Eem macro inclusion

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(Word version of document https://wiki.gpii.net/images/b/bc/Macroeconomic_Impacts_of_InclusionKMS3.docx )

(PDF version of document https://wiki.gpii.net/images/6/6a/Macroeconomic_Impacts_of_InclusionKMS3.pdf )

PDF version of shorter report (used in Prosperity4All deliverable) https://wiki.gpii.net/images/9/9a/Eem_macro_inclusion.pdf

Macroeconomic Impacts of Increased Inclusion on EU Economy Kevin Stolarick, PhD

Contents Explanation of Estimation Approach 2 Usefulness of this analysis to the rest of the project 2 Data Used; Disability and Limitations 2 EU-wide & Country-specific 2 Labor Market Impacts 2 Inclusion in Employment 2 Inclusion in Income 2 Inclusion in Education 2 Combined Annual Value of Increased Inclusion 2 Market (Supply/Demand) Impacts 2 Increased General Retail/Services Sales 2 Increased Sales of Accessible Products and Services 2 Potential Impacts of P4All on the ecosystem enabled by the infrastructure 2 Appendix One – Eurostat Data Sources 2 Appendix Two – EU Country Codes and Names 2

  Explanation of Estimation Approach This analysis is based on the pioneering work in estimating the potential economic impact of inclusion first used in the University of Toronto’s Martin Prosperity Institute’s work Releasing Constraints by Kemper, Stolarick, Milway, and Treviranus. Estimates are based on the assumption that increased inclusion creates increased opportunities that can be realized. These are potential opportunities based on achieving a very high (and likely unattainable but still aspirational) level of inclusion that are then adjusted to reflect expectations.

This analysis proceeds in two steps and in two different areas of potential impact. The first step is to estimate the potential impact of increased inclusion at an overall macroeconomic level. Estimates are developed for the entire EU and then on a country by country basis for each of the member states. These estimates are adjusted to reflect optimistic, realistic, and pessimistic expectations around the effectiveness of increased inclusion efforts. Once developed, these estimates show the annual macroeconomic impact that could be generated by successfully increasing economic inclusion of people with disabilities. These estimates are based on creating a full spectrum of inclusion that spans across the full range of possible challenges from physical, medical, mental, lifestyle, and other limitations.

Prosperity4All is not designed to address this full spectrum. Rather, Prosperity4All addresses inclusion across ICTs and focuses on developing the infrastructure to allow a new ecosystem to grow; one that is based on self-rewarding collaboration, that can reduce redundant development, lower costs, increase market reach and penetration internationally, and create the robust cross-platform spectrum of mainstream and assistive technology based access solutions required. While that development has the potential to impact a wide swath of disability-related challenges, by design, it will not address all the limitations that would be needed to achieve the full estimated impact. The second step is to take the estimates from the first step and reduce them to only include the potential impacts that could be expected from the implementation of Prosperity4All.

This analysis also considers two different areas of potential impact. The first is labor market impacts. By examining the differences for employment, income, and educational attainment between the EU-wide and national averages and those with disabilities, the impact from closing the gap can be estimated. What would happen if people with disabilities were employed at the same level as the population? What if their earnings had the same distribution? What if their educational attainment levels were the same as the EU or national average? This impact is based on the (somewhat) “heroic” but necessary assumption that this level of inclusion could be achieved, but those estimates do take degree of disability into account and also are then adjusted to differing potential expectations.

The second area of potential impact that is included considers the macroeconomic effects on the market for goods and services that could be expected from increased inclusion. This impact is at two levels. The first is the general market for retail goods and services. Increased inclusion creates a larger market with correspondingly greater demand. Inclusion, by definition, means that more people are able to access retail opportunities to purchase goods and services. This is especially true in the realm of ICT enabled markets which make up an increasing share of the general retail market. The potential impact on retail markets is made assuming the implementation of Prosperity4All. The impact is estimated as a range which primarily reflects a percentage increase in market size. The second level of market impacts is more specific to Prosperity4All. It is an estimate of the impact on the market for accessibility technologies and other accessibility-related goods and services. As specific estimates of the current market size for accessibility-related goods and services is not available, this is estimated using the current market for ICT goods and services.

With all of the estimates developed in this report, the intention is to provide clarity about the assumptions and the methods used to generate those estimates. The reader is encouraged to question the assumptions and develop their own robust estimates based on their assumptions. The question is not whether the impacts outlined here will happen. They will to some degree and will increase with greater inclusion. The question is the degree to which they will happen. Even at one-tenth of the impact estimated here, the results are still important and significant, and that is the broader point of this analysis.

Usefulness of this analysis to the rest of the project The estimates developed here are high-level and are intended to show the potential macroeconomic impact of increased inclusion across the EU and within its member states. These estimates are not individual estimates of impact from individual components and sub-projects of Prosperity4All. By design, these estimates show the potential economic impact created by the development of the inclusive ecosystem that the Prosperity4All infrastructure will enable. This is potential system-wide, top-down impact estimates and not a bottom-up aggregation of individual estimates of specific components.

These estimates are designed to show the significant potential impact that could be realized from increased inclusion across Europe. For the individual components and sub-projects of Prosperity4All, these estimates provide a greater sense of the scope of impact of this project and what greater inclusion for people with disabilities could mean for the economies of Europe. Additionally, these estimates document the benefits of greater inclusion. This should serve as a clarion call and motivation for the Prosperity4All project teams to always strive for greater inclusion and the development of more inclusive designs and approaches as outlined in other SP1 deliverables. The estimates presented here show the potential of what could happen – it is the challenge to the project teams to implement solutions that realize this potential.

Data Used; Disability and Limitations This analysis relies exclusively on data provided by Eurostat . This data includes overall macroeconomic data and indicators and specific information on people with disabilities. This data is available for both the entire EU and for all of the 28 individual member states. Macroeconomic data from 2013 was the most complete and widely available and is what is used here. All estimates are for average annual impact. Where appropriate, only working age population (15-64) are considered.

The 2011 European Health and Social Integration Survey (EHSIS) forms the basis for the economic participation and disability data used to estimate the gaps between those with and without disabilities. The data collected in that survey differentiated individuals into three levels of impairment severity based on limitations in life areas. From the metadata definitions for the survey data : According to the biopsychosocial model applied to the survey, people with disabilities are those who face barriers to participation in any of 10 life areas, associated inter alia with a health problem or basic activity limitation. Therefore, a person identifying a health problem or basic activity limitation as barrier in any life domain is categorised as disabled.

As regards the severity of disability, several measures can be derived from the survey. The following ones were considered for presenting the results: Severity of disability indicator calculated by adding up the number of life areas where a respondent encounters a barrier associated with a health problem or basic activity limitation. The following levels were created: LD1 Barriers to participation in 1 life domain LD2-3 Barriers to participation in 2-3 life domains LD_GE4 Barriers to participation in 4 or more life domains

This definition results in disability determination based on limitations, a functional based approach, which fits well with the potential impacts of Prosperity4All in reducing or elimination functional limitations with ICT and ICT-related accessibility. It also aligns with the typical framework of identifying disabilities as being moderate (LD1), mild (LD2-3), or severe (LD_GE4). While the estimates and discussion are based on the idea of increasing inclusion, the actual data being used supports an analysis based on reducing or eliminating barriers and limitations. While it can easily be argued that those two ideas, increasing inclusion/eliminating barriers, are the same thing as in the case in this analysis which relies on reducing barriers to increase participation, it should be noted that increasing inclusion and inclusive design are more than accessibility and eliminating barriers. Inclusion is an active process that should go beyond merely increasing accessibility. While accessibility is an important and necessary first step, it is, by itself, insufficient to guarantee inclusion. The goal should always be to enhance inclusion and not just increase accessibility. EU-wide & Country-specific Labor Market Impacts Both EU-wide and member-nation-specific estimates for potential annual impact from increased inclusion are developed. These estimates are developed for: (1) increasing employment of those with disabilities to equal averages; (2) increasing income levels of those with disabilities so the distribution matches the overall distribution; and (3) increasing educational attainment, with corresponding wage impacts, of those with disabilities to equal averages. Both EU-wide and national averages are considered.

A similar process is used for each of these three estimates: 1. Determine the gap between the overall average and the average for those with a disability using the three limitation (severity) levels. 2. For each gap, estimate the potential to close that gap using optimistic, realistic, and pessimistic assumptions. These assumptions are based on the share of the gap that can be closed . Those assumptions are: a. “Optimistic” i. 100% for those with 1 limitation (mild disability) ii. 75% for those with 2-3 limitations (moderate disability) iii. 25% for those with 4 or more limitations (severe disability) b. “Realistic” i. 75% for those with 1 limitation (mild disability) ii. 50% for those with 2-3 limitations (moderate disability) iii. 25% for those with 4 or more limitations (severe disability) c. “Pessimistic” i. 50% for those with 1 limitation (mild disability) ii. 25% for those with 2-3 limitations (moderate disability) iii. 10% for those with 4 or more limitations (severe disability) 3. Convert those estimates to annual economic impact (in Euro) based on those with a disability closing a portion of the gap and reaching overall average levels. 4. These estimates will show the overall potential macroeconomic impact of increased inclusion which will later be adjusted to estimate the potential impact resulting from the implementation of Prosperity4All.

For each set of estimates, first the overall EU estimate will be presented, then the individual member state estimates.

Inclusion in Employment

EU EU27/28 (M) LD_1 (000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 329.34 25,936.80 21,025.20 26,068.50 73,030.50 Employed 213.38 9,048.80 4,554.90 2,948.10 16,551.80 Share Employed 64.8% 34.9% 21.7% 11.3% 22.7% Gap (%) 29.9% 43.1% 53.5% 42.1% Gap (people) 7,755.81 9,067.45 13,941.84 30,765.10 Average Wage (€) 18,080

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 140,225 26,637 63,017 229,879 Realistic 75-50-25 105,169 17,758 63,017 185,944 Pessimistic 50-25-10 70,113 8,879 25,207 104,198

Increased economic inclusion of people with disabilities could generate between 100 and 230 billion Euro in additional employment income every year. While getting to the point of closing the employment gap (pessimistic assumption) for 50% of those with a mild disability (LD_1), 25% of those with a moderate disability (LD_2-3) and 10% of those with a severe disability (LD_GE4) would be a significant undertaking and require action well beyond what is being taken by Prosperity4All, the potential macroeconomic impact is significant. Estimates for specific impacts from Prosperity4All are developed later in this report.

The table below summarizes the results for each of the 25 countries for which detailed data to develop the estimates is available. When considered on an individual basis, which compares overall employment rates at the country level to that same country’s employment rates for people with disabilities (so, for example, the estimates use Greece’s 49.4% employment rate as the baseline to reach for those with a disability but also considers Germany’s 73.8% employment rate), the aggregate impact is higher than the impact calculated using EU average values. Note that the aggregate does not include Estonia, Ireland, or Croatia. At a country level, the potential impact of inclusion in employment obviously varies by country size but still ranges in the hundreds of millions to billions of Euro annually.


