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

20

10

US

do

llars

, P

PP

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!