“Job Quality, Labour Market Performance and Well-Being”_Hijzen_extending the framework final

EC/OECD seminar, Brussels, 
27-28 November 2014 
FUTURE OECD WORK ON JOB QUALITY
2 
Will include: 
• Extending the OECD framework to emerging 
economies 
• Shifting the focus from jobs to careers 
• Filling up the gaps in the data 
Future OECD work
Future OECD work 
1. Job quality in emerging economies 
– Some preliminary results
• The framework needs to be adapted 
– To account for the risk of low-pay 
– To deal with data limitations (especially w.r.t. QWE) 
• Informality plays a crucial role 
– Is job quality lower in informal jobs? If lower in all dimensions of 
job quality cannot be a voluntary choice 
– Is informality a stepping stone or a trap? 
• Country coverage restricted to emerging economies with a 
link to the OECD or G20 for which suitable data are available 
– Asia (CHN, IDN, IND), Africa and Middle East (TUR, ZAF), Latin 
America (ARG, BRA, CHL, COL, CTR, MEX) – not there yet 
Job quality in emerging economies
Earnings quality in EEs 
Source: OECD calculations based on national surveys: EPH (Argentina), PNAD (Brazil), CASEN (Chile), ESLF (Colombia), ENHAO (Costa Rica), ENOE (Mexico), SILC 
(Turkey), NIDS (South Africa) 
* The earnings measures used are net and hourly 
2010 $ (PPP), high inequality aversion (alpha= - 3) 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0 
0 
1 
2 
3 
4 
5 
6 
7 
ZAF COL BRA MEX TUR CRI ARG CHL 
2010 US dollars, PPP 
Earnings quality Average earnings Earnings inequality (right axis)
The risk of low-pay in EEs 
Low-pay threshold: 2.5 $ (PPP) 
Source: OECD calculations based on national surveys: EPH (Argentina), PNAD (Brazil), CASEN (Chile), ESLF (Colombia), ENHAO (Costa Rica), ENOE (Mexico), SILC 
(Turkey), NIDS (South Africa) 
*Mobility threshold is 2.5 $ PPP per hour 
Mobility rates are calculated using a pseudo-panel approach where individual mobility is approximated by cohort mobility (see appendix for more details and validation). 
A cohort is defined on the basis of gender, education and year of birth. 
Only individuals between the age of 25 and 55 at t=0 are considered for this calculation ( approximately one cohort) 
0 
0.2 
0.4 
0.6 
0.8 
1 
COL MEX ZAF TUR BRA CHL CRI ARG 
Steady-State incidence of low pay Upward Downward
• To what extent is the job-demands job-resources model appropriate 
in EEs? 
– Not designed to deal with self-employment even though this trend to be s 
widespread in EEs 
• To what extent does it need to be calibrated differently? And how 
can this be done? 
– Should the same demands and resources be considered? Can the same 
cutoff be used to define strained jobs? 
• How to measure QWE with the data available? 
– Focus on physical work accidents as reduced-form alternative to job strain? 
– But even data on work accidents is patchy and subject to various quality 
concerns 
7 
Quality of the working environment
• Informality is measured either by social security coverage or having a 
formal contract 
• Job quality tends to be lower on average among informal workers which 
point at exclusion 
– Average earnings gap between 30 to 50%; earnings dispersion similar -> overlap 
modest 
– Informal workers much more likely to earn less than 2.5$ 
– Reflect higher probability of becoming low paid and lower probability of leaving 
low pay 
• However, analysis falls short of full assessment of informality, in part due to 
difficulty of measuring QWE in a comprehensive way 
– To what extent could job satisfaction data provide a way out? 
