study to examine the socio- economic impact of copernicus ... · programme case study. final report...

Study to examine the socio-

economic impact of

Copernicus in the EU

Report on The socio-economic impact of the

Copernicus programme

Written by PwC October - 2016

European Commission

EUROPEAN COMMISSION Directorate-General for Internal Market, Industry, Entrepreneurship and SMEs

DG GROW — Directorate-General for Internal Market, Industry, Entrepreneurship and SMEs

I.3 Unit — Space Data for Societal Challenges and Growth

Contact: Thibaud Delourme

E-mail: [email protected]

European Commission

B-1049 Brussels

EUROPEAN COMMISSION

Study to examine the socio-

economic impact of Copernicus in the EU

Report on The socio-economic impact of the

Copernicus programme

Final report – The socio-economic impacts of the Copernicus programme

i

LEGAL NOTICE This document has been prepared for the European Commission however it reflects the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein. More information on the European Union is available on the Internet (http://www.europa.eu). Luxembourg: Publications Office of the European Union, 2016 ISBN number 978-92-79-59010-8 doi:number 10.2873/733800 © European Union, 2016 Data provided in this report are the property of their rightful owners. Further data reuse is not permitted without the express authorisation of the data owner.

Printed in Belgium

Europe Direct is a service to help you find answers

to your questions about the European Union.

Freephone number (*):

00 800 6 7 8 9 10 11

(*) The information given is free, as are most calls (though some operators, phone boxes or hotels may charge you).

http://www.europa.eu/http://europa.eu.int/citizensrights/signpost/about/index_en.htm#note1#note1

Report Socio-economic impacts of space activities in the EU in 2015 and beyond

ii

Executive summary

This report presents an assessment of the overall economic impact derived from public spending on

the Copernicus programme. The report compiles the results from two other reports:

Strategy&, 2015. Study to examine the GDP impact of space activities in the EU. Final

Report Prepared by Strategy& for the European Commission. September, 2015.

This study focused on the GDP impact of EC & ESA spending on the Copernicus Space

component over the period 2008 – 2013.

PwC – Strategy&, 2016. Study to examine the socio-economic impact of Copernicus in

the EU. Final Report Prepared by PwC – Strategy& for the European Commission. July,

2016.

This study focused on the socio-economic impacts of freely available and open Copernicus

data & products in Europe. The project analysed the use of Copernicus data along eight

sector value chains: agriculture, ocean monitoring, insurance, O&G, renewable energies,

urban monitoring, air quality monitoring and forestry.

The economic assessment was performed using two different approaches. The economic benefits

derived from public investment in the Space & Services components of the Copernicus programme

were assessed using a GDP impact methodology. The GDP impact – or transactional economic impact

– is the first impact to fully materialize after the initial investment. GDP impact mostly includes the

impact of space manufacturing activities on the local or regional industrial sectors. However, this

assessment does not include the actual use of infrastructure, i.e. the usage of Copernicus data &

products available for free. The complexity of the economic linkages and imapcts arising from the

use of Copernicus data & products justifies the use of a micro-diffusion model to understand at the

level of the firm how the data & products are used and how they are creating specific knowledge

that leads to sales increases or cost reductions. Wider methodologies such as the GDP impact

assessment methodology are not able to capture the complexity of this type of phenomenon and

assess accurately such economic impact.

The overall economic impact of the Copernicus programme was estimated using two different

scenarios: a conservative scenario and an optimistic one.

The conservative scenario is more prudent and robust than the optimistic one; it relies only on

the results of the eight value chain case studies and uses lower-bound estimates of impacts.

The scenario offers a very conservative result on the catalytic impact derived from the availability of

free and open Copernicus data & products. The assessment has led to the estimation of ex-post

enabled revenues of EUR 38.3 M (2015) and ex-ante cumulative enabled revenues of EUR 445.1 M

(2016 – 2020).

The optimistic scenario is derived from the overall size of the markets under scrutiny, optimistic

growth rates (CAGR), and optimistic adoption rates for end-users, together with GIS revenues

for Europe. The assessment has led to the estimation of ex-post enabled revenues of EUR 342.7 M

(2015) and ex-ante cumulative enabled revenues of EUR 2 792.9 M (2016 – 2020).

Figure 1 summarises together all the monetary impacts – transactional and catalytic impacts – derived

from public investment (EC & ESA) in the Copernicus programme. In some cases, the initial

investment in the space programme varies considerably between years, and so to, therefore, do some

estimated impacts. Other impacts materialise at a date later than the initial investment. Consequently,

it is more informative to look at results for the period as a whole rather than for individual years,

distinguishing only between 2014 and 2021 and the period before it.

Report Socio-economic impacts of space activities in the EU in 2015 and beyond

iii

Figure 1 – Overall monetary impact1 of EC & ESA investment in the Copernicus programme,

based on eight selected value chains (Source: Strategy& - PwC analysis)

As stated earlier, the enabled revenues derived from the use of Copernicus products are only based

on eight very specific value-chains and do not include the overall enabled revenues for all the

potential sectorial use of Copernicus in Europe. Furthermore, all the non-monetary benefits that are

generated by the Copernicus programme are not included in this assessment. In the case of the

enabled revenues for the downstream market and end-users, two scenarios were derived to represent

the variance in the use and the acceptance of Copernicus products among the EO downstream and

GIS markets, and among end-users.

The overall cumulative GVA and enabled revenues generated by the Copernicus programme (Space

& Services components and downstream usage of Copernicus products & data) from its beginning

and 2021 have been estimated on the basis of the following two scenarios:

Conservative scenario: EUR 10 766.0 M;

Optimistic scenario: EUR 13 418.2 M.

In both cases, EUR 4 405.04 M was generated before 2014.

1 The category “Before 2013” illustrates the cumulative benefits from the beginning of the Copernicus programme up to 2013. The category “2014-2021” illustrates the cumulative benefits from 2014 to 2021 but it does not include the

benefits from the previous category.

Final report – EEE Non-dependence

Table of contents

EXECUTIVE SUMMARY ................................................................................................... II

INTRODUCTION ........................................................................................................ - 1 -

Objectives and scope of the study ....................................................................... - 1 -

THE COPERNICUS PROGRAMME .................................................................................. - 2 -

Programme description ...................................................................................... - 2 -

Programme structure ..................................................................................... - 3 -

Programme funding and financial overview ........................................................... - 4 -

SOCIO-ECONOMIC ASSESSMENT METHODOLOGY ......................................................... - 6 -

Introduction ...................................................................................................... - 6 -

GDP Impact Assessment Methodology .................................................................. - 8 -

What is GDP Impact? ................................................................................... - 8 -

GDP Impact Assessment Methodology ...................................................... - 10 -

Baseline “Single Tier” modelling approach description ............................ - 12 -

Available data for test case modelling ........................................................ - 14 -

Space Supply Chain Modelling - Black box model evolution ................... - 16 -

Micro-diffusion model ....................................................................................... - 18 -

The original BETA methodology ............................................................... - 18 -

The adaptation of BETA methodology to the context of the enabled

revenues by the availability of Copernicus data & products ........ - 21 -

SUMMARY OF THE PREVIOUS STUDIES ...................................................................... - 24 -

The GDP impact of the public investment made in the Copernicus programme ........ - 24 -

Financial overview ..................................................................................... - 24 -

Results and analysis .................................................................................... - 25 -

Conclusion .................................................................................................. - 29 -

The enabled revenues derived from the use of the Copernicus products ................. - 31 -

Agriculture .................................................................................................. - 31 -

Forestry…. .................................................................................................. - 32 -

Urban monitoring ....................................................................................... - 34 -

Insurance ..................................................................................................... - 35 -

Ocean monitoring ....................................................................................... - 37 -

Oil and Gas ................................................................................................. - 37 -

