Monetary distribution effects of Horizon 2020 – An updated analysis (June 2017)

Following-up on a first analysis for Horizon 2020 (THINK Piece 1/2016), this paper looks at Horizon 2020 in terms of monetary redistribution between Member States for the period from 2014 up to May 2017. The paper is structured in four parts: Part one provides a description of the data used, whereas part two consists of a mainly descriptive overview on the key findings, for reasons of comparability presented in the same format as the previous analysis. The third part presents a closer look on how the “market shares” in FP funding have developed over the recent years for the six largest Member States. The final part presents just four simple conclusions from the analytical findings.

 

0.      Intro

 

This paper is the third one (after an analysis of FP7 in THINK Piece 2/2015 and a first analysis of Horizon 2020 in THINK Piece 1/2016) deliberately not touching on the key objectives for Horizon 2020, such as strengthening the knowledge base, developing human capital, increasing the international competitiveness, supporting the development of new goods and services, and providing evidence for designing better public policy. Instead, the intention of this paper is to look at the (basically unintended) monetary distribution effects of the Framework Programme, notably the direct distribution effects between Member States. Horizon 2020 was never meant to be a policy tool for monetary re-distribution, but nevertheless it is of some importance to get an idea on the size and directions of these effects.

 

Within the EU budget, the Framework Programme for Research and innovation is in a rather singular situation, as two totally different approaches are used to define the relative shares of the Member States:

 

-          For the spending on the Framework Programme (“money out”), funds are coming from the overall EU budget, for which the national contributions are based on economic strength and political bargaining (the most significant example for this is the “British rebate”). The distribution of the financial burden is thus the result of a political negotiation process.

 

-          For the income from the Framework Programme (“money in”), funds are mainly coming through co-financed research projects. The selection is based on a scientific peer-review system, aiming at identifying the proposals of highest scientific quality. The distribution of funds is therefore based on the judgement of independent experts – and entirely outside any political influence.

 

Against this background it is not surprising at all that the two distributional approaches lead on balance to diverging results – and such differences are therefore not per se “bad” or “unfair”.

 

1.      Data

 

For the subsequent analysis, three datasets were used (The complete data and calculations are presented in the Table 1 in the Annex, together with links to the public sources used):

 

·       For the spending on Horizon 2020 (“money out”), the assumption is made that the financing of the FP budget by Member States follows the same pattern as the financing of the overall EU budget. Since the real expenditure on Horizon 2020 is linked to the “life time” of the supported projects and will thus cover a period from 2014 up to 2020 or even later, it appears justifiable to use the EU budget for the year 2015 as reference point for the period from 2014 to mid-2017 – assuming that differences for the previous years and the yet unknown changes in the subsequent years are likely to roughly level out. The figures used refer to the “total own resources” per Member State, which are the “final” figures after all calculations for rebates and adjustments have been made.

 

·       For the income from FP7 (“money in”), the European Commission published on 1 June 2017 in the “European Union Open Data Portal“ several files providing funding information for some 55.000 project participants. This information is constantly updated as new contracts are signed. Data presented here have thus to be regarded as a “snapshot” at a given (random) moment in time.

For the sake of comparability and clarity these data have been adjusted by excluding two projects from the calculations:

-       “Eurofusion” is the flagship project in fusion research, both for its huge budget (427 Million €) and its unusual structure (roughly 75% of the funds going to one single country (DE)). Since Fusion Projects were not included in public FP7 data, an inclusion would also hamper a direct comparison between these two Framework Programmes.

-       “COST H2020” is a block grant of 89 Million € devoted to finance COST activities across Europe, formally (and misleadingly for the analysis undertaken here) attributed to Belgium (only).

 

·     Given the huge differences in the size of Member States, population figures from Eurostat for 2015 are used to complement absolute figures with calculations “per capita”.

 

For the sake of simplicity, the subsequent analysis is exclusively focused on spending and income related to the 28 Member States – making it a “zero sum game”. The funding of project partners from associated states or third countries is therefore not included here, nor are the contributions from associated countries taken into account. These restrictions are however of limited impact, as almost 95% of the Horizon 2020 funding goes to project partners in Member States.

 

2.      Analysing the first years of Horizon 2020

 

2.1.            Spending on FP7 (“Money out”)

 

Table 1 in the annex presents in column 6 the “total own resources” per Member State for the EU budget 2015. Column 7 shows the percentage share per country, with Germany and France in the lead, contributing 21.7 % and 16.1% respectively to the EU budget. In column 8 these percentage shares are used to calculate the “virtual” financial contribution per Member State to the total Horizon 2020 funding (on project partners in Member States) for the period from 2014 to mid-2017.

Box 1 presents the amount of spending so far on Horizon 2020 per capita as shown in column 9. Whereas Luxembourg, Denmark, Belgium, Sweden and the Netherlands spent each roughly 70€ per capita or even more, the corresponding amounts for Bulgaria and Romania turn around 10€.

