RELI: Relative Engagement Labor Index

An Innovative Measure for the KSA

May 9, 2018Carole Chartouni, Robert Holzmann, and Gustavo Paez

Job Course - WB

Motivation

Deep engagement heterogeneity across groups of individuals

An index that measures the level of engagement within these groupsTo cluster individuals into groups with similar levels for targeted interventions

Most importantly jobseekers, but can also target interventions to clusters of employed and inactive

Track development of engagement level with continuous updates. Even if unemployment status does not change, intervention may have increased

engagement level.

2

KSA Labor Market Context

Segmented Labor Market by at least three dimensions:between the Saudis (nationals) and the many temporary foreign workers

(expats)

between the public sector (where mostly nationals work) and the private sector (that is dominated by the expats),

between men and women

Unemployment Rate for Saudis 12.7% (Youth and Women)

Participation Rate for Women very low at 19% (Q32016 data)

Vision 2030: decrease UR to 7% and increase LFP to 30%

3

Methodology

1- Identifying labour subgroups and engagement dimensions

Level of engagement is dependent on three dimensions:

Six sub-groups identified:

Inactive Women

Employed Women

Unemployed Women

Inactive Men

Employed Men

Unemployed Men

PreferencesIntensity Barriers

4

Methodology (cont’d)2- Identifying variables from questions per group and dimension

Variables for Preferences Variables for Intensity Variables for Barriers

Type of works that are considered acceptable People that applied for jobs Self-identified reasons why the individual has no job

Constraints on the jobs that the person is

willing to accept

People that updated their CVs Particular barriers that individuals face (looking

for/during their) jobs

Minimum hours that the person is willing to

work

Number of job search actions Amount of hours that a guardian allows a woman to

work - Women

Reasons why the individual is not working Time when the last application was

done

If the guardian allows mixing working environments -

Women

Willingness to reallocate in order to find a job Number of applications done by the

individual

Types of transport allow by the guardian - Women

Attitude towards gender mixing environments

- Women

Number of recent search actions done If the guardian allows the women to work - Women

Attitude towards women working - Women Hours dedicated to job search Hours dedicated to household chores - Women

Attitudes towards work How serious is the job search Availability of a domestic worker - Women

Flexible working conditions Types of transport acceptable for the women -

Women

Amount of working (or willing to work) hours

Willingness to do work shifts

Questions already Existed prior to Index

UNEMPLOYED

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Methodology (cont’d)

3- Construction of dimension indices using principal componentanalysis (PCA) to extract the common information of these variables:

Variables - Intensity PCA 1- Weight

actual_applications 0.52

cv_update 0.38

job_search_actions 0.14

last_applications 0.53

num_applications 0.46

recent_search_actions 0.24

serious_job_search 0.09

search_time 0.12

UNEMPLOYED Men - Intensity

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Methodology (cont’d)

4- Aggregation into one single index RELI

𝑅𝐸𝐿𝐼 =1

3𝐵𝑎𝑟𝑟𝑖𝑒𝑟𝑠 +

1

3𝐼𝑛𝑡𝑒𝑛𝑠𝑖𝑡𝑦 +

1

3𝑃𝑟𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒𝑠

Standard mean is 0 and standard deviation is the level

For robustness PCA was also used to generate variable weights

5- Cluster analysis identifies those individuals that have similar levels at the different dimensions.

a hierarchical cluster is used using the first principal component of each dimension 𝑃𝑟𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒, 𝐼𝑛𝑡𝑒𝑛𝑠𝑖𝑡𝑦, 𝐵𝑎𝑟𝑖𝑒𝑟𝑠

7

Results – Profiling Unemployed men

Preferences Intensity Barriers

Cluster 1 Well below Below Average

Cluster 2 Average Above Well below

Cluster 3 Well above Well below Above

Cluster 4 Above Well above Above

Hardest to Place

Barriers High! ¾ stated that their lack of experience and education pose a barrier for finding jobs

Intensity Low! ¾ updated their cv more than 1 year ago

Easiest to Place

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Results – Profiling Unemployed men (cont’d)

Most Engaged - Mostly SingleLeast Engaged - Lower Education Least Engaged – Mostly in Qasim9

Results – Profiling Unemployed men (cont’d)

• Very low education and English levels

• Highest shared of married men and oldest population distribution (40% 35+)

• Highest share of people that embrace traditional beliefs

• Few are in Riyadh

Profile 1

Hardest to Activate

• Lowest education levels and low English levels

• Relatively younger than profile 2 (20% 35+)

• Geographically spread

Profile 2

High Barriers

• Better educational levels but low English levels

• Higher share of married men

• Similar age distribution to profile 2

• Geographically spread

Profile 3

Low Intensity

•Better educational levels and English Skills

•Youngest distribution and higher share of single men

•Non-negligent share in Riyadh

Profile 4

Easiest to Place 10

Results – Profiling Unemployed Women

Preferences Intensity Barriers

Cluster 1 Average Below Well below

Cluster 2 Below Above Well below

Cluster 3 Well above Well below Well above

Cluster 4 Above Well above Well above

Intensity Low and Barriers High! Hardest to Place

Preferences Low & Barriers High! Hardest to Place!Most likely to be affected by restrictions by guardians; lowest work attitudes, not willing to work shifts, etc..

