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The slide describes the Rural Labour Markets in India
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Study of spatial and
temporal dynamics of labor
market behavior in India
A Amarender Reddy
ICRISAT
Outline of the presentation
Objectives of the study
Key findings of the project on rural labour
dynamics at ICRISAT
Synthesis of three paper
From longitudinal data from 1975 to 2012
In depth study for the year 2010
Trends in rural wage rates across states from
1995 to 2011
Conclusions and Policy prescriptions
Objectives and Methods
The study used the data of Village Dynamic Studies in
South Asia(VDSA),and National Sample Survey
Organisation (NSSO) and also wage data of labour
buero
The spatial and temporal structural changes in the
labour force and employment structure in India and
Bangladesh.
Trends in Real wage rates
Factors determining the labour productivity (Modified
Mincer Equation) and workers occupational choice
(Multinomial Logit Model) will be assessed.
Future labour markets Structural transformation in GDP is faster, but labour
markets are slow
Until early 1980s agriculture is the driving force
From 1990s non-farm sector is driving growth
Increasing real wage rates even in rural areas
Higher productivity/wage differentials: rural-urban, farm- nonfarm; men-women declining
Growing income inequality- high social costs
Education and other institutions are increasing intergenerational inequality?
Bottom 20-30% of rural population is critical, mostly agricultural labourer
Increasing productivity in farm sector
Liberalisation policies for RNF/informal sector
Framers, agricultural labourer interest groups
Driving forces in rural labour markets
Skill skill
productivity
0
1
2
3
4
5
6
7
0
10
20
30
40
50
60
70
80
1973 1977 1983 1988 1993 1999 2004 2009 2012
Lab
our
pro
duct
ivity(
non-a
gril/
agri
l)
Shar
e o
f la
bour(
%)
Macro Trends in GDP and labour productivity
share of non-agricultural labour
share of agril. Labour
Labour productivity gap between agril and non-agril
86 86
71 58
14 14
29 42
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1975 1984 2004 2010
% o
f to
tal m
ale w
ork
ers
Farm and non-farm employment (%)
in VDSA villages
farm non-farm
Cultivators in 1975
Shift to agriculture sector Shift to non-agriculture
Year Cultivators Livestock
Agricultural
Labourer
Attached
labourer
Non-
farm
labour
Caste
occupatio
n Business Salaried Others Total
1975 100 100
1984 77 6 5 2 1 2 0 5 1 100
2004 59 3 10 3 1 1 5 17 3 100
2010 44 6 9 1 8 2 11 15 4 100
Casual labourer in agriculture in 1975
Shift to agriculture sector Shift to non-agriculture
Cultivators Livestock
Agricultural
Labourer
Attached
labourer
Non-
farm
labour
Caste
occupatio
n Business Salaried Others Total
1975 0 0 100 0 0 0 0 0 0 100
1984 13 5 70 6 3 3 1 0 0 100
2004 46 8 20 2 4 0 4 12 4 100
2010 32 16 18 4 14 0 7 9 2 100