Country Optimistic 100-75-25 (M €) Realistic 75-50-25 (M €) Pessimistic 50-25-10 (M €) EU28/27 229,879.0 185,943.8 104,198.3 25 Countries Aggregate 231,924.8 186,477.7 105,113.7

Belgique/België 5,008.5 4,066.3 2,256.6 Bulgarija 1,163.1 928.9 548.0 Česká republika 2,373.4 1,940.3 1,086.4 Danmark 5,371.2 4,352.7 2,399.1 Deutschland 59,658.2 47,354.0 26,646.9 Elláda 2,115.0 1,705.7 982.3 España 16,601.6 13,465.2 7,622.5 France 29,582.3 23,603.5 13,446.3 Italia 21,188.4 17,294.1 9,843.2 Kýpros 325.2 262.1 146.8 Latvija 500.4 399.6 230.0 Lietuva 697.8 562.9 323.0 Luxembourg 315.7 246.8 139.5 Magyarország 1,802.5 1,509.5 811.4 Malta 146.5 114.3 69.8 Nederland 10,097.8 7,902.0 4,548.4 Österreich 6,687.0 5,181.2 3,135.5 Polska 7,210.5 5,856.6 3,345.3 Portugal 2,491.3 1,974.0 1,176.7 România 1,358.0 1,137.9 612.2 Slovenija 743.5 595.9 340.8 Slovensko 1,061.5 833.4 491.7 Suomi/Finland 4,267.9 3,342.1 1,978.8 Sverige 7,231.6 5,590.6 3,347.0 United Kingdom 43,925.8 36,258.2 19,585.4

The tables below include individual country estimates (all in Euro) for those member states for which detailed information is available.

Belgique/België Country (M) LD_1 (000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 7.27 679.40 379.50 494.50 1,553.40 Employed 4.50 300.10 85.90 69.50 455.50 Share Employed 61.9% 44.2% 22.6% 14.1% 29.3% Gap (%) 17.7% 39.3% 47.8% 32.6% Gap (people) 120.44 149.01 236.59 506.05 Average Wage (€) 24,445

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 2,944 618 1,446 5,009 Realistic 75-50-25 2,208 412 1,446 4,066 Pessimistic 50-25-10 1,472 206 578 2,257


Bulgarija Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 4.80 600.60 312.50 456.40 1,369.50 Employed 2.93 138.90 40.00 20.80 199.70 Share Employed 61.0% 23.1% 12.8% 4.6% 14.6% Gap (%) 37.9% 48.2% 56.5% 46.5% Gap (people) 227.73 150.76 257.80 636.29 Average Wage (€) 3,793

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 864 55 244 1,163 Realistic 75-50-25 648 37 244 929 Pessimistic 50-25-10 432 18 98 548


Česká republika Country (M) LD_1 (000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 7.08 374.00 362.40 535.80 1,272.20 Employed 4.88 93.70 47.50 60.59 201.79 Share Employed 69.0% 25.1% 13.1% 11.3% 15.9% Gap (%) 43.9% 55.9% 57.7% 53.1% Gap (people) 164.23 202.43 308.92 675.57 Average Wage (€) 9,081

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 1,491 181 701 2,373 Realistic 75-50-25 1,119 120 701 1,940 Pessimistic 50-25-10 746 60 281 1,086


Danmark Country (M) LD_1 (000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 3.63 321.90 265.70 331.60 919.20 Employed 2.64 135.60 79.30 38.20 253.10 Share Employed 72.8% 42.1% 29.8% 11.5% 27.5% Gap (%) 30.7% 43.0% 61.3% 45.3% Gap (people) 98.76 114.14 203.22 416.12 Average Wage (€) 30,673

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 3,029 784 1,558 5,371 Realistic 75-50-25 2,272 522 1,558 4,353 Pessimistic 50-25-10 1,515 261 623 2,399


Deutschland Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 52.74 5,740.60 4,540.20 4,503.00 14,783.80 Employed 38.92 2,732.10 1,525.50 913.20 5,170.80 Share Employed 73.8% 47.6% 33.6% 20.3% 35.0% Gap (%) 26.2% 40.2% 53.5% 38.8% Gap (people) 1,503.93 1,824.75 2,409.60 5,738.28 Average Wage (€) 23,248

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 34,963 10,690 14,005 59,658 Realistic 75-50-25 26,223 7,127 14,005 47,354 Pessimistic 50-25-10 17,482 3,563 5,602 26,647


Elláda Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 7.04 607.30 497.30 582.00 1,686.60 Employed 3.48 146.00 48.80 65.82 260.62 Share Employed 49.4% 24.0% 9.8% 11.3% 15.5% Gap (%) 25.4% 39.6% 38.1% 34.0% Gap (people) 154.14 196.98 221.82 572.93 Average Wage (€) 9,438

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 1,455 137 523 2,115 Realistic 75-50-25 1,091 91 523 1,706 Pessimistic 50-25-10 727 46 209 982


España Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 30.75 2,012.40 2,159.90 2,378.80 6,551.10 Employed 17.21 458.00 256.90 207.40 922.30 Share Employed 56.0% 22.8% 11.9% 8.7% 14.1% Gap (%) 33.2% 44.1% 47.3% 41.9% Gap (people) 668.32 951.97 1,123.99 2,744.28 Average Wage (€) 16,052

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 10,728 1,363 4,511 16,602 Realistic 75-50-25 8,046 909 4,511 13,465 Pessimistic 50-25-10 5,364 454 1,804 7,623


France Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 40.93 2,478.80 2,071.80 2,254.80 6,805.40 Employed 26.11 836.50 564.80 330.60 1,731.90 Share Employed 63.8% 33.7% 27.3% 14.7% 25.4% Gap (%) 30.0% 36.5% 49.1% 38.3% Gap (people) 744.71 756.79 1,107.72 2,609.23 Average Wage (€) 25,147

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 18,727 3,891 6,964 29,582 Realistic 75-50-25 14,045 2,594 6,964 23,603 Pessimistic 50-25-10 9,364 1,297 2,786 13,446


Italia Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 39.16 2,303.30 2,185.50 2,910.70 7,399.50 Employed 21.81 503.00 139.90 329.17 972.07 Share Employed 55.7% 21.8% 6.4% 11.3% 13.1% Gap (%) 33.9% 49.3% 44.4% 42.6% Gap (people) 779.75 1,077.24 1,291.85 3,148.84 Average Wage (€) 18,354

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 14,311 949 5,928 21,188 Realistic 75-50-25 10,734 633 5,928 17,294 Pessimistic 50-25-10 7,156 316 2,371 9,843


Kýpros Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 0.57 37.80 32.30 34.00 104.10 Employed 0.36 13.80 7.00 3.85 24.64 Share Employed 62.1% 36.5% 21.7% 11.3% 23.7% Gap (%) 25.6% 40.5% 50.8% 38.5% Gap (people) 9.69 13.07 17.28 40.04 Average Wage (€) 20,162

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 195 43 87 87 Realistic 75-50-25 146 29 87 87 Pessimistic 50-25-10 98 14 35 35


Latvija Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 1.30 149.50 129.90 126.00 405.40 Employed 0.86 43.60 24.80 7.10 75.50 Share Employed 66.3% 29.2% 19.1% 5.6% 18.6% Gap (%) 37.1% 47.2% 60.7% 47.7% Gap (people) 55.50 61.31 76.42 193.22 Average Wage (€) 6,002

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 333 53 115 500 Realistic 75-50-25 250 35 115 400 Pessimistic 50-25-10 167 18 46 230


Lietuva Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 1.96 212.60 181.00 191.90 585.50 Employed 1.29 60.60 20.80 9.00 90.40 Share Employed 65.7% 28.5% 11.5% 4.7% 15.4% Gap (%) 37.2% 54.2% 61.0% 50.2% Gap (people) 79.04 98.08 117.04 294.16 Average Wage (€) 5,977

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 472 51 175 698 Realistic 75-50-25 354 34 175 563 Pessimistic 50-25-10 236 17 70 323


Luxembourg Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 0.36 30.60 22.20 15.50 68.30 Employed 0.24 15.80 8.00 3.80 27.60 Share Employed 66.6% 51.6% 36.0% 24.5% 40.4% Gap (%) 15.0% 30.6% 42.1% 26.2% Gap (people) 4.59 6.79 6.53 17.91 Average Wage (€) 39,188

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 180 72 64 316 Realistic 75-50-25 135 48 64 247 Pessimistic 50-25-10 90 24 26 139


Magyarország Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 6.59 651.80 505.60 915.40 2,072.80 Employed 4.07 212.00 72.40 47.20 331.60 Share Employed 61.8% 32.5% 14.3% 5.2% 16.0% Gap (%) 29.3% 47.5% 56.6% 45.8% Gap (people) 190.68 239.96 518.34 948.98 Average Wage (€) 5,209

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 993 134 675 1,803 Realistic 75-50-25 745 89 675 1,509 Pessimistic 50-25-10 497 45 270 811


Malta Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 0.28 20.10 10.70 11.30 42.10 Employed 0.18 4.30 1.70 1.28 7.28 Share Employed 62.3% 21.4% 15.9% 11.3% 17.3% Gap (%) 40.9% 46.4% 51.0% 45.0% Gap (people) 8.23 4.97 5.76 18.96 Average Wage (€) 14,277

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 117 8 21 146 Realistic 75-50-25 88 6 21 114 Pessimistic 50-25-10 59 3 8 70


Nederland Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 10.98 976.90 775.90 642.30 2,395.10 Employed 8.03 447.80 284.90 144.30 877.00 Share Employed 73.1% 45.8% 36.7% 22.5% 36.6% Gap (%) 27.3% 36.4% 50.7% 36.5% Gap (people) 266.48 282.41 325.33 874.22 Average Wage (€) 23,727

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 6,323 1,845 1,930 10,098 Realistic 75-50-25 4,742 1,230 1,930 7,902 Pessimistic 50-25-10 3,161 615 772 4,548


Österreich Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 5.68 598.50 301.10 263.10 1,162.70 Employed 4.03 227.00 88.20 46.40 361.60 Share Employed 71.1% 37.9% 29.3% 17.6% 31.1% Gap (%) 33.1% 41.8% 53.4% 40.0% Gap (people) 198.40 125.81 140.60 464.81 Average Wage (€) 25,602

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 5,079 708 900 6,687 Realistic 75-50-25 3,810 472 900 5,181 Pessimistic 50-25-10 2,540 236 360 3,136


Polska Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 25.28 1,972.50 1,641.90 2,190.70 5,805.10 Employed 15.59 421.80 170.30 94.40 686.50 Share Employed 61.7% 21.4% 10.4% 4.3% 11.8% Gap (%) 40.3% 51.3% 57.4% 49.9% Gap (people) 794.81 842.40 1,256.79 2,894.01 Average Wage (€) 6,139

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 4,879 402 1,929 7,211 Realistic 75-50-25 3,660 268 1,929 5,857 Pessimistic 50-25-10 2,440 134 772 3,345


Portugal Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 6.79 509.10 355.90 359.60 1,224.60 Employed 4.25 131.80 33.00 40.67 205.47 Share Employed 62.6% 25.9% 9.3% 11.3% 16.8% Gap (%) 36.7% 53.3% 51.3% 45.8% Gap (people) 186.99 189.86 184.51 561.36 Average Wage (€) 10,114

