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Measurement and policy
implications of changes in the
labour market
Selma MAHFOUZ
16th IAOS Conference
21 September 2018
1
Outline
« The changing world of work »:
  Are we missing something?
The usual suspects
 New forms of employment
 Changes in occupations
Going further?
Implications for Statistics
Policy implications
2
3
4
Outline
« The changing world of work »:
  Are we missing something?
The usual suspects
 New forms of employment
 Changes in occupations
Going further?
Implications for Statistics
Policy implications
5
Changes in the labour market
Major (well documented) trends over the last decades:
 
Ageing populations
Increase in women and seniors workers participation
Increase in average level of education
Deindustrialization
Increase in part-time and temporary jobs
Digitalization
Polarization (RBTC and globalization)
Increase in inequalities …
6
Are we missing something?
New forms of employment
Contingent work 
Alternative work arrangements
Non-standard workers
Platform workers
Gig economy…  
  
Disappearing occupations
Frey and Osborne (2013) : 
Jobs susceptible 
to computerization 
= 47% of US employment 
7
New forms of employment – definitions (1)
1- A broad definition of « Non standard workers »
= All workers that do not have an archetype full-time permanent
job with a single employer (« social protection point of view »)
Includes:
-Temporary jobs
-Part-time jobs
-Self-employed
But also on-call work or zero hours contracts
8
New forms of employment – definitions (2)
2- A « narrow » definition of new forms of employment
(Eurofound, 2018)
9
New forms of employment – definitions (3)
2- A narrow definition >> 9 broad new forms of employment
(Eurofound 2018)
-Strategic employment sharing
-Job sharing
-Interim management
-Casual Work
-ICT based mobile work (teleworking)
-Voucher based work
-Portfolio work
-Platform work
-Collaborative self-employment
10
New forms of employment – Measures (1)
1- « Traditional » measures (NSO)
- Labour force surveys >> part-time and temporary contracts
(if not too short?)
Limits: self-employment and second jobs not well captured?
-Special modules / additional LFS questions
- US: Contingent Work Survey (June 2018)
- US : Rand CWS (Katz and Krueger 2017)
- EU-LFS: ad-hoc module in 2017 (11 questions on self-employment)
-Surveys on working conditions (eg EWCS)
- Questions on autonomy and work organization
-Other HH surveys: on use of time / on Households budgets…
11
New forms of employment – Measures (2)
2- Other public data sources
- Administrative data
- Tax records (Abraham and al 2017)
- Business registries (Hathaway and al, 2016)
- Payroll data?
-Specific surveys on platform workers or crowd work
- Huws and al 2017 for 7 european countries
- BMAS / IZA 2018 in Gernmany
3- Private data sources
- Bank records (JP Morgan Chase and co Institute, 2018)
- Platform data (Uber, Hall and Krueger, 2015)
12
Non standard forms of employment – Results (1)
Major trends (Eurofound 2017, OECD, 2017)
-Temporary employment: increase from late 1980 to mid-2000
then stabilization to 14% for the EU, 16% for the OECD
-Temporary agency work: around 2% (EU)
-Part-time work: increase to 20% of employment (EU)
- Increase in involuntary part-time
- Increase in very short weekly hours (less than 10 hours/week)
-Self employment: decline to 16% in OCDE, 15% in EU
-Own account workers (self-employed with no employees):
- 10% of employment
- Motives: positive (autonomy) and negative (lack of options, no choice)
-Prevalence of platform work: US : 0,5% in 2015 13
Non standard forms of employment – Results (2)
Results of the US Contingent Work Survey (CWS, 2017)
-Independent contractors: 6,9% in 2017 (= 2005)
-On-call workers: 1,7% in 2017 (= 2005)
-Temporary help agency workers: 0,9% in 2017 (= 2005)
-Workers provided by contract firms: 0,6% in 2017 (1,4% in 2005)
14
Outline
« The changing world of work »:
  Are we missing something?
The usual suspects
 New forms of employment
 Changes in occupations
Going further?
Implications for Statistics
Policy implications
15
Digitalization: destructive creation?
• Frey et Osborne (2013) : 
In the US, 47 % of jobs at risk in 20 years? 
16
Cf. Nicolas LE RU, « L'effet de l'automatisation sur l'emploi : ce qu'on sait et ce qu'on ignore », France
Stratégie, Note d'analyse n°49, juillet 2016
Some examples
 
Banking  Hotels  
Automobile              Cardiologist 17
Things are more complicated
• OCDE (M.Arntz, T. Gregory et U. Zierahn, 2016) : 
– 9 % of jobs are at high risk in the US, 10 % in the UK, 
7 % in Japan
• Why? 