Occupational Mobility Matrix (% of male workers) for whose occupation is cultivation and agricultural labourer in 1975 (males)
Year 1975 Year 2010
Occupational structure OBC ST SC Others Total OBC ST SC Others Total
Males
Agriculture (I) 92 94 90 88 91 76 69 53 85 74
Cultivation 45 47 19 59 44 48 47 16 56 47
Livestock 14 18 7 16 14 6 9 5 5 7
Agricultural labourer 33 29 64 13 33 22 13 32 24 20
Non-agriculture (II) 8 6 10 12 9 24 31 47 15 26
Non-agricultural labourer 0 0 1 1 0 17 12 37 15 16
Salaried 2 5 5 6 3 6 3 11 0 4
Business 1 1 2 3 2 1 1 0 0 1
Others 4 0 2 2 3 1 15 0 0 6
Total (III) 100 100 100 100 100 100 100 100 100 100
Females
Agriculture (I) 100 84 100 100 93 76 72 75 71 74
Cultivation 49 38 0 8 35 47 48 24 55 46
Livestock 9 0 0 0 3 2 4 3 3 3
Agricultural labourer 42 46 100 92 55 27 20 48 13 25
Non-agriculture (II) 0 16 0 0 7 24 28 25 29 26
Non-agricultural labourer 0 0 0 0 0 1 1 2 0 1
Salaried 0 0 0 0 0 8 16 12 15 11
Business 0 4 0 0 2 4 4 1 9 5
Others 0 12 0 0 5 11 6 10 5 9
Total (III) 100 100 100 100 100 100 100 100 100 100
Notes: OBC: Other Backward Caste; SC: Scheduled Caste; ST: Scheduled Tribes
Major occupation of workers (% of total workers) by Social status
Major
Occupation Agricultur
al labor
Attached
laborer Cultivation
Domestic
work
Livestock
rearing
Nonfarm
laborer
Other
traditional Others All
Forward
1975 0 0 100 0 0 0 0 0 100
1984 0 0 100 0 0 0 0 0 100
1989 8 0 84 0 0 0 8 0 100
2010 4 0 83 0 0 0 0 13 100
OBC
1975 22 3 44 6 6 0 19 0 100
1984 19 3 46 5 3 0 24 0 100
1989 17 2 62 2 9 2 6 0 100
2010 41 0 45 0 2 2 7 3 100
SC
1975 46 31 23 0 0 0 0 0 100
1984 54 31 15 0 0 0 0 0 100
1989 29 14 57 0 0 0 0 0 100
2010 72 0 13 0 0 15 0 0 100
Major occupation of workers by Social status (two villages of AP)
Major occupation of workers
(Male in %) by education
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Illit
era
te
read
and w
rite
upto
pri
mar
y
upto
mid
dle
hig
h s
chool
dip
lom
a
grad
uat
e
All
pri
mar
y
mid
dle
hig
h s
chool
inte
r
dip
lom
a
grad
uat
ion
post
gra
duat
ion
Tota
l
1975 2010
all others
RFS
Farm labour
Farming
Female work structure by education level
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Illit
era
te
read
and w
rite
upto
pri
mar
y
upto
mid
dle
hig
h s
chool
grad
uat
e
All
illitera
te
pri
mar
y
mid
dle
hig
h s
chool
inte
r
dip
lom
a
grad
uat
ion
post
gra
duat
ion
Tota
l
1975 2010
Others
Farming
Farm labor
0
50
100
150
200
250
300
illiterate primary middle high
school
10+2 degree
and above
Illiterate Primary Middle High
school
10+2 degree
and above
Female Male
Work days (days/year) in 2010
Who is getting how many days of employment
Major occupation of workers (%)
by Social status (1975-2010)
0
5
10
15
20
25
30
35
40
45
1975 2010 1975 2010 1975 2010
farming agricultural
labourer
salaried job
Males
BC ST/SC Others
0
5
10
15
20
25
30
35
40
1975 2010 1975 2010 1975 2010
farming agricultural
labourer
salaried job
Female
BC ST/SC Others
Credit delivery still land is major
collateral?