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 1,891 134 467 2,491 Realistic 75-50-25 1,418 89 467 1,974 Pessimistic 50-25-10 946 45 187 1,177


România Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 13.53 942.30 825.80 1,495.50 3,263.60 Employed 8.25 265.30 109.10 75.30 449.70 Share Employed 61.0% 28.2% 13.2% 5.0% 13.8% Gap (%) 32.9% 47.8% 56.0% 47.2% Gap (people) 309.72 394.83 837.30 1,541.85 Average Wage (€) 2,433

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 754 95 509 1,358 Realistic 75-50-25 565 63 509 1,138 Pessimistic 50-25-10 377 32 204 612


Slovenija Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 1.40 120.10 94.80 105.30 320.20 Employed 0.89 39.30 18.00 12.10 69.40 Share Employed 63.9% 32.7% 19.0% 11.5% 21.7% Gap (%) 31.2% 44.9% 52.4% 42.2% Gap (people) 37.43 42.56 55.17 135.16 Average Wage (€) 12,981

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 486 79 179 744 Realistic 75-50-25 364 52 179 596 Pessimistic 50-25-10 243 26 72 341


Slovensko Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 3.85 340.60 276.70 196.80 814.10 Employed 2.35 108.20 49.20 19.80 177.20 Share Employed 61.0% 31.8% 17.8% 10.1% 21.8% Gap (%) 29.2% 43.2% 50.9% 39.2% Gap (people) 99.48 119.51 100.20 319.19 Average Wage (€) 7,557

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 752 120 189 1,061 Realistic 75-50-25 564 80 189 833 Pessimistic 50-25-10 376 40 76 492


Suomi/Finland Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 3.47 331.80 242.60 193.10 767.50 Employed 2.39 115.80 50.70 25.20 191.70 Share Employed 68.7% 34.9% 20.9% 13.1% 25.0% Gap (%) 33.8% 47.8% 55.7% 43.7% Gap (people) 112.23 116.03 107.51 335.76 Average Wage (€) 27,134

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 3,045 493 729 4,268 Realistic 75-50-25 2,284 329 729 3,342 Pessimistic 50-25-10 1,523 164 292 1,979


Sverige Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 6.14 574.90 345.80 244.30 1,165.00 Employed 4.60 252.10 100.50 45.60 398.20 Share Employed 74.9% 43.9% 29.1% 18.7% 34.2% Gap (%) 31.0% 45.8% 56.2% 40.7% Gap (people) 178.28 158.37 137.29 473.94 Average Wage (€) 29,263

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 5,217 1,010 1,004 7,232 Realistic 75-50-25 3,913 673 1,004 5,591 Pessimistic 50-25-10 2,609 337 402 3,347


United Kingdom Country

(M)	LD_1

(000) LD_2-3 (000) LD_GE4 (000) Any Limitation (000) Population 41.07 3,260.20 2,442.50 4,565.80 10,268.50 Employed 29.53 1,315.40 716.20 672.40 2,704.00 Share Employed 71.9% 40.3% 29.3% 14.7% 26.3% Gap (%) 31.6% 42.6% 57.2% 45.6% Gap (people) 1,028.62 1,039.91 2,610.33 4,678.86 Average Wage (€) 22,999

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 23,657 5,260 15,009 43,926 Realistic 75-50-25 17,743 3,507 15,009 36,258 Pessimistic 50-25-10 11,829 1,753 6,003 19,585

  Inclusion in Income Distribution A second approach to estimating the potential macroeconomic impact of inclusion is to consider the distribution of income and compare the distribution of income for the general population and those with disabilities. The gaps in the distributions can then be identified and estimates made from closing those gaps. Again, separate estimates can be developed based on severity of disability (LD_1, LD_2-3, LD_GE4) with optimistic, realistic, and pessimistic assumptions for narrowing those gaps. As before, estimates using values for the entire EU are first developed, followed by estimates for the individual member states. Again, the overall macroeconomic (income quartile distribution) data are from 2013 and the data on disabilities is from the 2012 EHSIS survey results.

EU 27 Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 10,111 20% 32.3% 38.1% 46.8% -12.3% -18.1% -26.8% 2 10,111 - 13,652 20% 22.5% 24.4% 23.8% -2.5% -4.4% -3.8% 3 13,652 - 17,540 20% 20.1% 18.4% 16.2% -0.1% 1.6% 3.8% 4 17,540 - 23,308 20% 14.7% 12.4% 8.8% 5.3% 7.6% 11.2% 5 23,308 + 20% 10.4% 6.7% 4.4% 9.6% 13.3% 15.6%

Number of People Shift In/Out (000) Quintile Midpoint (€) LD_1 LD_2-3 LD_GE4 1 5,056 -3,202 -3,809 -6,993 2 11,882 -647 -935 -1,002 3 15,596 -28 345 1,000 4 20,424 1,383 1,607 2,925 5 23,308 2,495 2,793 4,070

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 62,066 54,691 30,735 147,492 Realistic 75-50-25 46,549 36,461 30,735 113,745 Pessimistic 50-25-10 31,033 18,230 12,294 61,557

Some explanation is needed for each table. The first shows how the income distributions are different between the overall population and the population of people with disabilities. While for the overall population, 20% of the total is in each income quintile, that is not the case for people with disabilities who are strongly over-represented in the lower income quintiles and under-estimated in the higher income quintiles. As a result, you have a negative gap when the share is higher than it should be and a positive gap when the share is lower.

The second table shows the number of individuals for each severity level that would have to shift for the income distribution among those with a disability to be the same as the overall income distribution for the EU. It shows the number of people who would have to move out of each lower income quintile and the number that would have to move into the higher income quintiles. When overall impact is calculated, the midpoint of lower income quintiles is subtracted out and the midpoint from higher income quintiles is added back in to develop a net change impact.

The final table shows the results, using the previous assumptions of varying percentages in accomplishing the necessary changes to achieve that percentage of the net change impact. So, for example, the optimistic assumption would be that 100% of the shift could be made for people with a mild disability (LD_1) and 75% of the shift for those with a moderate disability (LD_2-3) and 25% of the necessary shift among the income quintiles for those with a severe disability (LD_GE4). So, the impact of the full shift as shown in the second table is first calculated, and this is then weighted by the percentage assumptions. If the full shift (moving everyone with a severe disability so their income distribution was 20% in each quintile) could be made, the overall impact would be to increase wages annually across the EU by nearly 123 million Euro.

The EU-wide results show that if even a portion of the necessary shift in incomes could be made so that the income distribution for people with disabilities could more resemble the average distribution the annual increase in incomes would range from 61 to nearly 150 million Euro.

The table below shows the country by country estimates for the 25 countries for which data is available. It also shows the aggregate of those 25 countries which is slightly lower than the EU-wide estimated impact. This difference is due to the variability in income quintile ranges across countries and the use of quintile midpoints for the estimates, but the results are very similar. As with employment, increased inclusion for people with disabilities across the countries of the EU could result in annual income increases in the hundreds of millions to billions of Euro.

Country Optimistic 100-75-25 (M €) Realistic 75-50-25 (M €) Pessimistic 50-25-10 (M €) EU28/27 147,492.2 113,745.3 61,557.3 25 Countries Aggregate 122,406.2 94,287.8 50,903.3

Belgique/België 464.5 420.0 277.0 Bulgarija 932.6 715.3 413.1 Česká republika 141.7 115.0 55.6 Danmark 2,338.2 1,810.7 934.1 Deutschland 41,831.1 31,950.9 17,366.6 Elláda 867.5 623.1 356.5 España 13,014.8 9,639.7 5,271.0 France 10,809.0 8,339.3 4,316.7 Italia 13,629.9 10,391.9 5,789.5 Kýpros 200.4 150.6 84.4 Latvija 362.6 271.7 154.7 Lietuva 208.2 162.4 90.1 Luxembourg 274.0 204.9 121.2 Magyarország 1,150.6 909.9 488.8 Malta 64.4 48.5 29.0 Nederland 4,600.8 3,396.4 1,864.4 Österreich 2,691.9 2,008.5 1,187.5 Polska 3,556.0 2,720.4 1,503.9 Portugal -630.0 -464.7 -212.6 România 2,274.7 1,756.2 968.2 Slovenija 335.7 260.5 137.8 Slovensko 769.7 568.7 320.6 Suomi/Finland 2,584.3 1,934.7 1,102.7 Sverige 1,823.2 1,383.5 830.7 United Kingdom 18,110.3 14,969.5 7,451.9


Below are results for individual countries. The individual shift in income quintiles (the second table above) is not shown but the data is available. In some cases, especially among countries with lower average incomes, the share of the population with a disability and in a high income quartile can be more than 20%. In that case, getting the income distribution to match the average would require shifting people with disabilities from a higher income quintile to a lower one. We are, quite obviously, not arguing that income for anyone with a disability should be decreased. However, in keeping with the approach taken here of getting the income distribution to match the general population, the estimates are done in that way – reducing total impact on income. By doing this, it can easily be argued that the true impact of achieving a consistent income distribution though inclusion of those with disabilities would be higher than what is shown here, especially for those countries with more than 20% of a population with a disability in a higher income quintile.

Belgique/België Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 14,030 20% 19.0% 18.9% 29.7% 1.0% 1.1% -9.7% 2 14,030 - 18,943 20% 30.4% 20.5% 22.6% -10.4% -0.5% -2.6% 3 18,943 - 24,178 20% 17.8% 11.2% 10.6% 2.2% 8.8% 9.4% 4 24,178 - 30,573 20% 18.2% 10.2% 5.4% 1.8% 9.8% 14.6% 5 30,573 + 20% 14.5% 39.1% 31.8% 5.5% -19.1% -11.8%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 667.4 -367.1 164.2 464.5 Realistic 75-50-25 500.5 -244.8 164.2 420.0 Pessimistic 50-25-10 333.7 -122.4 65.7 277.0


Bulgarija Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 1,713 20% 39.0% 43.6% 51.9% -19.0% -23.6% -31.9% 2 1,713 - 2,528 20% 35.9% 34.0% 33.0% -15.9% -14.0% -13.0% 3 2,528 - 3,396 20% 13.5% 9.4% 7.3% 6.5% 10.6% 12.7% 4 3,396 - 4,717 20% 3.9% 6.5% 3.9% 16.1% 13.5% 16.1% 5 4,717 + 20% 7.6% 6.5% 3.9% 12.4% 13.5% 16.1%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 556.7 234.6 141.4 932.6 Realistic 75-50-25 417.5 156.4 141.4 715.3 Pessimistic 50-25-10 278.4 78.2 56.5 413.1