Renewable energies .................................................................................... - 38 -

Air quality ................................................................................................... - 40 -

UPDATE OF THE GDP IMPACT OF COPERNICUS ........................................................... - 42 -

Copernicus upstream investment over the period 2014 – 2015 and the forecast for the period 2016 – 2021 ........................................................................... - 42 -

Copernicus core services: GDP impact of the EC spending made in the Copernicus core services’ entrusted entities ............................................................... - 44 -

OVERALL ECONOMIC ASSESSMENT OF EUROPEAN PUBLIC INVESTMENT MADE IN THE

COPERNICUS PROGRAMME ............................................................................... - 46 -

The Copernicus Space Component impact assessment ......................................... - 46 -

The Copernicus Services Component impact assessment ...................................... - 48 -

The Copernicus downstream and end-user impact assessment .............................. - 51 -

Copernicus infrastructure and utilisation: a comparison of costs and benefits .......... - 53 -

Final report – EEE Non-dependence

5

Conclusion on the overall economic impact of the Copernicus programme ................... 54

Final report –Socio-economic impacts of space activities in the EU in 2015 and beyond

- 1 -

Introduction

Objectives and scope of the study

This study aims to provide the European Commission with an overall socio-economic assessment of

the GDP impact of the Copernicus programme in Europe and the enabled revenues derived from the

programme. The report combines the results of two past studies performed by Strategy& - PwC:

Study to examine the GDP impact of space activities in the EU. The Copernicus

Programme case study. Final Report Prepared by Strategy& for the European Commission.

September 2015.

Study to examine the socio-economic impact of Copernicus in the EU. Report on the

Copernicus downstream sector and user benefits. Final Report Prepared by Strategy& - PwC

for the European Commission. June 2016.

The report also contains an update on the GDP impact of the public spending (EC & ESA) on the

Copernicus Space and Copernicus Services Components.

The objective of the study is to address two evidence gaps in the literature. The first gap is a lack of

analysis of the Copernicus programme at the downstream and end-user level. No overall assessment

of the end-user benefits, both public and private, derived from the Copernicus programme has been

performed in the past.

The second gap in the literature is related to the absence of an overall assessment of the socio-

economic impact of the Copernicus programme, which combines the upstream and downstream

analyses. The recent study conducted by Strategy& - PwC to assess the socio-economic impact of

the Copernicus downstream sector and end-users fills this gap in the literature, in conjunction with

the study focusing on the upstream GDP impact of the Copernicus programme, to offer a full picture

of the programme and its impacts.

Draft report –Socio-economic impacts of space activities in the EU in 2015 and beyond

- 2 -

The Copernicus Programme

Programme description

The Copernicus European Earth observation programme (formerly called Global Monitoring for

Environment and Security - GMES) was initiated in 1998. The programme is a joint initiative between

the European Commission (EC), its Members States, the European Space Agency (ESA), and the

European Environment Agency (EEA).

The rationale and motivation for Copernicus came from the need to have autonomous and

independent access to information in relation to the environment and security on a global level.

Copernicus represents the European contribution to the international observation systems focusing

on environment monitoring (land, marine, atmosphere and climate change): the Global Earth

Observation System of Systems (GEOSS), the Global Climate Observing System (GCOS), and the

Global Ocean Observing System (GOOS).

From its inception, the programme gradually acquired relevance and strategic importance within the

wider European space policy and was ultimately adopted by the EU as the second flagship space

programme, next to Galileo, which is the European global navigation satellite system (GNSS)

programme. In 2012, the European Commission renamed the GMES Programme as Copernicus.

The main objective of the Copernicus programme is to provide Earth Observation (EO) services to

European society to support economic development and increase the well-being of European

citizens. It relies on an open and free-of-charge data policy, and aims to increase European capacity

and demand for EO. The general objectives for the Copernicus programme, as specified by the

European Parliament2 are:

Monitor the Earth to support the protection of the environment and the efforts of civil

protection and civil security;

Maximise the socio-economic benefits, thereby supporting the Europe 2020 strategy and its

objectives of smart, sustainable and inclusive growth by promoting the use of Earth

observation in applications and services;

Foster the development of a competitive European space and services industry and maximise

opportunities for European enterprises to develop and provide innovative Earth observation

systems and services;

Ensure autonomous access to environmental knowledge and key technologies for Earth

observation and geo-information services, thereby enabling Europe to achieve independent

decision-making and action.

The European EO programme will rely on a constellation of seven EO satellites called Sentinels which,

together with other satellites that form “contributing missions” and ground infrastructures for unified

data processing, represent the space segment of the programme. The space segment enables

Copernicus core services, which are described in the following subsections.

2 Sources: Regulation (EU) No 377/2014 of the European Parliament and of the Council of 3 April 2014 establishing the

Copernicus Programme and repealing Regulation (EU) No 911/2010)


- 3 -

The successful orbit insertion of Sentinel 1A in April 2014 and Sentinel 2A in June 2015 initiated the

operational phase of Copernicus services, which enabled the commencement of the land and ocean

monitoring services.

Programme structure

Copernicus is managed by the European Commission (EC) and the European Space Agency (ESA): the

space segment procurement and deployment is coordinated by ESA, while the services side is

managed by the EC.

The Copernicus Space segment comprises two types of satellite missions, the dedicated Copernicus

Sentinels and “Contributing Missions”, which are Earth Observation missions originating from

national space agency programmes within Europe. Data from all missions are streamed and made

freely available for Copernicus services from a unified ground segment which completes the Space

Component. A mechanism to integrate, harmonise and coordinate access to all the relevant data

from different missions is being developed by ESA in cooperation with other national space agencies,

EUMETSAT and, where applicable, with non-European contributors to the Copernicus objectives. The

set-up and deployment of the space segment engages the upstream space industry in satellite and

ground segment manufacturing and also in launch services.

The Copernicus Services segment includes the six core services enabled by the Copernicus

programme: land monitoring, emergency management, atmosphere monitoring, maritime

environment monitoring, climate change and security. The service part also includes an “In-situ

component”, which is coordinated by the EEA and supports both main areas of the Copernicus

programme, “Copernicus Services” and “Copernicus Space Segment” with data. The subsection

“Copernicus Services” provides more information about each of the six core services and the

contribution of the EEA.

The high level view of the organisation of the Copernicus Programme is illustrated in the figure below.

Figure 2 – Organisation of Copernicus programme


- 4 -

Programme funding and financial overview

The figures used in this sub-section are based on the GDP impact report of Strategy& (2015) 3. The

figures up to 2013 are based on payments actually made by EC & ESA, while all the investments made

over the period 2014 – 2021 are based on commitments by EC & ESA (spending that is planned but

not yet made). No more recent figures were available to update the commitments over 2014-21.

The Copernicus programme is co-funded by EC & ESA. Global funding for the Copernicus programme

over 2000-13 was about EUR 3.2 B. A large part of the Copernicus budget (76%) was dedicated the

Space component, and mainly for the development of the Sentinels. The Space component budget

was EUR 2.43 B, out of which ESA provided EUR 1650 M (67,90%) with the remaining EUR 780 M

(32,01%) coming from the EC.

For the Services component, including in-situ component, the EC provided funding to the tune of

EUR 520 M (68,42%), completed by EUR 240 M (31,57%) from ESA. The Space/Services Components

budget breakdown, with further breakdown into EC & ESA spending, is shown in the figure below.

Figure 3 – Copernicus programme funding by EC & ESA over the period 2000-2013 (Source:

Strategy&, 2015)4

The total funding (for both segments, incl. in situ) by ESA is approx. EUR 1.9 B, while that for EC is

estimated to be EUR 1.3 B5.