0
10
20
30
40
50
60
70
80
Formal
sources
Informal
sources
Formal
sources
Informal
sources
Borrowers (%) Multiple borrowers
(%)
Social group
Others OBC ST SC
0
10
20
30
40
50
60
70
80
Formal
sources
Informal
sources
Formal
sources
Informal
sources
Borrowers (%) Multiple borrowers
(%)
Land class
landless small
medium large
Work days excluding domestic work
0
50
100
150
200
250
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
2006
2008
2009
2010
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
2006
2008
2009
2010
female male
Standard work days per year
paid days Days in Economic Activity (including own farm)
Work days including domestic work
0
50
100
150
200
250
300
1975
1977
1979
1981
1983
2006
2009
1976
1978
1980
1982
1984
2008
2010
female male
work days per year
Paid work and wage rates, 2010
0
50
100
150
200
250
Male Female Male Female
Farm Non-farm
Non-farm sector even lopsided educational policy is gender
biased
Paid work (Days) Wages rate (Rs/day)
0
50
100
150
200
250
300
Un-irrigated Irrigated Un-irrigated Irrigated
Female Male
Self-employment days (days) and wage rates (Rs/day), 2010
self-employment Wage rates
0
50
100
150
200
250
300
350
400Illit
era
te
Pri
mar
y
Mid
dle
Hig
h
Inte
r
Hig
h
educa
ted
Illit
era
te
Pri
mar
y
Mid
dle
Hig
h
Inte
r
Hig
h e
duca
ted
Female Male
Education level by paid work (days) and wage
rates (Rs/day) in 2010
Paid work Wage rates
0
20
40
60
80
100
120
140
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1989
2005
2006
2007
2008
2009
2010
Real wages in farm sector
(1986 prices) (Rs/day for male and females; Rs/pair days for
bullock labour; Rs/hour of tractor work)
Bullock
Female
Male
Tractor
0
5
10
15
20
25
30
35
40
2005 2006 2007 2008 2009 2010
wag
e r
ate (
Rs/
day
) Rural non-farm sector wage rates in
constant prices (Rs/day)
Female Male
Urban migration of male population in Andhra Pradesh
50
100
150
200
250
300
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Rs/
day
All India Real wage Rates (at constant prices of 2011)
Mason Carpenter Tractor Driver Ploughing
Sowing Harvesting Unskilled Labourers
100
150
200
250
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
slack peak
Seasonal real wage rates (Rs/day) at 2011 prices
Mason Carpenter Tractor Driver Ploughing
Harvesting Sowing Unskilled Labourers
Work type
Mean 2012
(Rs/day)
Annual growth rates
Slack Peak
2001-07 2008-12 2001-07 2008-12
Mason(construction) 269 -1.3 4.5 -0.9 5.4
Carpenter 243 -0.9 4.5 -0.8 5.5
Well digging 231 -0.4 8.5 -0.7 10.3
Tractor Driver 194 -0.5 5.6 -0.4 5.9
Blacksmith 186 -1.7 4.9 -1.4 6.2
Ploughing 184 -1.4 6.1 -1.2 7.1
Sowing 163 -1.6 6.5 -0.7 7.4
Cane crushing 162 1.5 6.3 0.5 8.2
Harvesting 161 -0.5 7.7 0.2 8.3
Unskilled Laborers 158 -0.9 7.8 -0.5 7.6
Threshing 158 -1.3 8.8 -0.2 7.3
Transplanting 151 0.2 7.2 0.4 7.2
Winnowing 149 0.4 6.8 0.8 7.4
Picking 148 -0.3 8.1 -0.7 7.2
Weeding 145 -0.1 6.9 0.1 7.2
Cobbler 131 -1.4 3.9 -1.1 5.2
Sweeper 112 -1.9 5.7 -1.7 6.2
Herdsman 101 -2.3 8.0 -2.2 8.4
