliable and almost instantaneous information about the flows of asylum seekers to all member states must be available. Currently, the latest month for which Eurostat has data on the asylum applications received in all EU member states is December 2015: that is,  at the moment, the reference shares can be updated with at least a 4-month lag. This might be too slow to accommodate the rapidly changing flows of asylum seekers to Europe and might quickly grind the fairness mechanism to a halt.

The disadvantage of a relatively short reference period of 12 month that is constantly updated is that some member states might have to receive transferred applications at one point of time and then be eligible to redistribute applications to other countries just a few months afterwards. Such moving around of asylum seekers across the continent is of course highly undesirable, and costly as well.

Although the system might be able to correct the gross imbalances, it might still allow significant differences in the asylum application burden that different EU countries carry to persist. This fact requires attention to the way the ‘excess’ applications are to be distributed among the eligible member states that have not achieved their reference shares yet (since, typically there will be more available slots than requests for redistribution).

Finally, given the scale of required transfers to make the fairness mechanisms work, the size of the proposed penalties (solidarity contributions) for refusing additional applications is so huge as to be completely unrealistic. If under this mechanism member states are potentially liable for amounts that exceed their total annual contributions to the EU budget, there is little chance they will agree to participate in the mechanism in the first place.

All in all, while in principle the proposed fairness mechanism can work to reduce significantly the imbalances in the distribution of asylum applications across the EU, once the member states realize the amount of additional applications they might have to deal with under this policy, it is highly unlikely they will approve it. And certainly not with the current parameters regarding the reference periods, the references shares or the financial penalties.

Notes

[1] The Polish foreign minister already called the proposals an ‘April Fool’s Day joke.’

[2] The population and GDP estimates are based on statistics provided by Eurostat. GDP is in current prices and comes from the ‘tec00001’ database, in particular.

[3] In addition to asylum applications, the system will also take in to account the number of resettled persons. Eurostat however does not provide monthly data on resettlement. And the (annual) numbers of resettlements relative to asylum applications are so low (less than 1%) that we can ignore them in the analysis without much harm.

[4] The monthly statistics on asylum applications are available in the ‘migr_asyappctzm’ database. The version used in the analysis has been last updated on 6  May 2016

[5] Wait, what? Greece would have to receive more asylum applications? That’s right. Although hundreds of thousands (if not millions) of migrants have arrived on Greek territory in the past year and a half, in 2015 the Greek state has registered as asylum seekers only a negligible proportion of them. So, according to the official statistics (that would be used to run the fairness asylum distribution mechanism), Greece would have to register more applications and would be eligible to receive transfers from other member states until it reaches its fair share. I will leave it to you to judge whether this is a feature or a bug of the proposed system.

[6] The UK and Ireland, by the way, are invited but are not required to join the proposed system, even if the rest of the member states approve it.

[7] From the available documents, it does not seem to be the case that the fairness mechanisms will start with a clean state; that is, with a reference period not extending 12 months back.

[8] Curiously, Hungary appears to have made more transfers than actual applications received during the year according to the simulation, due to the huge fluctuations in the monthly amount of applications registered (which average 20,000 in the first 9 months of the year, but then drop to less than a thousand in the last three) and the moving reference period for calculating the reference shares.

Key numbers

COUNTRY
CODE
REFERENCE KEY
ASYLUM APPLICATIONS 2015
REFERENCE
SHARES FOR
2015
EXCESS/DEFICIT FROM REFERENCE SHARES FOR 2015
EXCESS/DEFICIT FROM 150% OF REFERENCE SHARES FOR 2015
TRANSFERS TO BE
MADE IN THE COURSE OF
2015 (SIMULATION)
Austria AT 2,0% 88.160 25.631 62.529 49.713 -51.796
Belgium BE 2,5% 44.665 32.039 12.626 -3.393 0
Bulgaria BG 0,9% 20.375 11.534 8.841 3.074 -4.676
Croatia HR 0,6% 205 7.689 -7.484 -11.329 5.510
Cyprus CY 0,1% 2.265 1.282 983 343 -850
Czechia CZ 1,6% 1.515 20.505 -18.990 -29.242 14.694
Denmark DK 1,5% 20.940 19.223 1.717 -7.895 1.159
Estonia EE 0,2% 230 2.563 -2.333 -3.615 1.838
Finland FI 1,3% 32.345 16.660 15.685 7.355 -9.319
France FR 14,2% 75.755 181.982 -106.227 -197.217 94.098
Germany DE 18,4% 476.510 235.807 240.703 122.799 -120.770
Great Britain (UK) GB 14,4% 38.795 184.545 -145.750 -238.022 127.292
Greece GR 1,7% 13.210 21.787 -8.577 -19.470 7.408
Hungary HU 1,3% 177.130 16.660 160.470 152.140 -184.043
Ireland IE 1,1% 3.270 14.097 -10.827 -17.876 9.674
Italy IT 11,8% 83.535 151.224 -67.689 -143.301 56.460
Latvia LV 0,3% 335 3.845 -3.510 -5.432 2.756
Lithuania LT 0,4% 320 5.126 -4.806 -7.369 3.674
Luxembourg LU 0,2% 2.505 2.563 -58 -1.340 431
Malta MT 0,1% 1.850 1.282 568 -72 -519
The Netherlands NL 4,0% 44.975 51.262 -6.287 -31.919 9.498
Poland PL 5,2% 12.185 66.641 -54.456 -87.777 47.751
Portugal PT 1,6% 900 20.505 -19.605 -29.857 14.694
Romania RO 2,5% 1.255 32.039 -30.784 -46.803 22.958
Slovakia SK 0,8% 325 10.252 -9.927 -15.054 7.345
Slovenia SI 0,3% 275 3.845 -3.570 -5.492 2.756
Spain ES 8,3% 14.780 106.369 -91.589 -144.774 76.221
Sweden SE 2,5% 162.455 32.039 130.416 114.397 -134.256

