Acknowledgments This document is published by ATHENA Research Centre,Sustainable Development Unit under AE4RIA,under the leadership of Prof.Phoebe Koundouri,in collaboration with PricewaterhouseCoopers(PwC)Greece and Huawei.The final document prepared by Prof.Phoebe Koundouri,Dr.Conrad Felix Michel Landis and Mrs.Eleni Toli from AE4RIA,benefited from the valuable inputs,review and constructive comments received by Ms.Giorgia Epicoco,Dr.Cao Hui,Dr.Rene Arnold from Huawei,Ms.Katerina Papanikolaou and Ms.Maria Slamari from PwC Greece,and Mr.Salvatore Moccia from the EIT Digital.The authors are grateful to the colleagues,partners,and friends for their continued support and invaluable contributions.Recommended citation:Koundouri,P.,Landis,C.,Toli,E.,Papanikolaou,K.,Slamari,M.,Epicoco,G.,Hui C.,Arnold,R.,Moccia,S.(2023).Twin Skills for the Twin Transition:Defining Green&Digital Skills and Jobs.December 2023,AE4RIA,ATHENA Research Centre,Sustainable Development Unit.Disclaimer This White Paper is intended for informational purposes only.The views,opinions,and analysis expressed herein are solely those of the author(s)and do not necessarily reflect the official policy or position of Huawei.Contents List of Abbreviations 2List of Definitions 3Executive Summary 51.Introduction 62.The need for Green&Digital Skills 72.1 A Political Twin Transition:The Policy Context.72.2 The Industrial Twin Transition:the examples of the ICT&Energy.113.The New Set of Green Digital Skills 154.A New Framework for Green&Digital Occupations in the EU 194.1 The ESCO Framework.194.2 Classification of Green and Digital Occupations and Groups of Occupations.214.3 Green and Digital Skills,Occupations and Employment.244.4 Green and Digital Skills and Occupations,Future Demand.275.Recommendations 316.Conclusion 36References 36Appendices 40Appendix 1-Technical.40Appendix 2-Additional Results.44 1|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper List of Abbreviations Abbreviation Description AI Artificial Intelligence CBAM Carbon Border Adjustment Mechanism CEPR Centre for Economic Policy Research CEAP Circular Economy Action Plan CSRD Corporate Sustainability Reporting Directive CSDD Corporate Sustainability Due Diligence Directive CRM Act Critical Raw Materials Act CFRIDiL Common Framework of Reference for Intercultural Digital Literacies DESI Digital Economy and Society Index ETS Emissions Trading System EU European Union EGDC European Green Digital Coalition ESCO European Skills,Competences,Qualifications and Occupations classification HR Human Resources IRENA International Renewable Energy Agency IT Information Technology ICT Information and Communication Technology PRF Recovery and Resilience Facility R&D Research and development SMEs Small and medium-sized enterprises STEM Science,technology,engineering,and mathematics 2|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper List of Definitions Twin Transition The approach that intertwines the green transition(sustainable and environmentally friendly economy)and digital transition(adoption and integration of digital technologies and innovations)and consider them equally important for the future of societies.Green skills The European Centre for the Development of Vocational Training(Cedefop)defines green skills as“the knowledge,abilities,values and attitudes needed to live in,develop and support a sustainable and resource-efficient society”.Green skills are those skills needed to reduce environmental impacts and support economic restructuring with the purpose of attaining cleaner,more climate-resilient and efficient economies that preserve environmental sustainability and provide decent work conditions.Green jobs Green jobs can be defined as those impacting the environment in a positive way.Specifically,but not exclusively,this includes jobs that help to protect and restore ecosystems and biodiversity;reduce energy,materials,and water consumption through high-efficiency and avoidance strategies;decarbonize the economy;and minimize or altogether avoid generation of all forms of waste and pollution(UNEP,2008).Brown jobs Brown jobs concern highly polluting activities,for example mining,manufacturing,agriculture.White jobs White jobs are the ones that are relatively neutral in their environmental impact.Digital skills Digital skills are defined as a range of abilities to use digital devices,communication applications,and networks to access and manage information.They enable people to create and share digital content,communicate,collaborate,and solve problems for effective and creative learning,work,and social activities at large(UNESCO,2018).Entry-level digital skills,meaning basic functional skills required to make basic use of digital devices and online applications,are widely considered a critical component of a new set of literacy skills in the digital era,with traditional reading,writing,and numeracy skills.At the advanced spectrum of digital skills are the higher-level abilities that allow users to make use of digital technologies in empowering and transformative ways e.g.,by using artificial intelligence(AI),machine learning,and big data analytics.Underskilling To lack the skills and abilities necessary to perform the current job to acceptable standards(CEDEFOP).Skill shortage Demand for a particular type of skill exceeds the supply of available people with that skill(CEDEFOP).Skill gap The level of skills of the person employed is less than that required to perform the job adequately or the type of skill does not match the requirements of the job(CEDEFOP).3|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Employee An employee is an individual who works for someone else(a person or a company)in exchange for compensation.ICT Specialist Eurostat defines ICT specialists as workers who have the ability to develop,operate and maintain ICT systems,and for whom ICT constitutes the main part of their job.Fit for 55 Package The“Fit for 55”is a set of proposals to revise and update EU legislation and to put in place new initiatives with the aim of ensuring that EU policies are into line with the climate goals agreed by the Council and the European Parliament.The package of proposals aims at providing a coherent and balanced framework for reaching the EUs climate objectives,which:ensures a just and socially fair transition maintains and strengthens innovation and competitiveness of EU industry while ensuring a level playing field vis-vis third country economic operators underpins the EUs position as leading the way in the global fight against climate change Hard skills Hard skills,or technical skills,are measurable abilities and knowledge that come through learning and can be job or task-specific(e.g.,data analysis).Soft skills Soft skills are the behavioural,interpersonal attributes people need to succeed in the workplace.They refer to how someone works with and relates to others,efficiently(e.g.,communication,teamwork).4|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Executive Summary In an era of multiple crises,we witness a broad consensus that addressing primarily economic growth aspects without paying equal attention to environmental sustainability is short-sighted and does not produce the expected(successful)economic results.In parallel,the presence of digital technologies in almost all aspects of our life has exponentially increased the speed of changes and their impact on people and businesses.Societies must make the strategic move to prepare for a rapidly changing world and to address critical global challenges.In this respect,the recent pandemic revealed the readiness level that is required to handle global shocks.Coping with all the above successfully is a laborious process that requires people capable of developing and deploying green digital solutions.In fact,two important and interlinked drivers are at the top of the EUs agenda:the digital and green transitions,also known as Twin Transition.A transition underpinned by policy ambitions that wish for the EU to become climate neutral by 2050.Nevertheless,there is an ever-debated challenge in the EU and beyond,which is the development of the necessary skills to achieve the ambitions included in proposals and targets set under the European Green Deal.This report focuses specifically on identifying the new set of Green Digital Skills that will define the present and future course of action required to skill and upskill people within the EU and beyond,in order to develop and deploy the net-zero technologies needed to achieve climate neutrality by 2050.Insights from this report further seek to provide recommendations for the education sector,to support the integration of the newly proposed taxonomy into existing and new curricula so as to meet the industry and labour market demand.An EU policy analysis under the sustainability and digital EU policy portfolio was conducted,as well as a review of the industrial sectors at the intersection of the Twin Transition(i.e.the ICT and Energy sectors).Next,the report elaborates on the driving role policymaking plays in supporting the industry to shift to environmentally friendly business models,and how new legislations can eventually shape the landscape for skills and jobs development.A novel classification model to identify the most important Green and Digital skills,as well as knowledge concepts,is presented.The classification model utilizes the European Skills and Competences framework(ESCO).Subsequently,the report assessed the level of“Greenness and Digitalization”of Occupations(with a focus on the European labour market),highlighting the jobs requiring a high share of green and digital skills.The report provides data-based evidence on changes related to green and digital skills and occupations,showing that the portion of occupations that require both green and digital skills simultaneously has noticeably increased in the last decade.The report highlights that the Agenda 2030,whereby global goals were formally agreed upon by 191 United Nations Member States in 2015 is no longer simply a declarative text.The 17 goals and 169 targets have been widely integrated into public policies and strategic guidelines that impact priorities and needs for future skills and occupations.The next challenge for a successful use of the Green Digital Skills taxonomy and integration into educational programs,is to involve Technical and Vocational Education and Training(TVET)systems,as well as universities.This will significantly increase the capacity to close current skills gaps in the digital and green fields at large,while enabling economies and societies to proactively respond to changing requirements and conditions,in a world where uncertainty has become the new reality.5|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper 1.Introduction The Twin Transition raises the need to pay increased attention to intertwined skills and climate policies given the potential to develop green and digital skills to drive both climate neutrality and a recovery full of job opportunities.Currently,more than three quarters of companies in the EU report difficulties in finding workers with the necessary skills to meet job requirements,and latest figures from Eurostat suggest that only 37%of adults undertake training on a regular basis1.Thus,having the relevant skills will undoubtedly empower people to successfully navigate labour market changes and to fully engage in society.Furthermore,a workforce with the skills that are in demand also contributes to sustainable growth,leading to more innovation,and improved industrial competitiveness.However,at the same time this constitutes a big challenge,as identifying the“right”skills for this new era demands a holistic approach;given the variety of occupations and the skills each one of them is associated with.It is important to note also,that for this to happen,focus should be placed mainly on soft skills,as they feature across different jobs(in contrast to the technical“hard”skills).In addition,it is necessary for a common understanding of green skills across occupations to be created.When it comes specifically to the changes in the labour market due to the Twin Transition,these are less clear.Undoubtedly,the accelerated obsolescence of some technologies and products will have an impact on the labour markets structure,which can subsequently affect how certain jobs will be performed,or which roles will be in higher demand.This is also reflected in the linguistic evolution within the labour market:the terms green,brown,and white”jobs are an increasingly common categorization for describing the environmental impact of jobs(Vandeplas et al,2022).The importance of focusing on skills and how those can be obtained by individuals is also confirmed by the European Commissions adopted proposal which declares the year 2023 the European Year of Skills,following the announcement by President Ursula von der Leyen in her 2022 State of the Union address2.The European Year of Skills promotes lifelong learning,empowering people and companies to contribute to the green and digital transitions,supporting innovation and competitiveness.Nonetheless,to tackle any existing skill gaps and understand the needs for upskilling and/or reskilling,it is crucial to firstly map the skills that are expected to be in high demand.Therefore,this report aims to firstly define a new set of green digital skills,relying on well-defined competence frameworks.Going beyond the skillset definition,it is necessary at a second stage to link the green digital skills with occupations and employment,and highlights thereby relevant trends in the EU labour market.1 https:/eunec.eu/european-heartbeat-news-eu/2023-european-year-skills 2 https:/ec.europa.eu/commission/presscorner/detail/en/speech_22_5493 6|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper 2.The need for Green&Digital Skills The Twin Transition is paving the way for the European Union to become climate neutral by 2050.By proposing policies fit for the development of clean technologies manufactured by abiding to the highest sustainability standards,the EU may be ready for the next industrial revolution.The Twin Transition is currently at the top of the EUs agenda with the understanding that this is and will continue to have a substantial impact on several life aspects in the short,medium,and long term.While a green transition differs from the digital transition,with each one being subject to specific dynamics,their twinning i.e.,their capacity to reinforce each other deserves closer attention.It is recognized by the global community at large that digital technologies play a key enabling role to achieve climate neutrality,reduce pollution,and restore biodiversity by monitoring pollution exposure and accessing environmental data.Moreover,Wuppertal Institute(2021a,2021b)and Ramesohl et al(2022a,2022b)focus on the impact digital solutions have on changing behavioural patterns of stakeholders,incentive systems,market structures and business models as prerequisites for transformative changes towards sustainability and climate protection.This enabling role is further supported by the need of multiple economic operators to achieve climate neutrality and energy efficiency by 2030,e.g.in data centres and cloud infrastructures,which will support the greening of other technologies,such as big data analytics,blockchain,or the internet of things.2.1 A Political Twin Transition:The Policy Context The first alarming warnings on the impact current economic and industrial policies have on the environment have been published as early as 1972(Meadows et al,1972).However,it took several years for humanity to fully grasp the meaning of these warnings and start reacting on a global level.Precisely until 2015,which represents a milestone year in the development of climate policies.This is the year of the Paris Agreement,adopted by 196 Parties,and the agreement of the 2030 Agenda for Sustainable Development,including the 17 Sustainable Development Goals(SDGs),to be achieved by 2030.Since then,policy efforts targeting sustainable development have been intensified in the European region,as summarized in Figure 1.The second report published by the SDSN Europe Senior Working Group provides a comprehensive summary of the efforts undertaken by the EU to integrate the Agenda 2030 into the strategic guidelines on various policy areas and the European Semester(the central process for coordinating national economic and employment policies in the EU)through the implementation of the European Green Deal.The European Green Deal,introduced in December 2019 by the European Commission,serves as Europes growth plan aiming to make it a climate-7|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paperneutral,resource-efficient,innovative,and socially inclusive continent.It includes several goals spanning many different policy areas,such as Clean Energy,Sustainable industry,Buildings and Renovation,Sustainable Agriculture Farm to Fork,Eliminating Pollution,Sustainable mobility,Biodiversity and Sustainable Finance.Moreover,as a response to the health,environmental,and economic consequences of the COVID-19 pandemic,the European Commission introduced 2021,the“Next Generation EU”,a generous package of funds to mobilize policies supporting economic recovery while pursuing Europes green and digital transition”3.Figure 1 Summary of the policy framework for the transition to sustainabilityKoundouri et al(2021)provides a framework to map the policies to 17 SDGs.Figure 2depicts how the SDGs are mainstreamed into the policies of the European Green Deal.The results indicate that overall,the policies resulting from the European Green Deal affect all SDGs,some to a greater extent(E.G.,EU Strategy on Adaptation to Climate Change,New Industrial Strategy,Fit for 55)and others to a lesser extent(e.g.,EU Commission Recommendation on Energy Poverty).The most significant impact is found in goals 7,8,9,12 and 13.3https:/egd-report.unsdsn.org/8|Twin Skills for the Twin Transition:Defi ning Green Digital Skills and Jobs|White Paper Figure 2 Connection of the European Green Deal to the 17 SDGs The“European Green Deal”(EGD)builds on three main policy domains:Sustainable Finance and Corporate Sustainability Reporting(ESGs),Environment and Energy requirements and Industry.Considering that these domains cover a broad range of businesses and economic activities,it is easily understood that any ESG related policies have a great impact on the current job market and any future trends.We can with high probability assume that new green jobs will be created as the result of the implementation of policies focusing on environmental sustainability and the reduction of carbon emissions,not only in sectors where this is expected,such as renewable energy,energy efficiency,sustainable agriculture,and environmental management,but also in more traditional”business sectors.Sustainability managers,environmental consultants,renewable energy specialists,sustainability analysts,are only few examples of recently introduced occupations.In parallel,traditional sectors and occupations are“enhanced”through the addition of sustainability dimensions:for example,the Sustainable Supply Chain Manager,the Sustainable Architect/Designer,the Sustainability Auditor,the Sustainable Finance Specialist.The digital pillar of the Twin Transition also addresses numerous policy initiatives.Among those,it is worth noting the increased attention the EU Institutions attached to the definition and development of digital skills.Indeed,the European Commission has set targets in the European skills agenda and the digital education action plan to ensure that 80%of adults will have basic digital skills and 20 million Information and Communication Technology(ICT)Specialists-with equitable participation of men and women-will have been trained,by the end of this decade.The Digital Economy and Society Index(DESI)which summarizes indicators on Europes digital performance and tracks the progress of EU countries helps towards that effort,as the European Commission has been monitoring Member States digital progress through the DESI reports since 2014.9|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper While continuously monitoring skills-related data,the EU has invested significant resources to support digital transformation.127 billion Euros has been dedicated to digital reforms and investments in the national Recovery and Resilience Plans.Moreover,Member States dedicated on average 26%of their Recovery and Resilience Facility(RRF)allocation to the digital transformation,above the compulsory 20%threshold.Member States that chose to invest more than 30%of their RRF allocation to digital are Austria,Germany,Luxembourg,Ireland,and Lithuania.Finally,the Digital Skills and Jobs Coalition has been set up to successfully address the digital skills gap.This is an indicative EU initiative that brings together Member States,companies,and non-profit organizations aiming to tackle this gap.It offers organizations that work towards the increase of digital skills across Europe to learn from peers and showcase their actions and impact,while the actions done under the Coalition umbrella are key to reaching the“Digital Decade”targets.With 2023 being the European Year of Skills,it is evident that skills are now centre-stage.Not only are skills-related initiatives highlighted across the EU,but skills become active chapters to be embedded into legislative proposals.This also applies to the Net-Zero Industry Act,the latest proposal for a regulation that aims to re-industrialize the European Union,attract investments and create better conditions and market access for clean tech in the EU.Supporting people to get the right skills(green and digital)and helping companies,in particular small and medium enterprises,to address skills shortages in the EU is what this Year is all about.This happens by showcasing skills development opportunities and activities across Europe,by fostering easier recognition of qualifications across borders,by bringing organizations and people together to share their experiences and insights,setting out how EU initiatives and funding possibilities can help.It is understood from the above that focusing on enhancing green and digital skills through suitable training programmes is deemed crucial.For that to happen though,it is vital to have a good understanding and clarity of what exactly“green and digital skills”entail.In the next sections we provide data-based evidence on changes related to green and digital skills and occupations,and also link them to concrete policies(presented in Section 3).Global Outlook I Frameworks that reflect each regions priorities and strategies for addressing both sustainability and digitalization highlighting the interconnectedness of these two policy domains United States In the heart of the Sustainability Transition Framework in US stands the Infrastructure Investments,that is proposed infrastructure plans,such as the American Jobs Plan,which include significant investments in green infrastructure,renewable energy and electric vehicle charging networks.Clean Energy:Federal and state incentives for renewable energy adoption,as well as efforts to reduce carbon emissions from the Power Sector.Furthermore,Environmental Regulations:Federal agencies like the Environmental Protection 10|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Agency(EPA)enforce environmental regulations to reduce pollution and promote sustainability.Digital Transition Framework consists of Digital Infrastructure(Investments in digital infrastructure,5G,and broadband expansion to support the digital transition and bridge the digital divide)and Innovation(Promotion of innovation in digital technologies,including AI,advanced manufacturing,and quantum computing).China Green Growth:Ambitious targets for reducing carbon emissions and increasing the use of renewable energy sources as part of Chinas commitment to sustainability.Belt and Road Initiative(BRI):The BRI includes green development principles,emphasizing sustainability in infrastructure projects across Asia and beyond.Digital Infrastructure:China is a leader in 5G deployment and invests heavily in technologies like AI and the Internet of Things(IoT).E-commerce and Digital Platforms:Thriving e-commerce sector and digital platforms,including Alibaba and Tencent,with global expansion.Japan Energy Transition:Transitioning away from nuclear energy and investing in renewable energy sources,such as solar and wind.Resource Efficiency:Promoting a circular economy and resource efficiency to reduce waste and conserve