Tasks versus occupations
18
19
Beyond occupations: skills
•Questions: 
– How to identify slills required by employers
– How to certify and signal workers’ skills
– How to talk the same language? (ESCO, O*NET, skill 
referentials)
20
Skills: définitions
• Different words: 
Abilities, skills, aptitudes, capabilities, etc..
• Different from the level of education or qualification
• Defined in relation to a production context:
– Skill = “Ability to apply knowledge and use know-how to complete 
tasks and solve problems” 
(Source: Cedefop; European Parliament and Council of the European Union, 2008)
– Which implies “applying knowledge, using tools, cognitive strategies 
and routines, /…/ convictions, attitudes and values..”.
(Source : OCDE, L’évaluation des compétences des adultes, 2013)
21
Skills: measures on the supply side
Measuring skills (supply of skills)
Indirect measure (proxy) Education level
Direct objective measure Standardized tests (PIAAC, PISA…)
Directe subjective
measure
- Auto-evaluation (Big Five…)
- Auto-evaluation of skills required by a job
- Evaluation by supervisors
Sources :
-Allen, J., and van der Velden, R. (2005). The role of self-assessment in measuring skills. REFLEX,
Working paper
-Eurostat
22
Measuring skills (demand side)
Indirect measures
(proxy)
Occupation :
-Qualification level,
-Experts (Rome, O*NET, ESCO),
-Tensions on the labour market (vacancies, etc..)
Directe objective
measure
At the individual level :
-Tasks: working conditions surveys …
-Skills required in job offers
Directe subjective
measure
- Employer Surveys
- Evaluation of skills required by managers
- Auto-valuation of skills required by workers
(PIAAC)
Skills: measures on the demand side
In the US and in Australia, two surveys
Qualitative questions to employers
- The Occupational Requirements Survey in the US
- The Survey of Employers who have Recently Advertised
23
New measures?
Outline
« The changing world of work »:
Are we missing something?
The usual suspects
 New forms of employment
 Changes in occupations
Going further?
Implications for Statistics
Policy implications
24
Going further?
Implications for Statistics (tentative)
Provide new « concepts »: new forms of employment, skills
Provide alternative measures of emerging phenomena
Dig into new sources of data
Go beyond the usual suspects and look for other sources of
heterogeneity in labour market outcomes
- Household level (eg Eurostat unemployment)
- New geography of jobs (Enrico Moretti)
- Changes in working conditions in « old » jobs
- Intergenerational reproduction of occupations ?
(% of sons doing the same job as their father)
- Firm level heterogeneity (Van Reenen super star firms)
25
Going further?
Policy implications?
Non standard forms of work
>> Social protection model: Benefits and labour regulations
Changes in working conditions in standard work
>> Labour regulations: Working time? Place?...
Changes in skills
>> Education and training
Geographical heterogenity
>> Mobility and innovation policies?
Intergenerational reproduction
>> Education
26
Measurement and policy
implications of changes in the
labour market
Selma MAHFOUZ
16th IAOS Conference
21 September 2018
27

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IAOS 2018 - Measurement and policy implications of changes in the labour market, S. Mahfouz

  • 1. Measurement and policy implications of changes in the labour market Selma MAHFOUZ 16th IAOS Conference 21 September 2018 1
  • 2. Outline « The changing world of work »:   Are we missing something? The usual suspects  New forms of employment  Changes in occupations Going further? Implications for Statistics Policy implications 2
  • 3. 3
  • 4. 4
  • 5. Outline « The changing world of work »:   Are we missing something? The usual suspects  New forms of employment  Changes in occupations Going further? Implications for Statistics Policy implications 5
  • 6. Changes in the labour market Major (well documented) trends over the last decades:   Ageing populations Increase in women and seniors workers participation Increase in average level of education Deindustrialization Increase in part-time and temporary jobs Digitalization Polarization (RBTC and globalization) Increase in inequalities … 6
  • 7. Are we missing something? New forms of employment Contingent work  Alternative work arrangements Non-standard workers Platform workers Gig economy…      Disappearing occupations Frey and Osborne (2013) :  Jobs susceptible  to computerization  = 47% of US employment  7
  • 8. New forms of employment – definitions (1) 1- A broad definition of « Non standard workers » = All workers that do not have an archetype full-time permanent job with a single employer (« social protection point of view ») Includes: -Temporary jobs -Part-time jobs -Self-employed But also on-call work or zero hours contracts 8
  • 9. New forms of employment – definitions (2) 2- A « narrow » definition of new forms of employment (Eurofound, 2018) 9