• Some preliminary evidence that informality harms career prospects 
– Takes a long time to find good formal job for informal workers; most transitions 
from informal to formal result in temporary jobs 
8 
Job quality and informality
Informality and non-standard work 
0% 
2% 
4% 
6% 
8% 
10% 
12% 
14% 
I--> Permament (Formal) I--> Temporary (Formal) 
0% 
2% 
4% 
6% 
8% 
10% 
12% 
14% 
Permanent (Formal)-->I Temporary (Formal) --> I 
Transitions out of 
informality 
Transitions into 
informality 
Source: OECD calculations based on Encuesta Social Longitudinal de Fedesarrollo (ESLF) for Colombia . Informal employees only. Informality: Does not pay any 
social contributions 
Transition rates over consecutive survey waves 
Colombia
Future OECD work 
2. Shifting the focus from jobs to 
careers – Initial thoughts
• Shift focus from jobs to worker careers over the life cycle 
– Individual well-being not only depends on current job but also the prospects it provides 
– Also matters for assessment of social welfare because of its implications for risk and 
inequality (see next slide) 
-> Main in interest is understanding what drives poor outcomes and suggest policy policy 
instruments 
• Life-cycle approach provides alternative approach for assessing labour 
market performance in terms of job quantity & quality 
– Captures earnings (potential) and labour market security 
– But also non-employment spells and working time 
• For the moment no intention to also look at quality of the working 
environment in detail 
The quality of working lives
• Quality of working lives can be summarised in terms of life-time 
earnings and incomes 
– Since long panel data are not available on a cross-country basis simulation 
techniques may need to be used 
• Has potentially important implications for international comparisons 
of inequality and the incidence of low-paid work 
– Life-time measures of earnings take account of differences in earnings-experience 
profiles and exclude transitory shocks 
– e.g. countries with steeper earnings profiles and higher incidences of transitory 
shocks are likely to look less unequal from a life-time perspective 
• Also has important implications for the assessment of social welfare 
– High mobility may alleviate concerns over inequality in the short-term but raise 
others over risk -> reduce calls for redistribution but increase those for insurance 
– e.g. US traditionally accepted high inequality as mobility was also high; recently 
rising concerns that mobility is stalling despite rising inequality 
Life-time earnings, mobility 
and earnings inequality
• What is the role of job quantity (unemployment and working 
time) and job quality (earnings) for inequality in life-time 
earnings? 
• To what extent are low life-time earnings associated with higher 
labour market risk? 
• What is the role of taxes-and-benefits systems for insurance and 
redistribution over the life course? 
• To what extent does having a temporary contract have long-lasting 
effects for worker careers? 
– EmO 2014 shows that many temporary workers do not manage to find 
permanent jobs even after three years 
What explains low life-time earnings?
• What is the role of learning? 
– How do the returns to potential labour market experience differ across 
countries? 
– And how do these compare across socio-economic groups (gender and 
education)? 
• What is the role of job mobility? 
– Job mobility is a potentially important channel for advancement for workers 
– Governments may also be interested in promoting job mobility for both social 
(to reduce low-quality work) and economic reasons (improve optimal allocation) 
• What is the role of firm productivity, work organisation and worker 
representation? 
14 
What explains upward mobility?
Future OECD work 
3. An ambitious statistical agenda
16 
• Inventory of information on the quality of the working environment 
(international sources) 
– identify questions, underlying concepts, data sources and gaps 
– document key insights on job quality 
• OECD database on job quality 
– based on quality assessment and covering indicators for all three 
dimensions of Job Quality 
– with currently available information by country and eventually also by 
socio-economic group 
– gradually extend country coverage to non-OECD members 
– to become available via OECD.Stat 
• Further work with OECD countries to fill in methodological and 
statistical gaps and improve harmonisation 
Ambitious statistical agenda
17 
Motivation: To take stock of available international data sources and 
identify gaps 
 7 international surveys were identified that : 
 Have a focus on working lives 
 Collect information specifically on individuals’ own job 
 In total cover 25 years and 160+ countries 
 EWCS, ESS, ISSP, EULFS AHMs, Gallup World Poll, EQLS, Eurobarometer 
 18 sub-dimensions of QWE shown to have an impact on well-being in 
the literature were identified 
 E.g. Work intensity, Physical risk factors, Task discretion and autonomy, organisational participation 
 Relevant questions in each survey were classified and documented in 
the Inventory 
 Analytical work on comparability of indicators across surveys underway 
OECD Inventory of Indicators on 
Quality of Working Environment
18 
OECD Inventory of Indicators on 
Quality of Working Environment 
Identifying gaps: 
Example: Task discretion and autonomy 
The inventory soon downloadable from the OECD database. 