resources.Digital Innovation:Known for innovation in digital technologies and robotics,with applications in healthcare,manufacturing,and disaster response.Cybersecurity:Prioritizing cybersecurity to protect digital assets and critical infrastructure 2.2 The Industrial Twin Transition:the examples of the ICT&Energy Considering the overall policy framework,it is useful to look into two specific industrial sectors that may be both driving the twin transition,as well as experience an important shift in labour demand and competition:the ICT and Energy sectors.There are many factors responsible for the expected increase in demand for green and digital skills within these sectors in the European Market.An important role is played by External factors such as the accelerated phasing out of fossil fuels at a global scale.The implementation of the Paris Agreement inevitably refers to the development of new technologies and greener sources of energy.Moreover,countermeasures against foreign policies such as the IRA in the United States requires Union to completing the 11|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Single Market,improving education and training,spurring R&D,streamlining and accelerating permitting processes for green investment,reaching trade agreements,as well as pursuing broader aims,including competitiveness in general,speedy decarbonization and formulating broad foreign policy and development policy goals,while also reviewing the State-Aid framework in a targeted way.Other important factors relate to the Business environment.As trade and commercial value happens along the value chain there is an increased demand for more and better accountability and traceability of sustainability practices,which is expected to increase the demand for green and digital skills,and dictates companies to focus on the identification of more green talents.Finally,following the framework for the transition to sustainability,there is a gradual shift in Consumer behaviour with an increasing demand for environmentally friendly technologies and energy efficient products.When it comes specifically to the ICT sector,it is certain that the sector plays a pivotal role in the acceleration of the green and digital transition.In general,the number of ICT specialists in the EU grew by 50,5%from 2012 to 20214,almost eight(8)times as high as the increase(6.3%)for total employment.However,according to DESI 2022,the EUs 9 million ICT specialists(representing 4.5%of the total EU workforce)fall well short of the EU aim of 20 million specialists by 2030 and are not enough to address the skills shortages that businesses,SMEs and organizations are now experiencing,despite the fact that 500.000 ICT specialists entered the labour market between 2020 and 2021.The second sector that is directly connected with the green transition is,without a doubt,the energy sector.According to projections,the direct employment in the sector could go up by more than 66%.5 Focusing on the renewables in the EU,direct employment in the production of energy from renewable sources reached nearly 660.000 jobs in 2016 in the EU.6 However,despite the ever-growing share of renewable energy,a downward trend in related jobs occurred from 2011 onwards,turning to stagnation in the following years.Factors behind this development include the aftermath of the 2008 financial crisis,the relocation of some renewables manufacturing capacities outside of Europe,and changes in subsidy schemes for renewables within the EU.The solid biomass and wind sectors each supported nearly a quarter of total EU renewable-energy jobs,with liquid biofuels,heat pumps,photovoltaics and hydropower following.When it comes to the solar industry alone,it is expected to require one million skilled workers by 2030,twice as many as today.An analysis by the International Renewable Energy Agency(IRENA)7 further confirms a steady increase in job opportunities in the field of solar energy technology,which dominates the renewable energy jobs market.These jobs demand more technician level skilled workforce to perform jobs-tasks along 4https:/ec.europa.eu/eurostat/web/products-eurostat-news/-/ddn-20220505-1#:text=The number of ICT specialists,6.3 %) for total employment.&text=Despite a slight increase over,specialists (19.1%) in 2021 5 https:/ https:/joint-research-centre.ec.europa.eu/jrc-news-and-updates/employment-energy-sector-2020-07-09_en 7 https:/www.irena.org/-/media/Files/IRENA/Agency/Publication/2018/May/IRENA_RE_Jobs_Annual_Review_2018.pdf 12|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper the solar energy value chain(manufacturing,construction and installation,operation and maintenance).Global Outlook II The ICT and Energy sectors in the United States and China have also experienced growth from 2015 to today,with China being a global leader in these sectors.Key factors are summarized below United States ICT Sector Digital Economy Growth:The digital economy has continued to expand significantly in the United States.This growth encompasses various segments,including software development,IT services,e-commerce,and digital content creation.Tech companies like Apple,Amazon,Google(Alphabet),and Microsoft have continued to thrive,contributing to job creation and economic growth.Cloud Computing and Data Centers:The adoption of cloud computing services has grown substantially.Leading cloud providers,including Amazon Web Services(AWS),Microsoft Azure,and Google Cloud,have expanded their data center infrastructure to meet increasing demand.Telecommunications:The telecommunications sector has evolved with the deployment of 4G and the ongoing rollout of 5G networks.These developments have led to increased connectivity and faster data speeds.Cybersecurity:The need for cybersecurity solutions has grown due to the increasing frequency and sophistication of cyber threats.This has led to growth in the cybersecurity industry,including companies specializing in threat detection,identity protection,and data security.Energy Sector Renewable Energy Expansion:The U.S.has seen significant growth in renewable energy capacity,particularly in solar and wind power.Falling renewable energy costs,government incentives,and corporate sustainability goals have driven this expansion.Natural Gas Production:The United States has become a major producer of natural gas due to advancements in hydraulic fracturing(fracking)technology.Natural gas has played a significant role in the countrys energy mix.Energy Efficiency:The focus on energy efficiency has grown,with businesses and households adopting energy-saving technologies and practices.Energy-efficient appliances,lighting,and building designs have become more common.13|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Electric Vehicles(EVs):The adoption of electric vehicles has increased,with a growing number of automakers offering EV models.This shift is driven by both consumer interest in cleaner transportation options and government incentives.Grid Modernization:Investments in grid modernization and smart grid technologies have aimed to enhance the reliability and efficiency of the energy infrastructure.China ICT Sector Digital Economy Growth:Chinas digital economy continued to expand rapidly,encompassing various segments such as e-commerce,mobile payments,social media,and digital services.Companies like Alibaba,Tencent,and JD.com played pivotal roles in this growth.Mobile Internet:The widespread adoption of smartphones and mobile internet access contributed to the growth of online services,mobile apps,and digital entertainment.5G Development:China was actively investing in and deploying 5G technology,with the aim of becoming a leader in 5G infrastructure and services.Artificial Intelligence(AI):China made significant strides in AI research,development,and application across industries,including healthcare,finance,and manufacturing.E-commerce and Retail:Chinas e-commerce market continued to thrive,with platforms like Alibabas Taobao and Tmall expanding both domestically and internationally.Energy Sector Renewable Energy Expansion:China increased its investment in renewable energy sources,particularly solar and wind power.It became one of the largest producers of solar panels and wind turbines in the world.Energy Efficiency:China implemented energy efficiency measures and standards across various sectors,including manufacturing and construction,to reduce energy consumption and emissions.Electric Vehicles(EVs):The Chinese government promoted the adoption of electric vehicles(EVs)and set ambitious targets for EV production and sales.Several domestic EV manufacturers,like BYD and NIO,gained prominence.Coal-to-Gas Conversion:Efforts to reduce air pollution led to the conversion of coal-fired heating systems to natural gas and the implementation of cleaner technologies in power generation.14|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper 3.The New Set of Green Digital Skills The aim of this report is to identify a new set of Green Digital Skills that will support the attainment of the targets and goals of the Twin Transition.As discussed in previous sections,this refers to the EUs commitment to pursuing two major transitions simultaneously:the transition to a green economy(achieving climate neutrality and addressing environmental challenges)and the transition to a digital economy(embracing digital technologies and ensuring digitalization across various sectors).These transitions are definitely seen as a way to drive economic growth,create jobs,and make the EU more competitive globally.Through the use of the European Skills and Competences framework(ESCO),we develop a novel classification model to identify the most important Green and Digital skills and knowledge concepts.Focusing on the EU labour market,we also assess the level of“Greenness and Digitalization”of Occupations(jobs),highlighting the jobs requesting a high share of green and digital skills.Table 1 presents an overview of such Twin Skills for the Twin Transition.Focusing on the Policy mapping,the corporate sustainability framework is expected to horizontally affect companies,irrespective of their sector of incorporation.On the other hand,specific sectors such as Energy Supply,Manufacturing,Construction,ICT,Transport and storage,Water and Wastewater Treatment and Agriculture,Forestry and Fishing are primarily influenced by the European Policies in relation to the Environment and Energy.The European Green Deal has a profound impact on the energy sector,particularly in promoting renewable energy sources,enhancing energy efficiency,and reducing greenhouse gas emissions.This affects electricity and heat production from renewable sources,as well as the fossil fuel energy sector.Moreover,the Green Deal aims to decarbonize the transportation sector,which includes road and rail transport,aviation,and shipping.Policies focus on electric and sustainable mobility,reducing emissions,and shifting to cleaner fuels.Manufacturing sector is also impacted by encouraging energy-efficient and sustainable production processes and the adoption of circular economy principles.This includes many industries related to automotive,chemicals,and machinery.Policies promote energy-efficient and 8 https:/ec.europa.eu/eurostat/documents/3859598/5902521/KS-RA-07-015-EN.PDF The Twin Skills for the Twin Transition are presented:first,the policy context is listed under the three major pillars of our analysis that is Corporate Sustainability Reporting,Environment and Energy and Industry;second,the underlying sectors of economic activity.For the classification of sectors,we use the NACE rev.2(Nomenclature of Economic Activities in the European Community)Level 2 classification8.Third,the relevant skills and occupations are presented.15|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper sustainable building practices,having a direct impact on the construction and real estate sectors.Waste Management and recycling businesses are also directly impacted by the policies supporting a transition to a circular economy by promoting recycling and reducing waste.Agriculture and Forestry is also influenced by efforts to combat deforestation and promote afforestation.Finally,the European Green Deal encourages innovation in green technologies and sustainable practices,which affects companies involved in research,development,and production of clean technologies.In the same vein,the European Industrial Policy aims to support and promote the growth and competitiveness of various industries within the EU.The manufacturing sector encompasses a wide range of industries,from automotive and aerospace to pharmaceuticals and machinery.The ICT sector includes the development and manufacturing of computer hardware,software,telecommunications equipment,and services,which is directly affected by policies to boost innovation and digitalization in this sector.The EU Industrial Policy places a strong focus on the development and growth of renewable energy sources such as wind,solar,and hydropower(Energy Supply).Moreover,the EU Industrial Policies include measures to support the development of electric and autonomous vehicles and to enhance the competitiveness of European car manufacturers(Manufacturing).Also,initiatives related to circular economy and eco-friendly production greatly affect the Textiles and other Manufacturing sectors.Along these lines,and supported by the frameworks and empirical results presented in the next session,our work is highly important in identifying the soft and hard skills needed to support the twin transition of all sectors.Moving one step forward,and to further connect results with the European Labour market,we also identify,the top“Green and Digital”occupations9;these are the jobs which require the greatest share of jointly Green and Digital Skills and knowledge concepts.Having said that,the fourth column of Table 1 presents a set of“Soft”Skills,petences,required for the transition.Critical Thinking,Judgement and decision making,Complex Problem Solving,Monitoring,Writing and Coordination are the top six“Soft”Skills jointly classified as Green and Digital which are very important in the most occupations under all pillars.Focusing on the Skills and Competences,for the ESG(Corporate Sustainability)Pillar,we can identify several skills such as advising on environmental issues,environmental sciences,complying with environmental protection laws and standards,computer use,analysing and evaluating information and data as the top jointly green and digital skills.Focusing on Labour market and specific occupations environmental education officer,environmental expert,green ICT consultant,natural resources consultant and sustainability officer are among the top“Twin”Occupations,expected to be of high need on the way to the implementation of the ESG related policies.Equivalently,for the Environmental and Energy pillar,top skills include analysing and evaluating information and data,complying with environmental protection laws and standards,computer use,database and network design and administration,designing electrical or electronic systems or equipment,disposing of non-hazardous waste or debris,electricity and energy environmental protection technology,handling and 9 As explained in the next session,each occupation is related to of a set of skills and competences which are required.16|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper disposing of hazardous materials,maintaining electrical,electronic and precision equipment,monitoring environmental conditions operating agricultural or forestry equipment and using precision measuring equipment.In addition,the top jobs in terms of their level of Greenness and Digitalization include electric meter technician,electrical,transmission system operator,electricity distribution technician,energy assessor,energy systems engineer,environmental education officer,geothermal technician,green ICT consultant,hazardous waste inspector,irrigation technician,recycling specialist,smart home engineer and smart home installer are considered.Finally,in relation to the Industrial Pillar,the results overlap partly with the Environmental and Energy pillar,while electronics and automation and analysing scientific and medical data are also among the top skills and acoustical engineer,botanist and ecologist among the top occupations.17|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Table 1 Top Green Digital Skills and Occupations(Jobs)EU Policy10 Industrial Sector (NACE Rev.2)Green Digital Skills Green Digital Occupations Corporate Sustainability Reporting(ESG)All sectors advising on environmental issues environmental education officer EU Taxonomy Regulation analysing and evaluating information and data environmental expert EU Sustainable Finance Disclosure Regulation(SFDR)complying with environmental protection laws and standards green ICT consultant EU Sustainable Investment Plan computer use natural resources consultant Corporate Sustainability Reporting Directive(CSRD)database and network design and administration nature conservation officer EU Action Plan on Financing Sustainable Growth environmental sciences sustainability manager Environmental and Energy Policies analysing and evaluating information and data electric meter technician European Green Deal Agriculture,Forestry and Fishing complying with environmental protection laws and standards electrical transmission system operator EU Biodiversity strategy for 2030 Construction computer use electricity distribution technician Circular Economy Action Plan Energy Supply database and network design and administration energy assessor Waste Framework Directive ICT designing electrical or electronic systems or equipment energy systems engineer Air Quality Directive Manufacturing disposing of non-hazardous waste or debris environmental education officer Water Framework Directive Transport and Storage electricity and energy geothermal technician Renewable Energy Directive Water and Wastewater Treatment environmental protection technology green ICT consultant Energy Efficiency Directive handling and disposing of hazardous materials hazardous waste inspector EU Emission Trading System(EU ETS)maintaining electrical,electronic and precision equipment irrigation technician Just Transition Fund monitoring environmental conditions recycling specialist Connecting Europe Facility(CEF)operating agricultural or forestry equipment smart home engineer Fit for 55 using precision measuring equipment smart home installer Industry Policies analysing and evaluating information and data acoustical engineer EU Industrial Policy Construction analysing scientific and medical data botanist Green Deal Industrial Plan Energy Supply complying with environmental protection laws and standards ecologist EcoDesign Health and Social Care computer use energy assessor Critical Raw Materials Act ICT database and network design and administration energy systems engineer Chips Act Manufacturing designing electrical or electronic systems or equipment environmental education officer Mining and Quarrying electronics and automation green ICT consultant maintaining electrical,electronic and precision equipment smart home engineer using precision measuring equipment smart home installer 10 Note:at the time of publication of this report,several policy proposals in examine,are still undergoing interinstitutional negotiations 18|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper 4.A New Framework for Green&Digital Occupations in the EU A data-driven framework is developed to classify Skills,Knowledges and Occupations in the EU Labour Market The demand for Occupations with a high“Green and Digital”Score has significantly increased from 2015 for all sectors.The Skills classified as the“most”Digital”or jointly“Digital and Green”are among the most demanded skills for all occupations.Filling the gap in the need for Green and Digital skills will accelerate the transition This section describes the methodologies used to derive the results presented in the following section.In this direction,the report develops and presents a data-driven framework to assess the level of“Greenness”,“Digitalization”and its combination(Greenness and Digitalization),of the EU labour market occupations,and subsequently explore shifts in the demand for Green and Digital Skills during the last 5 years,as well as its trend and projections to 2035.4.1 The ESCO Framework The ESCO framework11 is the multilingual classification of European Skills,Competences and Occupations.ESCO is part of the Europe 2020 strategy12,the European strategy for smart,sustainable and inclusive growth.The ESCO classification13 identifies and categorizes skills,competences,and occupations relevant for the EU labour market and education and training.ESCO identifies 3008 occupations(Level 0)and is built on the International Standard Classification of Occupations ISCO-0814 which serves as the hierarchical structure for ESCOs occupations pillar.The Occupations are classified in Groups on 4 Levels(Level 1,2,3 and 4 corresponds to 10,42,126 and 426 groups of occupations respectively15).Similarly,ESCOs skills pillar provides a comprehensive list of knowledge,skills and competences relevant to the European labour market.It contains 13,895 concepts(Level 0 10831 11 https:/esco.ec.europa.eu/en 12 https:/ec.europa.eu/eu2020/pdf/COMPLET EN BARROSO 007 - Europe 2020 - EN version.pdf 13 We use the most recent version v1.1.1 14 The International Standard Classification of Occupations(ISCO)is a four-level classification of occupation groups managed by the International Labour Organisation(ILO).Its structure follows a grouping by education level.The two latest versions of ISCO are ISCO-88(dating from 1988)and ISCO-08(dating from 2008).15 Level 1 Skills refer to broader level sets of skills,grouping the granular 19|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper skills/competences and 3059 Knowledge concepts)structured in a hierarchy which contains four sub-classifications:Knowledge Language skills and knowledge Skills Transversal skills The Skills pillar distinguishes between i)skill/competence concepts and ii)knowledge concepts by indicating the skill type.There is however no distinction between skills and competences.Similar to Occupations the Skills and Knowledge concepts are organized to 3 levels(Level 1,2 and 3 refer to 8,74 and 296 groups of skills and 11,29 and 86 groups of Knowledge Concepts respectively)The ESCO system also identifies skills which are labelled as green16,to support the transition the green transition of the EU labour market.As workers need a skill set that can respond to the need of reducing emissions in working practices,the Skills/Competences pillar has been enriched with the additional information at skill level to distinguish green skills and knowledge concepts.The labelling of skills and knowledge concepts as green follows a methodology based on a 3-step process,which combines human labelling and validation,and the use of Machine Learning(ML)algorithms.Figures 3 and 4 show the distribution of the green concepts in the skills and knowledge skills hierarchies.A total of 571 ESCO skills and knowledge concepts are labelled as green.This includes:386 skills and 185 knowledge concepts.Figure 3 Green Skills Source:ESCO Publications-Green Skills and Knowledge Concepts:Labelling the ESCO classification 16 https:/esco.ec.europa.eu/en/about-esco/publications/publication/green-skills-and-knowledge-concepts-labelling-esco#:text=The European Classification of Occupations,are now labelled as green.20|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Figure 4 Green Knowledge Concepts Source:ESCO Publications-Green Skills and Knowledge Concepts:Labelling the ESCO classification Similarly,ESCO provides a classification of 725 Skills/Competences and 475 Knowledge Concepts as Digital,following the Digital Competence Framework as presented in Section 4.1.Finally,the ESCO framework provides the relations between the Occupations and the Skills and Knowledges,e.g.which skills and Knowledge concepts are relevant for the each of the occupations.4.2 Classification of Green and Digital Occupations and Groups of Occupations Using the above setup and the classifications and hierarchies provided by the ESCO API,we develop a framework to classify Occupations based on their level of“Greenness”,“Digitalization”and“Greenness and Digitalization”.Our data driven methodology is presented in Technical Appendix 1,and consist of the calculation of a score,ranging from 0 to 100,which is defined as the share of green,of digital and jointly green and digital skills and