  • 10. New forms of employment – definitions (3) 2- A narrow definition >> 9 broad new forms of employment (Eurofound 2018) -Strategic employment sharing -Job sharing -Interim management -Casual Work -ICT based mobile work (teleworking) -Voucher based work -Portfolio work -Platform work -Collaborative self-employment 10
  • 11. New forms of employment – Measures (1) 1- « Traditional » measures (NSO) - Labour force surveys >> part-time and temporary contracts (if not too short?) Limits: self-employment and second jobs not well captured? -Special modules / additional LFS questions - US: Contingent Work Survey (June 2018) - US : Rand CWS (Katz and Krueger 2017) - EU-LFS: ad-hoc module in 2017 (11 questions on self-employment) -Surveys on working conditions (eg EWCS) - Questions on autonomy and work organization -Other HH surveys: on use of time / on Households budgets… 11
  • 12. New forms of employment – Measures (2) 2- Other public data sources - Administrative data - Tax records (Abraham and al 2017) - Business registries (Hathaway and al, 2016) - Payroll data? -Specific surveys on platform workers or crowd work - Huws and al 2017 for 7 european countries - BMAS / IZA 2018 in Gernmany 3- Private data sources - Bank records (JP Morgan Chase and co Institute, 2018) - Platform data (Uber, Hall and Krueger, 2015) 12
  • 13. Non standard forms of employment – Results (1) Major trends (Eurofound 2017, OECD, 2017) -Temporary employment: increase from late 1980 to mid-2000 then stabilization to 14% for the EU, 16% for the OECD -Temporary agency work: around 2% (EU) -Part-time work: increase to 20% of employment (EU) - Increase in involuntary part-time - Increase in very short weekly hours (less than 10 hours/week) -Self employment: decline to 16% in OCDE, 15% in EU -Own account workers (self-employed with no employees): - 10% of employment - Motives: positive (autonomy) and negative (lack of options, no choice) -Prevalence of platform work: US : 0,5% in 2015 13
  • 14. Non standard forms of employment – Results (2) Results of the US Contingent Work Survey (CWS, 2017) -Independent contractors: 6,9% in 2017 (= 2005) -On-call workers: 1,7% in 2017 (= 2005) -Temporary help agency workers: 0,9% in 2017 (= 2005) -Workers provided by contract firms: 0,6% in 2017 (1,4% in 2005) 14
  • 15. Outline « The changing world of work »:   Are we missing something? The usual suspects  New forms of employment  Changes in occupations Going further? Implications for Statistics Policy implications 15
  • 16. Digitalization: destructive creation? • Frey et Osborne (2013) :  In the US, 47 % of jobs at risk in 20 years?  16 Cf. Nicolas LE RU, « L'effet de l'automatisation sur l'emploi : ce qu'on sait et ce qu'on ignore », France Stratégie, Note d'analyse n°49, juillet 2016
  • 18. Things are more complicated • OCDE (M.Arntz, T. Gregory et U. Zierahn, 2016) :  – 9 % of jobs are at high risk in the US, 10 % in the UK,  7 % in Japan • Why?  Tasks versus occupations 18
  • 19. 19 Beyond occupations: skills •Questions:  – How to identify slills required by employers – How to certify and signal workers’ skills – How to talk the same language? (ESCO, O*NET, skill  referentials)
  • 20. 20 Skills: définitions • Different words:  Abilities, skills, aptitudes, capabilities, etc.. • Different from the level of education or qualification • Defined in relation to a production context: – Skill = “Ability to apply knowledge and use know-how to complete  tasks and solve problems”  (Source: Cedefop; European Parliament and Council of the European Union, 2008) – Which implies “applying knowledge, using tools, cognitive strategies  and routines, /…/ convictions, attitudes and values..”. (Source : OCDE, L’évaluation des compétences des adultes, 2013)
  • 21. 21 Skills: measures on the supply side Measuring skills (supply of skills) Indirect measure (proxy) Education level Direct objective measure Standardized tests (PIAAC, PISA…) Directe subjective measure - Auto-evaluation (Big Five…) - Auto-evaluation of skills required by a job - Evaluation by supervisors Sources : -Allen, J., and van der Velden, R. (2005). The role of self-assessment in measuring skills. REFLEX, Working paper -Eurostat
  • 22. 22 Measuring skills (demand side) Indirect measures (proxy) Occupation : -Qualification level, -Experts (Rome, O*NET, ESCO), -Tensions on the labour market (vacancies, etc..) Directe objective measure At the individual level : -Tasks: working conditions surveys … -Skills required in job offers Directe subjective measure - Employer Surveys - Evaluation of skills required by managers - Auto-valuation of skills required by workers (PIAAC) Skills: measures on the demand side
  • 23. In the US and in Australia, two surveys Qualitative questions to employers - The Occupational Requirements Survey in the US - The Survey of Employers who have Recently Advertised 23 New measures?
