Annex B. The PAL dashboard
|
Table A B.1. Urgency – dimension, sub-dimensions, indicators
|
||||
|---|---|---|---|---|
|
Sub-dimension |
Indicator |
Description |
Reference year |
Source |
|
Population ageing |
Old-age dependency ratio 2015 |
Population aged 65+ as % of population aged 15-64, 2015 |
2015 |
UN world population prospects |
|
Old-age dependency ratio 2050 |
Population aged 65+ as % of population aged 15-64, 2050 |
2015 |
UN world population prospects |
|
|
Automation and structural change |
Risk of automation |
% of workers facing a significant risk of automation (>50%) |
2011-12/ 2015 |
PIAAC / OECD 2018 |
|
Structural change |
Lilien index (structural change over last ten years - calculated as the weighted standard deviation of sectoral employment growth relative to aggregate employment growth) |
2015 |
OECD national accounts database |
|
|
Adult skills |
Numeracy and/or literacy skills |
% of the adult population (25-64) with low literacy and/or numeracy proficiency (0/1 level) |
2011-12/ 2015 |
PIAAC |
|
Problem-solving skills |
% of the adult population (25-64) who have no computer experience, failed the ICT core test or have minimal problem-solving skills in technology-rich environments (0/1 level) |
2011/2012 |
PIAAC |
|
|
Globalisation |
Trade openness |
Total trade (export + import) as a % of GDP |
2016 |
OECD national accounts database |
|
Trend in trade openness |
10-year change in total trade (export + import) as a % of GDP |
2007-16 |
OECD national accounts database |
|
|
Workers engaged in meeting foreign demand |
% of business sector jobs sustained by foreign final demand |
2014 |
OECD Science, Technology and Innovation Scoreboard 2017 |
|
|
Trend in workers engaged in meeting foreign demand |
10-year change in the % of business sector jobs sustained by foreign final demand |
2004-14 |
OECD Science, Technology and Innovation Scoreboard 2017 |
|
|
Table A B.2. Coverage – dimension, sub-dimensions, indicators
|
||||
|---|---|---|---|---|
|
Sub-dimension |
Indicator |
Description |
Reference year |
Source |
|
Employers |
Provision of training |
% of enterprises providing continuing vocational training |
2015 |
CVTS/ENCLAa/ Business Operations Surveyb/ Basic Survey of Human Resource Developmentc |
|
Coverage of training provision |
% of training enterprises providing continuing vocational training courses to more than 50% of their employees |
2015 |
CVTS/ Business Operations Survey |
|
|
Trend |
10-year change in the share of enterprises providing continuing vocational training (%) |
2005-15 |
CVTS/ Business Operations Surveyd |
|
|
Individuals |
Formal and non-formal learning |
% of adults who participate in formal or non-formal job-related adult learning in the past 12 months |
2011-12/ 2015 |
PIAAC |
|
Informal learning |
% of workers who learn from others, learn by doing, or keep up-to-date with new products or services at least once per week (participate in informal job-related learning) |
2011-12/ 2015 |
PIAAC |
|
|
Learning intensity |
Median number of hours participants spend on non-formal job-related adult learning per year |
2011-12/ 2015 |
PIAAC |
|
|
Trend |
10-year change in the share of adults participating in non-formal job-related adult learning (%) |
2007-16 |
AES/WRTALe |
|
|
Note: a. ENCLA (Chile, 2014) data refers to training provision in the last two years, while other sources refer to the last year; b. The Business Operations Survey (New Zealand, 2016) refers to firms with at least six employees, while other sources only exclude firms with less than ten employees; c. The Basic Survey of Human Resource Development (Japan, 2016) refers to firms with at least 30 employees; d. The trend in the Business Operations Survey (New Zealand) refers to the period 2005-16; e. The trend in the WRTAL survey (Australia) refers to the period 2005-16/17. |
||||
|
Table A B.3. Inclusiveness – dimension, sub-dimensions, indicators
|
||||
|---|---|---|---|---|
|
Sub-dimension |
Indicator |
Description |
Reference year |
Source |
|
Socio-demographic characteristics |
Age gap |
Percentage point difference in the participation rate between older (>55) and prime age population (25-54) |
2011-12/ 2015 |
PIAAC |
|
Gender gap |
Percentage point difference in the participation rate between women and men |
2011-12/ 2015 |
PIAAC |
|
|
Skill gap |
Percentage point difference in the participation rate between low-skilled (literacy and/or numeracy at or below level 1) and medium/high-skilled workers |
2011-12/ 2015 |
PIAAC |
|
|
Low-wage gap |
Percentage point difference in the participation rate between low-wage (i.e. earning at most two third of the national median wage) and medium/high wage workers |
2011-12/ 2015 |
PIAAC |
|
|
Employment and contract status |
Unemployment gap |
Percentage point difference in the participation rate between the unemployed and employed |
2011-12/ 2015 |
PIAAC |
|
Long-term unemployment gap |
Percentage point difference in the participation rate between the long-term unemployed and employed |
2011-12/ 2015 |
PIAAC |
|
|
Temporary workers gap |
Percentage point difference in the participation rate between workers on temporary and permanent contracts |
2011-12/ 2015 |
PIAAC |
|
|
SME gap |
Percentage point difference in the participation rate between workers in SMEs and large enterprises |
2011-12/ 2015 |
PIAAC |
|
|
Table A B.4. Financing – dimension, sub-dimensions, indicators
|
||||
|---|---|---|---|---|
|
Sub-dimension |
Indicator |
Description |
Reference year |
Source |
|
Government |
Government spending per unemployed |
Public expenditure on ALMPs training per unemployed-year, % of GDP per head |
2015 |
OECD/ Eurostat |
|
Government spending per participant |
Public expenditure on ALMPs training per participant-year, % of GDP per head (5-year average) |
2015/2016 |
OECD/ Eurostat |
|
|