knowledge concepts in each occupation or occupation Group.Following our methodology,Table 2 presents the ranking of the top 15 occupations,at Level 0(the most granular level),based on their scores on“Greenness”,“Digitalization”and“Greenness and Digitalization”respectively17.17 Appendix 2 Tables A2.1,A2.2 and A2.3 presents the ranking of the Occupations at Level 1,2 and 0 based on their level of Greenness,digitalization and Greenness and Digitalization respectively.For All levels except 1,only the top 15 of occupations(for Level 0)or occupation groups(Levels 1 and 2)are displayed.21|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Table 2 Top 15 Green,Digital and Green and Digital Occupations Green Occupations Score energy assessor 90.909 natural resources consultant 78.788 energy conservation officer 75.000 environmental policy officer 75.000 energy analyst 70.833 environmental expert 70.588 hazardous waste inspector 69.697 recycling specialist 67.568 sustainability manager 65.278 environmental geologist 64.706 environmental protection manager 64.583 environmental education officer 64.000 forestry adviser 62.857 nature conservation officer 60.345 liquid waste treatment plant operator 60.000 Digital Occupations webmaster 98.837 software tester 96.154 user interface developer 93.878 ICT network administrator 93.684 database integrator 93.548 system configurator 93.478 database designer 93.069 mobile application developer 92.941 ICT network engineer 92.784 data warehouse designer 92.593 knowledge engineer 91.954 embedded systems software developer 91.892 integration engineer 91.860 web developer 91.837 ICT integration tester 91.667 Green and Digital Occupations smart home engineer 6.818 smart home installer 6.667 geothermal technician 4.878 green ICT consultant 4.762 irrigation technician 4.348 environmental education officer 4.000 acoustical engineer 3.846 electricity distribution technician 3.571 electric meter technician 3.571 energy systems engineer 3.448 ecologist 3.448 interior planner 3.333 electrical transmission system operator 3.333 pastry chef 3.226 botanist 3.125 22|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Equivalently,Table 3 presents the ranking of the Skills/Knowledge Groups at Level 3(the more detailed group of skills and Knowledges)18.Table 3 Top 15 Green,Digital and Green and Digital Skills/Knowledge Groups(Level 3)Green Skills Score handling and disposing of waste and hazardous materials 100.000 environmental sciences 90.000 environmental protection technology 86.667 complying with environmental protection laws and standards 84.444 natural environments and wildlife 80.000 advising on environmental issues 65.517 forestry 62.500 disposing of non-hazardous waste or debris 47.619 monitoring environmental conditions 47.619 electricity and energy 36.905 designing electrical or electronic systems or equipment 35.000 social and behavioural sciences not elsewhere classified 33.333 crop and livestock production 32.143 community sanitation 30.435 handling and disposing of hazardous materials 29.730 Digital Skills browsing,searching and filtering digital data 100.000 resolving computer problems 100.000 setting up computer systems 100.000 using word processing,publishing and presentation software 100.000 using computer aided design and drawing tools 100.000 using digital tools for collaboration,content creation and problem solving 100.000 programming computer systems 100.000 working with computers 100.000 computer use 100.000 information and communication technologies not elsewhere classified 100.000 managing,gathering and storing digital data 98.413 software and applications development and analysis 97.436 protecting ict devices 95.833 using digital tools for processing sound and images 93.750 designing ict systems or applications 93.548 Green and Digital Skills environmental protection technology 6.667 complying with environmental protection laws and standards 4.444 operating agricultural or forestry equipment 3.846 using precision measuring equipment 3.333 designing electrical or electronic systems or equipment 2.500 monitoring environmental conditions 2.381 computer use 2.381 electricity and energy 2.381 analysing scientific and medical data 1.724 maintaining electrical,electronic and precision equipment 1.563 electronics and automation 1.333 analysing and evaluating information and data 1.220 database and network design and administration 0.935 disposing of non-hazardous waste or debris 0.000 handling and disposing of hazardous materials 0.000 18 Appendix 2 Tables A2.4,A2.5 and A2.6 presents the ranking of the Skills/Knowledge Groups at Level 1 and 2 based on their level of Greenness,digitalization and Greenness and Digitalization respectively.For All levels except Level 1,only the top 15 of skills/knowledge concepts groups are displayed(Levels 2 and 3).23|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper 4.3 Green and Digital Skills,Occupations and Employment In this section,the report explores the relationship between green and digital skills and knowledge concepts and employment growth in the European Markets,based on the scoring system we developed in the previous subsection.Employment data by Occupation Groups are downloaded from Eurostats Labour Force Survey(LFS)19.For all Level 1 Occupation groups,we performed cross-sectional regressions of the average,over years 2012 to 2022,annual employment growth on their Green,Digital and Green&Digital Scores20.Results indicate a strong and steady increase in the annual employment growth rates of Occupations with a high Digital and Jointly Green and Digital Scores.As the digital/green&digital score increases by 1%,the average annual growth rate of occupations over the years 2012 to 2022,increases by 0.28%/28.89%respectively.On the other hand,the negative and significant estimate for Green Occupations(-0.22%)is mainly due to the fact that Agriculture related occupations have a high green score,while on the same time the Agriculture sector employment suffered a significant reduce during the last decade.As such,it is important to study the employment of green,digital and jointly green and digital occupations after controlling for the NACE sector.Focusing on the most recent data(year 2022),we performed cross sectional regressions of the occupations(Level 2)employment rates by NACE sector(NACE Level 2)to the Green,Digital and Green and Digital Scores21.Interestingly results reveal a positive and significant relation of highly“Green”Level 2 Occupations and employment,for the Agriculture Forestry and Fishing,the Energy and the Water and Waste Management treatment sectors.That is Level 2 Occupations with a higher“Green”Score,tend to have higher employment rates for 2022.Focusing on Digital Scores,as expected a highly significant positive relationship,is estimated for the ICT sector that is 2022 employment is higher for occupations with a high Digital Score while a negative relationship is estimated for Health and Social Care and Mining and Quarrying Sectors.Finally,we estimate a highly significant positive relation between the employment rate for occupations with a high green and digital score for ICT,Construction and Energy sectors,while a negative relationship is estimated for Wholesale and Retail Trade and Mining and Quarrying Sectors.In order to measure,how the above results have also evolved through the period 2016 to 2022 that is from the year the Paris Agreement took effect we perform the following cross-sectional regression:!,#= ! !,#Where!,#is the employment rate growth(2016 to 2022)of the ith occupations Group(Level 2)for the jth Level 2 NACE sector and !the Green/Digital/Green&Digital Scores 19 https:/ec.europa.eu/eurostat/web/lfs/database.Data refer to Levels 1 and 2.20 Regression results are presented in Appendix 1,Table A1.1.21 Results are included in Appendix 1,Table A1.2.24|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper of the ith occupations Group(Level 2).The Newey-West p values are also reported in parenthesis,while bold denotes significance at 5%level.The number of observations(n)as well as the R squared is included in Table 4.25|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Table 4 Employment Growth(2016-2022)Occupations Level 2 of NACE sectors Level 2 vs Green,Digital and Green and Digital Scores NACE Level 2 Green Score Digital Score Green and Digital Score b p value n R2 b p value n R2 b p value n R2 1.1 Administrative Services 0.06 0.04 9 0.31 0.05 0.34 9 0.07-0.02 0.78 9 0.02 1.2 Arts and Recreation and other services-0.03 0.23 9 0.09 0.05 0.03 9 0.28 0.07 0.04 9 0.67 1.3 Finance and Insurance 0.08 0.51 6 0.04 0.10 0.03 6 0.45 0.13 0.02 6 0.56 1.4 ICT -0.07 0.69 7 0.02 0.11 0.00 7 0.57 0.10 0.03 7 0.46 1.5 Professional Services-0.05 0.42 8 0.02 0.09 0.00 8 0.56 0.10 0.01 8 0.57 2.1 Construction 0.11 0.61 8 0.01 0.10 0.29 8 0.40 0.03 0.83 8 0.01 3.1 Accommodation and Food 0.11 0.18 8 0.10 0.07 0.02 8 0.43 0.05 0.12 8 0.17 3.2 Transport and Storage 0.11 0.00 9 0.51 0.02 0.63 9 0.02-0.06 0.41 9 0.13 3.3 Wholesale and Retail Trade-0.05 0.12 9 0.12 0.08 0.00 9 0.35 0.00 0.97 9 0.00 4.1 Manufacturing-0.11 0.00 9 0.41 0.14 0.00 9 0.75 0.09 0.04 9 0.45 5.1 Education-0.21 0.06 8 0.24 0.03 0.43 8 0.04 0.00 0.96 8 0.00 5.2 Health and Social Care-0.09 0.00 9 0.43 0.09 0.00 9 0.52 0.04 0.20 9 0.08 5.3 Public Sector and Defence -0.04 0.38 9 0.04 0.12 0.01 9 0.31 0.00 0.98 9 0.00 6.1 Agriculture,Forestry and Fishing -0.14 0.00 8 0.64 0.11 0.00 8 0.46 0.08 0.19 8 0.18 6.2 Energy Supply Services-0.04 0.51 9 0.01 0.09 0.03 9 0.55 0.10 0.01 9 0.51 6.3 Mining and Quarrying-0.03 0.15 5 0.06-0.07 0.21 5 0.14-0.05 0.13 5 0.11 6.4 Water and Wastewater treatment 0.01 0.91 8 0.00 0.11 0.01 8 0.62-0.01 0.82 8 0.00 26|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper It is interesting to note that the employment growth of“Green”occupations mainly occurs within the Administrative Services and the Transportation and Storage Sectors;while within the Manufacturing,Health and Social Care and Agriculture,Forestry and Fishing Sectors the employment growth of“Greener”occupations is lower than the employment growth of less green occupations.On the contrary,the results for Digital Occupations are striking,with almost all sectors having shifted employment to occupations with a higher level of digitalization.The same is true for the jointly Green and Digital occupations with the most significant positive relationships to be reported for ICT,Energy,Professional Services,Manufacturing and Finance and Insurance Sectors.4.4 Green and Digital Skills and Occupations,Future Demand All the above results,indicate a clear positive and statistically significant trend between the development of occupations and their level of Greenness and Digitalization.Moreover,the demand for green and digital skills are experiencing a considerable growth over the years 2016 to 2022.CEDEFOP Skills Intelligence,the online tool of the European Centre for the development of Vocational Training22,utilizes the analysis of labour market data to provide estimates for the Future job prospects of Level 1 and Level 2 Occupations in EU27 for the years 2022-2035.The CEDEFOP estimates refer to a score from 0 to 100,in relation to how much the demand for the specific occupations is expected to grow.Table 5 presents the relevant estimates.Table 5 Future job prospects for Level 1 Occupations Occupations Value Professionals 100 Managers 78 Technicians and associate professionals 75 Elementary occupations 75 Plant and machine operators and assemblers 64 Service and sales workers 60 Craft and related trades workers 43 Clerical support workers 41 Skilled agricultural,forestry and fishery workers 0 Comparing the entries of this table with Tables 1,2 and 3,it is clear that the Top Occupations(Professionals,Managers and Technicians and associate professionals)also correspond to the top“Green and Digital”occupations,where their demand is expected to continue to growth until 2035.Focusing on skills,it is also important to know which are the most requested skills in the job market by occupation.For each Level 2 ESCO occupation,Appendix 2,Table A2.7 reports the share of all the skills(level 1)requested in online job ads in 2022 in EU2723.Table 6 below focuses on the shares for information and communication technologies 22 https:/www.cedefop.europa.eu/en/tools/skills-intelligence/23 Appendix Table 5.7 presents the results in a greater detail.27|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper(ICTs)and engineering which are,as shown in previous sections,the top Green and Digital Skills in Level 1.The first two columns of Table 6 report the Level 2 occupation group,and the ESCO Level 1 Skills and Knowledge Groups respectively.The 3rd column contains the frequency that the underlying skill/Knowledge appears in the online job adds.Focusing on the level 1 skills with the highest Green and Digital Score(information and communication technologies(ICT)and engineering),it is striking that those are among the top skills requested in all of the occupations24.24 Appendix Tables 5.4-5.6 present the ranking of Level 1 skills.28|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Table 6 Most Requested Skills(Level 1)by Occupation Occupations(Level 2)Skills and Knowledge Concepts(Level 1)Share In online Adds health associate professionals information and communication technologies(icts)9.5 engineering and engineering trades 5.6 Information and communications technicians information and communication technologies(icts)49.4 engineering and engineering trades 13.8 Legal,social,cultural and related associate professionals information and communication technologies(icts)10.8 business and administration associate professionals information and communication technologies(icts)19.3 Science and engineering and engineering trades associate professionals engineering and engineering trades 30.1 information and communication technologies(icts)19.5 Numerical and material recording clerks information and communication technologies(icts)14.7 Customer services clerks information and communication technologies(icts)12.5 General and keyboard clerks information and communication technologies(icts)19.5 Other clerical support workers information and communication technologies(icts)15.4 engineering and engineering trades 6.3 Agricultural,forestry and fishery labourers engineering and engineering trades 3.2 information and communication technologies(icts)1.1 Cleaners and helpers engineering and engineering trades 1.0 Food preparation assistants engineering and engineering trades 1.6 Refuse workers and other elementary workers engineering and engineering trades 4.4 information and communication technologies(icts)1.4 Street and related sales and service workers information and communication technologies(icts)16.3 engineering and engineering trades 6.0 Food processing,wood working,garment and other craft and related trades workers engineering and engineering trades 3.1 Market-oriented skilled agricultural workers information and communication technologies(icts)10.1 engineering and engineering trades 9.9 Market-oriented skilled forestry,fishery and hunting workers information and communication technologies(icts)11.5 Administrative and commercial managers information and communication technologies(icts)26.6 Chief executives,senior officials and legislators information and communication technologies(icts)29.5 Hospitality,retail and other services managers information and communication technologies(icts)44.1 Production and specialized services managers information and communication technologies(icts)28.8 Assemblers engineering and engineering trades 52.1 Drivers and mobile plant operators engineering and engineering trades 4.0 information and communication technologies(icts)2.5 Machine&plant operators engineering and engineering trades 18.4 health professionals information and communication technologies(icts)5.1 engineering and engineering trades 2.8 Information and communications technology professionals information and communication technologies(icts)64.3 Legal,social and cultural professionals information and communication technologies(icts)11.6 business and administration professionals information and communication technologies(icts)29.7 Table 6 Most Requested Skills(Level 1)by Occupation(Continued)29|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Science and engineering and engineering trades professionals information and communication technologies(icts)40.1 engineering and engineering trades 37.5 Teaching professionals information and communication technologies(icts)16.5 engineering and engineering trades 5.6 Protective services workers information and communication technologies(icts)4.7 Sales workers information and communication technologies(icts)15.1 Labourers in mining,construction,manufacturing and transport engineering and engineering trades 12.4 engineering and engineering trades 2.9 Electrical and electronic trades workers engineering and engineering trades 46.9 engineering and engineering trades 10.1 information and communication technologies(icts)3.7 Handicraft&printing workers engineering and engineering trades 14.1 information and communication technologies(icts)7.1 Metal,machinery and related trades workers engineering and engineering trades 37.7 engineering and engineering trades 8.3 Building and related trades workers,excluding electricians engineering and engineering trades 7.3 information and communication technologies(icts)4.2 30|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper 5.Recommendations The report provides a thorough assessment of the EU policy context,the classification of skills and knowledges,as well as trends in the EU labour market in relation to the demand for skills and occupations based on their level of Greenness and Digitalization.One of the main objectives of this report is to further translate the empirical results in a set of recommendations for universities and TVET to integrate and/or develop green digital skills in existing and future curricula.Evidence presented in this study shows that following the introduction of the Paris Agreement and the Agenda 2030,there is a statistically significant and gradual increase in the demand for the skills classified as of high level of greenness and digitalization.So,it is of crucial importance these skills to be mainstreamed in TVET and University Curriculums.Technical and vocational education and training(TVET)systems play an important role in equipping youth and adults with the skills required for employment,decent work,entrepreneurship and lifelong learning.In the present development context,TVET can equip youth with the skills required to access the world of work,including skills for self-employment.Greening TVET and University Curriculum is an essential and cross-cutting theme for sustainable development.It refers to the efforts to reorient and reinforce existing TVET institutions and policies in order to reinforce achievement of sustainable development.Good practice I:Turning university-industry collaboration into an ICT Academy that serves the future To date,over 170 countries have released digital strategies and over 50 countries have their own AI strategies.ICT talent development strategies are thus necessary to meet growing requirements set by countries around the world.University-enterprise collaboration thus becomes ever more necessary to serve the emerging digital industries such as cloud,big data,IoT.Huawei understands the challenge and built a talent development ecosystem with universities and colleges worldwide to deliver training that offer a fair and high-quality education.The Company has so far opened more than 2,600 ICT Academies,with more than 200 in Europe alone.The ICT Academy can count on more than 11,000 teachers who trained more than 200,000 students per year and supported ICT competitions that convened 580,000 students from 85 countries and regions to boost innovation.The ICT Academy builds upon a strong combination of theoretical and practical courses spanning from connectivity(cybersecurity,WLAN technologies and application,5G,and AI)to cloud and computing(deep learning,ML,big data,data storage),and application and development,focusing on vocational certifications.The success of such educational programs is 31|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper also reflected on the ambition to scale the number of partnerships to more than 7,000 globally to serve 1 million ICT Academy students by 2026.Good practice II:the(d)Academy(d)Academy will be a unique pan-European effort to upskill and reskill key workers across the continent,using an AI-based platform and aiming at leading the Reskilling Revolution in Europe.It will automatically suggest,match and deliver challenge-driven programs based on real-world scenarios to close the skills gap.The(d)Digital Academy will be executed in close collaboration with key European Partners,including the AI Data Robotics Association(ADRA),the European Cybersecurity Organization(ECSO),the Association for European Nanoelectronics Activities(Aeneas),the Big Data Value Association,the Software and Data Association(NESSI),the Robotics Association(euRobotics).