Česká republika Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 5,734 20% 25.3% 21.7% 24.6% -5.3% -1.7% -4.6% 2 5,734 - 7,044 20% 18.7% 29.9% 26.6% 1.3% -9.9% -6.6% 3 7,044 - 8,443 20% 15.7% 13.6% 16.0% 4.3% 6.4% 4.0% 4 8,443 - 10,883 20% 7.3% 6.9% 9.4% 12.7% 13.1% 10.6% 5 10,883 + 20% 33.0% 28.0% 23.5% -13.0% -8.0% -3.5%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 28.5 58.7 54.5 141.7 Realistic 75-50-25 21.4 39.1 54.5 115.0 Pessimistic 50-25-10 14.3 19.6 21.8 55.6


Danmark Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 18,556 20% 27.8% 40.3% 44.7% -7.8% -20.3% -24.7% 2 18,556 - 24,073 20% 20.2% 20.4% 24.4% -0.2% -0.4% -4.4% 3 24,073 - 29,824 20% 19.6% 17.6% 18.9% 0.4% 2.4% 1.1% 4 29,824 - 37,564 20% 19.1% 14.5% 5.8% 0.9% 5.5% 14.2% 5 37,564 + 20% 13.3% 7.3% 6.3% 6.7% 12.7% 13.7%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 695.2 1,061.2 581.9 2,338.2 Realistic 75-50-25 521.4 707.4 581.9 1,810.7 Pessimistic 50-25-10 347.6 353.7 232.8 934.1


Deutschland Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 12,837 20% 34.2% 44.5% 56.7% -14.2% -24.5% -36.7% 2 12,837 - 17,299 20% 19.3% 20.8% 16.1% 0.7% -0.8% 3.9% 3 17,299 - 22,157 20% 20.7% 13.7% 15.1% -0.7% 6.3% 4.9% 4 22,157 - 29,372 20% 14.5% 12.7% 8.2% 5.5% 7.3% 11.8% 5 29,372 + 20% 11.3% 8.3% 3.9% 8.7% 11.7% 16.1%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 17,401.5 16,589.4 7,840.2 41,831.1 Realistic 75-50-25 13,051.1 11,059.6 7,840.2 31,950.9 Pessimistic 50-25-10 8,700.7 5,529.8 3,136.1 17,366.6


Elláda Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 4,667 20% 24.0% 28.4% 28.3% -4.0% -8.4% -8.3% 2 4,667 - 6,870 20% 23.5% 26.5% 19.5% -3.5% -6.5% 0.5% 3 6,870 - 9,350 20% 21.2% 19.3% 12.3% -1.2% 0.7% 7.7% 4 9,350 - 12,693 20% 15.5% 13.6% 6.7% 4.5% 6.4% 13.3% 5 12,693 + 20% 15.8% 12.2% 33.2% 4.2% 7.8% -13.2%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 389.4 441.2 36.9 867.5 Realistic 75-50-25 292.1 294.2 36.9 623.1 Pessimistic 50-25-10 194.7 147.1 14.8 356.5


España Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 8,052 20% 28.8% 36.1% 33.1% -8.8% -16.1% -13.1% 2 8,052 - 11,583 20% 29.8% 34.1% 31.1% -9.8% -14.1% -11.1% 3 11,583 - 15,736 20% 18.4% 16.3% 12.5% 1.6% 3.7% 7.5% 4 15,736 - 21,926 20% 14.5% 9.6% 10.6% 5.5% 10.4% 9.4% 5 21,926 + 20% 8.6% 3.8% 12.7% 11.4% 16.2% 7.3%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 4,933.8 6,425.1 1,655.9 13,014.8 Realistic 75-50-25 3,700.3 4,283.4 1,655.9 9,639.7 Pessimistic 50-25-10 2,466.9 2,141.7 662.4 5,271.0


France Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 14,252 20% 24.3% 33.3% 39.8% -4.3% -13.3% -19.8% 2 14,252 - 18,854 20% 20.2% 21.2% 23.2% -0.2% -1.2% -3.2% 3 18,854 - 23,518 20% 23.7% 21.8% 18.2% -3.7% -1.8% 1.8% 4 23,518 - 30,809 20% 17.3% 11.7% 10.0% 2.7% 8.3% 10.0% 5 30,809 + 20% 14.5% 11.9% 8.9% 5.5% 8.1% 11.1%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 3,247.0 4,974.0 2,588.1 10,809.0 Realistic 75-50-25 2,435.2 3,316.0 2,588.1 8,339.3 Pessimistic 50-25-10 1,623.5 1,658.0 1,035.2 4,316.7


Italia Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 9,642 20% 30.6% 28.7% 32.2% -10.6% -8.7% -12.2% 2 9,642 - 13,557 20% 27.2% 28.1% 25.7% -7.2% -8.1% -5.7% 3 13,557 - 17,877 20% 23.1% 26.2% 24.6% -3.1% -6.2% -4.6% 4 17,877 - 23,879 20% 9.9% 12.1% 10.9% 10.1% 7.9% 9.1% 5 23,879 + 20% 9.2% 4.9% 6.6% 10.8% 15.1% 13.4%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 6,567.8 4,788.0 2,274.1 13,629.9 Realistic 75-50-25 4,925.8 3,192.0 2,274.1 10,391.9 Pessimistic 50-25-10 3,283.9 1,596.0 909.6 5,789.5


Kýpros Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 10,380 20% 18.2% 24.0% 21.5% 1.8% -4.0% -1.5% 2 10,380 - 13,897 20% 45.4% 45.0% 49.6% -25.4% -25.0% -29.6% 3 13,897 - 18,138 20% 19.5% 16.0% 14.9% 0.5% 4.0% 5.1% 4 18,138 - 25,071 20% 8.7% 7.8% 7.2% 11.3% 12.2% 12.8% 5 25,071 + 20% 8.1% 7.2% 6.7% 11.9% 12.8% 13.3%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 94.5 78.5 27.4 200.4 Realistic 75-50-25 70.9 52.3 27.4 150.6 Pessimistic 50-25-10 47.2 26.2 11.0 84.4


Latvija Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 2,830 20% 37.8% 39.6% 38.4% -17.8% -19.6% -18.4% 2 2,830 - 3,976 20% 22.8% 22.4% 25.2% -2.8% -2.4% -5.2% 3 3,976 - 5,577 20% 20.3% 20.9% 20.9% -0.3% -0.9% -0.9% 4 5,577 - 8,018 20% 13.9% 14.9% 11.8% 6.1% 5.1% 8.2% 5 8,018 + 20% 5.2% 2.2% 3.7% 14.8% 17.8% 16.3%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 185.5 133.5 43.5 362.6 Realistic 75-50-25 139.2 89.0 43.5 271.7 Pessimistic 50-25-10 92.8 44.5 17.4 154.7


Lietuva Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 2,780 20% 24.7% 22.5% 28.6% -4.7% -2.5% -8.6% 2 2,780 - 3,992 20% 22.3% 25.4% 29.4% -2.3% -5.4% -9.4% 3 3,992 - 5,409 20% 24.5% 22.3% 22.2% -4.5% -2.3% -2.2% 4 5,409 - 7,621 20% 18.3% 17.3% 12.3% 1.7% 2.7% 7.7% 5 7,621 + 20% 10.2% 12.5% 7.3% 9.8% 7.5% 12.7%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 106.8 57.3 44.1 208.2 Realistic 75-50-25 80.1 38.2 44.1 162.4 Pessimistic 50-25-10 53.4 19.1 17.6 90.1


Luxembourg Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 21,337 20% 29.8% 34.2% 42.6% -9.8% -14.2% -22.6% 2 21,337 - 28,751 20% 30.5% 19.4% 17.4% -10.5% 0.6% 2.6% 3 28,751 - 37,388 20% 18.0% 19.4% 12.9% 2.0% 0.6% 7.1% 4 37,388 - 50,283 20% 9.9% 11.3% 8.4% 10.1% 8.7% 11.6% 5 50,283 + 20% 11.8% 15.8% 18.7% 8.2% 4.2% 1.3%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 169.4 80.0 24.5 274.0 Realistic 75-50-25 127.1 53.4 24.5 204.9 Pessimistic 50-25-10 84.7 26.7 9.8 121.2


Magyarország Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 3,077 20% 32.3% 36.0% 44.7% -12.3% -16.0% -24.7% 2 3,077 - 4,068 20% 27.7% 27.0% 28.8% -7.7% -7.0% -8.8% 3 4,068 - 5,034 20% 19.1% 15.8% 14.6% 0.9% 4.2% 5.4% 4 5,034 - 6,607 20% 13.3% 14.0% 8.4% 6.7% 6.0% 11.6% 5 6,607 + 20% 7.6% 7.2% 3.6% 12.4% 12.8% 16.4%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 511.6 338.2 300.8 1,150.6 Realistic 75-50-25 383.7 225.4 300.8 909.9 Pessimistic 50-25-10 255.8 112.7 120.3 488.8


Malta Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 7,763 20% 38.8% 40.2% 41.6% -18.8% -20.2% -21.6% 2 7,763 - 10,533 20% 21.9% 18.7% 11.5% -1.9% 1.3% 8.5% 3 10,533 - 13,615 20% 12.9% 11.2% 22.1% 7.1% 8.8% -2.1% 4 13,615 - 17,644 20% 8.6% 8.6% 8.6% 11.4% 11.4% 11.4% 5 17,644 + 20% 17.8% 21.4% 16.2% 2.2% -1.4% 3.8%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 42.7 15.6 6.0 64.4 Realistic 75-50-25 32.0 10.4 6.0 48.5 Pessimistic 50-25-10 21.4 5.2 2.4 29.0


Nederland Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 14,881 20% 29.7% 36.6% 36.6% -9.7% -16.6% -21.3% 2 14,881 - 18,967 20% 20.8% 25.1% 25.1% -0.8% -5.1% 3.6% 3 18,967 - 23,006 20% 14.5% 19.2% 19.2% 5.5% 0.8% 5.1% 4 23,006 - 29,336 20% 21.4% 11.7% 11.7% -1.4% 8.3% 12.5% 5 29,336 + 20% 13.6% 7.4% 7.4% 6.4% 12.6% 0.1%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 1,766.5 2,288.3 546.0 4,600.8 Realistic 75-50-25 1,324.8 1,525.6 546.0 3,396.4 Pessimistic 50-25-10 883.2 762.8 218.4 1,864.4


Österreich Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 14,974 20% 34.0% 40.5% 38.6% -14.0% -20.5% -18.6% 2 14,974 - 19,785 20% 16.9% 15.9% 22.5% 3.1% 4.1% -2.5% 3 19,785 - 24,653 20% 18.5% 14.4% 11.3% 1.5% 5.6% 8.7% 4 24,653 - 31,368 20% 19.6% 13.7% 4.8% 0.4% 6.3% 15.2% 5 31,368 + 20% 11.0% 15.5% 22.8% 9.0% 4.5% -2.8%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 1,649.3 813.3 229.3 2,691.9 Realistic 75-50-25 1,237.0 542.2 229.3 2,008.5 Pessimistic 50-25-10 824.7 271.1 91.7 1,187.5