The EU Horizon 2020 programme includes the provision of about EUR 4.3 B for the environment

monitoring programme6. EC and ESA have signed a common agreement to commit over EUR 3 B to

manage and implement the Copernicus Space Component between 2014 and 2021. More specifically,

the planned investments over the period 2014 – 2021 for the Service and Space components amount

to EUR 897 M and EUR 3394 M respectively.7

3 Sources: publicly available EC documentation;

EC-ESA Agreement on the implementation of the Space Component of GMES (2013). ESA Annual financial report. 4 Sources: Strategy&, 2015. Study GDP Impact. Final Report Prepared by Strategy& for the European Commission.

September, 2015. 5 Sources: EC publicly available documentations;

EC-ESA Agreement on the implementation of the Space Component of GMES (2013). ESA Annual financial

report. 6 Sources: EC publicly available documentations;

EC-ESA Agreement on the implementation of the Space Component of GMES (2013). ESA Annual financial

report. 7 Sources: Regulation (EU) No 377/2014 of the European Parliament and of the Council of 3 April 2014

establishing the Copernicus Programme and repealing Regulation (EU) No 911/2010)

EC: 32%

ESA: 68%

Space Component(EUR 2 430)

EC: 68%

ESA: 32%

Services Component(EUR 760)


- 5 -

Figure 4 – Planned public spending (EC & ESA) on the Copernicus programme over the

period 2014 - 2021 (Source: EC; Strategy&, 2015)4

As mentioned earlier, the team does not have access to most recent figures to perform a more up-

to-date analysis.

Services: 897

Space Components: 3 394

Copernicus Services & Space Components over the period

2014 – 2021(EUR 4 291 M)


- 6 -

Socio-economic Assessment

Methodology

Introduction

Socio-economic impact assessments are important for public institutions since they demonstrate the

broad benefits and value for money of public spending, and help provide transparency vis-à-vis

stakeholders. Investments made in a given programme have different types of impacts, ranging from

monetary to non-monetary impacts. Figure 5 gives an overview of the monetary and non-monetary

impacts derived from a given investment in space activities.

Figure 5 – Socio-economic impacts related to investments in a space programme (Source:

Strategy&, 2015)4

The transactional economic impact – or GDP impact – is the first impact to fully materialize after the

initial investment. The GDP impact includes three main economic assessments (direct, indirect and

induced impacts) and an employment impact; it is one of the two main monetary impacts, together

with the catalytic impact, related to an investment in space activities. The GDP impact mostly includes

the impact of space manufacturing activities on the local or regional industrial sectors. More detail

on to these GDP impacts is available in the next section. The transactional economic impact

materializes over the short-term compared to the other socio-economic impacts and various

standardized methodologies exist to assess these impacts, which facilitate comparison over time and

with other industrial sectors.

Catalytic impacts are the second monetary impact materializing from investments in space activities.

In most cases, this type of impact requires more time to materialize compared to the GDP impact.

Catalytic impacts can be split into two main categories: utilization of an infrastructure funded by the

initial investment under scrutiny and spin-off/spillover effects. The first one includes all the enabled

revenues by the use of a given infrastructure and this is particularly of interest in the case of the

Copernicus programme. The enabled revenues of the Copernicus programme, for example, include

all the revenues enabled by the availability of free Copernicus products, such as an increase in sales

of existing products or the creation of new streams of revenues. Enabled revenues from the utilization

Transactional Economic Impact (GDP)

Direct Impact

(spending of the upstream)

Indirect

(spending

of tier 2

suppliers)

Induced

(spending

of

employees)

Catalytic

Impacts

Employment

Impact

Other

Quantitative

Impacts

Qualitative

Impacts

(Revenues

enabled by

space

systems –

satellite

industry

and

services

and non-

space

industries

and

services;

Spin-offs)

(Employment

supported

by GDP

impacts)

(Patents,

publications

etc.)

(Non

quantifiable

R&D spillovers,

social and

environmental

impacts,

impacts on

security,

prestige,

outreach etc,)

Monetary impacts


- 7 -

of infrastructure materialize mainly in the downstream industry. More details on enabled revenues

are available in the section on the Micro-diffusion model. The second category of catalytic impacts,

the spin-off effect – also called spillover effect – aims at assessing the expertise and knowledge

developed by an organization related to the initial investment. The knowledge and expertise

developed and re-used to develop new products, new services, improvements in quality or efficiency,

cost reduction, etc. are classified as spin-off effects and are quantified in terms of enabled revenues

and cost reduction. Spin-off impacts are mostly technological and industrial, and most of these

effects will be realized in the upstream part of the industry; this report does not assess the spin-off

effect of the Copernicus programme on the upstream industry.

The non-monetary impacts gather the “other quantitative impacts” and the “qualitative impacts”. The

first category includes all the metrics that cannot be turned into, or not typically available as monetary

values. The range of metrics vary from the number of patents or publications related to the

programme under scrutiny to the number of lives saved thanks to the use of a type of satellite, for

example. The “qualitative impacts” gather all the non-quantifiable information such as social and

environmental impact, education & science or the prestige and strategic impacts related to a given

space programme. This report does not assess the non-monetary impacts of the Copernicus

programme.

The following sections present the two type of methodologies used in the previous studies to assess

the GDP impact in one hand and the enabled revenues on another hand of the Copernicus

programme.


- 8 -

GDP Impact Assessment Methodology

What is GDP Impact?

The GDP impact represents the straight economic impact derived from an injection of spending into

the economy. The concept is the basis of expansive policies to boost economies in periods of

recession: institutional spending stimulates further spending in the wider economy, leading to a

multiplying effect.

In the space sector specifically, spending that is injected in the upstream industry (usually) leads to a

cascade of spending and economic activity through the supply chain, as shown in Figure 6. The space

industry spends a portion of the funding on purchases from suppliers (e.g. for components or

subsystems). These suppliers, in turn, spend a part of those funds further down the supply chain (e.g.

for raw materials). Meanwhile, all companies within the supply chain pay their employees’ salaries.

These salaries, in turn, support consumer spending in the wider economy. The compound effect of

all the spending that results from the initial upstream spending constitutes the GDP impact of the

initial investment.

Figure 6 – Schematic of the relationships among GDP impact components (Source: FAA)

According to generally accepted best practices, the GDP impact is calculated by combining these

three components:

Direct GDP Impact: The GDP impact of direct spending into the space industry, which is

typically initiated in upstream manufacturing, is the economic activity stimulated in the space

industry itself; it represents the Gross Value Added (GVA, equal to labour plus profit) realised

in the industrial sector receiving the initial spending

Indirect GDP Impact: The indirect impact is the economic activity (i.e. GVA) supported by

the expenditures on suppliers of equipment and supplies to support the space industry

orders, and their own suppliers further along in the value chain. These secondary or “2nd

round” impacts would not occur if the upstream space industry operations had not required

the support to fulfil their orders


- 9 -

Induced GDP Impact: The induced impact is represented by the economic activity (i.e. GVA)

supported by those people directly or indirectly employed (i.e. in space suppliers) via the

space industry when they spend their incomes on goods and services in the wider European

economy. This induced spending supports the industries that supply these non-space

purchases, and includes housing, retail outlets, companies producing consumer goods and

a variety of service industries.

Figure 7 - GDP Impact components (Source: Strategy&, 2015)

An assessment of these three components theoretically implies tracing the flow of spending through

the entire extended supply chain in the local/regional economy of interest, with all imports subtracted

as cash outflows. In practice, spending effects are statistically modelled for a variety of industrial

sectors in order to enable assessments of the GDP impact.