 

5 simple things to know about asylum policy in the European Union

Migration is quickly turning into the defining issue of our time. This might sound cliché, but is true. Not only does migration top the list of most important problems facing society, but it is also divisive in a way no other issue is. Unlike problems like inequality or the environment, immigration polarizes and divides opinions of ordinary people in a manner that cuts through social classes, education levels, age groups, and political affiliations. Divisions and bitter disagreements run even within families and close circles of friends. For no other issue do I see on my Facebook wall the full gamut of opinions ranging from strong rejection of migrants and refugees to their unconditional welcome and embrace. Most opinions of course fall somewhere in-between expressing, for example, support for `genuine’ refugees fleeing war but not for economic migrants, or for Christian but not for Muslim immigrants; yet, deep and important disagreements remain.

The current crisis with the influx of hundreds-of-thousands asylum-seekers in Europe in the summer of 2015 is only but the current episode of the unfolding migration drama. The crisis and the political responses to it bring powerful emotions in people: fear and compassion, anger and humility, empathy and contempt. Together with polarization, emotions further cloud the discussion of asylum policies and the right thing for the European countries to do in this situation. In response, I want to share five simple things I happen to know about asylum policies in the EU. I am by no means a specialist on the legal aspects of asylum or migration law. My expertise comes from two rather technical policy studies I have conducted on the aggregate patterns of asylum applications and country refugee recognition rates over the last decade, and on their relationships with the broader social and political contexts. (see here and here for the academic articles and here for a blogpost and visualization based on them)

1) The asylum policies of the countries members of the European Union still differ a lot. Despite a considerable body of EU legislation harmonizing national asylum policies, in effect these national policies have not converged to a common set of standards and rules. The differences concern the handling of asylum application procedures (e.g. their duration), the actual support provided by the state to the applicants during the procedure, the quality of the reception facilities, the rights and privileges gained after (and if) a refugee status is granted, the forms of alternative protection if a refugee status is not granted, and what happens to those who are refused any protection. Most importantly of all, however, the EU member states differ significantly with respect to their recognition rates (the share of applications that are granted the refugee status) even for applicants from the same country of origin. By implication, this means that different states apply rather different criteria when assessing the asylum applications.
These differences are crucial to understand why a joint common EU asylum application center does not seem politically feasible at the moment and is not even being discussed as an option to respond to the current crisis. Until such considerable differences exist, a truly single European policy on asylum would remain out of sight.

2) The strictness of national policies towards asylum-seekers matter relatively little for the asylum flows they receive. You can think that by tightening their asylum policies – making reception conditions worse, reducing support during the application and after, or lowering the recognition rate, countries can lessen the asylum application burden that they face. But in fact asylum flows tend to be relatively insensitive and unresponsive, at least in the short and medium terms, to the strictness of national asylum policies and to how low or high the national recognition rates are. So manipulating national policy is not an effective tool to divert (or attract) asylum application flows. The same goes for the effect of current economic conditions or the political climate in a country (for example, whether there is broad public and party support or opposition to migrants). Asylum flows are directed to a large degree by geographical convenience and existing transit networks, by hearsay and stereotypes to be affected by the details of national asylum policies or recognition rates. The implication of all that is that no single country can unilaterally isolate itself from the asylum flows coming to Europe. That being said, because asylum flows are highly clustered (see below), not being on what is at the moment the most convenient route to Western and Northern Europe can dramatically affect the number of asylum-seekers that pass through or end up in your country.