Polska Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 3,288 20% 28.0% 32.1% 31.5% -8.0% -12.1% -11.5% 2 3,288 - 4,559 20% 29.7% 28.2% 34.6% -9.7% -8.2% -14.6% 3 4,559 - 5,843 20% 18.3% 19.6% 17.1% 1.7% 0.4% 2.9% 4 5,843 - 7,955 20% 19.4% 14.7% 13.0% 0.6% 5.3% 7.0% 5 7,955 + 20% 4.6% 5.4% 3.8% 15.4% 14.6% 16.2%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 1,657.1 1,264.0 635.0 3,556.0 Realistic 75-50-25 1,242.8 842.6 635.0 2,720.4 Pessimistic 50-25-10 828.6 421.3 254.0 1,503.9


Portugal Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 5,116 20% 15.6% 10.3% 10.5% 4.4% 9.7% 9.5% 2 5,116 - 7,189 20% 26.3% 12.9% 17.8% -6.3% 7.1% 2.2% 3 7,189 - 9,429 20% 21.6% 14.2% 15.4% -1.6% 5.8% 4.6% 4 9,429 - 13,098 20% 21.4% 10.1% 7.4% -1.4% 9.9% 12.6% 5 13,098 + 20% 15.0% 52.5% 48.9% 5.0% -32.5% -28.9%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 42.1 -527.4 -144.7 -630.0 Realistic 75-50-25 31.6 -351.6 -144.7 -464.7 Pessimistic 50-25-10 21.1 -175.8 -57.9 -212.6


România Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 1,152 20% 69.2% 72.8% 73.5% -49.2% -52.8% -53.5% 2 1,152 - 1,774 20% 18.4% 18.7% 16.8% 1.6% 1.3% 3.2% 3 1,774 - 2,408 20% 12.4% 8.4% 9.7% 7.6% 11.6% 10.3% 4 2,408 - 3,356 20% 0.0% 0.0% 0.0% 20.0% 20.0% 20.0% 5 3,356 + 20% 0.0% 0.0% 0.0% 20.0% 20.0% 20.0%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 1,079.9 745.4 449.4 2,274.7 Realistic 75-50-25 809.9 496.9 449.4 1,756.2 Pessimistic 50-25-10 540.0 248.5 179.8 968.2


Slovenija Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 8,115 20% 29.0% 34.6% 46.6% -9.0% -14.6% -26.6% 2 8,115 - 10,748 20% 23.6% 30.1% 23.1% -3.6% -10.1% -3.1% 3 10,748 - 13,022 20% 18.9% 12.2% 8.2% 1.1% 7.8% 11.8% 4 13,022 - 16,418 20% 3.2% 3.2% 22.1% 16.8% 16.8% -2.1% 5 16,418 + 20% 25.3% 19.9% 0.0% -5.3% 0.1% 20.0%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 123.6 133.0 79.1 335.7 Realistic 75-50-25 92.7 88.6 79.1 260.5 Pessimistic 50-25-10 61.8 44.3 31.7 137.8


Slovensko Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 4,813 20% 35.7% 43.4% 47.6% -15.7% -23.4% -27.6% 2 4,813 - 6,150 20% 23.0% 27.1% 25.3% -3.0% -7.1% -5.3% 3 6,150 - 7,471 20% 10.0% 7.5% 5.9% 10.0% 12.5% 14.1% 4 7,471 - 9,520 20% 27.0% 22.1% 0.0% -7.0% -2.1% 20.0% 5 9,520 + 20% 4.3% 0.0% 21.1% 15.7% 20.0% -1.1%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 353.1 338.2 78.4 769.7 Realistic 75-50-25 264.8 225.5 78.4 568.7 Pessimistic 50-25-10 176.5 112.7 31.3 320.6


Suomi/Finland Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 16,210 20% 31.4% 44.8% 48.3% -11.4% -24.8% -28.3% 2 16,210 - 20,981 20% 36.1% 24.6% 28.0% -16.1% -4.6% -8.0% 3 20,981 - 25,978 20% 13.4% 9.0% 5.7% 6.6% 11.0% 14.3% 4 25,978 - 33,111 20% 4.3% 4.3% 4.3% 15.7% 15.7% 15.7% 5 33,111 + 20% 14.8% 17.3% 13.7% 5.2% 2.7% 6.3%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 1,325.8 954.4 304.1 2,584.3 Realistic 75-50-25 994.3 636.3 304.1 1,934.7 Pessimistic 50-25-10 662.9 318.1 121.7 1,102.7


Sverige Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 17,842 20% 28.3% 26.8% 33.0% -8.3% -6.8% -13.0% 2 17,842 - 23,744 20% 17.4% 20.6% 19.6% 2.6% -0.6% 0.4% 3 23,744 - 29,152 20% 25.3% 17.5% 20.7% -5.3% 2.5% -0.7% 4 29,152 - 36,336 20% 14.9% 11.8% 6.0% 5.1% 8.2% 14.0% 5 36,336 + 20% 14.2% 23.2% 20.6% 5.8% -3.2% -0.6%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 1,262.2 372.6 188.5 1,823.2 Realistic 75-50-25 946.6 248.4 188.5 1,383.5 Pessimistic 50-25-10 631.1 124.2 75.4 830.7


United Kingdom Share Gap Quintile Range (€) Share LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 1 0 - 12,107 20% 30.1% 32.1% 53.0% -10.1% -12.1% -33.0% 2 12,107 - 16,216 20% 13.0% 16.2% 17.0% 7.0% 3.8% 3.0% 3 16,216 - 21,345 20% 24.8% 26.9% 16.9% -4.8% -6.9% 3.1% 4 21,345 - 29,132 20% 17.7% 17.8% 8.3% 2.3% 2.2% 11.7% 5 29,132 + 20% 14.3% 6.9% 4.8% 5.7% 13.1% 15.2%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 5,573.0 5,242.4 7,294.8 18,110.3 Realistic 75-50-25 4,179.8 3,494.9 7,294.8 14,969.5 Pessimistic 50-25-10 2,786.5 1,747.5 2,917.9 7,451.9

  Inclusion in Education The third way in which the available Eurostat data supports estimating the macroeconomic impact of increased inclusion for people with disabilities is by examining the differences in educational attainment and using the well-documented relationship between educational attainment and income to analyze the potential increase in overall income from greater education. Generally, those with disabilities are not able to complete education and reach the same levels of education as those without. This is an area where the ICT-focus of Prosperity4All could have a significant impact as more and more post-secondary institutions increase their availability of on-line and remote learning. The gap being analyzed in this case is in educational achievement. By closing the gap for educational attainment between the general population and those with disabilities and by assuming average wages based on education level, the overall impact can be estimated.

Once again, optimistic, realistic, and pessimistic assumptions are made in the ability to close that gap. Additionally, since several levels of educational attainment are considered, individuals with disabilities are considered to be moving one step up the ladder – going to the next highest educational attainment level so that the distribution by educational attainment ends up the same for those with disabilities as the general population.

Eurostat reports on education attainment using the following categories: 0 Less than primary 1 Primary 2 Lower Secondary 3 Upper Secondary 4 Post-secondary, non-tertiary 5 Short cycle tertiary 6 Bachelor’s or equivalent 7 Master’s 8 Doctorate

Data on educational attainment for those with disabilities (limitations LD_1, LD_2-3, LD_GE4) and for the overall population and for wages by education level are reported in the following categories: ED0_2 ED3_4 ED5_6 (8) – 5-6 are reported in the EHSIS survey and 5-8 for the general population

EU 28 Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 27.6% 13,742 38.6% 46.6% 52.7% -10.9% -19.0% -25.1% ED3_4 46.1% 16,708 42.7% 38.8% 34.5% 3.4% 7.3% 11.6% ED5-6(8) 25.1% 24,475 17.8% 13.3% 11.9% 7.3% 11.8% 13.2%

Current Number of People (000) Number of People Shift In/Out (000) Ed Level Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 13,742 9,999.2 9,803.2 13,738.6 -2,839.2 -3,999.1 -6,542.2 ED3_4 16,708 11,075.5 8,157.7 9,001.7 891.3 1,543.0 3,025.9 ED5-6(8) 24,475 4,610.6 2,791.0 3,093.3 1,901.4 2,487.9 3,451.8


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 18,305.6 23,459.1 11,505.8 53,270.5 Realistic 75-50-25 13,729.2 15,639.4 11,505.8 40,874.4 Pessimistic 50-25-10 9,152.8 7,819.7 4,602.3 21,574.8

The three tables above show the educational attainment gaps, the shifts in educational attainment that would have to occur to get the distribution the same for those with a disability and the general public and the total economic impact on annual wages under the various assumptions of closing the gaps.

The important thing to note about the second table is the shifts occur up the ladder. So, while 2.8 million more people with a single limitation or a mild disability (LD_1) need to move to level 3 or 4, 1.9 million people currently at level 3 or 4 need to move to level 5 or 6. The number of people shifting among all levels is not equal as the reported numbers for each category don’t report level 7 or 8 (post-secondary) for those with a disability, but they are in the totals. The reported numbers for people that need to shift makes it look like nearly 2 million people need to jump from level 0 to level 6, but that is not the case. The estimates in the third table make the shifts up the ladder, and consider the net change in total income, including income lost from people at lower education level who move up the ladder. And, all moves are from one level to the level immediately above it.

The overall estimates in the third table show that if even a portion of the necessary shift in educational attainment is made so that the distribution by education for people with disabilities resembles the average distribution, the annual increase in incomes associated by the increase in education would range from 21.5 to over 53 million Euro.

The table below shows the country by country estimates for the 24 countries for which data is available. It also shows the aggregate of those 24 countries which is lower than the EU-wide estimated impact but is for fewer countries. This difference is partly due to the variability in average income for educational attainment across countries, but the results are still similar. As with employment and income distribution, increased inclusion for people with disabilities across the countries of the EU could result in higher educational attainment creating annual income increases in the hundreds of millions to billions of Euro.

Country Optimistic 100-75-25 (M €) Realistic 75-50-25 (M €) Pessimistic 50-25-10 (M €) EU28 53,270.5 40,874.4 21,574.8 24 Countries Aggregate 38,239.1 29,618.7 15,376.6

Belgique/België 1,256.1 961.7 529.5 Bulgarija 420.1 325.4 176.4 Danmark 559.5 442.9 225.6 Deutschland 1,926.5 1,546.2 655.6 Elláda 1,448.8 1,083.0 602.0 España 7,339.7 5,552.9 2,902.8 France 7,954.6 6,038.8 3,248.9 Italia 5,973.2 4,799.8 2,438.0 Kýpros 1,395.8 1,086.0 596.5 Latvija 165.6 126.2 68.8 Lietuva 228.6 174.5 92.1 Luxembourg 192.8 143.0 81.1 Magyarország 569.0 455.0 233.5 Malta 1.3 1.2 0.6 Nederland 1,409.7 1,035.9 578.4 Österreich 703.8 549.4 322.3 Polska 3,855.1 2,960.7 1,615.1 Portugal 12.4 14.5 6.8 România 592.0 471.1 241.0 Slovenija 234.9 178.8 101.3 Slovensko 188.2 140.2 79.7 Suomi/Finland 982.0 734.5 421.7 Sverige 578.4 429.9 249.0 United Kingdom 251.1 367.1 -90.2

Below are results for individual countries. The individual shifts across the educational attainment levels are not shown but the data is available. There are some cases (Germany and Sweden) where the share of people with disabilities at the middle or higher education levels exceeds the national average. In that case, the estimate, as with income distribution above, considers those shifts and generates a negative impact on wages. Because of the shifts in the other education levels, the overall total impact remains positive. But, as with income distribution above, we are not arguing that education levels should in any way be decreased for people with disabilities. Rather, the net impact estimation creates a negative impact in one place that would actually be avoided with the result that the actual positive impact would be larger than what is shown here.


