Upload
others
View
5
Download
0
Embed Size (px)
Citation preview
Wage employment, mobility and development
IDE-JETRO, World Bank, Asashi Shimbun Joint Symposium
“Evolving Sources of Value-added: Good-jobs, Bad-jobs?”
United Nations University
Tokyo, March 19, 2015
Martin Rama
Chief Economist for South Asia
The World Bank
World Development Report 2013 The World Bank 3/13/2012
Moving jobs to center stage 2
Access the report athttps://openknowledge.worldbank.org/handle/10986/20395
Overview
4
• Jobs take people out of poverty. But not all jobs involve an employer and an employee.
• Wage employment drives mobility. Whether jobs are formal or informal seems less relevant.
• Firm dynamics matter. But we have a distorted picture of firm dynamics in developing countries.
• Cities are the engine of job creation. Employment opportunities are different along the rural-urban gradation
Overview
5
• Jobs take people out of poverty. But not all jobs involve an employer and an employee.
• Wage employment drives mobility. Whether jobs are formal or informal seems less relevant.
• Firm dynamics matter. But we have a distorted picture of firm dynamics in developing countries.
• Cities are the engine of job creation. Employment opportunities are different along the rural-urban gradation
Source: Covarrubias and others 2012 for the WDR 2013
Jobs are the main source of household income
Source: Inchauste and others 2012 for the WDR 2013
Jobs take households out of poverty
Source: Inchauste and others 2012 for the WDR 2013, Azevedo and others 2012 for the WDR 2013
Jobs account for much of the decline in extreme poverty
Jobs get better with development
But what is a job?
A job does not always come with a wage
Overview
12
• Jobs take people out of poverty. But not all jobs involve an employer and an employee.
• Wage employment drives mobility. Whether jobs are formal or informal seems less relevant.
• Firm dynamics matter. But we have a distorted picture of firm dynamics in developing countries.
• Cities are the engine of job creation. Employment opportunities are different along the rural-urban gradation
Considerable occupational mobility exists across generations in India
13
Sources: Based on India Human Development Survey (IHDS) 2004–05.
Occupational mobility is higher for younger population cohorts
14
Sources: Based on IHDS 2004–05.
Occupational mobility has increased more for the most disadvantaged population groups in India
15
Sources: Based on IHDS 2004–05.
Upward mobility in South Asian countries is similar to that in the United States and Vietnam
16
Sources: Based on Dang and Lanjouw 2014 for this report and Dang, Lanjouw, and Khandker 2014 for this report.
Upward mobility is much stronger in cities than in rural areas in India
17
Sources: Based on IHDS 2004–05.
Wage employment is associated with greater upward mobility in urban areas
18
Sources: Based on data from Dang and Lanjouw 2014 for this report and Dang, Lanjouw, and Khandker 2014 for this report
Overview
19
• Jobs take people out of poverty. But not all jobs involve an employer and an employee.
• Wage employment drives mobility. Whether jobs are formal or informal seems less relevant.
• Firm dynamics matter. But we have a distorted picture of firm dynamics in developing countries.
• Cities are the engine of job creation. Employment opportunities are different along the rural-urban gradation
Job creation and destruction happen everywhere
Source: WDR 2013 team based on Bartelsman, Haltiwanger, and Scarpetta (2009), and Shiferaw and Bedi(2010).
But enterprise surveys give us a distorted picture
Source: Li and Rama (2015).
Household surveys Enterprise surveys
Germany
Chile
The employment share of microenterprises is greater in developing countries
The dispersion of productivity across firms is much higher in developing countries
Source: Li and Rama (2015).
0 5 10 15 20 25 30
Mexico
India
El Salvador
Uruguay
Bolivia
Chile
Ecuador
Argentina
China
United States
productivity ratio between
90th percentile and 10th percentile of TFP distribution
Bigger firms pay higher wages than smaller ones and much more than microenterprises
Source: Li and Rama (2015).
02
46
freq
ue
ncy (
%)
0 .2 .4 .6 .8wage difference, relative to microenterprises (%)
Small Large
kernel = epanechnikov, bandwidth = 0.0221
wage premium, relative to microenterprise, %
esti
mat
es, %
But most jobs are created by microenterprises, among which there are very few “gazelles”
Source: Li and Rama (2015).
0
20
40
60
80
[0-5] [6-9] [10-49] [50-199] [>=200]
per
cen
t
firm employment size
shares in job creation, % shares in job destruction, %
shares in employment, %
0
20
40
60
80
[0-5] [6-9] [10-49] [50-199] [>=200]
per
cent
firm employment size
shares in job creation, % shares in job destruction, %shares in employment, %
Job creation and destruction based
on enterprise surveys
Job creation and destruction re-
weighted by household surveys
Chile 2000-06
Overview
26
• Jobs take people out of poverty. But not all jobs involve an employer and an employee.