To understand the actual GDP impact relative to “some kind of spending,” economists define GDP

multiplier(s), which typically relate the final resulting GDP impact to the direct GDP impact. Two

types of GDP multipliers are commonly used in socio-economic impact studies8:

𝑇𝑦𝑝𝑒 𝐼 𝐺𝐷𝑃 𝑀𝑢𝑙𝑡𝑖𝑝𝑙𝑖𝑒𝑟 = (𝐷𝑖𝑟𝑒𝑐𝑡 𝐼𝑚𝑝𝑎𝑐𝑡 + 𝐼𝑛𝑑𝑖𝑟𝑒𝑐𝑡 𝐼𝑚𝑝𝑎𝑐𝑡)

𝐷𝑖𝑟𝑒𝑐𝑡 𝐼𝑚𝑝𝑎𝑐𝑡

𝑇𝑦𝑝𝑒 𝐼𝐼 𝐺𝐷𝑃 𝑀𝑢𝑙𝑡𝑖𝑝𝑙𝑖𝑒𝑟 = (𝐷𝑖𝑟𝑒𝑐𝑡 𝐼𝑚𝑝𝑎𝑐𝑡 + 𝐼𝑛𝑑𝑖𝑟𝑒𝑐𝑡 𝐼𝑚𝑝𝑎𝑐𝑡 + 𝐼𝑛𝑑𝑢𝑐𝑒𝑑 𝐼𝑚𝑝𝑎𝑐𝑡)

𝐷𝑖𝑟𝑒𝑐𝑡 𝐼𝑚𝑝𝑎𝑐𝑡

Type I multiplier does not include the induced impact: such a multiplier is calculated when statistical

data on consumer spending is not available. The Type II multiplier is on the other hand representative

of the overall GDP impact as it captures also the induced impact, i.e. the space industry’s and

suppliers’ employee spending effects (household spending): as such, it is more commonly used.

These multipliers provide an indication of how the initial spending quantity creates economic activity

(GVA) in industrial sectors other than the recipient of the institutional investments, i.e. how wide is

the reach of the investment and how extensive is the industry’s supply chain.

In some cases, the Type II GDP multiplier is referred to the initial spending rather than the Direct

Impact:

𝑇𝑦𝑝𝑒 𝐼𝐼 𝐺𝐷𝑃 (𝑅𝑒𝑡𝑢𝑟𝑛)𝑀𝑢𝑙𝑡𝑖𝑝𝑙𝑖𝑒𝑟 = (𝐷𝑖𝑟𝑒𝑐𝑡 𝐼𝑚𝑝𝑎𝑐𝑡 + 𝐼𝑛𝑑𝑖𝑟𝑒𝑐𝑡 𝐼𝑚𝑝𝑎𝑐𝑡 + 𝐼𝑛𝑑𝑢𝑐𝑒𝑑 𝐼𝑚𝑝𝑎𝑐𝑡)

𝐼𝑛𝑖𝑡𝑖𝑎𝑙 𝑆𝑝𝑒𝑛𝑑𝑖𝑛𝑔

8 Richardson, Harry, W. 1985. “Input-output and economic base multipliers: Looking backward and forward,” Journal of

Regional Science, Vol. 25, No. 4, pp. 607-662


- 10 -

When expressed in this way, the multiplier provides an indication of the “return” in terms of

incremental GVA, obtained as a result of the initial spending.

A GDP impact analysis provides a rules-based and transparent measure of the economic

importance of investment (in space) for the European economy. It communicates the importance

of such investments using standard measures of economic activity (GDP). Additionally, such an

impact assessment allows the derivation of further impacts on jobs, wages and tax revenues; those

being a direct consequence of the increased economic activity, as shown in the figure below.

Figure 8 – Economic activity metrics connected to GDP Impact Analysis

Of all the metrics above, Government Tax Revenues is of particular interest and the impact of the

Copernicus programme on Government Tax Revenues is estimated as the difference from the

baseline (represented by the economy with no institutional spending in the specific space

programme) of the following four components:

Income direct tax

Indirect tax (Value Added Tax)

Employers social security contribution

Employees' social security contribution

It is important to stress here that government revenues are not a part of the total value added: they

represent the total spending that goes back to the government, i.e. which goes out the

macroeconomic flow. Government revenue calculations provide an extremely powerful argument to

decision makers, since they can show whether the increased economic activity stimulated by the

original investment returns tax revenues, and scale of these revenues.

Practically, GDP impact assessments are usually realised using linear input-output models based on

the use of statistical spending data per each industrial sector. In the case of the space sector, no

statistical sectorial spending data exists for Europe as a whole: input-output models group space

within the wider transportation sector (i.e. together with aviation, shipbuilding, land transportation

etc.), thus losing all details pertaining to the peculiarities of the space supply chain. This means that

GDP impact modelling for space requires complementary data retrieval from the space industry

and dedicated modelling of the space sector’s upstream activity.

To date, the GDP impact from space activities has been assessed for specific topics in the US (via FAA

and NASA contracted studies) and for a few European countries (UK, France). No structured GDP

impact assessment has been conducted at EU level.

GDP Impact Assessment Methodology

The study has the objective to produce a simple and actionable GDP impact assessment

methodology, which produces results that are comparable with similar studies carried out for non-

space sectors, and which can be applied to EU-funded space programmes in a repeatable way.

The approach chosen uses the E3ME model for the modelling of the wider knock-on effects on the

European economy, and carries out dedicated modelling of the space supply chain in order to provide

the E3M3 model with spending inputs associated with non-space industrial sectors.

1. First step – modelling of the space upstream: This step takes as input the institutional

spending in space, and produces as output the space Gross Value Added (equal to labour

GDP EmploymentSalaries and

Wages

Government Tax

Revenues

Standard Measures of Economic Activities


- 11 -

plus profit) and the spending into a number of non-space industrial sectors that are modelled

in the E3ME.

2. Second step: The spending into non-space industrial sector is fed into the E3ME model,

producing as output the overall GDP impact (total GVA), employment impact and

government revenues.

The key to the methodology definition is the approach taken to model the space upstream, i.e. the

part that is complementary to E3ME model.

Different approaches can be chosen depending on the data available. An analysis of the input

tracking data of EU space programmes showed that input spending is usually tracked in the form of

payments per company per country, rather than by contract information. This implies that most

subcontractors are tracked together with the associated payments.

The most common type of available input data led to the choice of an upstream modelling approach

as a “single tier”, one without the need to rebuild the contractual structure within the space supply

chain (Figure 9).

Figure 9 – GDP impact assessment approach at a glance

Another reason the single tier approach was chosen was the potential for a future adaptation into a

“plug-and-play” approach: with subsequent application of the “single tier” approach on more EU

space programmes, and the continual retrieval of data from the European space industry, an

opportunity is there to build a model that is precise enough to be used as a black-box. This is

elaborated in the following sub-sections.

Upstream industry model

Modelling of the upstream space industry

per country

Spending allocation per sector and per

country

E3ME Model

EU Programme

spending

A

B


- 12 -

Cambridge Econometrics’ E3ME Model

E3ME is a computer-based model of the world’s economic and energy systems and the

environment. It was originally developed through the European Commission’s research framework

programmes and is now widely used in Europe and beyond for policy assessment, for forecasting

and for research purposes. Although the model is usually applied economic impacts analysis of

energy and climate policies, E3ME can also be applied, as in this study, for investigating supply

change, multipliers and labour market impacts.

The figure below summarises the model’s key features. For more details on the model, see the

appendix.

Baseline “Single Tier” modelling approach

description

Consultation with the EC about available input spending data related to the major EU programmes

allowed the conclusion that a reference format of data tracking for EU programmes does exist:

programme data are generally tracked in the form of payments retained by each recipient company

in each EU country. Most payments to subcontractors down the supply chain are tracked, with a

resolution of one thousand Euros.

The approach is based on the following steps:

1. Review of the companies receiving payments within the programme in each country:

The input data in the form of payment per company per country provide a repository of

companies involved in the specific programme, providing an exhaustive de facto mapping

of the space supply chain for that specific programme.