Government investments towards individual’s training |
% of participants in formal and non-formal training whose training was fully or partially paid for by public institutions |
2016 |
AES |
|
|
Government investments towards firm’s training provision |
% of training enterprises that benefitted from government subsidies and/or tax incentives to provide CVT |
2015 |
CVTS |
|
|
Employers |
Employers investment |
Investment in non-formal training, % of GVA |
2011/2012 |
OECD calculations based on PIAAC dataa |
|
Employer-sponsored training |
% of participants who have received funding from their employer for at least one learning activity |
2011-12/ 2015 |
PIAAC |
|
|
Financial barriers to training provision |
% of enterprises stating that high costs of continuing vocational training courses was a limiting factor on provision or a reason for non-provision |
2015 |
CVTS/ Business Operations Surveyb |
|
|
Employers spending |
Investment in training of employees, % of total investments |
2016 |
EIBIS |
|
|
Individual |
Individuals spending |
% of participants who paid for taking part in non-formal learning activities (fully or partially) |
2016 |
AES/ WRTAL |
|
Financial barriers to training participation |
% of adults who wanted to participate (more) in training, but did not because too expensive |
2011-12/ 2015 |
PIAAC |
|
|
Note: a. Calculations from Squicciarini, M., L. Marcolin and P. Horvát (2015), “Estimating Cross-Country Investment in Training: An Experimental Methodology Using PIAAC Data”, OECD Science, Technology and Industry Working Papers, 2015/09, OECD Publishing, Paris. b. The Business Operations Survey (New Zealand, 2016) refers to firms with at least six employees, while other sources only exclude firms with less than 10 employees. Firms in the Business Operations Survey are said to see high costs as a limiting factor when they respond that the cost of training was a restriction on training of employees (either high, medium or low restriction). |
||||
|
Table A B.5. Alignment – dimension, sub-dimensions, indicators
|
||||
|---|---|---|---|---|
|
Sub-dimension |
Indicator |
Description |
Reference year |
Source |
|
Assessment of skill needs |
Firms assessing skill needs |
% of enterprises that assess regularly or not regularly their future skill needs |
2015 |
CVTS |
|
Training for future skill needs |
Training to fill skill gaps |
% of enterprises that provide continuing vocational training to employees or recruit and train new staff in response to future skill needs |
2015 |
CVTS |
|
Non-compulsory training |
% of training hours outside compulsory training (health and safety at work) |
2015 |
CVTS |
|
|
Training for development |
% of the top three skills priorities for the enterprise that are also among the top three skills targeted by CVT courses in terms of training hours |
2015 |
CVTS |
|
|
Training for workers at risk |
Easy-to-fill occupations |
Percentage point difference in participation between workers in easy-to-fill occupations and hard-to-fill occupations |
2011-12/ 2015 |
PIAAC |
|
Jobs at risk of automation |
Percentage point difference in participation between workers in jobs with significant risk of automation and low risk of automation |
2011-12/ 2015 |
PIAAC |
|
|
Labour market imbalances |
Self-reported training needs |
% of workers reporting they need more training to do their current tasks |
2011-12/ 2015 |
PIAAC |
|
Hiring difficulties |
% of employers reporting difficulty filling jobs |
2017/2018 |
Manpower talent shortage survey |
|
|
Obstacle to long-term investments |
% of enterprises reporting availability of staff with the right skills as a major obstacle to long-term investment decisions |
2016 |
EIBIS |
|
|
Table A B.6. Perceived impact – dimension, sub-dimensions, indicators
|
|||
|---|---|---|---|
|
Indicator |
Description |
Reference year |
Source |
|
Usefulness of training |
% of participants for whom at least one formal or non-formal job-related adult learning activity was “very useful” for the job they had at the time of the learning activity |
2011-12/ 2015 |
PIAAC |
|
Use of acquired skills |
% of participants in non-formal job-related adult learning who are currently using or are expected to use (a lot or a fair amount of) the skills or knowledge acquired |
2016 |
AES/WRTALa |
|
Impact on employment outcomes |
% of participants in non-formal job-related adult learning for whom the skills and knowledge acquired helped them: i) getting a (new) job, ii) higher salary/wages, iii) promotion in the job, iv) new tasks, and/or v) better performance in present job. |
2016 |
AES |
|
Wage returns to adult learning |
Hourly wage returns to participation in formal or non-formal job-related adult learning |
2011-12/ 2015 |
OECD calculations based on PIAAC |
|
Note: a. The Australian WRTAL Survey (2016/2017) refers to individuals responding that they use at least sometimes their acquired skills. |
|||
|
Table A B.7. Flexibility and Guidance – dimension, sub-dimensions, indicators
|
||||
|---|---|---|---|---|
|
Sub-dimension |
Indicator |
Description |
Reference year |
Source |
|
Flexibility of AES provision |
Time or distance barriers to participation |
% of adults who wanted to participate (more) but did not due to time or distance constraints |
2011-12/ 2015 |
PIAAC |
|
Distance learning |
% of participants in job-related adult learning who state that at least one of their adult learning activities was organised as distance learning |
2011-12/ 2015 |
PIAAC |
|
|
Use of career guidance services |
Looked for information |
% of adults who looked for information concerning learning possibilities (formal or non-formal) |
2016 |
AES |
|
Received information |
% of adults who received (free of charge or paid for) information or advice/help on learning possibilities from institutions/organisations |
2016 |
AES |
|