Intensity Low! Barely used any search methods

Easiest to Place

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Results – Profiling Unemployed Women (cont’d)

Unemployed Educated! Most Engaged – More likely Single Least Engaged – Traditional Beliefs12

Results – Profiling Unemployed Women (cont’d)• High share of married women and older population distribution (40% 35+)

• High share of women that embrace traditional beliefs

• Lower educational levels and English skills

• Reservation wages high

Profile 1: Low Intensity/High

Barriers• High share of married women and older population distribution (40% 35+)

• High share of women that embrace traditional beliefs

• 40% in two areas (Asir and Jouf)

• Highest reservation wages

Profile 2: Low Pref/High Barriers

• Lower educational levels but high English levels

• Highest share of young women and single people

• Lower share of women that embrace traditional beliefs

• Lowest reservation wages

Profile 3

Low Intensity

•Better educational levels and English Skills

•Lower share of women that embrace traditional beliefs

•Significant share in Riyadh (40%)

•Widespread distribution of reservation wages

Profile 4

Easiest to Place13

Results – Profiling of UnemployedProfiles by engagement dimension Intervention focus by engagement dimensions

Preferences Intensity Barriers RELI Preferences Intensity Barriers Comments

UEP - Male

Cluster 1 Well below Below Average Well below Attitude

change

Job search motivation Education and

skills

Hardest to place; Starting with regional

focus suggested

Cluster 2 Average Above Well below Well below Change in

sector

orientation

n.p. Education,

English

Young group; 90 percent are singles

Cluster 3 Well above Well below Above Average Job search skills,

counselling, etc

n.p. Job intermediation and motivation

Cluster 4 Above Well above Above Well above Reservation

wage and job

attitude

n.p n.p Ready for the labor market but perhaps

in different sector

Can search on own for first few months

UEP – Female

Cluster 1 Average Below Well below Well below Attitude

change

Job search motivation

and skills

Addressing

gender-specific

issues

Hardest to place as gaps in all

engagement dimensions required

Cluster 2 Below Above Well below Below n.p Intermediation services

with focus on gender

adequate jobs

Interventions

toward

influencers

Gender specific intervention most

promising

Cluster 3 Well above Well below Well above Above n.p Job search skills,

counselling, placement

assistance etc

n.p. Regional concentration of cluster

members and hence regional

interventions promising

Cluster 4 Above Well above Well above Well above n.p. n.p. n.p Ready for the labor market but demand

may be missing; focus sector for demand

intervention to be explored14

Results – Profiling of Unemployed

For each cluster of unemployed, tailored interventions need to bedesigned

When individuals register, they will answer questions which willidentify which cluster they belong to and receive up to date profile onlevel of engagement according to three dimensions

Possibility of calculating the index value of an individual who was notpart of the original sample

Offers a frequent assessment of changes and progress among the keylabor market participants for which interventions are needed

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Results – Profiling Other Groups (Inactive Women)

Preferences Intensity Barriers

Cluster 1 Below Above Well below

Cluster 2 Below Average Below

Cluster 3 Above Average Average

Cluster 4 Above Average Above

Depending on policy objectives, government mayfocus on cluster 3 and 4 to increase LFP for women.Reasons for inactivity partly due to discouragementor lack of skills

Cluster 1 and 2 largely inactive due to familyrestrictions. Interventions could focus oncommunication campaigns, edutainment, reachingout to influencers, etc…

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Results – Tracking Progress in Engagement

Repeat survey/collection of data

Standards (weights, means and standard deviations) are fixed at time𝑡 (index calculated from 2016 data)

Treat the future population as out-sample individuals who arecompared under the same standards as the present population.

An increase in the index in the future would reflect improvement inthe variables that define the index.

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Challenges!

Questions were developed prior to formulation of indexShould there be identical questions across all subgroups for easy aggregation

to a single index?

Questions need to be reviewed and reformulated

New questions may need to be added

CAN YOU THINK OF NEW QUESTIONS THAT CAN BE USEFUL TOPROFILE JOB SEEKERS?

Preferences Intensity Barriers

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