2. Subtraction of imports from input data: Payments given to companies from outside the

EU do not contribute to EU GDP, and are therefore excluded. In fact, some GDP impact to

Europe may still come from payments given to companies outside the EU in the form of

knock-back effects (non-EU companies still buying supplies from EU), but such effects are

very difficult to assess and are usually insignificant.

3. Classification of the companies as Space and Non-Space: Each company in the space

supply chain is classified as (aero)space and non-(aero)space on the basis of their main

source of revenues; indeed, the wider supply chain of any major space programme includes

companies that do not consider space as their main sector of business.

4. Classification of non-space companies into an E3ME industrial sector, and direct

allocation of the related spending to E3ME: Non-space companies are, when applicable

Detailed Coverage

• 33 European regions

+ 20 world regions

• 69/43 economic

sectors and 43/28

consumption

categories

• 22 fuel users of 12

fuels

Consistent

• Based on system of

national accounting

• Input-output tables

• Bilateral trade

Comprehensive

• Whole energy,

environment

(including material)

and economy system

• Two ways feedbacks

between each module

• Many policy

instruments

Forward Looking

• Annual projections to

2050

• Behavioural equations

with effects from

previous outcomes

• Ex-ante scenario

analysis (ex-post also

feasible)

• 1970-2010 database

• 33 stochastic

equations

• No prior assumptions

• Econometrics

specification allows for

short-medium and

long term analysis

• E3: Energy,

Environment (Inc.

material) and

economy modules

• Power generation

sub-module

• Research can be

decentralised

Highly Empirical

Modular


- 13 -

and possible, classified by E3ME as one of the non-space industrial sectors presented in

section 0, and the payments given to those companies are directly allocated to those sectors

as input to the E3ME model.

5. Classification of space companies in sub-categories: Companies that were classified as

space are further aggregated into categories like system integrators/primes, power control,

structures etc., on the basis of their analysed main role within the programme.

6. Retrieval of spending data per each space company sub-category, via offline survey:

The data retrieval is aimed at understanding, for each space category, how much of the

retained EC payment goes into labour, how much is profit (labour and profit together

constitute the space GVA), how much is spent on imports from outside the EU (taken out of

the assessment) and how much goes into untracked spending in other industrial sectors.

This is required to further allocate spending to E3ME non-space sectors.

7. Selection of major companies in each space sub-category for face-to-face meetings

and data retrieval: The major stakeholders and primes are selected for dedicated direct

consultation.

8. Processing of the upstream modelling results and input into the E3ME for the final

wider European economy GDP impact modelling.

The approach relies on an appropriate company classification, via a detailed understanding of

the space programme activities and of the role that major companies play in it. The company

classification effort was checked with major industry players (prime/integrators).

Figure 10 – Schematic of the detailed space upstream modelling approach

The chosen approach characterizes the actual supply chain structure in a non-deterministic manner

(a feature that makes it applicable to different space programmes), and is based on an industry data

retrieval effort that:

Uses aggregated industry data per company category, thus eliminating confidentiality and

sensitivity concerns in the industry data collection process: as source data is never used in

raw form in the final modelling, the data collection can happen under Non-Disclosure

Agreements, making the retrieval of sensitive industry data possible;

Can be easily standardized and implemented at institutional level on a regular basis: the

institution of a dedicated process to collect this data on the industry, under clauses of non-

disclosure of raw data, can be implemented at country and European level.

EC

spending

Space supply chain

Space companies Non-space

GVA:

• Labour spending

• Profit

Further spending:

• Other suppliers untracked in the input data

Sub-categories E3ME non-space

industrial sectors

E3ME

• Labour spending

• Profit

• Specific geographical spending

Step 1

Step 2

Step 3 and 4

Step 5 and 6

Step 7


- 14 -

A standardized procedure for data collection from the industry in aggregated form could make the

chosen methodology easily applicable to different EU programmes. Recommendations on regular

data retrieval processes from the industry are provided as part of the output of this study.

Available data for test case modelling

As explained in more detail in the next section dedicated to the Copernicus case study, the input

spending data set retrieved from EC was comprised of:

Item Type Granularity

Time

period

1 Payments per year, per programme, consolidated per

country

2008-2013

2 Payments per year, per programme, per company, per

country

2008-2013

3 Supply chain data list of involved companies per programme, per

country, with, in some cases, details on the

contract activity

2008-2013

Table 1 – Available data set for the GDP Impact Assessment

The available data covers the entire supply chain, including space and non-space companies involved

in the programme per each country. As mentioned earlier, after a first step involving a review of the

company list, the second step in the modelling process involves the classification of companies into

Aerospace or Non-Aerospace.

Non-Aerospace companies are directly associated to one or more of the selected industrial sectors

included within the E3ME model.

Once this classification is achieved, the single tier model is built as a custom tailored interface to the

E3ME model. This model provides input data to the E3ME model to assess the GDP impact of the EC

and ESA funding per year and per country in the form and format for which E3ME is optimized.

For Aerospace companies, this single tier approach basically derives the aggregated portion of

spending in labour, and untracked raw materials spending, as well as profits expressed in average %

of revenues. Additionally, the classification of non-space companies, in accordance to the E3ME

industrial sector list presented in Table 2, allows provision of aggregated spending in those E3ME

sectors.

The E3ME model then assesses the spending in the wider economy, employees spending, as well as

profits and government taxes.

E3ME

Industry

No. Applicable E3ME sectors

NACE Rev.2

classification

1 Coke & ref petroleum C19

2 Other chemicals C20

3 Rubber & plastic products C22

4 Non-metallic mineral prods C23

5 Basic metals C24

6 Fabricated metal prods C25

7 Computer, optical & electronic C26

8 Electrical equipment C27

9 Other machinery & equipment C28

10 Motor vehicles C29


- 15 -

E3ME

Industry

No. Applicable E3ME sectors

NACE Rev.2

classification

11 Other transport equipment C30

12 Repair & installation machinery C33

13 Electricity Part of D

14 Gas, steam & air conditioning Part of D

15 Water, treatment &supply E36

16 Sewerage & waste management E37-39

17 Construction F

18 Land transport, pipelines H49

19 Water transport H50

20 Air transport H51

21 Accommodation & food services (in Guiana) I

22 Telecommunications J61

23 Computer programming, info services J62_J63

24 Legal, account, & consulting services M69_M70

Table 2 – E3ME sectors identified as relevant in the modelling of the EU space supply chain

The result of the single tier modelling of the space supply chain is a detailed cost breakdown of all

economic activities carried out by companies involved into the programme, as well as the cost

breakdown of non-aerospace activities into sectorial buckets, whether directly performed under EC

contract by non-aerospace companies, or procured by aerospace companies from other sectors. This

results in a detailed allocation by country by sector by aerospace activity type by year, which is used

to feed the E3ME input/output modelling. The results included:

Spending on labour in aerospace, used (as part of the input) to calculate the GDP direct and

induced impact

Cumulative spending in other industrial sectors (E3ME sectors), used to calculate in the E3ME

model the GDP indirect impact, as well as the induced impact

The single-tier model output feeds into the E3ME model. Critical inputs to the E3ME model are

described in the following table.

Item Description Granularity

1 Employment figures (‘000) per year, per country

2 Total compensation of employees

(EUR)

per year, per country

3 Average wage (EUR/person) per year, per country

4 Gross output (EUR) per year, per country

5 Value added (EUR) per year, per country

6 Spending in other sectors per year, per country, for each of the sectors

identified in Table 2

Table 3 – E3ME Model Required Inputs

The E3ME model produces the outputs for the GDP impact assessment, as described in Table 4 below.

Item Description Granularity

1 Value added per year, per country

2 Government revenues / taxes per year, per country

4 Employment per year, per country


- 16 -

5 Multiplier type II - value added per year, per country

6 Multiplier type II – employment per year, per country

Table 4 – E3ME Outputs

The Figure 11 below shows a schematic of the actual space upstream modelling, and the way it

connects to the E3ME model. The figure also shows the logical flow behind the E3ME model itself,

and the outputs it produces.