3) Asylum-seekers from the same nationality or region tend to cluster in particular places. Not only do asylum-seekers from the same region or country tend to travel on the same routes employing the same networks and middlemen, but they also tend to cluster when and where they choose a place to lodge an application and where they settle if allowed. These points are quite intuitive. Extended family ties and networks provide for crucial information about handling the asylum-application process and about the living and working conditions in the host country and city. They also provide support and protection, etc. So no wonder that new asylum-seekers and refugees try to go to where they family and friends already are.
What is important to recognize, however, are the not so obvious policy implications of the fact that asylum-seekers and refugees cluster in space. Because migrants would tend to congregate in few places, these places would be subject to a much greater asylum burden than others. This goes for countries, but also for cities and regions within countries.
That is why countries are reluctant to let asylum-seekers and refugees settle wherever they wish in the EU. Otherwise, the fear is that because of the attracting power of existing networks of relatives and compatriots, very few places will have to deal with the challenges of supporting and integrating a great proportion of the refugees. The call for mandatory country (and existing regional within-country) quotas are partly responding to these expectations.

4) Even when recognized as such, refugees do not enjoy a freedom of movement in the EU. As mentioned above, refugees (and asylum-seekers) are not allowed to move, reside and work freely within the EU, unlike citizens of its member states. Even though recognized refugees might have the rights to work and live in the country that has recognized their status and even benefit from the national social protection policies, they cannot choose to relocate to another member states. This is important in order to understand why it is so crucial for the asylum-seekers to reach the desired place in Europe before they lodge an application.
But it is also important to understand why the compulsory re-settlement based on country quotas that the European Commission proposes would likely not work. Even if adopted by the Council (which at the moment seems rather unlikely), the scheme would run into troubles the moment the refugees try to skip their imposed host countries and go to where their family and support networks are. And they will. The resettlement quote scheme would then have to be coupled with measures like compulsory self-reporting or tagging that would allow for tracing the location of refugees and asylum seekers. Such measures would not only by expensive, but morally objectionable as well.

5) Even when their requests for asylum are rejected, asylum seekers often stay in Europe. This is the dirty little secret of asylum policy in Europe. Even when an asylum application has been rejected, and even when other forms of alternative protection are not granted, the migrants are rarely sent back to their country of origin. They either disappear into illegality but never leave the continent or exist in a para-legal limbo where their presence is tolerated but no support is provided. European countries differ in the extent to which they allow this to happen, and it is hard to get precise numbers about the scale of the problem, but it is in any case huge. Alternatives are, however, hard to find as locating and sending people back to their country of origin is expensive, often impossible if the migrants lack proper documents, and, many would argue, morally objectionable. But this fact undermines the idea that asylum-seekers are a special group of migrants who are only allowed to stay in the country if they face serious threats for their lives and dignity at home. If those who are rejected are allowed or tolerated to stay anyways, the difference between an asylum-seeker and a migrant motivated by economic or other reasons is much hard to draw in the public mind. Note that I am not saying that people migrating for reasons others than fleeing wars and persecution should not be welcomed; only that many people have different attitudes and policy preferences with respect to different groups of migrants, and that blurring the boundaries between the groups can have negative consequences for people’s selective support of particular groups, like refugees.

 All in all, none of these five points suggest a comprehensive solution to the current asylum crisis or point to a clear way forward. What they do, hopefully, is to outline some of the facts and constraints that those in power must have in mind when designing responses to the situation and some arguments with which the judge existing proposals.

To put my cards on the table, I currently think that a combination of three policies can be preferable to the current system and to existing proposals:

  • A centralized single EU-managed system of asylum application centers at places along (and perhaps even outside) the borders of the EU, financed by the EU budged and staffed by European civil servants (support for the regions where the application centers are located would be needed to handle the flow of asylum-seekers during the time their applications are being assessed);
  • Free movement for recognized asylum seekers within the continent. This should include the rights to move, settle, and work, but not necessarily access to the social systems of the host countries. Places where refugees happen to cluster disproportionately would get support from a pot to which all countries contribute.
  • Strict control of the external borders of the EU to channel the applications through the official centers and strict `no access’ policy for people denied asylum or alternative forms of protection.

This would represent a rather drastic change from the system currently in place so it probably has low political feasibility. At the same time, current proposals do not seem to fare much better in the EU decision-making bodies, so the scale of required changes should be no reason to disregard the ideas.

Visualizing asylum statistics

Note: of potential interest to R users for the dynamic Google chart generated via googleVis in R and discussed towards the end of the post. Here you can go directly to the graph.