  • 24. Outline « The changing world of work »: Are we missing something? The usual suspects  New forms of employment  Changes in occupations Going further? Implications for Statistics Policy implications 24
  • 25. Going further? Implications for Statistics (tentative) Provide new « concepts »: new forms of employment, skills Provide alternative measures of emerging phenomena Dig into new sources of data Go beyond the usual suspects and look for other sources of heterogeneity in labour market outcomes - Household level (eg Eurostat unemployment) - New geography of jobs (Enrico Moretti) - Changes in working conditions in « old » jobs - Intergenerational reproduction of occupations ? (% of sons doing the same job as their father) - Firm level heterogeneity (Van Reenen super star firms) 25
  • 26. Going further? Policy implications? Non standard forms of work >> Social protection model: Benefits and labour regulations Changes in working conditions in standard work >> Labour regulations: Working time? Place?... Changes in skills >> Education and training Geographical heterogenity >> Mobility and innovation policies? Intergenerational reproduction >> Education 26
  • 27. Measurement and policy implications of changes in the labour market Selma MAHFOUZ 16th IAOS Conference 21 September 2018 27

Editor's Notes

  1. Good morning Thank you for the invitation
  2. Voilà pour l’impact du numérique sur les métiers Mais le débat et les questions se sont déplacés sur la question des compétences
  3. Voilà pour l’impact du numérique sur les métiers Mais le débat et les questions se sont déplacés sur la question des compétences
  4. + Large fluctuations in unemployment (back to pre-crisis level in OECD)
  5. + Large fluctuations in unemployment (back to pre-crisis level in OECD)
  6. No unified definition - Not always « new » (on call work)
  7. No unified definition - Not always « new » (on call work)
  8. No unified definition - Not always « new » (on call work)
  9. + Large fluctuations in unemployment (back to pre-crisis level in OECD)
  10. + Large fluctuations in unemployment (back to pre-crisis level in OECD)
  11. + Large fluctuations in unemployment (back to pre-crisis level in OECD)
  12. + Large fluctuations in unemployment (back to pre-crisis level in OECD)
  13. Voilà pour l’impact du numérique sur les métiers Mais le débat et les questions se sont déplacés sur la question des compétences
  14. Le débat sur les risques de destructions d’emplois du fait de l’automatisation a été relancé et reste fortement marqué par la publication en 2013 d’une étude réalisée par deux chercheurs de l’université d’Oxford C B. Frey et M.A. Osborne intitulée « Future of employment: how susceptible are jobs to computerisation? » >> 47% des emplois risquent d’être automatisés au Etats-Unis d’ici 20 ans Leurs résultats ont été repris et transposés à d’autres pays et aboutissent à un ordre de grandeur comparable : 35% au Royaume Uni, 42% des emplois seraient menacés en France (Roland Berger Strategy Consultants 2014) 49% au Japon et 54% dans l’UE. Comment arrivent ils à ce résultat ? En demandant à des experts de l’intelligence artificielle de donner 70 professions pour lesquelles ils estimaient connaître avec certitude leur caractère automatisable/non automatisable. A ensuite été effectuée une correspondance entre ces 70 professions et neuf de leurs caractéristiques. Puis cette correspondance a été appliquée à 630 autres professions. 320 professions ont un risque élevé d’être automatisées au cours des 20 prochaines années et regroupent 47% des emplois aux États-Unis, 42% en France, etc… Cette approche a fait l’objet de nombreuses critiques - Une première limite, à rappeler, est qu’ils ne prennent pas en compte le fait que l’automatisation est également susceptible de créer des emplois : il y a les créations directes dans la filière numérique (par exemple, il y a désormais presque autant d’ingénieurs informatiques et des télécoms que de secrétaires), les créations directes induites par l’apparition de nouveaux besoins de consommation qui ne se substituent pas forcément à d’autres plus traditionnels, et les créations indirectes liées aux gains de productivité (baisse des prix, hausse des salaires, hausse des profits des entreprises pouvant être réinvestis, hausse de la demande globale adressée aux entreprises).