 

 

2.2.            Income from Horizon 2020 (“money in”)

 

Table 1 in the annex presents in column 3 the amount of Horizon 2020 funding going to research organisations or firms from the different Member States. The total financial support across the 28 Member States amounts so far to slightly more than 21 billion €. Column 4 shows the percentage share per country, with the United Kingdom and Germany in the lead with shares of 17.1% and 16.9% respectively.

 

May-be more revealing is a breakdown of the income from FP7 per capita, as presented in column 5 and illustrated in Box 2. While Luxembourg, the Netherlands, Denmark, Cyprus and Finland assured so far a total income from Horizon 2020 per capita of above 90€, these returns per capita were less than 10€ for Romania, Poland, Bulgaria, Croatia and Lithuania.

 

Somewhat surprisingly, the income from Horizon 2020 so far per capita is substantially higher for Ireland than for the United Kingdom, Austria is well ahead of Germany, and Slovenia generates more than double the funding per capita than Italy...

 

 

 

2.3.            Net monetary distribution effects

 

The most interesting part of this analysis is now the direct comparison between the spending on Horizon 2020 and the income from Horizon 2020.

 

In Table 1, column 10 presents the difference in absolute amounts per Member State, whereas column 11 shows the difference as percentage figures. Colum 12 indicates for all Member States what amount is received so far by Horizon 2020 projects for one € financial contribution. Finally, column 13 shows the net results on a per capita basis.

 

Box 3 (based on column 10) illustrates the position of each Member States in terms of absolute amounts. The most significant distribution effects can be observed for the United Kingdom with a “surplus” of over 1.1 billion €, followed by the Netherlands with a net “gain” of over 600 Million €. At the other end of the table, France and Germany show a “deficit” of almost 1 billion € each, followed by Italy with a “loss” of over 670 Million €.

 

 

 

Besides these countries at the extreme ends of the scale, it seems worth being noted that Greece performs remarkably well with a net surplus of over 200 million €. Spain as a net beneficiary does remarkably better than for example Italy or France. Poland is finally by far the highest net contributor from the “New Member States”, with a net position of almost minus 450 Million €.

 

Box 4 (based on column 12) illustrates the relative “success” of Member States in Horizon 2020 so far by indicating what amount of Horizon 2020 funding they receive for every € spent on the Horizon 2020 budget.

 

 

 

Surprisingly Cyprus, Slovenia and Estonia come out with the highest return ratio, receiving more than 2€ for every € spent on the Horizon 2020 budget so far. Greece, Ireland, Finland and the Netherlands also generated a return of over 1.50 € per € invested. At the other end of the scale, Poland, Romania and Lithuania received less than 50 cents out of Horizon 2020 for every € spent.

 

Finally, Box 5 (based on column 13) looks at the situation per capita, estimating the net distributional effects of FP7 for each inhabitant of the Member States.

 

 

 

Horizon 2020 generated per head of population net gains in the order of 60 € for Cyprus. For Slovenia, the Netherlands, Finland and Ireland, this surplus is well above 30 €.

 

At the opposite end, the net loss per capita is higher than 10 € for France, Lithuania, Germany, Poland and Italy. 

 

3.      A closer look at the “Market Shares” of the six largest Member States

 

Following-on to the analysis of the financial impact of Horizon 2020 for the six largest Member States (THINK Piece 1/2016), this chapter tries a very first and tentative analysis on how the relative performance of the “Big Six” is developing from FP7 to half-way through Horizon 2020.

 

Table 2 in the annex presents calculations for the respective “market share” of the 28 Member States. The same restrictions as for the rest of the paper apply, so that these Market shares add up to 100% (the funding going to non-EU countries is thus again not included in the analysis). The calculations refer to three consecutive periods:

-          The overall lifetime of FP7 from 2007 to 2013

-          The first period of Horizon 2020, based on data published at the beginning of 2016 and thus covering essentially the implementation in 2014 and 2015

-          A second period in Horizon 2020, based on the difference between data published in June 2017 and thus published at the beginning of 2016, thus essentially covering the implementation in 2016 and the first five months of 2017[1].

 

Table 2 presents a full set of data, but these should be interpreted very carefully. Especially the sometimes massive fluctuations in the “market share” of smaller Member states are often the result of success or failure of a very few proposals. Interpreting these as long-term “trends” seems at least premature at this stage.

 

The situation is different, however, when analyzing the situation for the six largest Member States, where the “market shares” calculated are based on thousands of projects. Box 6 summarises the relative changes, and although the fluctuations do not seem huge, these limited shifts have major financial implications.

 

 

 

Spain is the one of the “Big Six” with the best relative performance, increasing its “market share” from 7.9% in FP7 to 9.7% in Horizon 2020. This represents a rather remarkable relative increase of well above 20%. A possible reason behind this – but probably not the only explanation - could be the relatively strong performance of Spain in the newly designed SME support schemes of Horizon 2020.

 

The United Kingdom is the other big Member State with a positive momentum, increasing its “market share” from 16.1% in FP7 to 17.1% in Horizon 2020. One might be tempted to start interpreting these figures against the “Brexit” vote, but it should be noted that only a very small fraction of projects recently launched was designed after the referendum. It is in any case emblematic that the UK is up to now the Member State with the highest absolute amount of Horizon 2020 funding received, marginally ahead of the “traditional” leader Germany.