Belgique/België Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 30.4% 18,434 41.3% 48.7% 48.8% -10.9% -18.3% -18.4% ED3_4 38.1% 23,275 34.9% 25.5% 33.2% 3.1% 12.6% 4.9% ED5-6(8) 31.5% 29,600 21.7% 22.7% 17.0% 9.9% 8.8% 14.5%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 572.9 453.3 229.9 1,256.1 Realistic 75-50-25 429.7 302.2 229.9 961.7 Pessimistic 50-25-10 286.5 151.1 91.9 529.5


Bulgarija Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 22.1% 2,104 35.5% 45.2% 50.7% -13.4% -23.0% -28.6% ED3_4 55.7% 3,679 51.1% 45.1% 42.7% 4.6% 10.6% 13.0% ED5-6(8) 22.2% 5,752 13.0% 9.5% 6.1% 9.2% 12.7% 16.1%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 182.0 147.5 90.5 420.1 Realistic 75-50-25 136.5 98.4 90.5 325.4 Pessimistic 50-25-10 91.0 49.2 36.2 176.4


Danmark Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 28.4% 25,605 43.1% 43.9% 57.8% -14.8% -15.5% -29.5% ED3_4 39.8% 29,897 35.1% 38.9% 30.2% 4.7% 0.9% 9.6% ED5-6(8) 28.0% 35,714 21.8% 17.2% 12.0% 6.1% 10.8% 16.0%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 167.6 224.0 167.8 559.5 Realistic 75-50-25 125.7 149.3 167.8 442.9 Pessimistic 50-25-10 83.8 74.7 67.1 225.6


Deutschland Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 17.1% 17,496 15.4% 16.7% 25.0% 1.7% 0.5% -7.9% ED3_4 55.4% 21,547 61.1% 66.4% 58.4% -5.7% -11.0% -2.9% ED5-6(8) 24.5% 28,586 23.5% 17.0% 16.6% 1.0% 7.5% 7.9%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 -259.4 1,335.6 850.3 1,926.5 Realistic 75-50-25 -194.5 890.4 850.3 1,546.2 Pessimistic 50-25-10 -129.7 445.2 340.1 655.6


Elláda Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 34.5% 6,901 65.4% 77.8% 81.5% -30.9% -43.3% -47.0% ED3_4 41.4% 8,673 28.4% 16.0% 13.6% 13.0% 25.5% 27.8% ED5-6(8) 24.1% 13,689 6.2% 6.3% 11.9% 17.8% 17.8% 12.2%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 637.9 618.8 192.1 1,448.8 Realistic 75-50-25 478.4 412.6 192.1 1,083.0 Pessimistic 50-25-10 318.9 206.3 76.8 602.0


España Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 45.0% 12,512 70.3% 80.5% 80.5% -25.3% -35.5% -35.5% ED3_4 23.1% 15,939 16.0% 9.3% 11.4% 7.1% 13.8% 11.7% ED5-6(8) 30.5% 21,536 13.7% 10.2% 8.2% 16.8% 20.3% 22.4%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 2,161.8 3,739.1 1,438.9 7,339.7 Realistic 75-50-25 1,621.3 2,492.7 1,438.9 5,552.9 Pessimistic 50-25-10 1,080.9 1,246.4 575.5 2,902.8


France Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 27.9% 20,584 47.5% 57.4% 62.9% -19.6% -29.5% -35.0% ED3_4 43.1% 23,281 34.9% 30.3% 27.7% 8.2% 12.8% 15.4% ED5-6(8) 28.9% 31,264 16.2% 11.0% 8.6% 12.7% 17.8% 20.3%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 3,001.6 3,496.1 1,456.9 7,954.6 Realistic 75-50-25 2,251.2 2,330.7 1,456.9 6,038.8 Pessimistic 50-25-10 1,500.8 1,165.4 582.7 3,248.9


Italia Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 43.4% 14,930 71.6% 86.7% 90.8% -28.2% -43.2% -47.4% ED3_4 42.2% 18,762 21.9% 12.0% 7.0% 20.2% 30.2% 35.1% ED5-6(8) 14.4% 25,930 6.3% 13.3% 1.9% 8.1% 1.2% 12.5%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 1,889.1 2,103.2 1,980.8 5,973.2 Realistic 75-50-25 1,416.8 1,402.1 1,980.8 4,799.8 Pessimistic 50-25-10 944.6 701.1 792.3 2,438.0


Kýpros Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 25.4% 14,860 26.3% 22.0% 33.2% -0.9% 3.4% -7.8% ED3_4 39.2% 19,073 64.9% 68.0% 59.6% -25.7% -28.8% -20.4% ED5-6(8) 35.4% 25,698 8.8% 9.6% 6.8% 26.6% 25.7% 28.5%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 667.9 428.7 299.3 1,395.8 Realistic 75-50-25 500.9 285.8 299.3 1,086.0 Pessimistic 50-25-10 333.9 142.9 119.7 596.5


Latvija Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 16.6% 4,088 27.2% 32.9% 41.1% -10.6% -16.4% -24.5% ED3_4 56.4% 5,410 57.3% 53.9% 50.2% -0.9% 2.5% 6.2% ED5-6(8) 27.0% 8,767 15.5% 13.2% 8.3% 11.5% 13.8% 18.6%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 69.4 66.2 30.0 165.6 Realistic 75-50-25 52.1 44.1 30.0 126.2 Pessimistic 50-25-10 34.7 22.1 12.0 68.8


Lietuva Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 14.4% 3,887 22.7% 35.2% 44.1% -8.3% -20.9% -29.7% ED3_4 55.8% 5,270 57.8% 51.8% 44.6% -2.0% 4.0% 11.3% ED5-6(8) 29.8% 8,144 19.5% 12.9% 10.4% 10.3% 16.8% 19.4%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 76.7 104.9 47.0 228.6 Realistic 75-50-25 57.5 69.9 47.0 174.5 Pessimistic 50-25-10 38.4 35.0 18.8 92.1


Luxembourg Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 25.8% 29,251 41.2% 41.4% 47.7% -15.4% -15.7% -22.0% ED3_4 38.1% 39,721 40.2% 43.2% 39.4% -2.1% -5.2% -1.3% ED5-6(8) 34.7% 53,179 17.0% 12.6% 12.3% 17.8% 22.1% 22.5%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 93.2 79.2 20.3 192.8 Realistic 75-50-25 69.9 52.8 20.3 143.0 Pessimistic 50-25-10 46.6 26.4 8.1 81.1


Magyarország Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 22.8% 3,474 33.8% 41.5% 53.8% -11.0% -18.7% -31.0% ED3_4 57.8% 4,967 53.9% 48.0% 38.3% 3.9% 9.7% 19.4% ED5-6(8) 19.5% 7,680 12.0% 10.5% 7.8% 7.5% 9.0% 11.7%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 191.6 198.5 179.0 569.0 Realistic 75-50-25 143.7 132.3 179.0 455.0 Pessimistic 50-25-10 95.8 66.2 71.6 233.5


Malta Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 54.9% 11,823 82.6% 85.0% 82.3% -27.7% -30.2% -27.4% ED3_4 27.9% 15,542 13.9% 38.8% 34.5% 13.9% -10.9% -6.7% ED5-6(8) 17.3% 21,318 17.8% 13.3% 11.9% -0.5% 4.0% 5.4%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 0.8 -0.2 0.7 1.3 Realistic 75-50-25 0.6 -0.2 0.7 1.2 Pessimistic 50-25-10 0.4 -0.1 0.3 0.6


Nederland Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 28.4% 20,297 44.6% 49.2% 42.7% -16.1% -20.8% -14.2% ED3_4 40.8% 22,148 34.4% 35.1% 38.0% 6.4% 5.7% 2.8% ED5-6(8) 28.7% 28,128 20.2% 15.3% 18.3% 8.6% 13.5% 10.4%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 595.1 675.2 139.4 1,409.7 Realistic 75-50-25 446.4 450.1 139.4 1,035.9 Pessimistic 50-25-10 297.6 225.1 55.8 578.4


Österreich Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 22.2% 20,447 34.9% 33.6% 46.1% -12.7% -11.5% -24.0% ED3_4 60.2% 25,479 54.7% 46.4% 45.0% 5.5% 13.8% 15.1% ED5-6(8) 17.7% 31,289 10.1% 19.8% 7.7% 7.6% -2.1% 9.9%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 477.8 104.9 121.1 703.8 Realistic 75-50-25 358.4 69.9 121.1 549.4 Pessimistic 50-25-10 238.9 35.0 48.4 322.3


Polska Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 16.1% 4,194 47.9% 50.5% 65.7% -31.8% -34.4% -49.6% ED3_4 61.3% 5,583 48.5% 47.1% 31.8% 12.8% 14.2% 29.5% ED5-6(8) 22.6% 8,946 3.7% 2.4% 2.3% 19.0% 20.2% 20.3%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 1,679.4 1,423.7 752.0 3,855.1 Realistic 75-50-25 1,259.5 949.2 752.0 2,960.7 Pessimistic 50-25-10 839.7 474.6 300.8 1,615.1


Portugal Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 59.4% 8,287 78.6% 63.9% 67.1% -19.2% -4.5% -7.8% ED3_4 23.0% 10,923 5.8% 26.9% 24.5% 17.2% -3.9% -1.4% ED5-6(8) 17.6% 16,697 15.6% 9.2% 8.4% 2.0% 8.4% 9.2%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 9.8 -13.6 16.2 12.4 Realistic 75-50-25 7.3 -9.1 16.2 14.5 Pessimistic 50-25-10 4.9 -4.5 6.5 6.8


România Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 28.9% 1,514 38.7% 50.9% 59.1% -9.9% -22.0% -30.2% ED3_4 57.3% 2,439 55.5% 43.6% 38.1% 1.9% 13.7% 19.2% ED5-6(8) 13.8% 4,172 5.3% 5.2% 2.2% 8.5% 8.6% 11.6%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 189.3 220.8 181.9 592.0 Realistic 75-50-25 142.0 147.2 181.9 471.1 Pessimistic 50-25-10 94.7 73.6 72.8 241.0


Slovenija Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 18.5% 10,143 38.1% 52.6% 61.7% -19.6% -34.1% -43.2% ED3_4 57.1% 12,070 53.5% 42.8% 33.0% 3.7% 14.3% 24.1% ED5-6(8) 24.4% 17,246 8.4% 13.3% 11.9% 16.0% 11.1% 12.5%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 123.6 75.7 35.6 234.9 Realistic 75-50-25 92.7 50.5 35.6 178.8 Pessimistic 50-25-10 61.8 25.2 14.2 101.3