  15. -Parmi les exemples de transformation de contenu des métiers, on peut citer les métiers de la banque, où l’installation des distributeurs automatiques de billets, les services de banque en ligne et de paiement sans contact ont conduit à un recentrage des métiers sur les tâches moins automatisables (le profil d’emplois peu automatisables a augmenté parmi les techniciens et les employés de la banque (N. Le Ru 2016)). -Des caisses automatiques ont été mises en service dans la grande distribution en France à partir de 2004. En 2012, environ 3,5% des terminaux de caisses en grande distribution sont des caisses libre-service. Avec cette introduction, «l’employé n’est plus l’opérateur d’un seul poste, mais il accueille plusieurs clients sur un îlot de quatre à six automates. Cette relation simultanée avec plusieurs clients rend l’accueil plus complexe, car un caissier peut être mobilisé dans plusieurs interactions à la fois. Il ne peut alors appliquer un script standardisé » (Benoît-Moreau F., Bonnemaizon A., Cadenat S. et Renaudin V. « Le consommateur et les caisses automatiques : pour une compréhension du processus », travaux menés dans le cadre d’un contrat de recherche avec l’enseigne Auchan). -Le développement du véhicule du futur reposera sur trois domaines de technologies qui nécessiteront des compétences nouvelles : l’économie des matières premières (besoin de compétences en écoconception, matériaux composites et recyclage), les motorisations électrifiées (besoin de compétences en chimie, électronique et électrochimique), l’électronique et l’informatique embarquées (besoin de compétences en électronique et en informatique). Une étude prospective (« Etude prospective des mutations de la construction automobile et de ses effets sur l’emploi et les besoins de compétences », observatoire de la métallurgie page 81), indique des besoins croissants de compétences en lien avec l’automatisation dans les métiers de la construction automobile, notamment la supervision de production, le contrôle des dérives et des instruments de mesures, la maîtrise des langages informatiques, l’utilisation de la réalité virtuelle et de la réalité augmentée. - Le numérique a impacté l’ensemble des processus du métier de directeur d’hôtel. Selon Google, un voyageur sur deux fait désormais sa réservation en ligne (dont un quart via une application mobile). Par ailleurs, en France, cinq millions d’avis sont postés sur les hôtels chaque année (150 millions dans le monde) et 80 % des Français vérifient les avis sur des sites d’e-reputation avant d’effectuer un choix. « En tant que directrice, je ne dois plus seulement gérer les équipes et le compte d’exploitation mais également notre réputation numérique » analyse une directrice d’hôtel. (article du Monde). La réputation numérique, c’est à la fois être présent sur les réseaux sociaux et veiller à répondre à tous les commentaires postés par les clients, positifs ou négatifs. « Par exemple, il arrive qu’un client poste en direct un commentaire sur sa chambre ou sur l’hôtel. Nous sommes tenus de réagir très vite. A nous également de solliciter leur avis à la fin de leur séjour. Ces commentaires permettent de gagner de nouveaux clients. Il faut être à la fois réactifs et proactifs. »(Article du Monde) - Grâce aux outils numériques, les médecins peuvent désormais s’échanger très facilement des données, par mail ou par SMS. « On m’envoie régulièrement des électrocardiogrammes pour avis ou interprétation. Ceci permet une meilleure collaboration entre professionnels de santé », explique un cardiologue (article du Monde). Le numérique en médecine, c’est aussi le développement des objets connectés. Dans le cas de la cardiologie, ce sont par exemple les holters rythmiques ou les stimulateurs cardiaques (pacemakers) qui contiennent un petit boîtier de télétransmission. Pendant le sommeil du patient, les données sont téléchargées vers un serveur qui envoie ensuite des alertes au médecin ou au centre de soin. Ceci permet une prise en charge plus rapide et une meilleure détection d’une évolution de la pathologie. Par ailleurs, le numérique facilite considérablement l’accès à la connaissance pour le médecin. « Je peux maintenant consulter les travaux de la Société française ou internationale de cardiologie, les revues numériques de médecine, des cas similaires de pathologies… Auparavant, je devais les commander à la bibliothèque universitaire la plus proche de chez moi. Cela prenait du temps, c’était compliqué et il fallait se déplacer. Cette immédiateté de la connaissance est indéniablement un plus pour le médecin, et ce, dans l’intérêt de ses patients », constate le cardiologue Philippe Héno. (Article du Monde). Autre exemple : - Dans les vignes et les chais, même s’il y a déjà beaucoup de machines et de technologie, de nombreuses tâches restent encore manuelles, alors que les difficultés de recrutement se font de plus en plus prégnantes. Des expérimentations sont faites par certains domaines viticoles pour mécaniser des tâches comme la taille, le désherbage ou le traitement contre certaines maladies. (article du Monde).