(d)Digital Academy ecosystem will provide unparalleled access to industry-proven learning content,training programs,experts,educational technology and certification,relying on EIT-Digitals education services track record.Good practice III:Fostering STEM talent for the Twin Transition The green and digital twin transition brings about an array of opportunities to the industrial sector.Nevertheless,the industry wont succeed in this new industrial era if technological transfer and know-how does not happen across sectors and people.Tech-savvy and change-resilient young talents available worldwide deserve every opportunity to succeed in the future of technology.Huaweis global CSR flagship program Seeds for the Future seeks to develop local STEM talent to boost innovation and a deeper understanding of the ICT industry.Through this platform,top university students can tap into various learning opportunities from field visits to Huawei campus and labs in China,online lectures,conferences participation,competitions,and more.It is an encompassing experience that exposes the participants to improve their ICT skills,while learning about the impact of climate change and the need to sharpen digital skills for the green and energy transition.Indeed,digital solutions play a key enabling role to push the green transition forward,as also demonstrated by Huaweis TECH4ALL initiatives deployed across natural ecosystems worldwide.Solutions that combine acoustic or visual technology with cloud and AI to protect biodiversity,restore nature,and improve the quality of research.The use of technological solutions to protect the environment is a collaborative effort on multiple levels.But most importantly,cross-sector talent must be harnessed.ICT experts developing and deploying Tech4Nature solutions need to be educated about ecological issues,while nature conservationists need to know the potential of technologies like AI in nature conservation.Talent unlocks potential and cultivating STEM talent that sees the green and digital transition as the way forward will upscale initiatives such as TECH4ALL 32|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper As discussed in the chapters of this report,the“information and communication technologies(ICTs)”skill and knowledge group is the top requested Green and Digital skill in online job markets and the Education sector is not an exception.ICT in education improves engagement and knowledge retention,it not only assumes the role of assisting teaching in the integration process of TVET,but also helps teachers improve technological self-confidence and teaching quality.Following the global momentum in the commitment to SDGs and the climate change agreements,there is an evident momentum in the demand and the need of such skills from the ICT,Energy,Professional Services,Manufacturing and Finance and Insurance Sectors.In this direction,disadvantaged groups in the labour market(young people,women,persons with disabilities,rural communities and other vulnerable groups)require targeted support to develop their potential knowledge and skills for green jobs.So investing in training to help the disadvantaged groups acquire specialized skills will enable their participation in activities linked to transitioning to green economies.Finally,based on the results of section 4,greening of the TVET and university curriculums should be further reinforced on a sector-by-sector basis to the following directions:Financial Sector:Mainstream ESGs Enhance skills in ESG and SDG metrics Energy:technical knowledge for application of energy-efficiency measures technical knowledge for application of renewable energy technologies upgraded skills for emergent energy markets Manufacturing:raw material collection pre-processing production distribution trade(marketing)sustainable business and product development Agricultural and Food:advanced wastewater treatment practices improved packaging improved sensors and process control(to reduce waste and improve productivity)food irradiation water and wastewater reduction using closed loop/zero emission systems use of information and communication technology(ICT)in agriculture technical knowledge for new practices like organic farming and agroforestry 33|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Focusing more on the ICT and Energy sectors,the green and digital skills are increasingly important to foster the transition of the economies to sustainability.These skills are critical for addressing sustainability challenges,promoting the transition to clean energy sources,and harnessing digital technologies for efficient and eco-friendly operations.Below is an overview of the green and digital skills needed in these sectors:Green Skills:Renewable Energy Expertise:Proficiency in designing,installing,and maintaining renewable energy systems,such as solar panels,wind turbines,and hydropower systems.Energy Efficiency:Skills related to improving energy efficiency in buildings,industries,and transportation,including energy auditing and retrofitting.Circular Economy Knowledge:Understanding of circular economy principles,sustainable materials management,and waste reduction strategies.Environmental Regulations:Knowledge of EU environmental regulations and compliance requirements,including emissions standards and waste management.Digital Skills:Data Analytics:Proficiency in data analysis and interpretation for optimizing energy consumption,predicting equipment failures,and enhancing energy efficiency.Internet of Things(IoT):Skills related to IoT device deployment and management for monitoring and controlling energy systems remotely.Cybersecurity:Understanding of cybersecurity measures to protect critical energy infrastructure and data.AI and Machine Learning:Knowledge of AI and machine learning algorithms for optimizing energy production,consumption,and grid management.To meet the evolving demands of these sectors,educational institutions,training programs,and industry collaborations play a crucial role in preparing a skilled workforce.Global Outlook Essential Green and Digital skills in the ICT and energy sectors across different regions and Countries,reflecting each regions priorities and strategies for addressing both sustainability and digitalization.United States Green Skills Renewable Energy Technology:Expertise in solar and wind energy systems,including installation,maintenance,and grid integration.Energy Management:Skills in energy-efficient building design,HVAC systems,and smart lighting technologies.Sustainable Construction:Knowledge of sustainable building practices and green building certifications like LEED.34|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Environmental Policy:Understanding of federal and state environmental regulations and compliance.Digital Skills Big Data Analytics:Proficiency in analyzing large datasets to improve energy efficiency,grid management,and predictive maintenance.Cybersecurity:Expertise in protecting energy infrastructure from cyber threats and ensuring data security.Smart Grid Technologies:Knowledge of smart grid technologies,including advanced metering infrastructure(AMI)and grid automation.Blockchain:Understanding of blockchain technology for transparent and secure energy transactions and supply chain management.China Green Skills Renewable Energy Engineering:Expertise in solar and wind power systems,including manufacturing,installation,and grid integration.Environmental Engineering:Skills in managing air and water quality,pollution control,and waste management.Green Building Design:Knowledge of sustainable building materials and practices.Digital Skills 5G and IoT:Proficiency in 5G and IoT technologies for energy grid monitoring and management.Digital Manufacturing:Skills related to digital manufacturing and industrial automation for energy-efficient production.Japan Green Skills Nuclear Energy Expertise:Despite transitioning away from nuclear energy,Japan maintains expertise in nuclear power generation and decommissioning.Renewable Energy Technology:Skills in solar,wind,and hydroelectric systems,along with energy storage solutions.Digital Skills Robotics and Automation:Expertise in robotics and automation for energy infrastructure maintenance and disaster response.AI and Robotics:Knowledge of AI and robotics for optimizing energy production and consumption 35|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper 6.Conclusion In the context of the EU policy framework to be implemented during the forthcoming years,the Twin Transition is set to accelerate and trigger significant structural changes in EU labour markets.Following the ONET and ESCO classification systems,in this paper we provide a thorough analysis for the classification of jobs(occupations)in the EU,distinguish them into Green,Digital and jointly Green and Digital.Using Eurostat and CEDEFOP data,we show that the employment related to Jobs/Occupations with a high level of Digitalization,and simultaneously a high level of Greenness and Digitalization have significantly increased over the period 2011 to 2022.Moreover,focusing on employment data by NACE sector in 2022,the positive relationship between employment and level of Greenness is mainly apparent in Agriculture,Energy and Water management sectors,for Digitalization in ICT sector;while for occupations which are jointly classified as Green and Digital in the ICT,Construction and Energy Sectors.Focusing on the growth of employment from 2016 to 2022,the result is striking for Digital and jointly Green and Digital Occupations where we demonstrate a significant positive and significant relation to almost all the sectors.On the other hand,the sectors which appear to be laggards in the integration and demand for Green and Digital skills are the Mining and Quarrying and Wholesale and Retail trade sectors.Finally,focusing on data from online ads,groups of skills with a high level of Greenness,such as engineering and engineering trades,and Digitalization,such as information and communication technologies(ICTs)are included amongst the top requested skills for all occupations in the job market.Following the forecasts,the demand for Green jobs(Elementary occupations),Digital jobs(Professionals and Managers)and jointly Green and Digital jobs(Technicians and associate professionals)is expected to further grow during the period 2022 to 2035.It is apparent that EU talent development will be geared towards more Green and Digital skills and occupations.This trend and the associated new job opportunities are expected to support the green and digital transformation of the EU job market and economies,towards the implementation of the 2030 and 2050 goals.36|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper References CEDEFOP,Green skills and jobs:Highlights,2014.Retrieved from https:/www.oecd.org/employment/leed/Greener skills_Highlights WEB.pdf CEDEFOP,Quantifying skill needs in Europe,2013.Retrieved from http:/dx.doi.org/10.2801/13390 DigitalEurope,Position Paper on Digital Skills,2019.Retrieved from http:/www.digitaleurope.org/Document-Download/Command/Core_Download/EntryId/1089 Digital Skills and Jobs Platform,ICT specialists:the skills gap hinders growth in the EU countries,2021.Retrieved from https:/digital-skills-jobs.europa.eu/en/latest/news/ict-specialists-skills-gap-hinders-growth-eu-countries ESCO Publications,The crosswalk between ESCO and O*NET:Technical Report,2022.Retrieved from https:/esco.ec.europa.eu/en/about-esco/publications/publication/crosswalk-between-esco-and-onet-technical-report EU Science Hub.Employment in the energy sector:trends and impact of the green energy transition,2020.Retrieved from https:/joint-research-centre.ec.europa.eu/jrc-news-and-updates/employment-energy-sector-2020-07-09_en European Commission,The Green Deal Industrial Plan:Putting Europes net-zero industry in the lead,2021.Retrieved from https:/commission.europa.eu/strategy-and-policy/priorities-2019-2024/european-green-deal/green-deal-industrial-plan_en European Website on Integration.European skills agenda for sustainable competitiveness,Social Fairness and Resilience,2020.Retrieved from https:/ec.europa.eu/migrant-integration/library-document/european-skills-agenda-sustainable-competitiveness-social-fairness-and-resilience_en European Commision,Digital Economy and Society index(DESI).Shaping Europes digital future,2022.Retrieved from https:/digital-strategy.ec.europa.eu/en/library/digital-economy-and-society-index-desi-2022 European Commision,A European Green Deal:Striving to be the first climate-neutral continent,2021.Retrieved from https:/commission.europa.eu/strategy-and-policy/priorities-2019-2024/european-green-deal_en European Commision,Critical Raw Materials:ensuring secure and sustainable supply chains for EUs green and digital future,2023.Retrieved from https:/ec.europa.eu/commission/presscorner/detail/en/ip_23_1661 European Synthesis Report,Skills for green jobs,2018.Retrieved from https:/www.ilo.org/skills/pubs/WCMS_143855/lang-en/index.htm 37|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper European Commission,EU taxonomy for sustainable activities,2020.Retrieved from https:/finance.ec.europa.eu/sustainable-finance/tools-and-standards/eu-taxonomy-sustainable-activities_en European Commission,Circular Economy Action Plan,2023.Retrieved from https:/environment.ec.europa.eu/strategy/circular-economy-action-plan_en Joint Research Centre(European Commission).GreenComp,the European Sustainability Competence Framework,2022.Retrieved from https:/op.europa.eu/en/publication-detail/-/publication/bc83061d-74ec-11ec-9136-01aa75ed71a1/language-en IRENA,Renewable Energy and Jobs:Annual Review,2018.Retrieved from https:/www.irena.org/-/media/Files/IRENA/Agency/Publication/2018/May/IRENA_RE_Jobs_Annual_Review_2018.pdf Koundouri,P.,Devves,S.,and Plataniotis,A.(2021).Alignment of the European green deal,the sustainable development goals and the European semester process:Method and application.Theor.Econ.Lett.11,743770.doi:10.4236/tel.2021.114049 Lewandowski P.,The changing nature of jobs in Central and Eastern Europe,2017.Retrieved from https:/wol.iza.org/articles/the-changing-nature-of-jobs-in-central-and-eastern-europe/long OECD,Going Digital:Shaping Policies,Improving Lives,2019.Retrieved from:https:/www.oecd.org/publications/going-digital-shaping-policies-improving-lives-9789264312012-en.htm Skills Future SG,Skills demand for the future economy,2023,Retrieved from:https:/www.skillsfuture.gov.sg/skillsreport UNEVOC,Skills development and climate change action plans Enhancing TVETs contribution.2021.Retrieved from https:/unevoc.unesco.org/pub/skills_development_and_climate_change_action_plans.pdf UNEVOC,Greening Technical and Vocational Education and Training:A practical guide for institutions,2017.Retrieved from https:/unevoc.unesco.org/up/gtg.pdf Vandeplas A.,Vanyolos I.,Vigani M.,&Vogel L.,The Possible Implications of the Green Transition for the EU Labour Market,European Economy,2022.Retrieved from https:/economy-finance.ec.europa.eu/system/files/2022-12/dp176_en_green transition labour.pdf 38|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper 39|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Appendices Appendix 1-Technical This Technical Appendix presents in greater detail our methodology to assess individual Occupations(Level 0)and groups of Occupations(Levels 1,2 and 3),as well as Groups of Skills and Knowledge Concepts(Levels 1,2 and 3),as Green,Digital and jointly Green and Digital.We define the following green dummy variables at the granular(Level 0)skills and knowledge concepts:_!=1$%0,=1,10831._#=1$%0,=1,3059.For all groups of skills or Knowledges(Levels 1,2 and 3),the green skills and green knowledge indices for the underlying group takes the value of the number of Skills/Knowledge Concepts in the group which are classified as Green,divided by the total number of Skills/Knowledge Concepts belonging in the underlying group.Similarly,we define the following Digital Dummy variables:_!=1$%0,=1,10831._#=1$%0,=1,3059.Also,equivalently for all groups of skills or Knowledges(Levels 1,2 and 3),the digital skills and digital knowledge indices for the underlying group takes the value of the number of Skills/Knowledge Concepts in the group which are classified as Digital,divided by the total number of Skills/Knowledge Concepts belonging in the underlying group.Finally,we define the following Green and Digital dummy variables:&_!=1$%0,=1,10831.&_#=1$%0,=1,3059.Equivalently for all groups of skills or Knowledges(Levels 1,2 and 3),the green&digital skills and green&digital knowledge indices for the underlying group takes the value of the number of Skills/Knowledge Concepts in the group which are classified as Green and Digital,divided by the total number of Skills/Knowledge Concepts belonging in the underlying group.40|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper The Dummy variables can be used in order to calculate the levels of Greenness,Digitalization and Greenness and Digitalization,for all occupations or groups of occupations.The Green,Digital and Green&Digital Scores for Occupations(Level 0)or Groups of Occupations(Levels 1,2,3 and 4),or Groups of Skills(Level 1,2 and 3)are defined as:!=&!(# )* (,-.,#/01#/0 100(1),!=# )* (,-.,#/01#/0 100(2),&!=&# &)* (,-.,#/01#/0 100(3),Where:=.and =.Table A1.1 reports the cross-sectional OLS regression estimates of the following model != ! !Where!is the average annual employment growth,from 2012 to 2022,of level 1 Occupations Group and !the Green/Digital/Green&Digital Scores.The Newey-West p values are also reported in parenthesis,while bold denotes significance at 5%level.The number of observations(n)as well as the R squared are reported in Table.Table A1.1 Employment Growth vs Green Digital Green and Digital Scores-Occupations Level 1 a b n R2 Green 0.01-0.22 10 0.52(0.01)(0.00)Digital-0.02 0.28 10 0.55(0.04)(0.00)Green and Digital -0.01 28.89 10 0.62(0.29)(0.02)41|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Table A1.2 presents the cross-sectional regressions of the 2022 employment rates of occupations(Level 2)by NACE sector(NACE Level 2)to their Green,Digital and Green and Digital Scores.!,#= ! !,#Where!,#is the 2022 employment rates of occupations Group(Level 2)of the jth Level 2 NACE sector and !the Green/Digital/Green&Digital Scores.The Newey-West p values,the number of observations(n)and the R squared are also reported in table,while bold denotes significance at 5%level.42|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Table A1.2 Employment Occupations Level 2 vs NACE sectors Level 2 Level 2 Green Scores Digital Scores Green and Digital Scores b p value R2 n b p value R2 n b p value R2 n 1.1 Administrative Services 0.504 0.062 0.01 31-0.695 0.093 0.03 32-0.426 0.063 0.08 16 1.2 Arts and Recreation and other Services-0.622 0.012 0.02 34-0.588 0.082 0.02 35 0.008 0.979 0.00 17 1.3 Finance and Insurance-3.504 0.134 0.07 16-0.252 0.642 0.00 17-11.359 0.064 0.26 8 1.4 ICT 1.768 0.900 0.07 18 4.971 0.000 0.76 19 11.28 0.048 0.05 9 1.5 Professional Services 0.719 0.683 0.01 30 0.255 0.576 0.00 31-0.148 0.892 0.00 17 2.1 Construction 0.590 0.636 0.00 25-0.702 0.223 0.01 26 1.501 0.000 0.28 14 3.1 Accommodation and Food-1.452 0.207 0.01 20-2.630 0.181 0.03 20 13.007 0.157 0.10 10 3.2 Transport and Storage-0.480 0.357 0.00 26-0.643 0.201 0.01 27-1.343 0.132 0.02 14 3.3 Wholesale and Retail Trade-1.423 0.122 0.04 35-0.416 0.179 0.00 36-0.744 0.038 0.12 16 4.Manufacturing-0.052 0.918 0.00 35-0.190 0.443 0.00 35-0.209 0.727 0.00 17 5.1 Education-3.610 0.224 0.04 25-0.626 0.214 0.00 25-12.874 0.151 0.10 11 5.2 Health and Social Care-0.733 0.094 0.01 32-0.886 0.030 0.03 32-0.975 0.216 0.04 16 5.3 Public Sector and Defence -0.512 0.117 0.02 31 0.225 0.677 0.00 31-1.047 0.071 0.08 13 6.1 Agriculture,Forestry and Fishing 10.190 0.002 0.68 17-4.480 0.205 0.03 18 0.305 0.128 0.02 9 6.2 Energy Supply Services 5.026 0.001 0.44 14 0.099 0.883 0.00 15 2.269 0.003 0.33 9 6.3 Mining and Quarrying-3.336 0.147 0.12 6-14.13 0.010 0.67 6-3.569 0.017 0.57 5 6.4 Water and Wastewater treatment 4.750 0.049 0.35 12-1.998 0.338 0.05 13-0.761 0.058 0.04 8 43|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Appendix 2-Additional Results This Appendix contains additional results not included in detail in section 4.Tables A2.1,A2.2 and A2.3 presents the ranking of the Occupations at Level 1,2 and 0 based on their level of Greenness,digitalization and Greenness and Digitalization respectively.For All levels except 1,only the top 15 of occupations(for Level 0)or occupation groups(Levels 1 and 2)are displayed.Table A2.1 Top 15 Green Occupations(Level 0,1 and 2)Green Occupations Score Level 1 Skilled agricultural,forestry and fishery workers 18.875 Elementary occupations 8.175 Technicians and associate professionals 4.603 Professionals 4.507 Plant and machine operators and assemblers 3.739 Craft and related trades workers 3.701 Managers 3.681 Clerical support workers 2.493 Service and sales workers 2.487 Armed forces occupations 0.278 Level 2 Market-oriented skilled agricultural workers 23.800 Agricultural,forestry and fishery labourers 14.106 Refuse workers and other elementary workers 13.581 Science and engineering professionals 11.332 Market-oriented skilled forestry,fishery and hunting workers 11.052 Building and related trades workers,excluding electricians 9.934 Science and engineering associate professionals 8.251 Food preparation assistants 6.928 Health associate professionals 5.696 Cleaners and helpers 5.385 Administrative and commercial managers 5.239 Electrical and electronic trades workers 5.213 Protective services workers 4.602 Health professionals 3.994 Food processing,wood working,garment and other craft and related trades workers 3.938 Level 0 energy assessor 90.909 natural resources consultant 78.788 energy conservation officer 75.000 environmental policy officer 75.000 energy analyst 70.833 environmental expert 70.588 hazardous waste inspector 69.697 recycling specialist 67.568 sustainability manager 65.278 environmental geologist 64.706 environmental protection manager 64.583 environmental education officer 64.000 forestry adviser 62.857 nature conservation officer 60.345 liquid waste treatment plant operator 60.000 44|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Table A2.2 Top 15 Digital Occupations(Level 0,1 and 2)Digital Occupations Score Level 1 Professionals 15.615 Clerical support workers 10.362 Armed forces occupations 8.069 Technicians and associate professionals 7.924 Craft and related trades workers 6.693 Managers 6.118 Plant and machine operators and assemblers 3.818 Service and sales workers 2.892 Skilled agricultural,forestry and fishery workers 2.448 Elementary occupations 1.748 Level 2 Information and communications technology professionals 78.662 Information and communications technicians 44.517 General and keyboard clerks 37.081 Electrical and electronic trades workers 17.730 Science and engineering professionals 15.800 Other clerical support workers 14.693 Armed forces occupations,other ranks 11.671 Non-commissioned armed forces officers 10.414 Customer services clerks 9.876 Science and engineering associate professionals 9.276 Legal,social and cultural professionals 8.695 Production and specialized services managers 7.851 Metal,machinery and related trades workers 7.483 Teaching professionals 7.463 Assemblers 7.103 Level 0 webmaster 98.837 software tester 96.154 user interface developer 93.878 ICT network administrator 93.684 database integrator 93.548 system configurator 93.478 database designer 93.069 mobile application developer 92.941 ICT network engineer 92.784 data warehouse designer 92.593 knowledge engineer 91.954 embedded systems software developer 91.892 integration engineer 91.860 web developer 91.837 ICT integration tester 91.667 45|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Table A2.3 Top 15 Green and Digital Occupations(Level 0,1 and 2)Green and Digital Occupations Score Level 1 Professionals 0.077 Craft and related trades workers 0.067 Technicians and associate professionals 0.063 Managers 0.051 Service and sales workers 0.041 Plant and machine operators and assemblers 0.013 Armed forces occupations 0.000 Clerical support workers 0.000 Skilled agricultural,forestry and fishery workers 0.000 Elementary occupations 0.000 Level 2 Electrical and electronic trades workers 0.508 Science and engineering professionals 0.201 Legal,social,cultural and related associate professionals 0.116 Personal service workers 0.096 Science and engineering associate professionals 0.092 Building and related trades workers,excluding electricians 0.082 Administrative and commercial managers 0.079 Information and communications technology professionals 0.069 Drivers and mobile plant operators 0.059 Hospitality,retail and other services managers 0.057 Production and specialized services managers 0.046 Health associate professionals 0.023 Business and administration professionals 0.021 Food processing,wood working,garment and other craft and related trades workers 0.018 Teaching professionals 0.014 Level 0 smart home engineer 6.818 smart home installer 6.667 geothermal technician 4.878 green ICT consultant 4.762 irrigation technician 4.348 environmental education officer 4.000 acoustical engineer 3.846 electricity distribution technician 3.571 electric meter technician 3.571 energy systems engineer 3.448 ecologist 3.448 interior planner 3.333 electrical transmission system operator 3.333 pastry chef 3.226 botanist 3.125 46|Twin Skills for the Twin Transition:Defining Green Digital Skills and Jobs|White Paper Tables A2.4,A2.5 and A2.6 present the ranking of the Skills/Knowledge Groups at Level 1 and 2 based on their level of Greenness,digitalization and Greenness and Digitalization respectively.For All levels except Level 1,only the top 15 of skills/knowledge concepts groups are displayed(Levels 2 and 3).Table A2.7 reports in detail the share of all skills(level 1)requested in Linked in and online job markets by Occupation(Level 2).Table A2.4 Top 15 Green Skills Groups(Level 1,2 and 3)Green Skills Score Level 1 agriculture,forestry,fisheries and veterinary 27.635 natural sciences,mathematics and statistics 27.136 engineering,manufacturing and construction 14.112 constructing 6.682 services 6.507 handling and moving 6.270 business,administration and law 5.232 information skills 2.940 communication,collaboration and creativity 2.694 social sciences,journalism and information 2.525 working with machinery and specialized equipment 2.309 assisting and caring 2.295 management skills 1.776 health and welfare 1.147 information and communication technologies(icts)0.829 Level 2 environment 85.000 forestry 62.500 handling and disposing of waste and hazardous materials 59.116 agriculture 29.708 architecture and construction 20.316 hygiene and occupational health services 18.967 engineering and engineering trades 17.110 constructing 16.667 biological and related sciences 14.315 protecting and enforcing 13.497 fisheries 13.333 designing systems and products 11.423 tending plants and crops 10.833 installing interior or exterior infrastructure 9.722 analysing and evaluating information and data 9.476 Level 3 handling and disposing of waste and hazardous materials 100.000 environmental sciences 90.000 environmental protection technology 86.667 complying with environmental protection laws and standards 84.444 natural environments and wildlife 80.000 advising o