Figure 11 – Space supply chain modelling and E3ME wider economy model

The GDP impact assessment is carried out by the E3ME model on an annualized basis for the defined

programme periods, and per each participating country. However, since spending effects materialize

over multiple years (and not just in the year of the initial spending) and given the timespan of the

chosen test case, final results in terms of GDP multiplier are presented in the case study as an average

across the entire time-period.

Space Supply Chain Modelling - Black box

model evolution

The chosen modelling approach is based on the retrieval of company spending data per categories.

As a result of the modelling, it is possible to derive an aggregated spending per each country in a

specific space industrial area.

Once a certain number of programmes in the launcher, satellite and service categories have been

modelled, a simpler model could be built and tested. Such a model would work as a black box:

inserting as input spending data per each country would lead to an automatic calculation of space

GVA and spending into E3ME sectors:

In each country, spending allocation within a programme would have to be carried out within

three main categories: space launches, satellite manufacturing, and non-hardware related

space activities (IT, software, etc.).

Within the model, the spending allocation in each of those macro-categories would then

automatically produce a decomposition of the spending into space GVA (i.e. space labour +

profit), imports, and spending into other E3ME sectors.

Spending into the EU space programme

Wages

Suppliers to households

Imports

Savings

Imports

Other suppliers

(not detailed)

Taxes on

purchases

Social Security/

Public Welfare

Income taxes

VAT

Upstream

Modelling

Labour

ProfitProfit

Retained

Earnings

E3ME

Modelling

Capital flow in

Capital flow out

Prime and ALL suppliers (by payment value)

Labour

(by labour ratios)

Single

TIER

…

Imports Spending in other sectors (as per E3ME

categories)

S1

S2

Sn


- 17 -

The results of the black box modelling could then be easily entered into the E3ME model for

a calculation of the overall GDP impact.

Basically, the building and maintaining of such a black box-model allows quick GDP impact

assessments (from a run of the black box model plus a run of the E3ME model). The figure below

shows a schematic of such black-box approach.

Figure 12 – Schematic of a prospective Black-Box approach to space supply chain modelling

for GDP impact assessment

The maintenance of the model would, of course, require continual spending data retrieval and update

from the industry in order to keep model assumptions up to date.

Country i

Launchers Satellites Other

Space GVA

Non space sectors

…

…

%

EU Programme

spending


- 18 -

Micro-diffusion model

Micro-diffusion models are used to understand and assess complex economic phenomena, such as

knowledge and technological spin-offs, and their impacts. The most famous and commonly accepted

micro-diffusion model among economists is the BETA methodology that has been used since the

1980s to assess the spillovers derived from a public investment in a given space

project/grant/contract. It was used successfully for Europe, Canada and the United States of America.

The team has adapted a new methodology derived from the BETA one to assess the revenues enabled

as a result of the Copernicus data and products being free and open; such phenomena require a

micro-economic approach. The following sections present the original BETA methodology and how

it was adapted to assess the spillovers from the Copernicus programme.

The original BETA methodology

The economic benefits enabled by public investments in space activities are mostly intangible and

complex to understand. The changing nature of spillover – spillover and spin-off are both used to

describe such phenomenon – requires a micro-economic approach, rather than a macro-economic

one, in order to understand a complexity of the relationships and impacts at the level of the firm. The

BETA methodology was developed by the Bureau d’Économie Théorique Appliquée at the Université

Louis Pasteur in Strasbourg for this purpose. The main goal was to assess the impact of the knowledge

and expertise developed by an organisation during an ESA contract. The method was used afterwards

to assess the spillover derived from Canadian Space Agency (CSA) and NASA contracts. The

methodology relies on direct face-to-face interviews with executives from a large number of firms

that were contracted by a national space agency. The rationale behind this micro-economic approach

is to understand and capture the value-added of the expertise developed by the company being

employed by a space agency, contract by contract, company per company. The use of this

methodology is commonly accepted among both economists and space agencies to measure the

impact of spin-offs derived from public investments in space activities. It is a robust methodology

that has already been used several times to assess the economic benefits derived from public

investments in space.

The data collection is organised in a three-step process. First, it aims to understand, at the micro-

economic level, if a company has developed a particular knowledge on a contract funded by public

money. Then, if the first answer is positive, the interviewer has to understand if this particular

knowledge has led to significant improvements in the company. If there are significant

improvements, the next stage aims to estimate if this improvement has led to an increase in value-

added captured by the firm, in terms of sales increases, cost reductions and/or the retention or

creation of a critical mass of experts within the company. Finally, the last step aims to estimate the

paternity9 of the impact regarding the government funding, asking for a range of percentage values.

From the given range, the lower figure is always chosen for the analysis to provide a conservative

analysis. The aim here is to make a minimal estimation of a complex phenomenon to

demonstrate its existence rather than giving an exact estimation of the economic benefits

enabled by public investment, here through national space agency contracts.

The quantification method is based on the information gathered during direct interviews, and

secondary data such as internal documents from the companies, studies from expert groups, financial

reports or official reports from national space agencies. The aim of these direct interviews is to

understand and assess the effect over time of the contracts awarded to each company. These effects

9 Paternity means in this context the origin of the phenomena.


- 19 -

have to be unintended to be considered as spillover effects and are measured by quantifying the

added value associated with all investments (Guinet, 2011), estimated as the unintended sales

increase and cost reductions that result as a consequence of the expertise developed under each one

of these contracts. On the other hand, the secondary documents are necessary to better understand

the context and the particularity of a given technology or product, to assess properly the value-added

created and the real contribution of public funding.

The quantification method relies on the assessment of the four following sub-effects (Amesse et al.,

2002) presented below:

Technological effect: an improvement of existing technology and/or the development of a

new technology due to a contract with a national space agency, leading to an increase in

sales or cost reductions (in terms of value-added);

Commercial effect: a reputation effect, where having worked for a national space agency

leads to the development of an actual market or the creation of a new one, leading to an

increase in sales or cost reductions (in terms of value-added);

Organisation effect: the improvement or development of new organisational methods,

and better project management of quality control methods, leading to significant cost

reductions (in terms of value-added)

Critical mass: the retention or creation of a critical mass of experts (also called Highly

Qualified People (HQP)) who contribute to the competitive advantage of the firm.

The three first sub-effects are quantified through value-added at the firm level, represented by

unintended sales increases and cost reductions due to the expertise/technology developed while

working for a national space agency. This added-value is often supported or complemented by the

development and/or maintenance of a critical mass of experts within the firm. This highly skilled core

of people contributes to the competitive advantage of the company. This sub-effect can also be

quantified and expressed in terms of value-added for the company, but it is normally quantified

separately in order to capture the impact of a given national space agency contract on the creation

and/or retention of critical knowledge within an organisation. More details are available in the table

below.

Table 5: Economic effects related to public investments in space (Source: Mosaic, 2014)

The following quantification methodology is based on the work of Cohendet (1997).

Description of sub-effect

Technological effect Sales of technological products not included in the original contract with a national space agency

Sales of new products using a technology acquired or

developed during a contract with a national space

agency

Increased sales of current products enhanced by the

experience of working with a national space agency

Sales by a new department or a new company

created thanks to the technology developed working

with a national space agency

Commercial effect Reputation effect of working with a national space agency

New network and partnerships developed thanks to

the national space agency’s contract

International collaborations

Organizational effect Quality management Project management

Production methods

Critical mass Retention of a critical mass of expertise within the firm

Improvement of existing critical mass

Development of new competences


- 20 -

The final unit of measurement used to express spillover effects on a firm is the added value, together

with the estimated value that results from setting up and maintaining highly skilled design and

production teams (defined above as the “critical mass”). The quantification exercise thus involves

determining how the work carried out by national space agency projects affects these two

parameters. The process is illustrated in the diagram below (Figure 13). The contracts that firms obtain

from the national space agency, like all their other activities, affect the four basic factors

corresponding to the four types of effects described earlier (technological, commercial,

organisational, and critical mass). These, in turn, contribute to increases in sales and reductions in

costs, and thus, under some circumstances, help to increase the firm’s added value.