Slovensko Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 14.7% 5,707 23.9% 25.5% 29.9% -9.2% -10.8% -15.1% ED3_4 67.5% 7,407 67.8% 66.5% 61.9% -0.3% 1.0% 5.6% ED5-6(8) 17.7% 9,179 8.3% 8.0% 8.2% 9.5% 9.8% 9.5%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 93.1 74.2 21.0 188.2 Realistic 75-50-25 69.8 49.5 21.0 140.2 Pessimistic 50-25-10 46.6 24.7 8.4 79.7


Suomi/Finland Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 20.8% 23,082 40.1% 46.5% 52.1% -19.3% -25.7% -31.3% ED3_4 45.6% 24,388 43.5% 38.4% 35.8% 2.2% 7.2% 9.8% ED5-6(8) 33.6% 32,956 16.5% 15.0% 12.0% 17.1% 18.6% 21.5%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 522.6 350.5 108.9 982.0 Realistic 75-50-25 391.9 233.7 108.9 734.5 Pessimistic 50-25-10 261.3 116.8 43.6 421.7


Sverige Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 22.9% 25,160 30.4% 33.0% 28.9% -7.6% -10.1% -6.0% ED3_4 45.6% 28,329 48.1% 47.5% 56.8% -2.5% -2.0% -11.3% ED5-6(8) 31.3% 32,458 20.9% 19.5% 14.3% 10.4% 11.9% 17.1%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 315.6 208.5 54.2 578.4 Realistic 75-50-25 236.7 139.0 54.2 429.9 Pessimistic 50-25-10 157.8 69.5 21.7 249.0


United Kingdom Share Gap Ed Level Share Salary (€) LD_1 LD_2-3 LD_GE4 LD_1 LD_2-3 LD_GE4 ED0_2 21.0% 16,809 16.2% 22.0% 27.9% 4.8% -1.0% -6.9% ED3_4 41.4% 20,882 38.8% 35.6% 40.8% 2.6% 5.7% 0.6% ED5-6(8) 34.5% 28,656 39.6% 33.1% 27.6% -5.1% 1.4% 6.9%


Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 -1,425.7 721.1 955.7 251.1 Realistic 75-50-25 -1,069.3 480.7 955.7 367.1 Pessimistic 50-25-10 -712.9 240.4 382.3 -90.2


  Combined Annual Value of Increased Inclusion

The three different estimates of the potential impact of increased economic inclusion for people with disabilities across the EU are repeated below.

Impact from Inclusion in Employment Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 140,225 26,637 63,017 229,879 Realistic 75-50-25 105,169 17,758 63,017 185,944 Pessimistic 50-25-10 70,113 8,879 25,207 104,198

Impact from Inclusion in Income Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 62,066 54,691 30,735 147,492 Realistic 75-50-25 46,549 36,461 30,735 113,745 Pessimistic 50-25-10 31,033 18,230 12,294 61,557


Impact from Inclusion in Education

Assumptions LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Optimistic 100-75-25 18,305.6 23,459.1 11,505.8 53,270.5 Realistic 75-50-25 13,729.2 15,639.4 11,505.8 40,874.4 Pessimistic 50-25-10 9,152.8 7,819.7 4,602.3 21,574.8

Although it would be convenient to claim that total potential annual impact is the aggregation of these various estimates, it would not be accurate. Increasing educational attainment increases income which in turn would change the distribution of income for individuals with disabilities so that more are in the higher income quintiles. Increased employment similarly leads to increased income and higher income quintile distributions. Education can be one of the means by which employment opportunities can be enhanced and employment levels increased. These estimates are not independent of each other but are interrelated. And, while they have some overlap, they also do not overlap completely. Each is, in effect, a different lens through which one can look to answer the question: What are the potential macroeconomic impacts across the EU of increased economic inclusion of people with disabilities?

The answer (of course) is “it depends…” The numbers above represent an attempt to estimate the impacts using the available data and various scenarios to show what is possible each and every year. The only underlying assumption is that people with disabilities can and should be more widely included in European economic life. The only difference in the numbers is from the extent to which that inclusion can be successfully implemented (the optimistic, realistic, and pessimistic scenarios). These estimates only consider the GDP increases from increased wages. Assuming a level of inclusion appropriate to generate these results would also mean that social service costs would be reduced. Getting more people with disabilities economically engaged and earning wages means that social service and welfare costs would eventually be reduced .

What these estimates show is that increased economic inclusion for people with disabilities can have tremendous impacts. Even only marginal success in closing the existing gaps in employment, income distribution or education would create tens of billions of Euro of impact in the form or additional wages and additional GDP every year. It can extend to hundreds of billions when greater inclusion is achieved.

These benefits have been developed based on the growth of universal inclusion – addressing limitations in any and all of the ten life areas identified in the EHSIS survey analysis. We next consider how to weight these estimates to develop estimates specific to the potential impact of Prosperity4All. For simplicity and tractability, only the pessimistic estimates will be considered. That scenario assumes: • 50% of the gap can be closed for people with one limitation (LD_1, mild disability) • 25% of the gap can be closed for people with two or three limitations (LD_2-3, moderate disability) • 10% of the gap can be closed for people with four or more (out of 10) limitations (LD_GE4, severe disability) These assumptions equally imply that the share of people (50% of all people below the gap completely bridge the gap) or the share of impact (100% of the people below the gap average 50% of what is needed to bridge that gap) or an equivalent combination occurs. In using the pessimistic assumptions in estimating Prosperity4all impact, we are already assuming that Prosperity4All will not impact 50% of people with one limitation, 75% of people with two or three limitations, and 90% of people with four or more limitations.   Potential Impacts of P4All on the ecosystem enabled by the infrastructure

The table below summarizes the estimates developed from the EHSIS for the number of people across the EU (27 countries) that face each of the barriers across the ten life areas. The share of total limitations faced among those who report at least one limitation is also given. The estimates developed from the survey suggest that 42.2 million people face one or more limitations with 16.6 million (39.3%) with one; 11.4 million (27.0%) with two or three; and 14.2 million (33.7%) with four or more.

Limitation Type Number People Share Description Barriers to accessing buildings 12,150,200 7.3% Accessibility to buildings that everyone uses including workplaces, schools, offices, shops and other people’s homes. Barriers of perceived discrimination 11,359,900 6.8% Discrimination occurs when people are treated unfairly because they are seen as being different from others. Do you feel you are treated unfairly by other people because of any of the reasons on this card? (01) Age (02) Sex or Gender (03) Ethnicity (04) A longstanding health condition, illness or disease (05) Longstanding difficulties with basic activities (06) Religion (07) Sexual Orientation (08) None of these Barriers to education and training 12,782,900 7.7% Formal education or training opportunities that may be available to you. This addresses formal education at a school, college or university or formal training related to a job, trade or profession. Barriers to employment 21,632,700 13.0% The reasons why people may not be able to do the kind of paid work that they want to. By kind of paid work we mean the type of work people can do, where or when they can work or how long they can work for. Barriers to using the Internet 2,310,300 1.4% Your use of the Internet. Barriers to leisure 24,731,100 14.9% Hobbies or interests that involve spending time with other people. For example, belonging to a club or association, or taking part in sporting and fitness activities. Barriers to mobility 19,068,200 11.5% Your ability to leave your home whenever you want to. Barriers to paying for the essential things in life 9,091,900 5.5% How easy or difficult you are finding it to pay for the essential things in life such as food, clothing, medicine, housing and transport. Barriers to social contact 900,800 0.5% People you feel close to. you could count on them if you had a serious personal problem. speak with any of them, either in person or by telephone, as often as you wanted Barriers to transport 9,830,500 5.9% Your ability to use motorised transport whenever you want to.

Grand Total 166,086,900

Potential Prosperity4All to Impact Barrier Negligible; not at all (0%) Minimal; impact only in specific situations (10%) Moderate; ICT solutions can reduce some barriers but not all (25%) Significant; ICT focus should directly address most barriers (75%)

The shading indicates the degree to which Prosperity4All solutions could help to reduce those specific barriers. While barriers to access to the internet would be significantly reduced, reducing of perceived discrimination are not likely to see a direct impact. The key indicates the assumption for the share of people facing each barrier that could see a reduction in that barrier from the implementation of the Prosperity4All infrastructure which will enable the ecosystem of reduced barriers.

Weighed by these factors, Prosperity4All could reduce 18,049,015 of the 166,086,900 barriers faced by individuals across the EU. This is 10.9% of the total.

Returning to the original impact estimates and then further weighting by the potential of Prosperity4All to impact 10.9% of the barriers results in the table below.

Pessimistic Optimistic Realistic Original Estimate LD_1 (M €) LD_2-3 (M €) LD_GE4 (M €) Total (M €) Total (M €) Total (M €) Employment Impact 70,113 8,879 25,207 104,198 229,879 185,944 Income Distribution Impact 31,033 18,230 12,294 61,557 147,492 113,745 Education Impact 9,153 7,820 4,602 21,575 53,271 40,874

P4All Estimate Employment Impact 7,642 968 2,748 11,358 25,057 20,268 Income Distribution Impact 3,383 1,987 1,340 6,710 16,077 12,398 Education Impact 998 852 502 2,352 5,806 4,455

Given the already reduced estimates of varying potential impact by number of limitations that need to be overcome, this further reduction helps to create an estimate of the potential annual macroeconomic impact from the implementation of the Prosperity4All infrastructure with the subsequent development of the robust ecosystem that it is designed to enable. That impact ranges from around 2 to 25 billion Euro annually. The same 10.9% adjustment factor could also be applied to all of the individual country estimates (given above in this report) to document the potential of the emergence of the full inclusive ecosystem enabled by the Prosperity4All infrastructure.   Market (Supply/Demand) Impacts The second area in which to consider potential macroeconomic impacts is market impacts. Those impacts could emerge in two distinct ways. The first would be the indirect impact that enabling the ecosystem with the Prosperity4All infrastructure would have on the general market for goods and services. This is not expected to be a proportionally large impact but a small effect spread over a fairly large number. The second way that impacts could emerge would be the more direct effect of Prosperity4All on the ICT and ICT-based market for accessible and accessibility goods and services. Both of these are estimate below.

Increased General Retail/Services Sales General retail goods and services that could be positively impacted by increased accessibility is as follows :

EU28 (M €) Accommodation and food service activities 499,240 Information and communication 1,171,737 Professional, scientific and technical activities 1,262,572 Wholesale and retail trade; repair of motor vehicles and motorcycles 9,726,799 12,660,348

Approximately 8.4% of the population of the EU has at least one limitation. Those limitations do not all relate to the ability to consume goods and services, and in some cases, the limitation results in additional expense and consumption. However, (admittedly mostly preliminary and anecdotal) results show that the removal of “blue laws”, i.e., allowing retail and other consumer establishments to do business on Sundays can result in increased sales and not just a redistribution of existing sales. eRetail has had some negative impact on bricks and mortar retailers, but it has also increased the total amount of retail activity. Additional access may redistribute some sales, but it can also increase the “size of the pie”. Since the focus of this estimation is on increasing access, it does not stretch credibility too much to suggest that increased accessibility for people with disabilities could result in increased sales.