  16. Une seconde limite tient à la méthode employée pour estimer les emplois à risque Ces études partent des professions, c’est-à-dire qu’elles se demandent quelles professions dans leur ensemble peuvent être automatisées. Or des chercheurs ont souligné dans uné étude de l’OCDE qu’il fallait regarder plus finement, les tâches qui étaient automatisables Selon M.Arntz, T. Gregory et U. Zierahn (2016), raisonner au niveau global des professions peut mener à la surestimation de l’automatisation des emplois, puisque les professions dites à haut risque comprennent souvent une part substantielle de tâches difficiles à automatiser. Dans leur étude, à la différence d’autres études, ils prennent en compte l’hétérogénéité des tâches au sein des professions. >> ils estiment que 9 % des emplois sont automatisables en moyenne dans les 21 pays de l’OCDE. Pour 25 % des autres emplois, 50% des tâches seront cependant considérablement transformées par l’automatisation. La France se trouve dans la moyenne de ces 9% (10% au Royaume Uni et 7% au Japon). [Deux exemples : - Un garagiste peut être aidé d’une machine pour faire le diagnostic de la panne, mais ce n’est pas une machine qui la répare. - Alors qu’on anticipait leur disparition, le nombre de caissières a baissé de seulement 10% en dix ans.]
  17. En effet, au-delà de l’effet sur les métiers, la question qui se pose est de savoir si dans un monde plus numérique, les salariés ont les compétences requises L’idée est qu’une approche par les compétences permet …
  18. Il importe d’abord de clarifier un peu ce qu’on entend par compétences Différents termes Distinct du niveau d’éducation ou de la qualification Point important : Défini par rapport à un contexte de production
  19. La littérature économique s’est intéressée aux compétences dans le cadre du modèle de capital humain (équations de Mincer…). >> avec une approche du côté de l’Offre de compétences : La mesure la plus communément utilisée pour mesurer l’offre de compétences (les compétences disponibles sur le marché du travail) est une mesure indirecte : le niveau d’éducation. Mais il ne s’agit que d’un proxy, qui a ses limites : au sein d’un même niveau d’éducation, le niveau de compétences varie considérablement. Par ailleurs les compétences peuvent aussi être acquises ailleurs qu’à l’école (famille, amis, différence culturelle…). C’est le cas pour les compétences cognitives aussi bien que pour les compétences comportementales et sociales. L’OCDE développe des mesures directes objectives des compétences (The International Adult Literacy Survey (IALS), Adult Literacy and Lifeskills Survey (ALL), PIAAC, PISA, TIMMS et PIRLS). Inconvénient de ce type de mesures : souvent limitées à des domaines très particuliers. Ex : dans PIAAC, seules des compétences de base sont mesurées : littératie, numératie et résolution de problèmes. Plusieurs enquêtes retiennent une mesure directe subjective des compétences. C’est le cas par exemple des échelles de mesure des compétences comportementales (Big Five et OCEAN). Autre exemple : mesure du niveau de compétences numériques dans le cadre de l’enquête de l’Union Européenne sur l’utilisation des TIC par les ménages et les particuliers.
  20. On peut aussi approche les compétence par le côté de la Demande de compétences par les employeurs, ie les compétences requises pour un poste : Tableau Un Avantage de l’analyse du travail au niveau individuel : on se rend compte qu’un même métier peut être exercé de manière très différente, surtout en comparaison internationale. L’analyse du travail est utilisée au niveau individuel.
  21. Deux enquêtes innovantes tout d’abord, aux Etats-Unis et en Australie. Ces deux pays ont pour points communs de réaliser des enquêtes qui s’adressent directement aux employeurs pour recueillir leurs attentes en matière de compétences et d’investir dans des méthodes dites qualitatives, sans questionnaire, pour décrire de manière la plus complète possible les attentes spécifiques.
  22. Voilà pour l’impact du numérique sur les métiers Mais le débat et les questions se sont déplacés sur la question des compétences
  23. + Large fluctuations in unemployment (back to pre-crisis level in OECD)
  24. + Large fluctuations in unemployment (back to pre-crisis level in OECD)
  25. Good morning Thank you for the invitation