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The Global Talent Competitiveness Index2023 What a Difference Ten Years Make What to Expect for the Next DecadeBruno Lanvin and Felipe Monteiro,EditorsSPECIAL TENTH ANNIVERSARY EDITIONBruno LanvinFelipe MonteiroEditorsThe Global Talent Competitiveness Index2023 What a Difference Ten Years Make What to Expect for the Next DecadeSPECIAL TENTH ANNIVERSARY EDITIONINSEAD(2023):The Global Talent Competitiveness Index 2023:What a Difference Ten Years Make What to Expect for the Next Decade Fontainebleau,France.Disclaimer:No representation or warranty,either express or im-plied,is provided in relation to the information contained herein and with regard to its fitness,sufficiency,or applicability for any particular purpose.The information contained in this report is provided for personal non-commercial use and information purposes only and may be reviewed and revised based on new information and data.INSEAD,Descartes Institute for the Future,and the Human Capital Leadership Institute disclaim all liability relating to the content and use of the report and the information contained therein,and the report should not be used as a basis for any decision that may affect the business and financial inter-ests of the reader or any other party.The indexs methodology and the rankings do not necessarily present the views of INSEAD,Descartes Institute for the Future,or the Human Capital Leader-ship Institute.The same applies to the substantive chapters in this report,which are the responsibility of the authors.2023 by INSEAD,Descartes Institute for the Future,and the Human Capital Leadership InstituteThe information contained herein is proprietary in nature and no part of this publication may be reproduced,stored in a retrieval system,or transmitted,in any form or by any means,electronic,mechanical,photocopying,or otherwise without the prior per-mission of INSEAD,Descartes Institute for the Future,and the Human Capital Leadership Institute.ISBN:978-2-8399-4080-1Designed by Kenneth Benson,edited by Sarah Carrington,and published by INSEAD,Fontainebleau,France.CONTENTSTHE GLOBAL TALENT COMPETITIVENESS INDEX 2023 iiiContentsPreface.vBruno Lanvin,Co-Founder and Director,Descartes Institute for the Future;INSEAD Distinguished FellowFelipe Monteiro,Academic Director of the Global Talent Competitiveness Index;Senior Affiliate Professor of Strategy,INSEADHuman Capital Leadership Institute|Foreword.viiKevyn Yong,Chief Learning Officer,Human Capital Leadership InstituteINSEAD&Descartes Institute for the Future GTCI Team.ixCHAPTERSChapter 1:A Special Introduction:What a Difference Ten Years Make and What to Expect for the Next Decade.3Bruno Lanvin,Descartes Institute for the Future and INSEAD;Felipe Monteiro,INSEAD;and Michael Bratt,Descartes Institute for the FutureChapter 2:Global Talent Competition Against the Background of Continuing Uncertainties.13Bruno Lanvin,Descartes Institute for the Future and INSEAD;Felipe Monteiro,INSEAD;and Michael Bratt,Descartes Institute for the FutureStatistical Annex to Chapter 2.27Chapter 3:JRC Statistical Audit of the Global Talent Competitiveness Index 2023.45Jaime Lagera Gonzlez,Begoa Cabeza Martnez,Panagiotis Ravanos,OscarSmallenbroek and Michaela Saisana,European Commission Joint Research CentreCOUNTRY PROFILESHow to Read the Country Profiles.63Index of Countries.65Country Profiles.67DATA TABLESHow to Read the Data Tables.203Index of Data Tables.205Data Tables.207APPENDICESAppendix I:Technical Notes.287Appendix II:Sources and Definitions.289Appendix III:About the Contributors and Partners.299PREFACETHE GLOBAL TALENT COMPETITIVENESS INDEX 2023 vTEN YEARS AND COUNTINGThis edition of GTCI marks the reports tenth anniversary.It all started with a conversation between Bruno Lanvin,then Executive Director of eLab at INSEAD,and H.E.Tharman Shanmugaratnam,Minister of Manpower of Singapore,who had come to the local INSEAD campus for the launch of Global Inno-vation Index(GII)2012.A year later,the first edition of GTCI came out.Ten years after that,Dr Shanmugaratnam was elected Presi-dent of Singaporeand GTCI has established itself as a global reference on the Talent Competitiveness stage.This has been an exciting and eventful decade for the global talent scene(and beyond).Following the initial impetus and support from the Human Capital Leadership Institute(HCLI)in Singapore,the business sector and global employers stepped up to the plate.The report has benefited from support and con-tributions from some of the key players on the field of job crea-tion and talent strategies,such as Adecco,TCS,and Google.More recently,HCLI has returned as a GTCI sponsor and knowledge partner.Thanks are also due to INSEAD,in particular Professor Paul Evans,the founding academic director,and Deans Ilian Mihov and Peter Zemsky,who lent their support to the project.INSEAD put together a vibrant team of researchers and staffwith spe-cial thanks to Christine Hirzelwho contributed to a model that has proved robust and pertinent,as confirmed by the annual audit by the European Commissions Joint Research Centre(JRC).They have also contributed to the global visibility of the GTCI.This years report opens with a Special Introduction,which takes a look back at the themes and key messages produced dur-ing these intense first ten years,and underscores their continu-ing relevance over time.The special introduction also includes six prospective messages on what the next decade of talent competitiveness might look like.By and large,the GTCI has been at the leading edge of benchmarking and analytical thinking on labour markets,work organisation,and talent flows.The data accumulated during that process now constitute a significant and valuable resource that will allow more innovative and action-oriented analyses and projections.As co-editors of this ten-year edition of the GTCI Report,we know how much we owe to all those who invested their time,energy and resources to make the GTCI a stable and visible prod-uct of excellence,in particular our founding Advisory Board.As well as those already mentioned,we want to highlight the valu-able support and encouragements received from(in alphabeti-cal order)Thierry Breton,first as CEO of Atos,then as European Commissioner for Internal Market;Peter Capelli,George W.Taylor Professor of Management at The Wharton School and Director of Whartons Center for Human Resources;Alain Dehaze,CEO of Adecco from 2015 to 2023;Vinod Kumar,CEO and Managing Director of Tata Communications from 2011 to 2019;Jacqueline Poh,currently Managing Director of Singapores Economic Development Board;and Nicolas Schmit,first as Luxembourgs Minister of Labour,then as European Commissioner for Jobs and Social Rights.This is therefore a time for celebration and thanks,when pride is mixed with anticipation and excitement for future edi-tions of the GTCI.Bruno LanvinFounder and President,Descartes Institute for the Future;INSEAD Distinguished Fellow Felipe MonteiroAcademic Director of the Global Talent Competitiveness Index;Senior Affiliate Professor of Strategy,INSEADPrefacePREFACETHE GLOBAL TALENT COMPETITIVENESS INDEX 2023 viiOver the past ten years,the Human Capital Leadership Institute(HCLI)has gained countless insights from collaborating on the Global Talent Competitiveness Index(GTCI).Our thanks to col-laborators who have worked tirelessly on the GTCI over the past decade,especially INSEAD,who have committed to developing one of the very best indices of its kindif not the very best!Reflecting on this insightful body of work,three themes stand out.First,the GTCI has kept pace with the implications of tech-nology innovation for human capital.For instance,the 2015 GTCI report statement that“low-skilled workers continue to be replaced by robots,while knowledge workers are displaced by algorithms”is consistent with automation across factories and office tasks,as well as the advent of generative AI.At first glance,it often seems that technology innovations will destroy jobs.When automated teller machines(ATMs)were introduced to the US in 1969,it was claimed that they would lead to unemployment.In fact,the number of bank tellers went from approximately 300,000 to around 500,000 by 1980.ATMs had contributed to job creation,as human tellers were freed up to provide more complex banking services.Similarly,e-mail was predicted to be a job-destroyer,and although it did disrupt tra-ditional post and parcel services,some,if not most,postal com-panies found a way to pivot their business models to support the growth in ecommerce.At HCLI,we see technology innovations as opportunities to rethink and redesign our approach to human capital to create new value.Second,our work on the GTCI has almost always been for-ward thinking.For example,the GTCI anticipated the uneven war for talent from the very beginning.This resonates with our work on future foresight,and our advocacy that future foresight is less about how accurately we predict the future,and more about how we think of multiple possible futures so we can be ready to adapt or respond to expectedand unexpectedchallenges.Thanks to its comprehensive data and its thoughtful analy-sis,the GTCI is an exemplary tool for those developing future fore-sights from the ever-evolving trends in human capital.Consider Welcome to the Post-Industrial Age,a 2023 analysis of the global shortage of talent caused by declining birth rates in the post-industrial age from the Josh Bersin Academy.It makes clear that the GTCI was uniquely positioned to inform the reports recom-mendation,that of shifting to a new model of work characterised by organisational dynamism,human-centred leadership,and HR as a consulting and product organisation.The report shows how designing work around jobs and functional areas to create and deliver value is fast becoming obsolete.Instead,systemic HR can design and organise companies around people and skills,opti-mising output through projects,initiatives,and services to create new value.Finally,and perhaps most importantly,the GTCI is designed with a call to action.The GTCI defines talent competitiveness as the set of policies and practices that enable a country to develop,attract,and empower the human capital that contributes to pro-ductivity and prosperity.Hence its assessment of what countries do to produce and acquire talent(input)and what they do to build the workforces skills and capabilities to achieve the desired socio-economic outcomes(output.)This special tenth-anniversary edition of the GTCI also pre-sents several critical trends for the future that particularly reso-nate with HCLIs work:talent inequalities between individual countries remain high;talent inequalities within countries are stubbornly persistent;and growing uncertainties hamper brain circulation.In particular,our work on ecosystem collaborations can inform or address the problem of talent inequalities around the world(see 2020s Ecosystem Edge:Sustaining Competitive-ness inthe Face of Disruption by Arnoud De Meyer and Peter Williamson).For instance,the wide range of experiences and challenges regarding talent competitiveness across Southeastern Asia(Bru-nei,Cambodia,Indonesia,Laos,Malaysia,Myanmar,Philippines,Singapore,Thailand,and Viet Nam)suggest that a collaborative ecosystem approach could be designed to uplift talent competi-tiveness across the region.Founded on learning from each other to create inclusivity and accessibility it could raise productivity and prosperity for all countries.Similarly,our work on develop-ing Asian-origin leaders for global leadership positions,such as our Singapore Leaders Network(SGLN)Fellowship,can inform or address the challenges associated with brain circulation,at least with respect to the Southeastern Asian ecosystem.The tenth anniversary of the GTCI report is a timely reminder that the challenge of talent competitiveness is really a challenge for humanity.Talent competitiveness is defined as a set of poli-cies and practices for enabling individual countriesbut how might we re-imagine the challenges of talent competitiveness if we define it as the set of policies and practices that enable humanity?To this end,HCLI is proud and deeply grateful for our collaboration with INSEAD and the Descartes Institute for the Futureand looks forward to our collective call to action in dis-rupting the future of human capital.Kevyn YongChief Learning OfficerHuman Capital Leadership InstituteHuman Capital Leadership Institute|ForewordFOREWORDTHE GLOBAL TALENT COMPETITIVENESS INDEX 2023 ixINSEAD&Descartes Institute for the Future GTCI TeamBruno LanvinFounder and President,Descartes Institute for the Future,andINSEAD Distinguished FellowFelipe MonteiroAcademic Director of the Global Talent CompetitivenessIndex;Senior Affiliate Professor of Strategy,INSEADMichael BrattLead Researcher,Descartes Institute for the FutureAnna HenrySenior Project Manager,Descartes Institute for the FutureINSEAD&Descartes Institute for the Future GTCI TeamEditing TeamKenneth BensonGraphic Designer,Pegasus TypeSarah CarringtonCopy Editor,Number Forty TwoINSEAD&DESCARTES INSTITUTE FOR THE FUTURE GTCI TEAMChaptersFor the past ten years,GTCI has continued to collect data and improve its model to track various aspects of talent com-petitiveness.Over the decade,it has been organised around annual themes with every edition generating its own set of key messages.TEN YEARS OF FORWARD LOOKING THEMESSince 2013,GTCI has addressed a variety of topics that include:Growing Talent for Today and Tomorrow(2014);Talent Attraction and International Mobility(2015);and Talent and Technology(2017).Switching gears in 2018,the report turned to Diversity for Competitiveness,followed by Entrepreneurial Talent and Global Competitiveness in 2019,and Global Talent in the Age of Artificial Intelligence in 2020.In 2021,the focus shifted once more,this time to Talent Competitiveness in Times of COVID,and last years edi-tion entitled The Tectonics of Talent:Is the World Drifting Towards Increased Talent Inequalities?Looking back at those topics,themes,and messages,we can say with some confidence that the GTCI got it right more often than not and,in fact,was often ahead of the curve.Bruno Lanvin is the Founder and President of Descartes Institute for the Future,and an INSEAD Distinguished Fellow.Felipe Monteiro is Senior Affiliate Professor of Strategy at INSEAD.Michael Bratt is Lead Researcher at Descartes Institute for the Future.For this tenth anniversary edition,GTCI offers a detailed introduction that looks back at the past ten years of GTCI reports and proposes some key predictions about how the global talent scene might continue to evolve over the coming decade.CHAPTER 1:A Special IntroductionWhat a Difference Ten Years Make and What to Expect for the Next DecadeBruno Lanvin,Felipe Monteiro,and Michael BrattWHAT A DIFFERENCE TEN YEARS MAKETHE GLOBAL TALENT COMPETITIVENESS INDEX 2023 3TEN YEARS OF POWERFUL KEY MESSAGESSome of the key messages that emerged during this decade of analysis appeared repeatedly,as they raised issues that were both urgent and unresolved.This was true particularly for the theme of inequalities.In the very first edition of the report,the first key message was:“The global war for talent is on,and it is an uneven one.”Since then,GTCI reports have emphasised that“Talent inequalities are broadening”(2019);“The gap between talent champions(almost all of them high-income countries)and the rest of the world is widening”(2020);and“Recent and current crises could have a negative and sometimes irrevers-ible impact on the talent situation of poorer economies”(2022).Other key messages in 2022 included the statement that“Even in higher-income economies,labour markets may become more fragmented and hence generate new types of inequali-ties”;and“Amore unequal global talent landscape would signifi-cantly diminish our collective ability to meet some key targets of theSDGs.”Another recurring theme in the first ten years of the GTCI isthat of technological change and how its acceleration is critical to labour markets and even to the definition of work itself.In 2014,GTCI stressed that technological changes will affect new segments of the labour market,implying changes in the required profile of employable skills.In its next edition,the GTCI warned that low-skilled workers continue to be replaced by robots,while knowledge workers are displaced by algo-rithms.In 2017,a key message was that technology is changing the nature of work,and in 2020s issue devoted to Global Talent in the Age of Artificial Intelligence,“the emergence of AI in the workplace requires a massive re-skilling of the workforce”was a key message.The GTCI has also played a pioneering role in exploring the ways in which talent strategies matter at the local level,in particular at the city level.The establishment of a specific Global City Talent Competitiveness Index(GCTCI)has created its own invaluable data resource.This has led to useful insights into imaginative talent initiatives that could be developed and implemented at a sub-national level to create jobs and foster competitiveness.TEN YEARS OF DATA YIELDING UNIQUE TIME SERIESThe data accumulated by GTCI over the past decade constitute a unique resource that provides opportunities for plenty of fur-ther analyses.Based on the approaches taken in the ten years since GTCIs inception,it is possible to identify several important signals regarding changes to both the global and local scenes of talent competition.GTCI data point to at least six major trends in line with the key messages highlighted above:Talent inequalities between individual countries remain high Talent inequalities within countries are stubbornly per-sistent COVID has profoundly altered the global talent landscape Cities and regions play increasingly important roles in tal-ent initiatives Growing uncertainties hamper brain circulation New generations are reshaping the world of work1.Talent inequalities between individual countries remain highOne of the most frequently highlighted findings from GTCI anal-yses is that the global landscape for talent competitiveness isand remainsfraught with inequalities.In other words,poorer economies do not perform as well on the talent scene as other,richer economies.This has been illustrated annually by GTCIs famous scatter plot,which shows the strength of the relation-ship between income per capita and GTCI scores.Comparing the 2023 and the 2013 versions,creates a striking visual image of how strong that correlation has remained(see Figure 1).Despite the significant progress of the demographic pow-erhouses,India and China,up the talent ladder,and Indias successful efforts to close the gap between its economy and that of China,the wealth/talent correlation remains strong.GTCI data from the past ten years show that it has even increased:the correlation coefficient between GDP per capita and GTCI score has grown from 0.76 in 2013 to 0.85 in 2023.In Figure 1,this can be seen in the clearer separation of income groups along the tal-ent competitiveness ladder.Note that,although there were clear overlaps between such groups in 2013,there are almost none in 2023.CHAPTER 14 THE GLOBAL TALENT COMPETITIVENESS INDEX 20231020304050607080906.57.07.58.08.59.09.510.010.511.011.512.0GTCI scoreGDP per capita in PPP$(natural logarithm)High incomeUpper-middle incomeLower-middle incomeLow income2023(R2=0.85)Figure 1Talent performance remains closely linked to income level1020304050607080906.57.07.58.08.59.09.510.010.511.011.512.0GTCI scoreGDP per capita in PPP$(natural logarithm)High incomeUpper-middle incomeLower-middle incomeLow income2013(R2=0.76)WHAT A DIFFERENCE TEN YEARS MAKETHE GLOBAL TALENT COMPETITIVENESS INDEX 2023 52.Talent inequalities within countries are also stubbornly persistentAs new data became available at a global level,GTCI gave con-tinuous and prominent attention to the gender component of talent inequalities.Altogether,GTCI data from the past ten years have shown significant progress in legal and regulatory environ-ments as an increasing number of countries have committed to reduce gender gaps in labour markets.However,such efforts remain insufficient and need to be accelerated.In large parts of the world,women are paid less than men at comparable levels of training and qualifications.They also have fewer career development opportunities and less access to higher levels of responsibility.In many emerging and poorer economies,the gender divide is stronger still,with girls having fewer opportunities to attend school,not to mention higher education.GTCI also described and highlighted how COVID strengthened such inequalities,making them irreversible in some cases.These trends can be seen in GTCIs data on gender parity in high-skilled jobs(see Figure 2).GTCI 2022,which introduced additional data about gender divides,also emphasised how possible options for a post-COVID recovery could,in fact,increase domestic inequalities among various categories of workers.The rapid expansion of new work-ing practices,such as online collaboration,alongside the accel-erating adoption of AI in various industries will undoubtedly have an impact on some of the fundamental parameters of the jobs/skills equation.Unqualified or low-qualified labour will bear much of the additional pressure,while new categories of work-ers,some with higher skills,will suffer from stronger competition from algorithms and specialised equipment.Figure 2Slight progress in talent gender equality thwarted by COVIDGender parity ratio.8.91.02022202120202019201820172016201520142013Perfect equalitySource:ILO,but computation is our own.Note:Gender parity in high-skilled jobs,20132022(y axis shows the ratio,where 1 signifies perfect equality).CHAPTER 16 THE GLOBAL TALENT COMPETITIVENESS INDEX 20233.COVID has profoundly altered the global talent landscapeThe COVID years(202022)presented a challenge to both national and organisational talent strategies,which had to adapt to a dramatically changed environment in education,work,and social activity.Significant levels of public debt were accumu-lated in the process,as stop-gap and emergency measures were adopted to prevent a collapse in employment and output.It is now clear that the new practices adopted during these years will not fade away rapidly.Instead,some of the trends iden-tified by GTCI will contribute to a new normal,in which remote working and online collaboration will become close to common practice in all types of economies and societies.COVID also stimulated the emergence of new tools and techniques,and new ways to organise work and production.As a result,new needs and priorities have emerged in the area of skills and talent profiles.A new world of work is emerging in which talent is less tightly attached to a particular physical location;and this is espe-cially true for high-skilled workers.In such a renewed landscape,an increasing number of talent can make choices about where they want to live and where and how they wish to work.One of the resulting trends that GTCI identified is the growing value of quality of life in decisions made both by individuals and by recruiting organisations when considering physical location.Figure 3 illustrates the strong positive correlation between quality of life in a country and its talent performance before and after COVID.The trend resumed in 2022 and can be expected to continue,and possibly accelerate,in the following years.Figure 3For talents,quality of life matters more and moreLifestyle scoreGTCI score2014201520172018201920202021202220236263646566676869757779818385Pre-COVIDPost-COVIDCOVID disruption(20192021)WHAT A DIFFERENCE TEN YEARS MAKETHE GLOBAL TALENT COMPETITIVENESS INDEX 2023 74.Cities and regions play increasingly important roles in talent initiativesIn 1990,43%of the world population lived in a city.Today,that number is 56%,and is projected to be close to 70%by 2050.From sustainability to innovation and talent,core issues have now largely shifted from central governments to more regional and even municipal levels.Again,COVID has contributed to the acceleration of this trend,as a number of national governmentsincluding some in very large countriesproved unable or unwilling to take meas-ures to fight the spread of the virus and its various mutations.In many parts of the world,cities stepped up to the plate and took the initiative to organise and implement sanitary measures.Through its dedicated Global City Talent Competitiveness Index(GCTCI),GTCI has repeatedly described and measured how cities have been able to deploy original and effective talent strat-egies,and how much global talent competition was influenced by the emergence of new talent hubs among cities in all parts of the world.One of the findings of GCTCI(as shown in Figure4)was that second-tier cities increasingly became the places where the most successful talent policies were deployed.Such cities,often medium or modest sized,frequently demonstrated an ability to be more dynamic and more attractive than larger metropolises.Such a trend is only one facet of the complex set of phe-nomena by which cities have become prominent players on the global talent scene,and may be a harbinger of other possible changes.Cities could play a growing