• Wage employment drives mobility. Whether jobs are formal or informal seems less relevant.
• Firm dynamics matter. But we have a distorted picture of firm dynamics in developing countries.
• Cities are the engine of job creation. Employment opportunities are different along the rural-urban gradation
Job opportunities vary along the rural-urban gradation
27Source: Chatterjee, Murgai and Rama (work in progress)
Farming jobs fall sharply at around 5,000 inhabitants
Jobs in factories and
offices pick up much later
Employment shares(usual status for women aged 15 and above, 2011-12)
Productivity varies along the rural-urban gradation
28Source: Based on Li and Rama (work in progress).
0.5
11
.52
2.5
Den
sity
6.5 6.75 7 7.25 7.5 7.75 8 8.25 8.5 8.75 9DistrictXsize fixed effect, nominal consumption
Rural, 0-4999
Rural, 5000+
Urban, 0-1000000
Urban,1000000+
Household weights
“Big rural” and “small urban” are almost indistinguishable The best performers
are in “small urban”
Less productive locations
More productive
locations
Top performers cluster well-defined spots
Source: Based on Li and Rama (work in progress).
Bottom performer(bottom 5%)
Average performer
Top performer(top 5%)
No data
30Source: Based on South Asia Spatial Database
City size and city governance matter for performanceExample: share of employment in manufacturing
But city size and governance are correlated, so the analysis needs to take them into account together
Determinants of light intensity per capita
31Source: Based on South Asia Spatial Database
0.5
1
Estim
ate
d c
oe
ffic
ien
t
State
Cap
ital
Mun
icip
al C
orpo
ratio
n
Indu
stria
l Tow
nship
Mun
icip
ality
Not
ified
Are
a
Mor
e th
an 4
milli
on
1-4
milli
on
500,
000-
1 m
illion
100,
000-
500,
000
50,0
00-1
00,0
00
Administrative and size category
Base category: Administrative: Nagar Panchayat; Size: Less than 50,000
Log. Light intensity per capita
32Source: Based on South Asia Spatial Database
-.2
0.2
.4.6
Estim
ate
d c
oe
ffic
ien
t
State
Cap
ital
Mun
icip
al C
orpo
ratio
n
Indu
stria
l Tow
nshi
p
Mun
icip
ality
Not
ified
Are
a
Mor
e th
an 4
millio
n
1-4
millio
n
500,
000-
1 m
illio
n
100,
000-
500,
000
50,0
00-1
00,0
00
Administrative arrangement and size category
Base category: Administrative: Nagar Panchayat; Size: Less than 50,000
log of district mean of per capita expediture in urban areasDeterminants of household expenditure per capita
33Source: Based on South Asia Spatial Database
-10
01
02
03
0
Estim
ate
d c
oe
ffic
ien
t
Sta
te C
apita
l
Mun
icip
al C
orpo
ratio
n
Indu
stria
l Tow
nship
Mun
icip
ality
Not
ified
Are
a
Mor
e th
an 4
milli
on
1-4
millio
n
500,
000-
1 m
illion
100,
000-
500,
000
50,0
00-1
00,0
00
Administrative and size category
Base category: Administrative: Nagar Panchayat; Size: Less than 50,000
Share of wage employmentThe rural-urban gradation and wage employment
Not all top urban performers are equally inclusive
District - Meerut
District - Agra
District - Lucknow
District - Bhopal
District - Nagpur District - Faridabad
Delhi
District - Jaipur
District - Kolkata
District - Mumbai Suburban
District - Pune
District - Bangalore
District - Chennai
District - Ludhiana
District - Kanpur NagarDistrict - Varanasi
District - Patna
District - Haora
District - Indore
District - NashikDistrict - Hyderabad
District - Ludhiana
District - Ahmadabad
District - Vadodara
District - Surat
District - Thane
.1.1
5.2
.25
.3.3
5M
LD
7.6 7.8 8 8.2 8.4Location Premium
Less productive and less inclusive More productive but less inclusive
Less productive but more inclusive More productive and more inclusive
nominal consumption based
Source: Based on Li and Rama (work in progress).
Cities spread their prosperity to nearby locations7
.57
.75
8
8.2
58
.58
.75
0 0-25 25-50 50-75 75-100 100-150 150-200Distance to a mega city (km)
Rural, 0-4999 Rural, 5000+
Urban, 0-1000000
Delhi – Faiderabad - Jaipur
Source: Based on Li and Rama (work in progress).
But not all cities do so to the same extent
Bangalore7
.57
.75
8
8.2
58
.58
.75
0 0-25 25-50 50-75 75-100 100-150 150-200Distance to a mega city (km)
Rural, 0-4999 Rural, 5000+
Urban, 0-1000000
Source: Based on Li and Rama (work in progress).