02alessandro-penso
An emergency refugee center, opened in September 2013 in an abandoned school in Sofia, Bulgaria. Photo by Alessandro Penso, Italy, OnOff Picture. First prize at World Press Photo 2013 in the category General News (Single).

The tragic lives of asylum-seekers make for moving stories and powerful photos. When individual tragedies are aggregated into abstract statistics, the message gets harder to sell. Yet, statistics are arguably more relevant for policy and provide for a deeper understanding, if not as much empathy, than individual stories. In this post, I will offer a few graphs that present some of the major trends and patterns in the numbers of asylum applications and asylum recognition rates in Europe over the last twelve years. I focus on two issues: which European countries take the brunt of the asylum flows, and the link between the application share that each country gets and its asylum recognition rate.

Asylum applications and recognition rates
Before delving into the details, let’s look at the big picture first. Each year between 2001 and 2012, 370,000 people on average have applied for asylum protection in one of the member states of the European Union (plus Norway and Switzerland). As can be seen from Figure 1, the number fluctuates between 250,000 and 500,000 per year, and there is no clear trend. Altogether, during this 12-year period, approximately 4.5 million people have applied for asylum, which makes slightly less than one percent of the total EU population. Of course, this figure only tracks people who have actually made it to the asylum centers and filed an application – all potential refugees who have perished on the way, or have arrived but been denied the right of formal application, or have remained clandestine are not counted.

asylum_applications_small

Figure 1 also shows the annual number of persons actually recognized as ‘refugees’ under the terms of the Geneva Convention by the European governments: a status which grants considerable rights and protection. This number is quite lower with an average of around 40.000 per year (in the EU+ as a whole) which makes for less than half-a-million in total for the 12 years between 2001 and 2012. While the overall recognition rate remains between 7% and 14%, there is considerable variation between the different European states both in the share from the asylum flows they receive, and in the national asylum recognition rates.

Who takes the brunt of the asylum burden?
Both the asylum flows and the recognition rates are in fact distributed highly unequally across the continent, and in a way that cannot be completely accounted for by the wealth of destination countries, former (colonial) ties between asylum sources and destinations, nor geographical distance. To compare the shares of the total European pool of asylum applications and recognitions that a destination country gets, I create the so-called ‘burden coefficient’. The ‘burden coefficient’ compares the actual share of asylum applications a country received in a year to its ‘fair’ share which is defined as its relative share of the annual  total EU+ GDP. Simply put, if a country accounts for 10% of the European GDP, it would have been expected to receive 10% of all asylum applications filed in Europe that year. Taking account of GDP adjusts the raw asylum application shares in view of the expectation that richer and more populous countries should bear a proportionally higher share of the total European asylum ‘burden’ than poorer and smaller states.

asylum_applications_burden

Figure 2 shows the (logged) burden coefficient for asylum application shares for each EU+ country, averaged over the period 2010-2012. The solid line at zero indicates an asylum applications share perfectly proportional to a  country’s GDP share (a ‘fair’ burden). Countries with positive values receive a higher share of all applications than implied by their GDP level, and countries with negative values receive a lower than their implied share. (The dotted lines show where a country that is doing twice as much / twice as little as expected would be). Clearly, Spain, Portugal, Italy and many (but not all) of the East European countries underdeliver while Cyprus, Malta, Greece, and several West European states (notably Sweden, Belgium, and Norway) take a disproportionately high  share of the total pool of asylum applications filed in Europe over the last few years. Note that these comparisons already take into account (correct for) the fact that most of the Southern and Eastern European countries are poorer (have lower GDP) than the ones in the Western and Northern parts of the continent.

asylum_recognitions_burden

The picture does not change much when we focus on actual asylum recognitions (under the terms of the Geneva Convention) instead of applications. Figure 3 shows the burden coefficient (again averaged over 2010-2012) for full status refugee recognitions in Europe. The country ranking is similar with a few important exception – Greece grants much fewer asylum recognitions than expected even after we account for the state of its economy; Austria and Switzerland join the ranks of states which do much more than their implied share; and, sadly, many more countries in fact underdeliver when it comes to full refugee status grants. (Note that some states offer alternative protection to those denied the full ‘Geneva Convention’ status but the forms and level of this protection differs significantly across the continent).