ACGR of real wage rates (%)
Year Mason Carpenter Tractor
Driver Ploughing Sowing Harvesting
Unskilled
Laborers
High wage rate states
Tamil Nadu (P) 7.8 7.8 7.1 6.4 6.9 7.8 7.1
Tamil Nadu(S) 6.7 6.3 6.2 5.4 5.8 7.1 6.6
Andhra Pradesh(P) 5.7 5.7 6.9 9.6 9.4 8.7 8.2
Andhra Pradesh(S) 5.6 5.9 5.5 10.2 7.7 9.0 8.4
Haryana(P) 1.6 3.3 3.7 6.3 4.8 3.3 5.0
Haryana(S) 1.4 3.4 3.0 4.3 4.1 3.5 5.3
Punjab(P) 2.5 2.3 7.3 4.8 4.7 7.3 6.0
Punjab(S) 1.3 1.5 5.5 4.5 5.6 5.5 4.6
Medium wage rate states
Karnataka(P) 2.5 3.2 3.4 8.2 6.9 7.8 6.2
Karnataka(S) 2.1 3.0 4.1 5.7 6.2 7.0 5.7
Maharashtra(P) 2.6 2.2 4.4 6.3 6.2 7.0 5.5
Maharashtra(S) 1.3 1.4 3.5 4.8 5.1 5.0 4.0
Rajasthan(P) 3.3 3.0 2.9 3.3 4.4 7.9 6.5
Rajasthan(S) 3.3 2.1 2.0 4.8 0.4 7.0 6.6
West Bengal(P) 1.2 0.7 1.0 1.8 4.1 4.0 4.3
West Bengal(S) 0.3 -0.3 0.8 2.5 4.0 4.1 3.9
Gujarat(P) 0.3 -1.5 -1.5 0.5 -0.4 0.8 1.4
Gujarat(S) -1.0 -2.5 -1.7 -0.3 -1.3 -0.3 0.6
Low wage rates states
Uttar Pradesh(P) 2.9 1.9 3.7 4.1 4.3 4.1 5.2
Uttar Pradesh(S) 1.7 0.6 2.9 2.1 3.4 3.2 4.0
Bihar(P) 1.9 1.3 2.0 4.5 4.1 3.1 4.6
Bihar(S) 1.0 0.3 1.7 4.1 2.8 2.1 3.7
Orissa(P) 1.6 0.8 -0.9 6.8 5.3 5.8 6.8
Orissa(S) 0.7 -0.1 -1.2 6.6 7.0 6.7 6.5
MP(P) -0.6 -0.5 3.3 3.8 4.2 5.2 4.1
MP(S) -4.8 -1.0 1.8 2.2 2.2 2.5 3.6
All India(P) 2.5 2.3 3.4 4.5 4.1 5.0 5.2
All India(S) 1.8 1.6 2.7 3.8 3.4 4.0 4.7
Annual compound growth rates of real wage rates (2005-12),
State Period AP Punjab Haryana TN All India
Unskilled P-I 3.5 5.0 0.7 2.6 3.6
P-II 7.1 7.4 5.8 5.8 5.1
Over all 2.9 4.3 1.7 2.9 2.9
Ploughing P-I 2.5 1.0 2.1 5.1 1.3
P-II 10.3 6.3 6.4 6.5 4.7
Over all 4.7 2.7 3.0 3.0 1.7
Harvesting P-I 3.0 2.0 2.4 1.3 1.0
P-II 10.3 8.1 4.1 7.2 5.1
Over all 5.2 3.1 2.6 2.5 1.8
Sowing P-I 5.1 3.1 1.8 1.7 2.1
P-II 4.2 6.8 4.9 6.9 4.3
Over all 2.2 2.8 2.7 2.3 1.9
Tractor P-I 3.2 3.9 1.9 2.5 3.7
P-II 2.5 4.0 6.6 7.5 4.5
Over all 2.2 3.4 1.9 3.0 3.0
Mason P-I 1.2 0.1 2.5 4.6 2.0
P-II 2.1 2.4 3.5 7.8 2.7
Over all 1.5 0.2 1.4 4.0 1.4
Carpenter P-I -0.5 4.3 -0.2 4.5 4.2
P-II 4.0 2.8 2.4 7.6 -1.4
Over all 0.8 1.5 0.2 3.9 0.8
ACGR of wage rates in high real wage rate states (developed states)
State Period Bihar Orissa MP UP
Unskilled P-I 5.4 4.5 2.4 4.1
P-II 4.7 5.3 4.3 1.6
Over all 3.9 3.1 1.6 1.5
Harvesting P-I 2.6 2.2 2.1 3.5
P-II 4.4 7.2 0.7 4.7
Over all 2.2 3.2 0.9 2.3
Sowing P-I 4.2 5.7 4.7 4.4
P-II 4.5 4.0 3.5 -0.2
Over all 2.8 3.5 2.1 1.8
Tractor P-I 3.0 2.1 4.5 2.3
P-II 4.5 3.7 -0.6 3.0
Over all 2.8 2.4 1.8 1.0
ploughing P-I 5.3 4.1 3.7 4.0
P-II 4.8 7.0 3.2 3.7
Over all 4.2 3.6 2.1 2.7
Mason P-I 4.8 4.2 1.5 3.8
P-II 2.0 1.6 -0.7 1.3
Over all 2.8 2.0 0.2 1.8
Carpenter P-I 5.4 4.0 2.3 3.7
P-II 3.5 6.3 -0.2 0.8
Over all 2.5 3.2 0.6 1.7
ACGR in low real wage rate (less developed) states
Ratio of male to female wage rates
Farm and non-farm sector
0.0
0.5
1.0
1.5
2.0
2.5
2002
2003
2004
2005
2006
2007
2008
2009
2010
Rat
io
farm work non-farm work
Linear (farm work) Linear (non-farm work)
Declining gender wage gap
Ratio of wage rates(non-farm to farm)