role by taking on some of the responsibilities that national governments have abandoned,or are unable to fulfil.This could occur in fields like international trade or investment,for example,through the adoption of exceptional fiscal or incentive regimes at the local level.Figure 4Cities play increasingly important roles on the global talent sceneSan FranciscoBostonZurichSeattleLausanneSingaporeGenevaHelsinkiMunichDublinAmsterdamOsloChongqingSuratLahoreAddis AbabaDar es SalaamLagosAbujaDhakaR2=0.12041213141516171801020304050607080Population(log)GCTCI overall scoreSource:Authors computations.Note:The green oval highlights the variation of population size among the most talent-competitive cities.The red oval shows the least-talent-competitive cities and points to the potential talent disadvantages of large metropolitan areas.CHAPTER 18 THE GLOBAL TALENT COMPETITIVENESS INDEX 20235.Growing uncertainties hamper brain circulationIt is not an exaggeration to say that,over the past decade,tal-ent competitiveness has become a key vector of geopolitics.Just as international tensions and rivalries have contributed to a decrease in multilateral cooperation and disciplines,the ability of enterprises and organisations,such as universities,to cooperate across national borders has been significantly reduced.The effects of limiting international travel,as initially required by pandemic concerns,have been partially offset by the rapid adoption of online collaboration tools and new work habits.Yet,as the GTCI time series suggests,neither the recent period nor the one to come have created fertile ground for one of the most positive trends identified before COVID:that of brain circulation.In its 2015 edition,Talent Attraction and International Mobil-ity,GTCI highlighted the notion of brain drain/brain gain vs brain circulation.The report underlined that,for national economies as well as for private enterprise,it was an advantage to consider talent as a fluid resource,which would benefit from international exposure.A proven ability to operate in different geographical and cultural contexts has become a major plus for large seg-ments of the global workforce.By putting a sudden stop to international travel,COVID cre-ated a radically different environment for global brain circulation,as shown in Figure 5.To a large extent,this negative trend was offset by the growing tendency among organisations of all sizes to rely on a more systemic use of online collaboration tools.Although international travel resumed swiftly once health-related limita-tions were relaxed,persistent levels of geopolitical uncertainty,renewed nationalistic and protectionist tendencies,and the resulting decrease in international cooperation continue to hamper direct,face-to-face cooperation and,hence,the cross-fertilisation of talent.Figure 5International talent flows are hurt by uncertainties05001,0001,5002,0002,5003,0003,5004,0004,500Total passengersDomestic passengersInternational passengers202120192017201520132011200920072005200320011999199719951993199119891987198519831981197919771975197319711969196719651963196119591957195519531951194919471945Oil crisisIran-Iraq warGulf crisisAsian crisis9/11 terrorist attackSARSFinancial crisisPassengers carried(millions)46%to 49cline in world total passengers,2021 vs 2019 60cline in world total passengers in 2020GTCI yearsCOVID-19pandemicSource:Authors,based on ICAO reporting and estimates,https:/www.icao.int/Aviation-API-Data-Service/Pages/default.aspxNote:Air traffic passengersas measured by ICAObeing used as a proxy for international talent flows.ICAO=International Civil Aviation Organization.WHAT A DIFFERENCE TEN YEARS MAKETHE GLOBAL TALENT COMPETITIVENESS INDEX 2023 96.New generations are reshaping the world of workIn its 2021 edition,Talent Competitiveness in Times of COVID,GTCI warned that a post-COVID recovery could take a K-shape,which would create and feed new types of inequalities among work-ers with different kinds of skills.As shown in Figure 6(which uses the US economy as an example)the upper branch of the K would allow workers equipped with a future-ready sets of skills in key strategic sectors to benefit from the higher wages and career prospects produced by higher demand.In contrast,the lower branch of the K would indicate the path most likely to be imposed on other,less skilled or less adaptable workers.In such a scenario,younger generations preparing to find their first job could be expected to prioritise the acquisition of the most sought-after skills,and pick the most dynamic sectors of activity as their target.GTCI analyses showed this was not necessarily the case.An increasing proportion of younger gen-erations,especially among those with a higher level of educa-tion,were considering other priorities.This might include having a meaningful job by contributing positively to society or the environment,or enjoying a more healthy work-life balance.As mentioned above,when considering the role of cities as talent hubs,quality of life has become a key factor in the choices made by younger cohorts about their working and living environment.The same phenomena have also led to the emergence of a new generation of workers for whom the traditional value of loyalty to their employer has quickly eroded.Gig-working and short-term contracts,often combined into parallel lines of work,have become the norm for a growing number of free agents on the global talent scene.Figure 6A new world of work is taking shapePre-COVID20202021 recessionRecovery(2022 on)Jobs in recovery-supportive sectorsTechnologyRetailSoftware servicesJobs in distressed sectorsTravelEntertainmentHospitalityRestaurants2014201520162017201820192020202120222023Source:Authors,based on personal communication with Ernie Tedeschi,policy economist at Evercore ISI;Akhtar(2020).CHAPTER 110 THE GLOBAL TALENT COMPETITIVENESS INDEX 2023Figure 7A decade of top tensGTCI yearsGTCI2013GTCI2014GTCI20152016GTCI2017GTCI2018GTCI2019GTCI2020GTCI2021GTCI2022GTCI202312345678910GTCI ranksCHCHSGSGDKDKSESEGBGBFIFIUSUSAUAUISISLULUNLNLNONOGTCI PROVIDES A RICH GLOBAL PICTURE OF TALENT COMPETITION OVER THE PAST DECADEAs discussed above,one of the core and repeated messages of GTCI over the past ten years has been that the global talent scene remains uneven and unequal.However,the same analyses confirm that the overall landscape of global talent competitive-ness shows signs of significant mutation.For example,GTCI rankings continue to be dominated by rich countries,but for how long?How are the new dynamics of labour markets and talent competition being modified under the combined effect of post-COVID adjustments and longer-term demographic,economic,social and political trends?Although there have been some notable changes to the GTCI top ten in its first decade,the most high-performing,tal-ent-competitive economies are still found in a small group of countries.Figure 7 and its accumulated data shows that:The list of GTCI top-ten countries has been very steady over the past 10 years.Switzerland and Singapore are the clear leaders;the US is to a lesser extent.The top ten has otherwise been dominated by smaller European countries.Eight of the GTCI top ten in 2023 were also in the top ten in GTCI 2013.The only differences are that Luxembourg and Iceland,now in 11th and 15th position respectively,featured in 2013s top ten,while Australia and Norway have risen to the top ten from 15th and 12th position respectively.However,GTCI time series also suggest that such stability at the top needs to be considered against the background of rapid changes among heavily populated countries,who face growing levels of uncertainty that will affect the world economy in the foreseeable future.Everything is in place for massive disruptions of the global talent landscapeas suggested in the reference to tectonics in GTCI 2022.Although estimates vary,it is safe to assume that the total GDP of the E7(the seven leading emerging economies of Bra-zil,China,India,Indonesia,Mexico,Russia,and Trkiye)is now roughly comparable to that of the G7(Canada,France,Germany,WHAT A DIFFERENCE TEN YEARS MAKETHE GLOBAL TALENT COMPETITIVENESS INDEX 2023 11Italy,Japan,the United Kingdom,and the United States).Chinas rapid progression from 47th to 40th in GTCI rankings,and the level of excellence reached by Indian Institutes of Technology(IITs)suggests that emerging economies will play a significant role in challenging current global hierarchies on the global talent scenedespite Indias continuing struggle to bring its primary education system to the same standard as its higher education.This is further developed in subsequent sections of this report.WHAT TO EXPECT FOR THE NEXT DECADE?As Laurence J.Peter supposedly wrote:“An economist is an expert who will know tomorrow why the things he predicted yesterday didnt happen today.”Trying to describe the future is always a perilous exercise.However,the accuracy of GTCIs pre-dictions from its first ten years provides some level of reassurance in offering the following view of what talent competitiveness might look like in the next ten years.We therefore conclude with six key messages for the futurea time capsule to be reviewed and assessed against the reality of global talent competitiveness in 2033.Key Messages for the Future of the GTCI 2023 Key Message#1:Over the coming decade,talent competitiveness will gain even more importance as a critical element of competitiveness,innovation and geopolitical soft power.This will be true for nations,cit-ies and organisations alike.Key Message#2:Talent competition will grow fiercer.As uncertainties and international tensions continue to accumulate in trade,in investment,in politics and in diplomacy,we can expect more rather than fewer talent wars.This will be reinforced by growing needs to address domestic tensions in labour markets and growing trend towards nationalist postures and policies around topics such as immigration or friend-shoring,for example.Key Message#3:Significant aspects of the world of work will be uprooted under a combination of increasingly ubiquitous factors including:new expec-tations and attitudes from younger generations;the emergence of new economic and organisational models;and new possibilities offered by technologies,including AI.Key Message#4:Cities and regions will pave the way for new talent strategies and talent-based innova-tion.Quality of life and sustainability will be a critical asset for those aiming at becoming talent hubs.Key Message#5:Inequalities in global and local labour markets will take different forms and shapes.Talent-focused regulatory policies will be required at the global level to prevent unnecessary tensions,and to allow the planet to fully leverage its human and technological capacities for a better,sustainable,and more equal world.Key Message#6:In the rapidly moving and uncertain world of the coming decade,skills and educationwill remain vital tools to offer workers opportunitiestocon-tribute to economies and societies in a meaningful fashion.CHAPTER 112 THE GLOBAL TALENT COMPETITIVENESS INDEX 2023THE GTCI CONCEPTUAL FRAMEWORKAs made clear in previous editions of the GTCI,countries are competing globally for the talent they need,and who will con-tribute to competitiveness,innovation,and growth.This requires them to grow their own talent pools,attract talent from under-represented and under-privileged domestic sources as well as overseas and external sources,and to develop the means to retain these essential workers.In such a context,governments,businesses,and various other stakeholders need quantitative instruments that can inform their decisionswhether as inves-tors,employers,employees,or jobseekersand can help them design and implement better policies in areas such as education,employment,and immigration,among others.This is the pur-pose of the GTCI.This years GTCI data and analyses largely confirm the trends identified over the past decade.However,they also point at a few changes in individual rankings as well as in performance by regions and income groups.While the index methodology and structure remain largely unchangedsee the audit provided by JRC belowsuch changes should not be ignored,as some of them might constitute the weak signals that precede broader shifts.As shown and documented in the previous edition of the GTCI,the pandemic has generated long-term shocks across local and international labour markets.As uncertainties continue to grow throughout the world economy,countries,cities and organisations are adopting new talent strategies,which the GTCI attempts to detect and measure.CHAPTER 2Global Talent Competition Against the Background of Continuing UncertaintiesBruno Lanvin,Felipe Monteiro,and Michael BrattBruno Lanvin is the Founder and President of Descartes Institute for the Future,and an INSEAD Distinguished Fellow.Felipe Monteiro is Senior Affiliate Professor of Strategy at INSEAD.Michael Bratt is Lead Researcher at Descartes Institute for the Future.GLOBAL TALENT COMPETITION AGAINST THE BACKGROUND OF CONTINUING UNCERTAINTIESTHE GLOBAL TALENT COMPETITIVENESS INDEX 2023 13attract,and empower the human capital that contributes to pro-ductivity and prosperity.The GTCI is an Input-Output model(see Figure 1)that combines an assessment of what countries do to produce and acquire talent(Input)and the kind of skills that are available to them as a result(Output).Although the underlying structure of the report remains robust and unchanged,feedback on previous editions,additional research,and the availability of new data have allowed the model to be refined.The Input pillars of the GTCI are inspired by the Attract-Grow-Retain framework used by corporations to steer talent management.Multinational corporations frame talent manage-ment in these terms,defining talent management as an organi-sations efforts to attract,select,develop,and retain talented employees to meet their strategic needs.1 The GTCI focuses on efforts by countries,which means the model is fed by macroeco-nomic and country-level indicators.In the context of national competitiveness,Attracting tal-ent is viewed from two perspectives.Firstly,as a draw towards valuable external(i.e.,foreign)resources,which includes both productive businesses through foreign direct investment(FDI)and the like as well as creative people through high-skilled migration.Secondly,as an internal attraction that is focused on removing barriers to entering the talent pool for groups such as those from underprivileged backgrounds,women,and non-native people.Growing talent has traditionally meant education,but its definition should be broadened to include apprenticeships,training,and continuous education as well as experience and Who Is Expected to Use the GTCI and Why?Decision-making in the area of talent development,attraction,and empowerment is remarkably complex and multi-layered,covering many different issues in the fields of economics,edu-cation,human resource management and organisational behav-iour,entrepreneurship,innovation,and strategy,and requiring multi-disciplinary effort.At the policy level,this complexity is compounded by emotional considerations and the international consequences of choices regarding immigration,social equity,and fiscal incentives,among others.Faced with such intricate issues,decision-makersboth public and privateneed quantitative tools that will enable them to benchmark their efforts and results obtained across the different socioeconomic environments into which talent man-agement and talent competitiveness fall.The GTCI has been designed to help address this challenge by providing a compos-ite view of talent competitiveness that is applicable to a large number of countries(134 this year).Although several composite indices concerning skills,talent,and human capital have been developed in recent years,both private and public players in the field see the need for a neutral,global,and respected index that will enable them to:assess the effectiveness of talent-related pol-icies and practices;identify priorities for action in relevant areas;and inform international and local debate in this arena.The Structure of the GTCI ModelIn the context of the GTCI,talent competitiveness refers to the set of policies and practices that enable a country to develop,Figure 1The GTCI 2023 modelGlobal Talent Competitiveness Index(GTCI)InputOutputAttractEnableGrowRetainGKSkillsVTSkillsRegulatory LandscapeMarket LandscapeBusiness and Labour LandscapeExternal OpennessInternal OpennessFormal EducationLifelong LearningAccess to Growth OpportunitiesHigh-Level SkillsTalent ImpactSustainabilityLifestyleMid-Level SkillsEmployabilityNote:GK Skills=Global Knowledge Skills;VT Skills=Vocational and Technical Skills.CHAPTER 214 THE GLOBAL TALENT COMPETITIVENESS INDEX 2023access to growth opportunities.However,although we may acknowledge that most skill development occurs through expe-rience,much remains to be done to conceptualise and measure its role.Retaining talent is necessary because the more talented the person,the wider the global opportunities he or she has.The two key components of retention are sustainabilityboth personal and nationaland quality of life.In addition,the regu-latory,market,business,and labour landscapes within a country also facilitate or impede talent attraction and growth.The GTCI classifies these elements as parts of the Enable pillar.Together,Enable,Attract,Grow,and Retain constitute the four Input pillars of the GTCI model.Regarding Output,the GTCI differentiates between two levels of talent,which can be broadly thought of as mid-level and high-level skills.Mid-level skills,also known as Vocational and Technical Skills(VT Skills),describes skills that have a technical or professional base acquired through vocational or professional training and experience.The impact of VT Skills is measured by the degree of employability to which they lead.Employability is measured by indicators around skills gaps and labour market mis-matches and by the adequacy of education systems.High-level skills,also called Global Knowledge Skills(or GK Skills),describe the creativity and problem-solving skills required by knowledge workers in professional,managerial,or leadership roles.Their economic impact is evaluated by indicators around innovation,entrepreneurship,and the development of high-value industries.Together,VT Skills and GK Skills constitute the two Output pillars of the GTCI model.The GTCI provides an approach to talent competitiveness issues that is comprehensive,action-oriented,analytical,and practical.As noted above,the GTCI is a composite index,which relies on a simple but robust Input-Output model,composed of six pillars,as illustrated in Figure 1.As such,the GTCI generates three main indices that form the most visible focus for analysis,namely:1.The Talent Competitiveness Input sub-index,which is composed of four pillars that describe the policies,resources,and efforts a particular country can harness to foster talent competitiveness.Pillar 1,Enable,reflects the extent to which the regulatory and business environ-mentsincluding issues about competition,management practices,and the functioning of labour marketscreate a favourable climate for talent to develop and thrive.The other three pillars describe the three levers of talent com-petitiveness,which focus respectively on what countries are doing to Attract(pillar 2),Grow(pillar 3),and Retain(pil-lar 4)talent.The Input sub-index is the simple arithmetic average of the scores registered on these four pillars.2.The Talent Competitiveness Output sub-index,which aims to describe and measure the quality of talent in a country resulting from the above policies,resources,and efforts.It is composed of two pillars describing the current situation of a particular country in terms of Vocational and Technical Skills(pillar 5)and Global Knowledge Skills(pillar 6).The Output sub-index is the simple arithmetic average of the scores obtained in these two pillars.3.The Global Talent Competitiveness Index(GTCI),which is calculated as the simple arithmetic average of the scores of each of the four Input pillars and two Output pillars out-lined above.The GTCI model in the edition for 2023 is very similar to that of 2022.The only modifications of note are the removal of one indicator and the addition of another.The indicator that has been removed is 3.2.4 Formal and non-formal education and training,on grounds of data that are too fluctuating.The new indicator is 4.1.5 Vulnerable employment,which adds a more labour-focused dimension to the 4.1 Sustainability sub-pillar.The total number of indicators in this years model has stayedunchanged at 69.The GTCIs country coverage,mean-while,has increased from 133 to 134.Together these countries represent more than 97 percent of the worlds GDP and almost 94 percent of its population.The audit carried out by the JRC of the European Commission(see Chapter 3)has confirmed that the model remains solid and robust,these changes notwith-standing.Further details of the indicator definitions and the method of calculation can be found in the Sources and Defini-tions and Technical Notes appendices.The GTCI model will con-tinue to be refined,based on further discussions with academics and business and government leaders,as well as feedback from GTCI users.GLOBAL TALENT COMPETITIVENESS INDEX 2023:MAIN FINDINGSThe top positions in the ranking of the GTCI scores continue to be dominated by developed,high-income countries(see Table1),and there is a high correlation between GDP per capita and GTCI scores(see Figure 2).The Statistical Annex to this chap-ter presents more detailed information on country performance for the different sub-pillars and indicators.European countries continue to dominate the GTCI rank-ings,taking 17 of the top 25 positions.Switzerland retains its first-place position this year,followed by Singapore,and the United States.This has been the most common constellation in the top three over the past decade.The other non-European countries that make it into the top 25 are Australia,Canada,New Zealand,the United Arab Emirates,South Korea,and Israel.The most nota-ble change in the top 25 this year is that,for the first time,it does not include Japan,which has given way to South Koreaalso for the first time.An assessment of the top 15 countries in this ranking can be found in the Statistical Annex,along with an analysis and com-mentary on performances in the GTCI by income group and by region.GLOBAL TALENT COMPETITION AGAINST THE BACKGROUND OF CONTINUING UNCERTAINTIESTHE GLOBAL TALENT COMPETITIVENESS INDEX 2023 15Table 1Global Talent Competitiveness Index 2023 rankingsCOUNTRYSCOREOVERALL RANKINCOME GROUPREGIONAL GROUPREGIONAL GROUP RANKSwitzerland78.96 1High incomeEurope 1Singapore77.11 2High incomeEastern,Southeastern Asia and Oceania 1United States of America76.60 3High incomeNorthern America 1Denmark76.54 4High incomeEurope 2Netherlands74.76 5High incomeEurope 3Finland74.35 6High incomeEurope 4Norway73.96 7High incomeEurope 5Australia73.93 8High incomeEastern,Southeastern Asia and Oceania 2Sweden73.86 9High incomeEurope 6United Kingdom73.75 10High incomeEurope 7Luxembourg72.88 11High incomeEurope 8Ireland70.45 12High incomeEurope 9Canada70.13 13High incomeNorthern America 2Germany69.88 14High incomeEurope10Iceland69.38 15High incomeEurope11Belgium69.12 16High incomeEurope12Austria69.05 17High incomeEurope13New Zealand67.26 18High incomeEastern,Southeastern Asia and Oceania 3France66.91 19High incomeEurope14Estonia64.29 20High incomeEurope15Malta62.66 21High incomeEurope16United Arab Emirates62.56 22High incomeNorthern Africa and Western Asia 1Czech Republic62.43 23High incomeEurope17Korea,Rep.62.21 24High incomeEastern,Southeastern Asia and Oceania 4Israel62.20 25High incomeNorthern Africa and Western Asia 2Japan61.65 26High incomeEastern,Southeastern Asia and Oceania 5Portugal61.60 27High incomeEurope18Slovenia60.62 28High incomeEurope19Spain60.36 29High incomeEurope20Cyprus59.46 30High incomeNorthern Africa and Western Asia 3Lithuania58.73 31High incomeEurope21Italy58.07 32High incomeEurope22Latvia56.78 33High incomeEurope23Chile55.48 34High incomeLatin America and the Caribbean 1Qatar54.42 35High incomeNorthern Africa and Western Asia 4Slovakia54.24 36High incomeEurope24Poland54.10 37High incomeEurope25Hungary53.91 38High incomeEurope26Greece52.75 39High incomeEurope27China52.57 40Upper-middle incomeEastern,Southeastern Asia and Oceania 6Brunei Darussalam51.74 41High incomeEastern,Southeastern Asia and Oceania 7Malaysia51.35 42Upper-middle incomeEastern,Southeastern Asia and Oceania 8Uruguay51.29 43High incomeLatin America and the Caribbean 2Bahrain50.44 