To quantify the sales increase, the interviewees were asked to estimate, as a percentage, two sets

of coefficients:

The Q1 coefficients accounting for the estimated influence of each effect, whether

technological (Q1t), commercial (Q1c) or organizational (Q1o), on the effective sales increase.

These coefficients represent the proportion of economic value related to each one of the

various effect; the sum of Q1t, Q1c and Q1o must therefore be equal to 100%.

The Q2 coefficients accounting for the (minimal) estimated influence or paternity of national

space agency contracts (or projects, in this case) on each one of the three effects mentioned

above. These coefficients characterize how much of these effects is due to national space

agency investments, with regards to the firms’ other activities; while they must be between

0% and 100%, their sum is not equal to 100%. They are very often based on objective data

such as the share of national space agency’s funding in the development of the product or

service in question.

The increase in added value (related to sales increases) is obtained by multiplying the effective

increase in sales related to national space agency activities by these two sets of coefficients.

To quantify cost reduction, the interviewees were asked to estimate savings on inputs, lower reject

rates, savings in production time and miniaturization. This is calculated:

Directly, by adding up the savings made thanks to methods acquired under national space

agency contracts;

Indirectly, by multiplying the value of savings made over the period under scrutiny with the

percentage of influence of national space agency contracts (provided by the Q2 coefficients).

The increase in added value (related to cost reduction) is obtained by multiplying the effective cost

reduction related to national space agency activities by the set of Q2 coefficients, whenever required.

The total increase in added value is obtained by adding together the increase in sales and the cost

reduction related to national space agency investments. This sum represents the total spillover effect

or non-anticipated revenues generated by the industry over the period under scrutiny in addition to

the “direct” economic effects derived from national space agency investments. The “multiplier” for

each company’s national space agency projects is obtained by dividing the increase in added value

by the total value of the project (or sum of related contracts). The global multiplier is the average of

all company multipliers, or the average value created from the spillover effect for one dollar invested

in space.

This seemingly complex procedure, which remained well understood by all respondents, was

designed to meet two essential requirements. First, it enabled us to isolate the specific contribution

made by national space agency contracts from the firm's other activities, so as to allow for the fact

that technologies or production methods often stem from developments made in a number of

different projects over a period of time. Secondly, it enabled us to provide a minimum estimate of

the volume of spillover effects rather than a precise value attached to them (given, for instance, that

some items may be overlooked). Consequently, the corporate managers taking part in the survey

were asked to assess the influence of national space agency contracts in terms of an estimated range,


- 21 -

of which only the lower figure was used for the final calculation. The focus of this study, in that

respect, is more on the existence of the phenomenon, rather than on its exact quantification.

Figure 13 – Quantification method of economic spillovers (inspired by Mosaic, 2014)10

Once the results have been obtained by type of actors on the sample under scrutiny, the results can

be extrapolated from the sample to the overall population – in most of the cases the overall

population is considered to be the overall contracts granted by a national space agency on a given

period of time. The extrapolation is straightforward and commonly accepted among economists:

once multipliers have been derived from the sample for each type of actors per type of activity, the

same multipliers are applied directly to the overall population per type of activity. The overall results

give a sense of a minimal estimation of the spin-off enabled by the original national space agency

grants/contracts/investments.

The adaptation of BETA methodology to the

context of the revenues enabled by the

availability of Copernicus data & products

The economic impact derived from the availability of Copernicus data and products for free is similar

to the context of a spin-off in terms of economic quantification. As explained in the previous section,

the BETA methodology aims to understand and assess the knowledge created thanks to national

space contract and re-used in another context as either an increase in sales or a reduction in costs.

The free availability of Copernicus data and products for intermediates and end users can be assessed

by understanding and assessing the type of knowledge created by these users thanks to the existence

of a programme such as Copernicus. However, some calculations related to linking cost and revenues,

through the provision of multipliers, cannot be performed in the case of Copernicus. The

quantification of the critical mass of experts also cannot be directly performed because accessing

specific information in each value chain related to the average salary of specific position/jobs within

companies is too sensitive.

10 Source: adapted from Mosaic, 2014. Spillovers effects from CSA contracts for the period from 2005 to 2014. Report

prepared for the Canadian Space Agency. Montréal, Canada.

Non-aerospace activities

Space activities funded by public spending

Other space activities

Technological

effect

Commercial

effect

Organisational

effect

Critical mass

Cost reduction

Sales increase

Estimated value of critical mass

Increase in added

value

Δ Q2 coefficients

(Estimated influence of

national space agency

contract on four effects)

Δ Q1 coefficients

(Estimated influence of

four effects on economic

variables)


- 22 -

The methodology used to assess the revenues enabled by the Copernicus programme is a micro

diffusion model adapted from the original BETA methodology to fit to the context of the use of EO

data, in this particular case, the use of Copernicus data & products. The following paragraphs present

the approach used to assess the revenues enabled by the availability of free Copernicus data &

products.

The first step relies on the characterisation of the value chain under scrutiny. The goal of this

phase is to understand the value-chain and supply-chain structure in order to identify the scope

of analysis. Using a mix of secondary documents and direct consultation with experts, the structure

of each value chain is identified, highlighting the main actors in each value chain. Another goal of

this first expert consultation is to perform an initial market sizing in order to understand the main

components and trends on these markets (market size, growth rate, potential substitution products,

relative importance of EO, etc.).

The second step aims to identify and map the principal actors of a given value chain in order to

understand the role of each one and to gather information on each type of organisations. This step

also aims to develop a prior understanding on how EO data are used in general, and potentially

Copernicus data & products, in the value chain under scrutiny. This step should lead to the creation

of a data base gathering all the relevant information per actor, such as nature & size of actor,

geographic repartition, etc.

The third step is to pick a representative sample of specific end-users for each value chain. This

step varies from the original BETA methodology since no prior data facilitating analysis are available

on the population under scrutiny, such as national space agency’s contracts/grants. In the case of the

Copernicus programme, the team has decided to derive a specific case study within each value chain

considered as representative in terms of geographic repartition and type of actors. Each case study

should include organisations from all type of actors identified in the value-chain structure

(step one) and organisations coming from all over Europe. In statistics, a sample gathering at

least 30% of the observations can be considered representative if these observations chart the

diversity of the overall population in terms of type of actors, geographical repartition and size of the

companies. Given the size of the value chain under scrutiny (European O&G upstream, insurance

for disaster, agriculture, renewable energies, etc.) and the intangible character of the market for

Copernicus data & products within each value chain –no prior economic assessment was

performed on the revenues enabled by an open data EO programme on the value chains under

scrutiny – the team has decided to pick the more representative case studies, without being

able to respect exactly this statistical rule; this element is one of the main limits of the

methodology used.