Are asylum application shares responsive to the recognition rate?
Given these rather significant discrepancies across Europe in how many asylum applications countries get, and how much protection they offer, it is natural to ask whether the applications shares and the recognition rates are in fact related. Do asylum seekers flock at the gates of the European states which are most generous in their recognition policy? Do low recognition rates deter potential refugees from applying in certain countries? Can the strictness of asylum policy be an effective policy tool shaping future application flows? A comprehensive statistical analysis shows that while application shares and recognition rates are associated, their responsiveness to each other is rather weak. Simply put, manipulating the recognition rates is unlikely to have big practical effects on the asylum application share a country receives, and changes in the applications rates only weakly affect state recognition rates. The details of the analysis are rather technical and can be found here, but a dynamic visualization can help illustrate the patterns.

The dynamic interactive chart linked here shows the relationship between asylum applications and asylum recognition rates for each EU+ country over the last 12 years (the chart cannot be embedded in this post due to WordPress policy, but there is a screenshot below). When you press ‘Play’ each dot traces the experience of one country over time. You can choose to observe all, select a single state to focus upon, or tick a couple to compare their experiences.

dynamic-asylum-1

A movement of a dot (and the trace in leaves) in a horizontal direction means that the number of asylum applications received by a country increases while the recognition rates remains the same. Similarly, a vertical move implies a change in the recognition rate but a stable asylum application flow. A trajectory that follows a diagonal suggests a link between applications and recognition rates.

When paused, the state of the chart at each year shows the cross-sectional association between applications and recognition rates: it is easy to see that there is a (rather stable) weakly-strong positive relationship. But the trajectories of individual countries over time do not suggest that there is a temporal link between the two aspects of asylum policy for particular countries. For example, in the UK between 2001 and 2004 both the recognition rates and the applications fall, which would suggest strong responsiveness, but then the recognition rate moves up from 4% to almost 30% without any significant increase in applications. The trajectory of Denmark (try it out) exhibits something close to a dynamic link with rates depressing applications initially but then when they rise again, applications seem to pick up as well. Of course, asylum flows are driven by many other factors as well, so while suggestive, the patterns in the chart should be interpreted with care.

dynamic-asylum-2

More comprehensive analyses of asylum policy in Europe addressing these questions and more are available in my published articles accessible here and here. The original data comes from the UNHCR annual reports. The dynamic chart is generated using Google Chart Tools through the googleVis library in R, you can find the code here. I found it useful to generate a simple version, adjust the settings manually, and then copy the final settings via the Google Chart’s Advanced Panel back to R.

When ‘just looking’ beats regression

In a draft paper currently under review I argue that the institutionalization of a common EU asylum policy has not led to a race to the bottom with respect to asylum applications, refugee status grants, and some other indicators. The graph below traces the number of asylum applications lodged in 29 European countries since 1997:

My conclusion is that there is no evidence in support of the theoretical expectation of a race to the bottom (an ever-declining rate of registered applications). One of the reviewers insists that I use a regression model to quantify the change and to estimate the uncertainly of the conclusion. While in general I couldn’t agree more that being open about the uncertainty of your inferences is a fundamental part of scientific practice, in this particular case I refused to fit a regression model and calculate standards errors or confidence intervals. Why?

In my opinion, just looking at the graph is convincing that there is no race to the bottom – applications rates have been down and then up again while the institutionalization of a common EU policy has only strengthened over the last decade. Calculating standard errors will be superficial because it is hard to think about the yearly averages as samples from some underlying population. Estimating a regression which would quantify the EU effect would only work if the model is sufficiently good to capture the fundamental dynamics of asylum applications before isolating the EU effect, and there is no such model. But most importantly, I just didn’t feel that a regression coefficient or a standard error will improve on the inference you get by just looking at the graph: applications have been all over the place since the late 1990s and you don’t need a confidence interval to see that! But the issue has bugged me ever since – after all, the reviewer was just asking for what would be the standard way of approaching an empirical question.

Then two days ago I read this blog post by William M. Briggs who (unlike myself) is a professional statistician. After showing that by manipulating the start and end points of a time series you can get any regression coefficient that you want even with randomly generated data, he concludes ‘The lesson is, of course, that straight lines should not be fit to time series.’  But here is the real punch line:

If we want to know if there has been a change from the start to the end dates, all we have to do is look! I’m tempted to add a dozen more exclamation points to that sentence, it is that important. We do not have to model what we can see. No statistical test is needed to say whether the data has changed. We can just look.

But what about hypothesis testing? We need a statistical test to refute a hypothesis, right? Let me quote some more:

It is true that you can look at the data and ponder a “null hypothesis” of “no change” and then fit a model to kill off this straw man. But why? If the model you fit is any good, it will be able to skillfully predict new data…. And if it’s a bad model, why clutter up the picture with spurious, misleading lines?

In the inimitable prose of Prof. Briggs, ‘if you want to claim that the data has gone up, down, did a swirl, or any other damn thing, just look at it!’