44High incomeNorthern Africa and Western Asia 5Croatia50.38 45High incomeEurope28(continued on next page)CHAPTER 216 THE GLOBAL TALENT COMPETITIVENESS INDEX 2023Table 1(continued)Global Talent Competitiveness Index 2023 rankingsCOUNTRYSCOREOVERALL RANKINCOME GROUPREGIONAL GROUPREGIONAL GROUP RANKGeorgia50.25 46Upper-middle incomeNorthern Africa and Western Asia 6Costa Rica50.20 47Upper-middle incomeLatin America and the Caribbean 3Saudi Arabia49.86 48High incomeNorthern Africa and Western Asia 7Bulgaria49.05 49Upper-middle incomeEurope29Montenegro49.05 50Upper-middle incomeEurope30Mauritius48.77 51Upper-middle incomeSub-Saharan Africa 1Russian Federation48.72 52Upper-middle incomeEurope31Serbia48.56 53Upper-middle incomeEurope32Romania47.39 54High incomeEurope33Armenia46.67 55Upper-middle incomeNorthern Africa and Western Asia 8Albania46.61 56Upper-middle incomeEurope34Belarus46.41 57Upper-middle incomeEurope35Azerbaijan46.19 58Upper-middle incomeNorthern Africa and Western Asia 9Oman45.82 59High incomeNorthern Africa and Western Asia10Trinidad and Tobago45.68 60High incomeLatin America and the Caribbean 4Argentina45.60 61Upper-middle incomeLatin America and the Caribbean 5Uzbekistan44.97 62Lower-middle incomeCentral and Southern Asia 1Kuwait44.83 63High incomeNorthern Africa and Western Asia11Ukraine44.80 64Lower-middle incomeEurope36Moldova,Rep.44.22 65Upper-middle incomeEurope37Jamaica43.59 66Upper-middle incomeLatin America and the Caribbean 6Kazakhstan43.01 67Upper-middle incomeCentral and Southern Asia 2South Africa43.01 68Upper-middle incomeSub-Saharan Africa 2Brazil42.67 69Upper-middle incomeLatin America and the Caribbean 7Jordan42.56 70Lower-middle incomeNorthern Africa and Western Asia12North Macedonia42.53 71Upper-middle incomeEurope38Colombia42.44 72Upper-middle incomeLatin America and the Caribbean 8Botswana42.28 73Upper-middle incomeSub-Saharan Africa 3Mexico42.17 74Upper-middle incomeLatin America and the Caribbean 9Viet Nam41.50 75Lower-middle incomeEastern,Southeastern Asia and Oceania 9Mongolia41.31 76Lower-middle incomeEastern,Southeastern Asia and Oceania10Lebanon41.30 77Lower-middle incomeNorthern Africa and Western Asia13Cabo Verde41.11 78Lower-middle incomeSub-Saharan Africa 4Thailand40.77 79Upper-middle incomeEastern,Southeastern Asia and Oceania11Indonesia40.25 80Upper-middle incomeEastern,Southeastern Asia and Oceania12Trkiye40.20 81Upper-middle incomeNorthern Africa and Western Asia14Peru39.96 82Upper-middle incomeLatin America and the Caribbean10Bosnia and Herzegovina39.79 83Upper-middle incomeEurope39Philippines39.23 84Lower-middle incomeEastern,Southeastern Asia and Oceania13Ecuador38.77 85Upper-middle incomeLatin America and the Caribbean11Kyrgyzstan38.58 86Lower-middle incomeCentral and Southern Asia 3Panama38.56 87High incomeLatin America and the Caribbean12Egypt37.67 88Lower-middle incomeNorthern Africa and Western Asia15Dominican Republic37.51 89Upper-middle incomeLatin America and the Caribbean13Sri Lanka37.36 90Lower-middle incomeCentral and Southern Asia 4(continued on next page)GLOBAL TALENT COMPETITION AGAINST THE BACKGROUND OF CONTINUING UNCERTAINTIESTHE GLOBAL TALENT COMPETITIVENESS INDEX 2023 17Table 1(continued)Global Talent Competitiveness Index 2023 rankingsCOUNTRYSCOREOVERALL RANKINCOME GROUPREGIONAL GROUPREGIONAL GROUP RANKParaguay37.36 91Upper-middle incomeLatin America and the Caribbean14Tunisia36.67 92Lower-middle incomeNorthern Africa and Western Asia16Namibia36.67 93Upper-middle incomeSub-Saharan Africa 5Bolivia,Plurinational St.34.11 94Lower-middle incomeLatin America and the Caribbean15Ghana32.97 95Lower-middle incomeSub-Saharan Africa 6El Salvador32.74 96Upper-middle incomeLatin America and the Caribbean16Gambia32.48 97Low incomeSub-Saharan Africa 7Kenya31.66 98Lower-middle incomeSub-Saharan Africa 8Morocco31.53 99Lower-middle incomeNorthern Africa and Western Asia17Eswatini30.87100Lower-middle incomeSub-Saharan Africa 9Lao PDR30.83101Lower-middle incomeEastern,Southeastern Asia and Oceania14Algeria30.56102Lower-middle incomeNorthern Africa and Western Asia18India30.37103Lower-middle incomeCentral and Southern Asia 5Guatemala30.16104Upper-middle incomeLatin America and the Caribbean17Honduras29.71105Lower-middle incomeLatin America and the Caribbean18Cambodia29.69106Lower-middle incomeEastern,Southeastern Asia and Oceania15Nepal29.37107Lower-middle incomeCentral and Southern Asia 6Zambia29.32108Lower-middle incomeSub-Saharan Africa10Pakistan28.72109Lower-middle incomeCentral and Southern Asia 7Rwanda28.71110Low incomeSub-Saharan Africa11Cte dIvoire28.67111Lower-middle incomeSub-Saharan Africa12Senegal28.62112Lower-middle incomeSub-Saharan Africa13Benin28.45113Lower-middle incomeSub-Saharan Africa14Nigeria28.12114Lower-middle incomeSub-Saharan Africa15Nicaragua28.05115Lower-middle incomeLatin America and the Caribbean19Iran,Islamic Rep.28.03116Lower-middle incomeCentral and Southern Asia 8Zimbabwe26.16117Lower-middle incomeSub-Saharan Africa16Cameroon25.91118Lower-middle incomeSub-Saharan Africa17Uganda25.71119Low incomeSub-Saharan Africa18Malawi25.68120Low incomeSub-Saharan Africa19Tanzania,United Rep.25.33121Lower-middle incomeSub-Saharan Africa20Lesotho24.96122Lower-middle incomeSub-Saharan Africa21Bangladesh24.91123Lower-middle incomeCentral and Southern Asia 9Burundi23.46124Low incomeSub-Saharan Africa22Madagascar23.10125Low incomeSub-Saharan Africa23Mauritania23.09126Lower-middle incomeSub-Saharan Africa24Mali22.02127Low incomeSub-Saharan Africa25Guinea21.87128Lower-middle incomeSub-Saharan Africa26Burkina Faso20.55129Low incomeSub-Saharan Africa27Angola20.43130Lower-middle incomeSub-Saharan Africa28Mozambique20.40131Low incomeSub-Saharan Africa29Ethiopia19.77132Low incomeSub-Saharan Africa30Congo,Dem.Rep.17.57133Low incomeSub-Saharan Africa31Chad14.78134Low incomeSub-Saharan Africa32CHAPTER 218 THE GLOBAL TALENT COMPETITIVENESS INDEX 2023Figure 2GTCI scores versus GDP per capita1020304050607080906.57.07.58.08.59.09.510.010.511.011.512.0GTCI scoreGDP per capita in PPP$(natural logarithm)High incomeUpper-middle incomeLower-middle incomeLow incomeINCNUSIDPKNGBRBDRUMXJPETPHEGCDVNIRTRDETHFRGBTZZAITKECOKRESUGARDZCAUAPLMASAUZAOPEMYGHMZNPMGCICMAUBFMLLKMWZMKZCLROECTDNLGTSNKHZWGNRWBJBITNBOBEJODOGRCZSEHNPTAZHUILAEBYATCHLANIKGPYRSBGSVDKSGFILBNOSKCRNZIEMROMPAKWHRGEUYMNBALTJMAMALGMQABWMDNALSSIMKLVTTBHEEMUCYSZLUMECVMTBNISNote:GDP per capita in PPP$and population data(represented by the size of the bubbles)are drawn from the World Banks World Development Indicators database.The trend line is a polynomial of degree two(R2=0.85).GLOBAL TALENT COMPETITION AGAINST THE BACKGROUND OF CONTINUING UNCERTAINTIESTHE GLOBAL TALENT COMPETITIVENESS INDEX 2023 19Figure 2(continued)GTCI scores versus GDP per capita:ISO-2 country codesCODECOUNTRYAEUnited Arab EmiratesALAlbaniaAMArmeniaAOAngolaARArgentinaATAustriaAUAustraliaAZAzerbaijanBABosnia and HerzegovinaBDBangladeshBEBelgiumBFBurkina FasoBGBulgariaBHBahrainBIBurundiBJBeninBNBrunei DarussalamBOBolivia,Plurinational St.BRBrazilBWBotswanaBYBelarusCACanadaCDCongo,Dem.Rep.CHSwitzerlandCICte dIvoireCLChileCMCameroonCODECOUNTRYCNChinaCOColombiaCRCosta RicaCVCabo VerdeCYCyprusCZCzech RepublicDEGermanyDKDenmarkDODominican RepublicDZAlgeriaECEcuadorEEEstoniaEGEgyptESSpainETEthiopiaFIFinlandFRFranceGBUnited KingdomGEGeorgiaGHGhanaGMGambiaGNGuineaGRGreeceGTGuatemalaHNHondurasHRCroatiaHUHungaryCODECOUNTRYIDIndonesiaIEIrelandILIsraelINIndiaIRIran,Islamic Rep.ISIcelandITItalyJMJamaicaJOJordanJPJapanKEKenyaKGKyrgyzstanKHCambodiaKRKorea,Rep.KWKuwaitKZKazakhstanLALao PDRLBLebanonLKSri LankaLSLesothoLTLithuaniaLULuxembourgLVLatviaMAMoroccoMDMoldova,Rep.MEMontenegroMGMadagascarCODECOUNTRYMKNorth MacedoniaMLMaliMNMongoliaMRMauritaniaMTMaltaMUMauritiusMWMalawiMXMexicoMYMalaysiaMZMozambiqueNANamibiaNGNigeriaNINicaraguaNLNetherlandsNONorwayNPNepalNZNew ZealandOMOmanPAPanamaPEPeruPHPhilippinesPKPakistanPLPolandPTPortugalPYParaguayQAQatarRORomaniaCODECOUNTRYRSSerbiaRURussian FederationRWRwandaSASaudi ArabiaSESwedenSGSingaporeSISloveniaSKSlovakiaSNSenegalSVEl SalvadorSZEswatiniTDChadTHThailandTNTunisiaTRTrkiyeTTTrinidad and TobagoTZTanzania,United Rep.UAUkraineUGUgandaUSUnited States of AmericaUYUruguayUZUzbekistanVNViet NamZASouth AfricaZMZambiaZWZimbabweCHAPTER 220 THE GLOBAL TALENT COMPETITIVENESS INDEX 2023LONGER-TERM TRENDS IN TALENT COMPETITIVENESSThis fifth time-series analysis of the GTCI reaffirms the longer-term trends identified in previous reports.Above all,it under-scores that the most talent-competitive countries are not only better at developing,attracting,and empowering human capi-tal,but these trends also indicate that they are pulling away from less talent-competitive countries.In a word,talent inequalities are widening.The approach used to analyse how talent competitiveness has changed over time follows the general approach of previous editionsthat is,it compares performances in the GTCI over two periods.However,since this edition marks the tenth anniversary of the GTCI,the comparison is made with respect to the two halves over the past decade,rather than over two shorter peri-ods as in the previous editions.The two periods being compared are GTCI 2013GTCI 2018 and GTCI 20192023.2 Focusing on the averages from these longer periods has several advantages.For example,it can make it easier to spot general trends that might be missed in a year-by-year analysis.In addition,it allows for some smoothing of annual fluctuations in the data that,in turn,results in more reliable conclusions.Related to this is that the aggregation absorbs year-to-year changes because of improve-ments in the methodology of the GTCI.3In terms of country coverage,countries that have been included in two of the five years that make up a period have been included in the time-series analysis.For this edition,this means that a total of 113 countries are included,and all four income groups are represented:48 are classified as high-income countries,32 are upper-middle-income countries,26 are lower-middle-income countries,and seven are low-income countries.The regional breakdown,meanwhile,is as follows:six are in Cen-tral and Southern Asia;13 in Eastern,Southeastern Asia and Oce-ania;38 in Europe;18 in Latin America and the Caribbean;19 in Northern Africa and Western Asia;two in Northern America;and 17 in Sub-Saharan Africa.The calculation of the averages of the two five-year periods is based on the GTCI scores that the countries have achieved.More specifically,the calculation comprises two steps:(1)averag-ing overall scores for GTCI 2013GTCI 2018 and GTCI 2019GTCI 2023 periods,and(2)computing country rankings based on the resulting averages.The advantage of this approach is that it is straightforward and yields distinct rankings for each country.The drawback is that the scores are not necessarily fully comparable from one year to the next because of changes in data or meth-odological improvements.An alternative approach,in which five-year average rankings are computed based on ranks(rather than scores)of countries in different GTCI editions,is used to cor-roborate the findings.4Attracting and Growing Talent Are Key for Talent MoversFigure 3 shows how the relative positions of countries in the GTCI have changed in the two periods,GTCI 2013GTCI 2018 and GTCI 2019GTCI 2023.The left-hand and right-hand columns rank the countries according to their GTCI scores in the earlier and Figure 3GTCI rankings in 20132018 and 20192023Note:Colours refer to income groups,which range from dark blue(high income)to light blue(upper-middle income),light brown(lower-middle income),and dark brown(low income).2013201820192023123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113SwitzerlandSingaporeUnited StatesLuxembourgSwedenDenmarkUnited KingdomNorwayFinlandNetherlandsCanadaAustraliaIrelandNew ZealandIcelandGermanyAustriaBelgiumUAEJapanEstoniaFranceCzechiaIsraelQatarMaltaSloveniaSouth KoreaMalaysiaLatviaChilePortugalCyprusSpainSlovakiaLithuaniaPolandCosta RicaItalyHungarySaudi ArabiaBahrainMontenegroMauritiusBulgariaCroatiaPanamaUruguayChinaGreeceNorth MacedoniaKazakhstanOmanTrinidad and TobagoRussiaPhilippinesKuwaitJordanArgentinaSouth AfricaRomaniaArmeniaAzerbaijanGeorgiaLebanonSerbiaTrkiyeColombiaBotswanaMexicoBrazilMongoliaUkraineThailandMoldovaPeruTunisiaNamibiaEcuadorDominican RepublicGuatemalaAlbaniaBosnia&HerzegovinaSri LankaViet NamRwandaKyrgyzstanIndiaIndonesiaEl SalvadorParaguayKenyaNicaraguaHondurasEgyptMoroccoBoliviaSenegalGhanaIranLesothoCambodiaUgandaPakistanBangladeshTanzaniaAlgeriaEthiopiaMaliBurkina FasoZimbabweMozambiqueMadagascarSwitzerlandSingaporeUnited StatesLuxembourgSwedenDenmarkUnited KingdomNorwayFinlandNetherlandsCanadaAustraliaIrelandNew ZealandIcelandGermanyAustriaBelgiumUAEJapanEstoniaFranceCzechiaIsraelQatarMaltaSloveniaSouth KoreaMalaysiaLatviaChilePortugalCyprusSpainSlovakiaLithuaniaPolandCosta RicaItalyHungarySaudi ArabiaBahrainMontenegroMauritiusBulgariaCroatiaPanamaUruguayChinaGreeceNorth MacedoniaKazakhstanOmanTrinidad and TobagoRussiaPhilippinesKuwaitJordanArgentinaSouth AfricaRomaniaArmeniaAzerbaijanGeorgiaLebanonSerbiaTrkiyeColombiaBotswanaMexicoBrazilMongoliaUkraineThailandMoldovaPeruTunisiaNamibiaEcuadorDominican RepublicGuatemalaAlbaniaBosnia&HerzegovinaSri LankaViet NamRwandaKyrgyzstanIndiaIndonesiaEl SalvadorParaguayKenyaNicaraguaHondurasEgyptMoroccoBoliviaSenegalGhanaIranLesothoCambodiaUgandaPakistanBangladeshTanzaniaAlgeriaEthiopiaMaliBurkina FasoZimbabweMozambiqueMadagascarGLOBAL TALENT COMPETITION AGAINST THE BACKGROUND OF CONTINUING UNCERTAINTIESTHE GLOBAL TALENT COMPETITIVENESS INDEX 2023 21later period,respectively.Hence,an upward(downward)slope implies an improvement(deterioration)in the ranking over the two periods,which in turn suggests strengthening(weakening)talent competitiveness.An interesting feature of Figure 3 is that the criss-crosses become increasingly prevalent as ones eyes move from top to bottom.This implies that less talent-competitive countries tend to experience greater fluctuations in ranks over the long term than more talent-competitive countries.Indeed,the ranks of the top-three performers in the GTCI remained the same in both periods.They are,in descending order:Switzerland,Singapore,and the United States.In another example,14 countries in the upper half of the rankings in the earlier period saw their rank remain the same or change by only one position in the later period.For countries in the lower half of the rankings,only seven experienced similarly small movements.What might be the underlying reasons for this tendency?The strong association between talent competitiveness and income level could be one factor:just as better performers in the GTCI(typically high-income countries)are more stable in their talent competitiveness over time,high-income countries tend to experience less volatility than countries of lower income levels.Another plausible explanation is that the set of policies and prac-tices that bring about greater talent competitiveness are more stable and less susceptible to political and socioeconomic fluc-tuations.Viewed in this light,it will be interesting to see in the years ahead whether the tendency of lower fluctuations higher up in the rankings will remain as strong against a backdrop of greater political and socioeconomic uncertainties in the world,including in high-income countries.Given that large changes in the rankings are more com-mon further down the rankings,it will not come as a surprise that the greatest improvers in the GTCI over the past decade are lower-middle-income and upper-middle-income countries.The three countries that climbed the most over the two periods are Albania,Indonesia,and Azerbaijan,which jumped by 16,14,and 13 positions,respectively.All of them made particular strides with respect to Vocational and Technical Skills.Albania and Azer-baijan also considerably improved their ability to Attract talent,whereas Indonesia is also notable for strengthening its enabling environment and the ability to Retain talent.Analysing pillar-level performances of all the top-10 tal-ent improvers5 reveals that all of them improved their average ranks in the pillars Attract and Grow.Nine of the ten countries had their average ranks rise with respect to the enabling envi-ronment,while eight countries saw improvements in the ranks that relate to Vocational and Technical Skills.As for the remaining pillarsRetain and Global Knowledge Skillssix of the top-10 talent improvers enjoyed better ranks in the later period.The Dynamics of Talent Competition Are ChangingAs outlined in the special introduction,the global competition for talent has changed in both its nature and its modalities.Post-COVID,the competition for talent relies more on online coopera-tion,and focuses on specific,strategic areas in which demand is expected to grow or where the availability of new skills still lags local or global needs.National economies have prioritised different aspects of talent strategies in accordance with their own mix of comparative advantages and disadvantages.Some place particular emphasis on education and training of their own workforce,while others are trying to attract and retain the talent that best fits the pursuit of key national goals,be that competi-tiveness,innovation,sustainability or some other ambition.Regular readers of GTCI will recognise Figure 4 from previ-ous editions.It shows the longer-term path followed by countries covered by the index over the past ten years,and describes how talent performance changes over longer periods of timethus eliminating some of the noise created by year-on-year changes.However,as described above,for this tenth-anniversary edi-tion,two periods are being compared.Many important insights can be gathered from this type of analysis,not least the following,which indicate that emerging countries are the core engine of changing talent dynamics.Several of the largest emerging economies are among the best improvers over the past decade:China and Rus-sia have moved from being talent movers to talent cham-pions;Indonesia remains a talent mover,but is one of the countries with the greatest strides in talent competitive-ness over the past decade;Mexico has moved from being a talent laggard to a talent mover;Brazil is still among the talent laggards,but it has progressed within that quadrant and may well soon be categorised as a talent mover.All these five countries have in common an improvement in their ability to Retain talent.The share of countries from Latin America and Western Asia that are talent champions has increased since GTCI 2020.In GTCI 2020,Latin America represented 3%of the top-right quadrant.That rose to 6%in GTCI 2023.Similarly,Western Asia represented 9%of talent champions in GTCI 2020,but 13%in GTCI 2023.Conversely,the share of coun-tries in Europe,Northern America,and Eastern,Southeast-ern Asia and Oceania has decreased over the same period.Talent Champions Continue to Pull Away from the RestThe main finding in the long-term analyses of previous editions is that the gap between the most talent-competitive countries and the rest is widening.This finding remains just as valid in this years GTCI,which extends the long-term analysis to ten years.Figure 5 makes this visually clear,showing how the distribution of scores has changed in the four income groups over the two five-year periods.It can be seen that there has been a notable upward shift for the high-income group,whereas the trend is the opposite for the lower-middle-income and low-income groups.Scores in the upper-middle-income group have been fairly steady over the two periods.Taking the analysis one step further,looking at pillar-level performances by income group paints a broadly similar pic-ture.That is,higher-income groups have generally outpaced CHAPTER 222 THE GLOBAL TALENT COMPETITIVENESS INDEX 2023Figure 4GTCI long-term paths(change in scores for GTCI 20132018 vs 20192023 and GTCI 2023 score)High income Low income Lower-middle income Upper-middle income152535455565752015105051015GTCI 2023 scoreChange in percentAverage GTCI 2023 score:47.8CHCLDKHRHUKWPAPLQASGSKTTUSBFMGMLMZRWUGBDBODZEGGHINIRLSMANIPKTZIDSVALARAMAZBGBRCNCRGTMXMKMEMUMYPYRURSZAChampionsMoversLaggardsLimpersPTKRMTNLNote:A complete ISO-2 country code key can be found as part of Figure 2,page 20.Figure 5Average scores in GTCI 2013GTCI 2018 and GTCI 2019GTCI 2023 by income groupNote:Black bars indicate GTCI 2013GTCI 2018 values and blue bars indicate GTCI 2019GTCI 2023 values.020406080100 High income Upper-middle income Lower-middle income Low incomeMinimumMaximum25th percentileMedian75th percentile 20132018 20192023GLOBAL TALENT COMPETITION AGAINST THE BACKGROUND OF CONTINUING UNCERTAINTIESTHE GLOBAL TALENT COMPETITIVENESS INDEX 2023 23lower-income groups in each pillar during the past decade.Looking at relative pillar-level performances within each income group,they have generally been similar across all pillars in the high-income group over the past ten GTCI editions,although high-income countries seem to have a slight advantage in both the ability to Retain talent and in Global Knowledge Skills.As for upper-middle-income countries,there has been a convergence of pillar performances,which is reflected in the more narrow range of median ranks seen in GTCI 2023 than in GTCI 2013.This suggests that talent competitiveness has become more bal-anced in upper-middle-income countries in the past decade.Lower-middle-income countries have frequently performed comparatively well in the two Output-related pillarsVocational and Technical Skills and Global Knowledge Skillswhereas Ena-ble and Grow have often been among the weakest pillars in this income group.As for low-income countries,Attract has been the strongest pillar in every GTCI edition without exception.The trends are similar from a regional perspective(Figure6).The higher-scoring regionsEastern,Southeastern Asia and Oceania;Europe;Northern Africa and Western Asia;and North-ern Americahave improved their medians and means over the two periods,while Central and Southern Asia,Latin America and the Caribbean,and Sub-Saharan Africa have seen their cor-responding values decline.In terms of pillar-level performances within regions,Europe and Northern America have been the highest-ranked regions in all pillars in every GTCI edition.However,Europe has consistently enjoyed a particular advantage in its ability to Retain talent,while Northern America has been especially strong in growing talent throughout the decade.The two pillars that stand out in Eastern,Southeastern Asia and Oceania are Grow and Global Knowledge Skills,which have been that regions best-performing pillars in almost every GTCI edition.The most consistently strong pillar in the Northern Africa and Western Asia region refers to the ena-bling environment,but the greatest improvement relates to the ability to Attract talentthe regions weakest pillar at the begin-ning of the decade and its strongest pillar at the end of it.Latin America and the Caribbean has done well in the Attract and Grow pillars throughout the decade and it has also improved the ability to Retain talent.Central and Southern Asia has consist-ently maintained an advantage with respect to retaining talent,but there has been a clear deterioration in the regions ability to Enable and Attract talent.As for Sub-Saharan Africa,Attract has been the best-performing pillar in the region by far,although this advantage has weakened over time,especially in the past few years.The weakest pillar in the region has frequently been the ability to Retain talent.Main Findings from GTCI 2023 The talent champions are consistently strong in all,or almost all,dimensions of talent competitiveness.A constant theme throughout the GTCI is that the best performers do well in virtually all pillars.Switzerland,the global leader in all editions,is the talent champion par excellence in this regard.The same characteristic also applies to regions:Europe and Northern America outper-form other regions in all pillars,on average.Figure 6Average scores in GTCI 2013GTCI 2018 and GTCI 2019GTCI 2023 by regional groupNote:Black bars indicate GTCI 2013GTCI 2018 values and blue bars indicate GTCI 2019GTCI 2023 values.The plots for Northern America are without wide bars because they only contain two countries:Canada and the United States.020406080100 Sub-SaharanAfrica NorthernAmerica Northern AfricaandWestern Asia Latin Americaand theCaribbean Europe Eastern,Southeastern Asiaand Oceania Central andSouthern Asia MinimumMaximum25th percentileMedian75th percentile 20132018 20192023CHAPTER 224 THE GLOBAL TALENT COMPETITIVENESS INDEX 2023 The talent champions have a particular edge in their ability to Retain talent and in their Global Knowledge Skills.Although the most talent-competitive countries outshine other countries in their consistent all-round per-formance,the gap between them is particularly wide with respect to the Retain and Global Knowledge Skills pillars.In other words,it is primarily the performances in these pillars that seem to set the talent champions apart from the rest.The countries making the most headway in the past decade have strengthened the ability to Attract and Grow talent.The ten countries that have made the great-est strides in strengthening their talent competitiveness over the past decadethe talent improvershave fre-quently made progress in several pillars.However,there are two pillars where all of them have seen improvements:Attract and Grow.Countries looking to emulate the pro-gress of the talent improvers should therefore ensure that supporting these pillars are part of their efforts to strengthen talent competitiveness.The top performers among middle-income countries typically have a favourable enabling environment for nurturing talent.Although the highest-ranked middle-income countries sometimes differ in their particular strengths,many of them have in common a conducive enabling environment for talent.Several of the top per-formers also have strong pools of Vocational and Techni-cal Skills.ENDNOTES 1 See Cappelli&Keller(2014);Stahl et al.