The fourth step is based on the actual quantification of benefits for the intermediate and end

users of each value chain. It relies on the direct consultation of the organisation included in the

case study pinpointed during the previous step. Two types of data have to be collected during

interviews in order to measure benefits enabled by the availability of free Copernicus data &

products. Qualitative data enables better understanding the specific context of the

organisation and their business model. Understanding how the Copernicus data & products are

used (alone or coupled with other sources of data) and the importance of Copernicus data & products

are useful information to support and complement the quantitative analysis, especially for the

paternity assessment. Quantification of the benefits enabled by Copernicus data is the second

phase of the interview. The aim is to assess the intermediate and end-users’ benefits based on

revenues, investment made to support business development and the role play by Copernicus data

to enable revenues. The quantification process relies on the assessment of the increase in

revenues and reductions in costs, compared to the activities performed by the organisation

before the availability of free Copernicus data & products. The effects are inspired by the original

BETA methodology but they were adapted to better fit the Copernicus programme context. Three


- 23 -

types of effects have to be assessed in order to understand the impacts of Copernicus on the private

end-users. These three effects can be:

Market effect: the availability of open Copernicus data enables an innovative offer for the

private end-users by:

- Increasing sales of existing products;

- Increasing sales of new products on existing markets.

- Creating a new market.

Commercial effect: the availability of open and affordable Copernicus data enables the

development of a new or/and better commercial network for the private end-users by:

- Developing new networks and partnerships thanks to the Copernicus programme;

- Developing international collaborations.

Organisational effect: the availability of open and affordable Copernicus data enables

organisational improvements within the organisation by:

- Improving production methods;

- Improving efficiency/productivity.

Once the users’ benefits are assessed, a range of paternity coming from the Copernicus data &

products is estimated by the team in conjunction with the organisation interviewed. In most of the

cases, once the overall revenues of the company derived from the use of EO data in general have

been assessed, the interviewer can isolate a range for the contribution of Copernicus data & products

to the overall revenues of the firm. This process is strongly related to the qualitative and quantitative

data collected during all the process (context of the firm, substitution products available, etc.). On

this range, the team would automatically take the smallest figure in order to provide a minimal

estimation of the paternity coming from the use of Copernicus data. The aim of this micro-diffusion

approach is to show the existence of the phenomenon rather than providing an exact figure,

in order to prevent any overestimation of benefits. The complexity of the economic

phenomenon in the case of the use of Copernicus data & products justifies the use of a micro-

diffusion model to understand at the level of the firm how the data & products are used and

how they are creating specific knowledge that leads to sales increases or cost reductions. Wider

methodologies such as the GDP impact assessment methodology are not able to capture the

complexity of this type of phenomenon and assess accurately such economic impact.

The fifth and final step is to extrapolate the results obtained in the case study to the overall

population. The aim of the extrapolation is to assess the overall size of the potential market for each

type of actors identified in the first step of the approach. The overall market is assessed using a mix

of public (Annual financial statement, industry reports and surveys, etc.) and private (Bloomberg,

Technavio, Rystad Energy, etc.) sources of data. Once the market of each type of actor has been

identified, the percentage of the overall revenues attributed to the Copernicus data & products per

type of actor is extracted from the case study. The next phase aims to apply these percentages to the

overall size of the market for each type of actor; this step enables the potential size of the market for

Copernicus data & products in the value chain under scrutiny to be assessed.


- 24 -

Summary of the previous

studies

The GDP impact of the public investment made

in the Copernicus programme

The GDP impact of the public investment made in the Copernicus programme is based on the study

prepared by Strategy& in September 2015 for the European Commission. It aims at assessing the

GDP impact related to the joint-investment of EC and ESA in the Copernicus infrastructure

Financial overview

During the period under scrutiny, more than 1.6 billion euros were spent by EC and ESA in the

Copernicus programme. Of the total programme spending in the 2008-2013 period, about 30 %,

representing over EUR 480 M, was funded by EC. In addition to these EUR 480 M, EUR 106 M were

spent by EC as a pre-payment for the future launches of Sentinels satellites. The chart below shows

the split in the five main categories of spending over the period.

Figure 14 – Repartition of EC spending in Copernicus programme over the period 2008-2013

(Source: Strategy&, 2015)4

The geographical repartition of the companies receiving major EC spending enables us to point out

the main regional repartition of spending.

Figure 15 shows the European regional clusters of high economic activity related to Copernicus on

the period 2008-2013.


- 25 -

Figure 15 - Clusters of high economic activity connected to EC spending for the Copernicus

programme in 2008-2013 (Source: Strategy& 2015)

The figure reports a widely-spread clusters activity in Europe enabled by EC investment in Copernicus

programme. As expected, countries like Germany, France or Italy and also to a lesser extent UK and

Spain show clusters of high economic activity connected to the programme. The remaining 70% of

the total programme spending in the 2008-2013 is provided by ESA and represents around EUR 1.2

B over the period 2008-2013. The detailed input data as payment per company per country over the

period for ESA spending in Copernicus was not been made available, so no information regarding

the granularity of the ESA part of spending can be presented here.

Results and analysis Upstream Modelling

Figure 16 represents the repartition of EC-only and overall spending captured by the aerospace

industry but also the impact on other industrial sectors in Europe enabled by such investments. The

countries receiving the biggest share of spending are respectively Germany, France and Italy in both

samples. In both samples, around 3/5 of the spending remains in the aerospace organisations in the

EC-only and overall spending sample with respectively a space GVA of 56% and 60%. However,

spending in non-aerospace sectors are unexpectedly high compared to other public spending in

high-tech industry in Europe with around 40% of the spending in both samples.

Figure 16 – Spending in space GVA and non-aerospace industrial sectors in Europe for the

Copernicus programme over the period 2008-2013 (Source: Strategy&, 2015)

Overall spending in Copernicus programme (2008 – 2013)EC-only spending in Copernicus programme (2008 – 2013)

3%

11%

8%

56%

7%

4%

15%

3%

3%60% 0% 8%

12%

13%

Space GVA

Legal, account, & consulting services

Computer programming, info services

Telecommunications

Computer, optical & electronic

Electrical equipment

Other


- 26 -

These industrial sectors were then regrouped to larger categories to facilitate the spending’s analysis:

Raw materials, including “Coke & ref petroleum”, “Other chemicals”, “Rubber & plastic

products”, “Non-metallic mineral prods”, “Basic metals” and “Fabricated metal prods”;

Basic equipment & machinery, including “Electrical equipment”, “Other machinery &

equipment”, “Motor vehicles”, “Other transport equipment” and “Repair & installation

equipment”;

Value-added equipment, including “Computer, optical & electronic”;

Transport (freight and human), including “Land transport, pipelines”, Water transport” and

“Air transport”;

Facilities (management of existing facilities and new infrastructures), including “Electricity”,

“Gas, stream & air conditioning”, “Water, treatment & supply”, “Sewerage & waste

management”, “Construction” and “Accommodation & food services”;

Services, including “Telecommunications”, “Computer programming, info services” and

“Legal, account & consulting services”.

Figure 17 – Spending in non-aerospace organisations in Europe for the Copernicus

programme over the period 2008-2013 (Source: Strategy&, 2015)4

Even if some difference in terms of percentage can be noticed between both samples, the biggest

share of spending in non-aerospace sectors, more than 65%, is supporting the space manufacturing

industry (raw materials, basic equipment & machinery and value-added equipment). Facilities and

transport spending are rather high and correlated with the space manufacturing industry in order to

support this activity. Finally, investments in the services have 2 components. The first one is funding

technical experts to support the manufacturing part of activities (mostly engineering consultants).

The second one is supporting the development of applications and services and ground activities to

enable the Copernicus core services.

The difference between both samples can be explained by the composition of the overall spending

sample using only Top10 companies which gathers mainly satellites and ground equipment

manufacturing companies. This statement explains the strong importance of basic equipment &

machinery in the overall sample and the decreasing importance of raw materials. Since raw materials

are usually less expensive than value-added equipment and basic equipment & machinery, in a large

sample such as the overall one (compared to the EC-only sample), raw materials spending are diluted

and less important in terms of percentage.

GDP Impact Assessment (E3ME) results

The logic underpinning the calculation of the Type II multiplier using the E3ME model is as follows:

16%

6%

11%

29%

31%

6%

study to examine the socio- economic impact of copernicus ... · programme case study. final report...

Documents