But, that is not to say that this impact would be very large – the only argument required is that some impact is possible. Given that 8.4% of the population has a limitation and keeping with the conservative estimate that 50% of that population could be impacted in any way by increased accessibility and given that 10.9% of all limitations could be addressed by the ecosystem enabled by the implementation of the Prosperity4All infrastructure, retail sales could see a growth of about one-half of one percentage point (0.459%) per year. For the current estimate (above), this would result in an increase in EU GDP from the additional sales of goods and services of just over 58 billion Euro.

The table below shows by EU member state the total sales for the four industry groups listed above and the potential impact of the 0.459% increase. Estimates vary directly with market size as that forms the basis for the increase. The 27 country total and EU28 estimates are very much in line with each other.

Country Total Sales (M €) Prosperity4All Potential Impact (M €) EU28 12,660,348 58,111 27 Countries Aggregate 12,752,026 58,532

Belgique/België 511,575 2,348 Bulgarija 58,616 269 Česká republika 167,025 767 Danmark 214,417 984 Deutschland 2,376,430 10,908 Éire/Ireland 229,184 1,052 Elláda 136,199 625 España 857,410 3,936 France 1,862,166 8,547 Hrvatska 38,248 176 Italia 1,232,767 5,658 Kýpros 15,069 69 Latvija 28,600 131 Lietuva 33,592 154 Luxembourg 115,880 532 Magyarország 102,705 471 Malta 9,576 44 Nederland 739,060 3,392 Österreich 308,794 1,417 Polska 398,263 1,828 Portugal 150,693 692 România 117,073 537 Slovenija 37,835 174 Slovensko 60,639 278 Suomi/Finland 152,031 698 Sverige 380,394 1,746 United Kingdom 2,417,785 11,098


  Increased Sales of Accessible Products and Services The second and more direct impact that could result from the Prosperity4All infrastructure enabling an inclusive infrastructure is increases in the sale of ICT and ICT-related goods and services. This impact could be specific to accessible technologies, but as with general retail above, increased accessibility should also result in increased sales.

The specific industries included in this estimate are listed below. They are listed by NACE (r2) code which is what is reported by Eurostat. The J and C26 are higher level codes for which the more detailed industries included within that code are listed. Data is reported here aggregated to higher level codes. The industry codes for which data is reported are shaded below. These industries are either direct ICT industries or are industries with the potential for a significant ICT component.

nace_r2 Description J Information and communication J5811 Book publishing J5812 Publishing of directories and mailing lists J5813 Publishing of newspapers J5814 Publishing of journals and periodicals J5819 Other publishing activities J5821 Publishing of computer games J5829 Other software publishing J5911 Motion picture, video and television programme production activities J5912 Motion picture, video and television programme post-production activities J5913 Motion picture, video and television programme distribution activities J5914 Motion picture projection activities J5920 Sound recording and music publishing activities J6010 Radio broadcasting J6020 Television programming and broadcasting activities J6110 Wired telecommunications activities J6120 Wireless telecommunications activities J6130 Satellite telecommunications activities J6190 Other telecommunications activities J6201 Computer programming activities J6202 Computer consultancy activities J6203 Computer facilities management activities J6209 Other information technology and computer service activities J6311 Data processing, hosting and related activities J6312 Web portals J6391 News agency activities J6399 Other information service activities n.e.c. C182 Reproduction of recorded media C26 Manufacture of computer, electronic and optical products C261 Manufacture of electronic components and boards C262 Manufacture of computers and peripheral equipment C263 Manufacture of communication equipment C264 Manufacture of consumer electronics C265 Manufacture of instruments and appliances for measuring, testing and navigation; watches and clocks C266 Manufacture of irradiation, electromedical and electrotherapeutic equipment C267 Manufacture of optical instruments and photographic equipment C268 Manufacture of magnetic and optical media C275 Manufacture of domestic appliances C322 Manufacture of musical instruments C323 Manufacture of sports goods C324 Manufacture of games and toys C325 Manufacture of medical and dental instruments and supplies

The table below summarizes the total sales (turnover) for the EU28 for these industries . Across the EU, the ICT industry generates just over 1.5 trillion Euro in annual sales. Nearly three-quarters is specifically in the Information and Communications Industry, and almost three-quarters of the rest is in the Manufacture of Computer, Electronic, and Optical Products. As these are “higher level” categories, the should be expected to be larger. But, the table provides a rough sense of the distribution of sales across industy.

nace_r2 Total Sales (M €) Share (%) J 1,171,737 74.3% C182 3,589 0.2% C26 280,000 17.8% C275 43,703 2.8% C322 1,406 0.1% C323 6,357 0.4% C324 6,414 0.4% C325 63,384 4.0%

Total 1,576,591

The next challenge is to determine a method for estimating the potential impact from the implementation of Prosperity4All on sales for firms in the ICT and related industries. In estimating the potential general retail sales impact, the assumption was 50% of the 8.4% of the population that has at least one limitation could conceivably benefit from increased inclusion. That was then further weighted by the 10.9% of limitations that Prosperity4All might be able to address. Given that the impact in this case is specifically for ICT and ICT-related firms and that is the focus of Prosperity4All, the potential impact should be 4.2% (50% of 8.4%). The assumption that share of sales is correlated with share of the population with a disability is not an unreasonable one given that while the specifics of some of what is purchased may be different because a disability or other limitation, the amount of goods and services purchased is likely to be independent of disability status. This is further bolstered by the finding that among those reporting a limitation in one or more of the ten life areas, only 5.5% reported a barrier in “paying for the essential things in life”. Those in that 5.5% could easily be included among the 50% who are already assumed to be unable to benefit from increased inclusion. That 50% reduction already takes into consideration that many people with a disability will not be easily impacted and so are excluded from the estimation as they will not generate additional demand. However, little of current sales in ICT and related industries directly relates to accessibility technologies. While specific information is not available and the 8.4% is intended to provide some compensation, that compensation is on the demand side. An additional adjustment should be made to recognize that Prosperity4All is intentionally designed to improve access to information on accessibility and inclusion for the ICT industry and create for individuals with disabilities the infrastructure to enable a more inclusive ecosystem, which will involve new accessible and accessibility-enabled ICTs but that is only a small portion of the overall industry. The addition of a further 50% reduction in potential impact should provide some compensation.

Altogether the assumptions about share of the market impacted from the demand side (50% of 8.4%) and impact on the supply side (a further reduction of 50%) results in an estimated impact on sales for ICT and ICT-related industries of 2.1%. On total EU sales of 1.58 trillion Euro, the estimated annual increase in sales with its corresponding increase in GDP would be just over 33 billion Euro.

The table below shows by EU member state the total sales for the ICT industry groups listed above and the potential impact of the 2.1% increase. Estimates vary directly with market size as that forms the basis for the increase. The 27 country total and EU28 estimates are very much in line with each other.


Country ICT Total Sales (M €) Prosperity4All Potential Impact (M €) EU28 1,576,591 33,108 27 Countries Aggregate 1,562,598 32,815

Belgique/België 37,510 788 Bulgarija 4,381 92 Česká republika 25,487 535 Danmark 25,490 535 Deutschland 331,724 6,966 Éire/Ireland 83,669 1,757 Elláda 9,719 204 España 81,005 1,701 France 225,861 4,743 Hrvatska 3,936 83 Italia 143,552 3,015 Kýpros 1,088 23 Latvija 1,795 38 Lietuva 1,995 42 Luxembourg 8,612 181 Magyarország 23,781 499 Malta 833 17 Nederland 67,220 1,412 Österreich 28,090 590 Polska 41,865 879 Portugal 14,407 303 România 11,093 233 Slovenija 4,932 104 Slovensko 11,868 249 Suomi/Finland 42,889 901 Sverige 65,119 1,368 United Kingdom 264,679 5,558

  Appendix One – Eurostat Data Sources All data used in the report are from Eurostat (http://ec.europa.eu/eurostat/web/main/home). The data on people with disabilities is from the estimates developed from the 2011 European Health and Social Integration Survey (EHSIS) and was reported in 2012. General macroeconomic data is from 2013 whenever possible. Missing data, additional estimations, and other specific considerations are noted in the footnotes associated with the specific data items used. Estimates for Croatia generally are not included as it was not an EU member state during the EHSIS survey period. Estonia, and frequently Ireland, are also usually lacking data.

The specific data used in this report is as follows :

Employment Estimates lfsa_pganws Population by sex, age, citizenship and labour status (1 000) hlth_dpeh010 Population by sex, age, disability status and labour status hlth_dsi010 Disabled people by sex, age and severity of disability hlth_dsi015 Disabled people by sex, severity of disability and labour status ilc_di03 Mean and median income by age and sex (source: SILC)

Income Distribution Estimates hlth_dsi030 Disabled people by sex, severity of disability and income quintile hlth_dpeh030 Population by sex, age, disability status and income quintile ilc_di01 Distribution of income by quantiles (source: SILC)

Educational Attainment Estimates ilc_di08 Mean and median income by educational attainment level (source: SILC) lfsa_pgaed Population by sex, age and participation in education and training (last 4 weeks) (1 000) hlth_dsi020 Disabled people by sex, severity of disability and educational attainment level

General Retail/Services sbs_na_1a_se Annual detailed enterprise statistics on services (NACE Rev. 1.1 H-K) sbs_na_dt_r2 Annual detailed enterprise statistics for trade (NACE Rev. 2 G)

ICT and Related Sales/Services sbs_na_1a_se Annual detailed enterprise statistics on services (NACE Rev. 1.1 H-K) sbs_na_ind_r2 Annual detailed enterprise statistics for industry (NACE Rev. 2, B-E)



  Appendix Two – EU Country Codes and Names Code Country English French German BE Belgique/België Belgium Belgique Belgien BG Bulgarija Bulgaria Bulgarie Bulgarien CZ Česká republika Czech Republic République tchèque Tschechische Republik DK Danmark Denmark Danemark Dänemark DE Deutschland Germany Allemagne Deutschland E Eesti Estonia Estonie Estland IE Éire/Ireland Ireland Irlande Irland EL Elláda Greece Grèce Griechenland ES España Spain Espagne Spanien FR France France France Frankreich HR Hrvatska Croatia Croatie Kroatien IT Italia Italy Italie Italien CY Kýpros Cyprus Chypre Zypern LV Latvija Latvia Lettonie Lettland LT Lietuva Lithuania Lituanie Litauen LU Luxembourg Luxembourg Luxembourg Luxemburg HU Magyarország Hungary Hongrie Ungarn MT Malta Malta Malte Malta NL Nederland Netherlands Pays-Bas Niederlande AT Österreich Austria Autriche Österreich PL Polska Poland Pologne Polen PT Portugal Portugal Portugal Portugal RO România Romania Roumanie Rumänien SI Slovenija Slovenia Slovénie Slowenien SK Slovensko Slovakia Slovaquie Slowakei FI Suomi/Finland Finland Finlande Finnland SE Sverige Sweden Suède Schweden UK United Kingdom United Kingdom Royaume-Uni Vereinigtes Königreich