EWCS ISSP ESS ESS, ISSP 
EWCS, EQLS, Eurobar EWCS, ESS, EQLS 
EWCS, ESS, ISSP 
EWCS, ESS, EQLS, ISSP 
EWCS, EQLS, ISSP, Eurobar EWCS, EQLS, ESS, Eurobar ALL 5 SURVEYS
19 
Assessing the relevance and statistical 
quality of Job Quality indicators (I) 
Criteria used: 
Relevance 
• Face validity (capacity to measure 
what is intended to be measured) 
• Unambiguous interpretation (whether 
the indicator is good or bad for well-being) 
• Policy relevance (amenable to 
concrete policy actions) 
• Can be disaggregated (by socio-economic 
groups in order to assess 
distributional aspect of job quality) 
Statistical Quality 
• Well-established instruments collected 
(relying on statistical instruments 
developed within the official statistical 
system or academic community) 
• Comparable definition (via using 
internationally accepted standards and 
surveys) 
• Country Coverage (ensuring maximum 
coverage for the OECD and other 
major economies where possible) 
• Recurrent data collection (in order to 
monitor progress)
20 
Assessing the relevance and statistical 
quality of Job Quality indicators (II) 
Sub-indicator 
Properties 
Relevance to measure and monitor JQ Statistical Quality 
Face Validity 
Unambiguous 
interpretation 
Policy 
relevance 
Can be 
disaggregated 
Well-established 
instruments 
collected 
Comparable 
definition 
Country 
Coverage 
Recurrent 
data 
collection 
Earnings quality 
Average Earnings VV VV VV VV VV VV VV VV 
Earnings Inequality X 
Labour Market Security 
Unemployment risk 
U probability (monthly U inflows) 
Expected U duration 
(inverse of U outflows) 
Effective insurance 
Coverage rate of unemployment 
compensation (insurance/assistance) 
Average net replacement rate of 
insurance/ assistance 
V 
Quality of the working environment 
Work stressors 
Time pressure at work 
Physical Health risk factors 
Workplace intimidation 
Workplace resources 
Work autonomy & learning opportunities 
Workplace relationships 
Good management practices 
VV: Largely meets criterion 
V: Meets criterion to a large extent 
X: Does not meet the criterion or meets it only to a limited extent
21 
• For further information on OECD work on job quality 
please contact: 
– Sandrine Cazes (STD): sandrine.cazes@oecd.org 
– Alexander Hijzen (ELS): alexander.hijzen@oecd.org 
Thank you!
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“Job Quality, Labour Market Performance and Well-Being”_Hijzen_extending the framework final

  • 1. EC/OECD seminar, Brussels, 27-28 November 2014 FUTURE OECD WORK ON JOB QUALITY
  • 2. 2 Will include: • Extending the OECD framework to emerging economies • Shifting the focus from jobs to careers • Filling up the gaps in the data Future OECD work
  • 3. Future OECD work 1. Job quality in emerging economies – Some preliminary results
  • 4. • The framework needs to be adapted – To account for the risk of low-pay – To deal with data limitations (especially w.r.t. QWE) • Informality plays a crucial role – Is job quality lower in informal jobs? If lower in all dimensions of job quality cannot be a voluntary choice – Is informality a stepping stone or a trap? • Country coverage restricted to emerging economies with a link to the OECD or G20 for which suitable data are available – Asia (CHN, IDN, IND), Africa and Middle East (TUR, ZAF), Latin America (ARG, BRA, CHL, COL, CTR, MEX) – not there yet Job quality in emerging economies
  • 5. Earnings quality in EEs Source: OECD calculations based on national surveys: EPH (Argentina), PNAD (Brazil), CASEN (Chile), ESLF (Colombia), ENHAO (Costa Rica), ENOE (Mexico), SILC (Turkey), NIDS (South Africa) * The earnings measures used are net and hourly 2010 $ (PPP), high inequality aversion (alpha= - 3) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0 1 2 3 4 5 6 7 ZAF COL BRA MEX TUR CRI ARG CHL 2010 US dollars, PPP Earnings quality Average earnings Earnings inequality (right axis)
  • 6. The risk of low-pay in EEs Low-pay threshold: 2.5 $ (PPP) Source: OECD calculations based on national surveys: EPH (Argentina), PNAD (Brazil), CASEN (Chile), ESLF (Colombia), ENHAO (Costa Rica), ENOE (Mexico), SILC (Turkey), NIDS (South Africa) *Mobility threshold is 2.5 $ PPP per hour Mobility rates are calculated using a pseudo-panel approach where individual mobility is approximated by cohort mobility (see appendix for more details and validation). A cohort is defined on the basis of gender, education and year of birth. Only individuals between the age of 25 and 55 at t=0 are considered for this calculation ( approximately one cohort) 0 0.2 0.4 0.6 0.8 1 COL MEX ZAF TUR BRA CHL CRI ARG Steady-State incidence of low pay Upward Downward