0.8
0.9
1
1.1
1.2
1.3
1.4
1.5
2002
2003
2004
2005
2006
2007
2008
2009
2010
Rat
io
Male
Female
Linear (Male)
Linear (Female)
0.8
1.0
1.2
1.4
1.6
1.8
2.0
2.2
2.4
2.6
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Rat
io
Ratio of wage rates of mason to ploughing
Uttar Pradesh Gujarat Rajasthan Bihar
Orissa Punjab Madhya Pradesh Maharashtra
All India Haryana Karnataka Tamil Nadu
Andhra Pradesh West Bengal
-60
-40
-20
0
20
40
60
80
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2006
2007
2008
2009
2010
2011
2012
The coefficients for the year dummies on wages
ploughing harvesting unskilled sowing
mason tractor carpenter
0
2
4
6
8
10
12
14
16
18
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
2005
2006
2008
2009
2010
1979
1980
1981
1982
1983
1984
2005
2006
2008
2009
2010
female male
Rat
io: t
op t
o b
ott
om
Disparities in wage rates
9th percentile to 2nd percentile
10th percentile to 1st percentile
Work type /item Female Male % over female
(I) Hours with economic activities 23.1 36.2 56.7 Paid work 12.3 20.8 69 Own farm 5.2 8.5 62 Own livestock 5.1 6.3 24 Other own 0.5 0.6 33 (II)Hours with non-economic activities 28.1 8.8 -68.7 Domestic duties 26.3 6.5 -75 Seriously ill 0.9 0.6 -33 Unemployed 0.9 1.7 83
Hours with economic and non-economic activities (I+II) 51.2 45.0 -12.1
Wage income ( /year) 7920 27000 241 Wage rate ( /8 hours) 99 200
102 Imputed income , if income of non-monetary work days are
imputed with on-going wage rates for male and female
respectively
32967 58400
77 Imputed income , if income of non-monetary work days of both
men and women at the on-going wage rates of female ( 99/8
hours)
32967 42551
29.1 Average level of education 5 8
Average hours/week of female and male (2010)
Salient features
Structural transformation in rural economy
Raising real wage rates
Divergence in wage rates
Stagnation in labour productivity in agriculture
Shift in engines of growth
Increase in rural non-farm sector and diversity of income
Long run trends.. Most of the workers are spent more days in self-employment in agriculture with
very few days in paid work. Both men and women have more leisure time during
the 1970s compared to early 2000s. However, from 2001 onwards, there has been
an increase in non-farm employment opportunities in both self-employment and
also paid work mostly for rural male, but most of the rural women remained in
farm sector. Results also shows that even though education improves chances of
getting higher remunerative employment, still rural labour markets are segmented
based on social groups to 2 some extent. The high unemployment among
educated youth indicates that the skills acquired by the educational system are
not meeting the needs of the rural economy. However, many parents are investing
heavily in children’s education with the expectation of getting higher paid urban
jobs. Over the period, gender and caste differences in wage rates decreased
slightly, but are not eliminated wholly.