 

The “market shares” for the four other major Member States show a somewhat alarming pattern, as for all of them one could observe a fall by about 10 percentage points: The “market share” of Italy has fallen from 9.3% in FP7 to 8.6% in Horizon 2020 up to now, the “market share” for France went down from 12.5% to 11.3%. Also, the figures for Germany show a pronounced downward trend, with 18.7% in FP7 as compared to currently 16.6% in Horizon 2020. The corresponding figures for Poland, 1.07% versus 0.96%, indicate that the already rather low “market share” was further substantially eroding.

 

These changes might appear relatively minor in relative terms, but in absolute amounts they hint at major shifts in the monetary distribution through Horizon 2020. This might be illustrated by two fictive calculations:

·       The substantive increase in the “market share” for Spain means that this country received through Horizon 2020 so far some 380 Million € more than in case it would just have continued with its FP7 “market share”.

·       On the other hand, the relatively weak performance of Germany in Horizon 2020 so far translates into a loss of EU funding in the order of 360 Million € as compared to the situation under FP7.

 

4.      Four simple conclusions from this analysis

 

At a point in time were reflections on the next Framework Programme start circulating, the analysis provided here provides four simple, but politically important conclusions:

 

4.1.            The European Research Area seems far away…

 

Counties like the Netherlands or Denmark receive roughly 20 to 25 times more funding per capita from Horizon 2020 than countries like Poland or Romania. These differences highlight that the enormous regional differences in the breadth and depth of the European research and innovation landscape do persist and that contrary to the political ambition location still matters a lot …

 

4.2.            There is no catching up…

 

Within the group of “new” Member States (EU-13) there are huge differences, and especially some smaller countries such as Slovenia and Estonia perform remarkably well in Horizon 2020. But larger countries such as Poland, Romania and Bulgaria continue to perform rather badly – and moreover show no signs for an upward trend.

 

4.3.            The winner is about to quit…

 

The country with the highest absolute funding and with by far the highest net gains from Horizon 2020 is the UK, which generated a surplus of roughly 1.1 Billion € in the last three years. While a Brexit in 2019 is generally regarded as very bad news for research and innovation in the UK and in the European Union, it is also fair to state that from a strictly financial perspective the “fading away” of the best in class would mean that the net financial position of the remaining 27 Member States would improve.

 

4.4.            Small winners, big losers …

 

The financial flows resulting from Horizon 2020 show a somewhat peculiar pattern, since most of the relative winners are comparatively small countries, whereas the four biggest losers are all large Member States. Since the largest beneficiary (the UK) will most likely no longer take part in the FP9 deliberations, it might become a major political issue if France, Germany, Italy and Poland are all losing out on their Horizon 2020 participation, accumulating so far together a massive deficit of well over 3 Billion €. These figures might not be stimulating for these countries to support a hefty increase in the FP9 funding, unless there will be a substantive change in the narrative and design of the next Framework Programme.

 

 

 

Annex - Table 1

 

 

Data Sources:

Column 2                                   Population Figures                                     Eurostat table tps000001

 http://epp.eurostat.ec.europa.eu/tgm/table.do?tab=table&tableSelection=1&labeling=labels&footnotes=yes&language=de&pcode=tps00001&plugin=0

Column 3                                  Horizon 2020 Funding received CORDIS – EU research projects under Horizon 2020 (2014-2020), Version updated 2017-06-01

 https://data.europa.eu/euodp/de/data/dataset/cordisH2020projects

Column 6                        EU Budget 2015      Definitive Adoption (EU, Euratom) 215/339 of the European Union’s general budget for the financial year 2015, OJ L 69/2015 of 13.3.2015, Table 6, page 20

http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=OJ:L:2015:069:TOC

 

 

Annex - Table 2

Data Sources:

Column 2                                   FP7 Funding received                                                 FP/ Monitoring Report 2013, Table B7

https://ec.europa.eu/research/evaluations/pdf/archive/fp7_monitoring_reports/7th_fp7_monitoring_report.pdf#view=fit&pagemode=none

Column 4                                    Horizon 2020 Funding received              CORDIS – EU research projects under Horizon 2020 (2014-2020), Version updated 2016-01-26

https://open-data.europa.eu/en/data/dataset/cordis-h2020projects-under-horizon-2020-2014-2020

Column 6                                   Difference Column 8 – Column 4

Column 8                                    Horizon 2020 Funding received              CORDIS – EU research projects under Horizon 2020 (2014-2020), Version updated 2017-06-01

https://data.europa.eu/euodp/de/data/dataset/cordisH2020projects

 



[1] These somewhat clumsy explanations are needed as the data published do not provide any information about cut-off points and implementation periods covered. In the absence of such a full documentation, there is a risk that later versions do not only account for new projects added (as assumed here), but might also include corrections of errors and mistakes in previous versions.

 


Version 1.0 – 30.06.2017 - Thanks for your feedback

 


Download
Think Pieces 2-2017 Distribution Effects
Adobe Acrobat Dokument 969.9 KB