(2012).2 The question arises as to why GTCI 2013GTCI 2018 covers five editions rather than six.The reason for the apparent discrepancy is that the print year of the report has not always matched the launch year.More specifically,the GTCI reports are always printed towards the end of the calendar year and the first two editions of the GTCI referred to this in their titles(The Global Talent Competitiveness Index 2013 and The Global Talent Competitiveness Index 2014).However,because the launch of the report used to be held in January,a change was made in the third edition,whereby the title would refer to the launch year.Thus,the third edition became The Global Talent Competitiveness Index 201516 and subsequent editions have had the launch year included in the title.3 One caveat to the results discussed in this section is that the GTCI model has evolved over the years,with the possible implication that a score that changes from one year to the next might primarily reflect a methodological adjustment rather than new data.This potential problem is addressed by averaging the scores across five years,as this implies some smoothing of modifications to the GTCI model,and by focusing the analysis on aggregate overall GTCI scores,which entails a degree of cancelling-out effects.4 More concretely,the country with the best average rank for a five-year period would be ranked 1st,the country with the next-best rank would be ranked 2nd,and so on.5 In descending order of improvement in rank over the two periods:Albania(from 82nd to 66th),Indonesia(89th to 75th),Azerbaijan(63rd to 50th),Serbia(66th to 55th),Ukraine(73rd to 62nd),Algeria(107th to 96th),Georgia(64th to 54th),China(49th to 40th),Ghana(99th to 90th),and Egypt(95th to 87th).REFERENCESCappelli,P.,&Keller,J.R.(2014).Talent Management:Conceptual Approaches and Practical Challenges.Annual Review of Organizational Psychology and Organizational Behavior 1:305331.Stahl,G.K.,Bjrkman,I.,Farndale,E.,Morris,S.,Paauwe,J.,Stiles,P.&Wright,P.M.(2012).Six Principles of Effective Global Talent Management.Sloan Management Review,53,2542(January 2012).https:/journals.aom.org/doi/abs/10.5465/amd.2022.0028GLOBAL TALENT COMPETITION AGAINST THE BACKGROUND OF CONTINUING UNCERTAINTIESTHE GLOBAL TALENT COMPETITIVENESS INDEX 2023 25Statistical Annex to Chapter 2OVERVIEWThis annex analyses country performance in terms of overall score in the GTCI,as well as performance in individual pillars and sub-pillars.Performance data are broken down in different ways:by top performers(the top 15 GTCI score leaders),by region,and by income group(high,upper-middle,lower-middle,and low income).1 Also included is a comparative analysis of the BRICS countries(Brazil,Russia,India,China and South Africa).In total,there are 134 countries included in this years GTCI,up from last years 133.Of these,49 are high-income countries,34 are upper-middle-income countries,39 are lower-middle-income countries,and 12 are low-income countries.The regional distribution,meanwhile,is as follows:nine countries are in Cen-tral and Southern Asia;15 countries are in Eastern,Southeastern Asia,and Oceania;39 are in Europe;19 are in Latin America and the Caribbean;18 in Northern Africa and Western Asia;two coun-tries are in Northern America;and 32 are in Sub-Saharan Africa.All countries that were covered in the GTCI 2022 remain in this years edition.Uzbekistan is the addition to the 2023 index,the first time it is included in the GTCI.Figure A1 presents the dispersion of GTCI scores by income group and by region.In terms of income group,the left-hand panel(1a)illustrates the positive relationship between GTCI score and GDP per capita.More specifically,high-income countries outperform upper-middle-income countries in all percentiles.The same is true of lower-middle-income countries and low-income-country groups.The dominance of high-income coun-tries in the GTCI is particularly striking:indeed,the score at the 25th percentile of the high-income group exceeds the best-performing country in the upper-middle-income group.As for performance by region,as the right-hand panel inFigure A1(1b)shows,scores here also reflect income level.Thus,Northern America and Europewhich have the great-est shares of high-income countriesare the two best-performing regions,followed by Eastern,Southeastern Asia and Oceania.Conversely,the two regions with the greatest shares of low-income and lower-middle-income countriesSub-Saharan Africa and Central and Southern Asiaare also the two worst-performing regions.In addition,performance by region isalso a function of the number of countries within each region.For instance,the region with the highest num-ber of countries,Europe,has a wide dispersion of scores,even though itonlyincludes upper-middle-income and high-income countries.Figure A1Country dispersion of GTCI scores1a:By income group1b:By region0255075100Sub-Saharan AfricaNorthern AmericaNorthern Africa and Western AsiaLatin America and the CaribbeanEuropeEastern,Southeastern Asia and OceaniaCentral and Southern Asia0255075100LowLower-middleUpper-middleHighMinimumMedianMaximum25th percentile75th percentileGTCI scoreGTCI scoreNote:The figure for Northern America has only two bars because it contains only two countries:Canada and the United States.STATISTICAL ANNEX TO CHAPTER 2THE GLOBAL TALENT COMPETITIVENESS INDEX 2023 27At the country level,year-on-year changes in rankings are to be expected given updates to data and refinements of the GTCI model.These changes tend to be small,with only a few countries experiencing dramatic climbs or falls in the rankings.However,the past few years have seen greater fluctuations than usual,due to the impact of the COVID pandemic on labour markets and the methodological changes to the GTCI(a response to the discon-tinuation of certain indicators).This years GTCI rankings mark a return to greater stability,as would be expected now that COVID is no longer seen as an international public health concern,2 and because most indicators populating the GTCI are unchanged since last year.A notable consequence is that only two coun-tries in the GTCI 2023 saw their rankings move by 10places or more,whereas GTCI 2022 saw 18 countries experience this kind of change in their rankings.A constant in the GTCI over the past decade has been the dominance of European countries in the top 25,and GTCI 2023 is no exception.Switzerland,the worlds most talent-competitive country in every edition,remains firmly in the top spot.All Nordic countries but one make it into the top 10(Denmark in 4th place;Finland,6th;Norway,7th;and Sweden,9th.Iceland is the excep-tion,at 15th).Western European countries,such as the Nether-lands in 5th place,the United Kingdom in 10th,and Luxembourg at 11th,are also among the top performers.Four other regions are represented in the top 25:North-ern America(United States of America ranks 3rd;Canada 13th);Eastern and Southeastern Asia(Singapore,in 2nd;South Korea in 24th);Oceania(Australia 8th;New Zealand 18th);and Western Asia(the United Arab Emirates at 22nd;Israel 25th).Some of the differences in GTCI scores are driven by diver-gent performance in particular pillars(Figure A2).For example,dispersion in the Retain pillar is greater than in the Attract pil-lar,which suggests that the ability to retain talent varies much more than the ability to attract it.Similarly,ranking for Global Knowledge Skills is more varied than for Vocational and Techni-cal Skillsalthough less evident in the figurean indication that higher-level skills and their impact are what primarily set coun-tries apart,rather than more specialised,technical skills.A detailed overview of country-level performances is shown in Figure A3,a heatmap that presents the rankings in the GTCI overall and in each pillar,and which is shaded by the quartile to which the rankings of each of the 134 countries belong.As the heatmap indicates,there is a certain degree of complementarity across pillars,with performances in various pillars seeming to be mutually reinforcing.That is,a strong performance in one pillar is associated with positive showings in the othersand vice versa for weak performances.To give a specific example,countries ranked in the top quartile overall are typically also ranked in the top quartile in each of the six pillars(they account for 88 per-cent of top-quartile performances at the pillar level).The same pattern is seen among countries ranked in the bottom quartile overall(where they account for 82 percent of bottom-quartile performances at the pillar level).TOP 15 COUNTRIES IN THE GTCI 2023The top 15 in the GTCI has remained relatively stable over the past decade.Eighteen countries have featured among the top 15 countries on at least one occasion;12 of them have made this group of best performers in all ten GTCI editions.Switzerland has ranked as the worlds most talent-competitive country ever since the GTCI was launched in 2013,and this year is no different.Similarly,Singapore remains in 2nd place,a position it has held in every edition apart from GTCI 2020.The United States climbs one place and returns to the top three,which it has made five times in the past ten years.Denmark,3rd last year,drops to 4th this year,although its score is only slightly lower than that of the United States.Last year marked the second time that Denmark had featured in the top three.Figure A2Dispersion of country scores for each pillar020406080100GK SkillsVT SkillsRetainGrowAttractEnableMinimumMaximum25th percentileMedian75th percentileGTCI scoreNote:GK Skills=Global Knowledge Skills;VT Skills=Vocational and Technical Skills.CHAPTER 228 THE GLOBAL TALENT COMPETITIVENESS INDEX 2023COUNTRYGTCI RANKINGENABLEATTRACTGROWRETAINVT SKILLSGK SKILLSCountries ABOVE the median in the overall GTCI scoreSwitzerland11351210Singapore27233831United States342211515Denmark4278289Netherlands5584101216Finland639134417Norway781412377Australia8156614193Sweden9611147106United Kingdom101213211292Luxembourg111312291812Ireland1220510132315Canada1316109281618Germany141015166623Iceland1518182312114Belgium16171911241420Austria171417195525New Zealand18111220225711France1919257192521Estonia20222429183313Malta2133203384919United Arab Emirates2223417592832Czech Republic2325272621928South Korea2421592829278Israel25244443251314Japan2694221233933Portugal27301625204824Slovenia28323227261726Spain29262618176331Cyprus30412147163722Lithuania31273136274627Italy32294024313038Latvia33363540333429Chile34373435344442Qatar35282332772165Slovakia36425152322439Poland37437337402236Hungary38444751373235Greece39544339306640China40319115744743Brunei Darussalam41515446492645Malaysia42357144663834Uruguay43343634366976Bahrain44462930695663Croatia45567463355137Georgia46473871453660Costa Rica47402838526874Saudi Arabia48483953802057Bulgaria49528662395047Montenegro50633386424249Mauritius51393778415277Russia52788431564341Serbia53624858584151Romania54696667434556Armenia55704191445453Albania56555054516482Belarus571068165474044Azerbaijan58674579621595Oman59496156645985Trinidad and Tobago60854977463584Argentina61916342486775Uzbekistan627665100533164Kuwait63603084607570Ukraine64755768507750Moldova65886072576062Jamaica66505581795879Kazakhstan679356705412230(continued on next page)Figure A3Rankings in the GTCI overall,and by pillarSTATISTICAL ANNEX TO CHAPTER 2THE GLOBAL TALENT COMPETITIVENESS INDEX 2023 29COUNTRYGTCI RANKINGENABLEATTRACTGROWRETAINVT SKILLSGK SKILLSCountries BELOW the median in the overall GTCI scoreSouth Africa68575369829358Brazil69618860687469Jordan70457785617880North Macedonia71808388556167Colombia72717045867366Botswana73388293729655Mexico74819841657972Viet Nam75597255987171Mongolia767269737310048Lebanon77977966897046Cabo Verde785375106707673Thailand79659261838168Indonesia8058106648465100Trkiye819010750818061Peru82836848888586Bosnia and Herzegovina83989480716287Philippines848910249928654Ecuador85969557788398Kyrgyzstan8611252105767281Panama878776766310193Egypt888211075935591Dominican Republic89646797919288Sri Lanka907312287855396Paraguay9110458101679899Tunisia9277121947510759Namibia936864898791115Bolivia94113116599510589Ghana9566909511188112El Salvador96109118829782104Gambia971014698103114119Kenya9895105921149094Morocco997910810910111790Eswatini1009989102106118101Lao PDR101861001151169992Algeria1021051261119010397India10392132909912183Guatemala10410812774102104113Honduras10512111583100112110Cambodia10610385104110115117Nepal1071161241209494103Zambia1081076212312695111Pakistan10911112599105109107Rwanda1108487113113126114Cte dIvoire11110080103117120116Senegal1129493122107116122Benin113747812613089128Nigeria11411911211811812352Nicaragua11512599110108111105Iran116114134961049778Zimbabwe11712911711212287108Cameroon118122119107125110102Uganda11911897114131102120Malawi120115109125112108129Tanzania121102101116119124130Lesotho12212811112996128118Bangladesh123117131124109113109Burundi124131103108129106133Madagascar125124113117127119124Mauritania12612712912812084126Mali127110123127121131132Guinea128120120119132125127Burkina Faso12912396133124133125Angola130130104131123134106Mozambique131126114132115132131Ethiopia132132133121128129121Congo,Dem.Rep.133133128130133130123Chad134134130134134127134Note:The darkest colour means the country belongs to the 1st quartile(best performers);medium colour=2nd quartile;pale colour=3rd quartile;palest colour=4th quartile(worst performers).GK Skills=Global Knowledge Skills;VT Skills=Vocational and Technical Skills.Figure A3(continued)Rankings in the GTCI overall,and by pillarCHAPTER 230 THE GLOBAL TALENT COMPETITIVENESS INDEX 2023All other countries in this years top 15 also featured last year.Northern European countries continue to dominate,with the Netherlands,Finland,and Norway immediately following Den-mark in the top ten,with Sweden in 9th and Iceland in 15th.All but Iceland,which has made the grade eight times in total,have consistently ranked in the top 15 since 2013.As for the remain-ing countries,Australia at 8th place,the United Kingdom at 10th,Luxembourg at 11th,and Canada at 13th,all count among the countries that have consistently ranked in the top 15.Ireland,in 12th place this year,and Germany in 14th have featured six and seven times,respectively.The three countries that have previ-ously made the top 15,but fall outside it this year,are:Belgium(now in 16th place),Austria(17th),and New Zealand(18th).The top 15 performers also dominate all six pillars of the GTCI,which is further evidence that there are feedback loops across different areas of talent competitiveness.As can be seen in Table A1,the top three countries in each pillar also feature among the top 15 countries in the overall index.Switzerland,for instance,is the global leader in terms of enabling and retaining talent and is also a top-three performer in both the Attract pillar and the Vocational and Technical Skills pillar.The second-most talent-competitive country,Singapore,likewise features in the top three in four pillars,including 1st position for Global Knowl-edge Skills.The United States is the best performer in two pil-lars,Grow and Vocational and Technical Skills,while Luxembourg tops the Attract pillar.Analysing performances across pillars suggests that the top 15 countries are especially strong in the Input-related pillars.Thir-teen of them count among the top 15 countries in the Attract and Retain pillars,and 12 of them do so in the Enable and Grow pillars.The equivalent count for the two Output-related pillarsVocational and Technical Skills and Global Knowledge Skillsis 10 and 11 countries,respectively.However,there are also several countries that,although ranked outside top 15,do make it as top performers in spe-cific pillars.For example,Austria has the fifth-highest score in the Retain and in the Vocational and Technical Skills pillars.The United Arab Emirates is ranked 22nd overall,but has one of the best scores in the Attract pillar,while Japan(26th overall),France(19th),and Malta(21st)are among the top 10 performers in the Enable,Grow,and Retain pillars,respectively.Two other countries that shine in specific pillars are the Czech Republic(ranked 23rd overall)in Vocational and Technical Skills and South Korea(24th overall)in Global Knowledge Skills.Individual country analysesSwitzerland(1st)is at the top of the GTCI rankings this year,just as it has been every year since the index was launched ten years ago.The one aspect of Switzerlands talent competitiveness that makes it stand out is its impressive performances in multiple pil-lars and sub-pillars.It features in the top 10 in all six pillars,for example,and is the global leader in the Enable and Retain talent pillars.It ranks 2nd in Vocational and Technical Skills,thanks to the high relevance of its education system to its economy,and 3rd in the Attract pillar.As for the 14 sub-pillars,it is in the top 10 in all but two.Above all,Switzerland ranks 1st in Sustainability,which can be attributed to its high levels of social protection and the quality of its natural environment.The two lowest-ranked sub-pillars are Access to Growth Opportunities and High-Level Skills(it is ranked 15th in each case).In the former sub-pillar,there is scope to increase the use of virtual professional networks.In the latter sub-pillar,there is room to expand tertiary educated employees in the workforce.Singapore(2nd)has earned its 2nd-place ranking in almost all GTCI editions and this year is no different(GTCI 2020 was the exception).Above all,it is a global leader in Global Knowledge Skills,where its highly-educated labour force and innovative economy contribute to its top rank in the High-Level Skills and Talent Impact sub-pillars.The city-state also makes it into the top three in the following pillars:Attract,Grow,and Vocational and Technical Skills(2nd,3rd,and 3rd respectively).In these pillars,its top-ranked Formal Education,its ability to match workforce supply and labour market demand(it is 2nd in Employability),and its 4th-placed ranking for External Openness towards over-seas business and talent are particularly impressive.The countrys main weakness(36th position)remains its ability to Retain talent:greater personal rights and physician density would improve its ranking(currently 37th)in the Lifestyle sub-pillar.The United States(3rd)returns to the GTCI top three,after being ranked 4th in 2022.This means that this years top three reflects the most common grouping over the past decade:Swit-zerland,Singapore,and the United States have made up the top three in half of all GTCI editions.The United States is the global leader in two pillars:Grow and Vocational and Technical Skills.In terms of growing talent,its world-class universities and business schools contribute to its excellent 2nd place Formal Education and 1st-ranked Lifelong Learning.As for Vocational and Technical Skills,the countrys high labour productivity and ease of finding skilled employees translate into 6th-place rankings for both Mid-Level Skills and Employability.The countrys weakest pillar(22nd)is Attract,which would benefit both from greater External Open-ness towards overseas business and talent(where it ranks 24th)and from increased Internal Openness towards domestic human capital(17th),including greater gender equality.Denmark(4th)drops out of the top three after a year,although its score is only just below that of the United States in 3rd place.This marks the seventh time that the country has Table A1Countries with highest scores,by pillarPILLARTOP-RANKING COUNTRIESEnableSwitzerland,Denmark,FinlandAttractLuxembourg,Singapore,SwitzerlandGrowUnited States,United Kingdom,SingaporeRetainSwitzerland,Denmark,NorwayVocational and Technical(VT)SkillsUnited States,Switzerland,SingaporeGlobal Knowledge(GK)SkillsSingapore,United Kingdom,AustraliaSTATISTICAL ANNEX TO CHAPTER 2THE GLOBAL TALENT COMPETITIVENESS INDEX 2023 31ranked among the five most talent-competitive countries.As in previous years,strong performances across all pillars of the GTCI make Denmark an impressive force in talent competition.Its highest-ranked pillars are Enable and Retain(2nd in both),thanks to top-10 performances in all associated sub-pillars.In all remain-ing pillars,Denmark features in the top 10:it is 7th in Attract,8th in both Grow and Vocational and Technical Skills,9th for Global Knowledge Skills.Of particular note is Denmarks high degree of Internal Openness,for which it is ranked 3rd overall,which is primarily due to its merit-based opportunities for upward mobil-ity and strong gender equality.It is also ranked 3rd for providing Access to Growth Opportunities,including through extensive delegation of authority to subordinates.The Netherlands(5th)achieves its highest-ever rank in the GTCI this year and enters the top five for the first time.As in last years edition,it ranks higher in the Input-related pillars than in the two Output-related pillars.Its highest rank(4th)is in the Grow pillar,where contributing factors include the high quality of the tertiary education and 4th-place ranking for Formal Education,the extensive training in firms which help place it 7th for Life-long Learning,and widespread use of virtual networks(it is 4th in Access to Growth Opportunities).The Netherlands also boasts an impressive ability to Enable talent(ranked 5th),with excellent showings in all three related sub-pillars.Its two lowest rankings are for Vocational and Technical Skills and Global Knowledge Skills(12th and 16th respectively).In the case of Vocational and Technical Skills,its 13th place in Employability is offset by its 27th ranking in lower Mid-Level Skills.As for Global Knowledge Skills,its innovation capabilities help push it to 15th in the Talent Impact sub-pillar.Finland(6th)climbs two positions to 6th,matching its highest ever rank in the GTCI,which it also achieved in 2018 and 2019.In particular,the country stands out for its global leader-ship position in two sub-pillars:Business and Labour Landscape,and Internal Openness.Combined with a 2nd-placed Regula-tory Landscape,the strong Business and Labour Landscape has helped create an excellent ability to Enable talent,and a 3rd-place ranking in this pillar.Internal Openness contributes to Fin-lands 9th position in the Attract pillar,but is offset by its 28th position in the External Openness towards overseas talent sub-pillar.Finland is among the top-performing countries for ability to Retain talent and for its pool of Vocational and Technical Skills(4th in both pillars).Key assets include its world-class environ-mental performance and social welfare system,which contrib-ute to its 3rd position in the Sustainability sub-pillar.In addition,Finlands much-lauded Formal Education system is ranked 7th overall(reflecting its high scores in PISAthe Programme for International Student Assessment).As it is highly relevant to the needs of the economy,it also contributes towards its 8th-place ranking for Employability.However,its 13th position in the Grow pillar could improve with more opportunities for Lifelong Learn-ing(currently 25th).Norway(7th)retains its position from last year,which is the sixth time that it features in the top 10 in the GTCI(it has been in the top 15 every year).Norways performance in the Retain pillar(3rd)is particularly impr
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