Long run trends.. Men work days are more than women work days per year,
however If we take domestic work into consideration women work more days than men. Attached labourer are almost eliminated with the implementation of bonded labour abolition act and most of them shifted to different occupations including cultivation or casual agricultural labourer or took up petty businesses. There is significant increase in farm mechanisation in recent years due to scarcity of labour and higher wage rates. The results also show that the real wage rates started increasing much before the introduction of a major employment guarantee program (MGNREGA) and mostly driven by increased non-farm employment opportunities, rural-urban linkages, migration and increased agricultural productivity.
Conclusions
Overall, men reported 36.2 hours per week compared to only 23.1
hours per week in economic activities.
If we consider both economic and non-economic activities,
participation of women increased to 51.2 hours compared to only 45.0
for men as women spent more hours in attending domestic duties.
However, men work more hours in paid work (20.8 hours) than
women (12.3 hours).
The gap in income earned from monetary activities between men and
women is much higher. But, if we impute the value of the domestic
duties of both men and women equally, the gap in incomes between
men and women drastically reduced from 241% to just 29%.
Illiterate women loaded with more hours of paid-work as well as
domestic work. Labor markets are segmented based on social
background to some extent (after discounting for human and physical
capital) and supports segmented labor market theory.
Conclusions Cont.. It is interesting to see that the hours worked in economic activities
increases with ownership of land and assets rather than education in rural India.
Level of education and experience have little influence on choice of occupation and quality of employment of individuals both men and women, as still rural employment in rural India is mostly confined to the technologically backward sectors even in non-farm sector and business like petty business, general stores, toddy tapping, repair shops, transport and construction works which require very little skill levels and education levels.
However, the quality of work improves significantly for only few higher educated men and women in service sector employment like teachers, nurses, record keeper, health workers; most of the educated youth remain unemployed. Especially most of the educated women engaged in domestic duties due to lack of commensurate employment opportunities in rural areas. Even though in the villages returns to education is low or non-significant, people are investing heavily in educating their children with the expectation of getting urban employment mostly as engineer or doctor or even a software engineer in America etc.
Most of the parents persuade their children to go to urban centres as soon as they completed the higher education with expectation of huge remittance money.
THIS CONFIRMS THAT AT LEAST DEVELOPED STATES IN INDIA CROSSED THE LEWIS TURNING POINT.
THE ACCELERATION OF REAL WAGES EVEN IN SLACK SEASON INDICATES THAT THE ERA OF LABOR
SHORTAGE IS STARTED IN RURAL AREAS ESPECIALLY IN DEVELOPED STATES LIKE TAMIL NADU,
HARYANA, PUNJAB AND ANDHRA PRADESH, WHICH NEEDS TO BE TACKLED THROUGH LABOR SAVING
TECHNOLOGY AND WIDE SCALE FARM MECHANISATION. ON THE OTHER HAND IT APPEARS THAT
THE UNDERDEVELOPED STATES LIKE MADHYA PRADESH, UTTAR PRADESH AND BIHAR ARE NOT
REACHED THE LTP AND NEEDS TO DEVELOP POLICIES TO INCREASE PRODUCTIVITY OF RURAL LABOR
IN THESE BACKWARD STATES.
Wage rates…..
Rural society in India is traditionally highly segmented based on caste, gender and
traditional occupations, however, they are slowly reducing their influence on labor
market outcomes as they are not significant in choice of employment or hours worked,
they are replaced by the ownership of land and assets and owning high productive land
(like irrigated area) in influencing the labor market outcomes.
Demand for some caste occupations like traditional toddy-tapping (making locally
made alcohol), cleaning of cloths, etc is increasing in near-by towns which can be
captured by rural men and women with middle level of education.
Some of the policy prescriptions from the study are
• Enhancing the ownership of assets like land, irrigated area through providing loans
which will increase hours worked in economic activities
•Imbibing savings habit which generally increase labor force participation rate,
•Enhancing quality education in rural areas beyond the higher-secondary to take
advantage of growing employment in service sector and new emerging occupations like
repair of mobiles, electric motors computer centres
•Imparting skill development in both caste occupations and also in modern sectors and
•Balanced development of both urban and rural areas through promotion of small
towns.
Policy Options..