  • 7. • To what extent is the job-demands job-resources model appropriate in EEs? – Not designed to deal with self-employment even though this trend to be s widespread in EEs • To what extent does it need to be calibrated differently? And how can this be done? – Should the same demands and resources be considered? Can the same cutoff be used to define strained jobs? • How to measure QWE with the data available? – Focus on physical work accidents as reduced-form alternative to job strain? – But even data on work accidents is patchy and subject to various quality concerns 7 Quality of the working environment
  • 8. • Informality is measured either by social security coverage or having a formal contract • Job quality tends to be lower on average among informal workers which point at exclusion – Average earnings gap between 30 to 50%; earnings dispersion similar -> overlap modest – Informal workers much more likely to earn less than 2.5$ – Reflect higher probability of becoming low paid and lower probability of leaving low pay • However, analysis falls short of full assessment of informality, in part due to difficulty of measuring QWE in a comprehensive way – To what extent could job satisfaction data provide a way out? • Some preliminary evidence that informality harms career prospects – Takes a long time to find good formal job for informal workers; most transitions from informal to formal result in temporary jobs 8 Job quality and informality
  • 9. Informality and non-standard work 0% 2% 4% 6% 8% 10% 12% 14% I--> Permament (Formal) I--> Temporary (Formal) 0% 2% 4% 6% 8% 10% 12% 14% Permanent (Formal)-->I Temporary (Formal) --> I Transitions out of informality Transitions into informality Source: OECD calculations based on Encuesta Social Longitudinal de Fedesarrollo (ESLF) for Colombia . Informal employees only. Informality: Does not pay any social contributions Transition rates over consecutive survey waves Colombia
  • 10. Future OECD work 2. Shifting the focus from jobs to careers – Initial thoughts
  • 11. • Shift focus from jobs to worker careers over the life cycle – Individual well-being not only depends on current job but also the prospects it provides – Also matters for assessment of social welfare because of its implications for risk and inequality (see next slide) -> Main in interest is understanding what drives poor outcomes and suggest policy policy instruments • Life-cycle approach provides alternative approach for assessing labour market performance in terms of job quantity & quality – Captures earnings (potential) and labour market security – But also non-employment spells and working time • For the moment no intention to also look at quality of the working environment in detail The quality of working lives
  • 12. • Quality of working lives can be summarised in terms of life-time earnings and incomes – Since long panel data are not available on a cross-country basis simulation techniques may need to be used • Has potentially important implications for international comparisons of inequality and the incidence of low-paid work – Life-time measures of earnings take account of differences in earnings-experience profiles and exclude transitory shocks – e.g. countries with steeper earnings profiles and higher incidences of transitory shocks are likely to look less unequal from a life-time perspective • Also has important implications for the assessment of social welfare – High mobility may alleviate concerns over inequality in the short-term but raise others over risk -> reduce calls for redistribution but increase those for insurance – e.g. US traditionally accepted high inequality as mobility was also high; recently rising concerns that mobility is stalling despite rising inequality Life-time earnings, mobility and earnings inequality
  • 13. • What is the role of job quantity (unemployment and working time) and job quality (earnings) for inequality in life-time earnings? • To what extent are low life-time earnings associated with higher labour market risk? • What is the role of taxes-and-benefits systems for insurance and redistribution over the life course? • To what extent does having a temporary contract have long-lasting effects for worker careers? – EmO 2014 shows that many temporary workers do not manage to find permanent jobs even after three years What explains low life-time earnings?
  • 14. • What is the role of learning? – How do the returns to potential labour market experience differ across countries? – And how do these compare across socio-economic groups (gender and education)? • What is the role of job mobility? – Job mobility is a potentially important channel for advancement for workers – Governments may also be interested in promoting job mobility for both social (to reduce low-quality work) and economic reasons (improve optimal allocation) • What is the role of firm productivity, work organisation and worker representation? 14 What explains upward mobility?
  • 15. Future OECD work 3. An ambitious statistical agenda
  • 16. 16 • Inventory of information on the quality of the working environment (international sources) – identify questions, underlying concepts, data sources and gaps – document key insights on job quality • OECD database on job quality – based on quality assessment and covering indicators for all three dimensions of Job Quality – with currently available information by country and eventually also by socio-economic group – gradually extend country coverage to non-OECD members – to become available via OECD.Stat • Further work with OECD countries to fill in methodological and statistical gaps and improve harmonisation Ambitious statistical agenda
  • 17. 17 Motivation: To take stock of available international data sources and identify gaps  7 international surveys were identified that :  Have a focus on working lives  Collect information specifically on individuals’ own job  In total cover 25 years and 160+ countries  EWCS, ESS, ISSP, EULFS AHMs, Gallup World Poll, EQLS, Eurobarometer  18 sub-dimensions of QWE shown to have an impact on well-being in the literature were identified  E.g. Work intensity, Physical risk factors, Task discretion and autonomy, organisational participation  Relevant questions in each survey were classified and documented in the Inventory  Analytical work on comparability of indicators across surveys underway OECD Inventory of Indicators on Quality of Working Environment
  • 18. 18 OECD Inventory of Indicators on Quality of Working Environment Identifying gaps: Example: Task discretion and autonomy The inventory soon downloadable from the OECD database. EWCS ISSP ESS ESS, ISSP EWCS, EQLS, Eurobar EWCS, ESS, EQLS EWCS, ESS, ISSP EWCS, ESS, EQLS, ISSP EWCS, EQLS, ISSP, Eurobar EWCS, EQLS, ESS, Eurobar ALL 5 SURVEYS
  • 19. 19 Assessing the relevance and statistical quality of Job Quality indicators (I) Criteria used: Relevance • Face validity (capacity to measure what is intended to be measured) • Unambiguous interpretation (whether the indicator is good or bad for well-being) • Policy relevance (amenable to concrete policy actions) • Can be disaggregated (by socio-economic groups in order to assess distributional aspect of job quality) Statistical Quality • Well-established instruments collected (relying on statistical instruments developed within the official statistical system or academic community) • Comparable definition (via using internationally accepted standards and surveys) • Country Coverage (ensuring maximum coverage for the OECD and other major economies where possible) • Recurrent data collection (in order to monitor progress)
  • 20. 20 Assessing the relevance and statistical quality of Job Quality indicators (II) Sub-indicator Properties Relevance to measure and monitor JQ Statistical Quality Face Validity Unambiguous interpretation Policy relevance Can be disaggregated Well-established instruments collected Comparable definition Country Coverage Recurrent data collection Earnings quality Average Earnings VV VV VV VV VV VV VV VV Earnings Inequality X Labour Market Security Unemployment risk U probability (monthly U inflows) Expected U duration (inverse of U outflows) Effective insurance Coverage rate of unemployment compensation (insurance/assistance) Average net replacement rate of insurance/ assistance V Quality of the working environment Work stressors Time pressure at work Physical Health risk factors Workplace intimidation Workplace resources Work autonomy & learning opportunities Workplace relationships Good management practices VV: Largely meets criterion V: Meets criterion to a large extent X: Does not meet the criterion or meets it only to a limited extent
  • 21. 21 • For further information on OECD work on job quality please contact: – Sandrine Cazes (STD): sandrine.cazes@oecd.org – Alexander Hijzen (ELS): alexander.hijzen@oecd.org Thank you!