rural non-farm sector employment in india: distress driven or
TRANSCRIPT
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Rural Non-Farm Sector Employment in India:Distress Driven or Growth Driven?
Vinoj AbrahamCentre for Development Studies
Trivandrum, kerala
INTERNATIONAL CONFERENCE ON EMPLOYMENT OPPORTUNIES AND PUBLIC EMPLOYMENT POLICY IN GLOBALISING INDIA ,TRIVANDRUM:
3RD- 5TH APRIL, 2008
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• Background• Trends in rural employment• Patterns of rural non-farm employment• Distress in agriculture and RNFE• Determinants of employment in RNFS
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Background
• Structural transformation in india’s output but not in employment
• Transformation in employment and income from agro based rural economy to industry based urban economy is associated with a vibrant RNFS.
• Performance of RNFS is strongly related to agriculture sector
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Background
• A highly productive agriculture sector generates a vibrant RNFS , which is growth driven.
• A stagnant agriculture sector coexists with a low value adding RNFS that is residual of farm sector.
• What about INDIA?
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Trends in rural employment
• Some positive trends in 61st round NSS Report
– Both LFPR and WPR had increased after nearly a decade of jobless growth
– Rise of self employment and decline of casualisation
– intersectoral mobility of male workers increased
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• Can distress lead to employment increase?– Yes , under certain conditions– When income from the main bread winner of
the household does not meet even basic needs then the usually dependent members of household may join Labour force.
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1. female LFPR, after declining continuously since the peak in 1987-88, rose for the first time in 2004-05 to 24.9
percent. 2. Moreover, this rise is the largest between any two NSS
thick rounds, from 23.5 to 24.9 percent
Female LFPR
0
50
100
150
200
250
300
1983 87-88 93-94 99-00 2004-05
Female Female above 60
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increment in LFPR -99-00 to 04-05
-40 -20 0 20 40 60
5-9
15-19
25-29
35-39
45-49
55-59
personsfemalemale
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Change in WPR 99-00 to 04-05
-40 -20 0 20 40 60
5-9
15-19
25-29
35-39
45-49
55-59
personsfemalemale
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under employment in rural india
0123456789
10
1983 87-88 93-94 99-00 04-05
RM_PS+SSRM_CDSRF_PS+SSRF_CDS
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growth of real wages in rural india
0 1 2 3 4 5 6 7
male
female
Persons
male
female
Persons
Reg
ular
Cas
ual
1999-20041993-19991983-1993
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Share of RNFS in Rural India
22.826.1 26.3 28.8
33.8
13.817.5 15.3 15.9 18.6
0
10
20
30
40
1983 87-88 93-94 99-00 04-.05
Male RNFS Female RNFS
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status of rural male employment (%)
0100200300400500600700
Self-Employ Regular Casual
Rural Male
1993-941999-002004-05
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status of employment - male- secondary sector (%)
0102030405060
Self-Employed Regular Casual
Secondary sector 1993-94 Secondary sector 1999-00Secondary sector 2004-05
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RNFS-concepts• Rural non- farm sector employment is defined as any form of
employment other than farm employment in the type of wage, self,or unpaid family labour.
• Farm employment is taken to be those agricultural activities such as• growing of crops ;• market gardening; horticulture ( NIC 011)• farming of animals (NIC 012)• mixed farming ,i.e., both crops and animal farming combined (013); • agricultural and animal husbandry service activities (NIC 014);• hunting and related services (NIC 015)
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Data used
• Household level data of 61st NSSO round on employment-unemployment
• number of observations -145443 individuals in 62056 households.
• After cleaning -145359 observations in 62016 households.
• All tables generated below and the analysis done is based on this dataset.
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RNFE and GenderSector of Employment by Gender - Share
10077.8722.13Non-farm employment10062.3937.61Farm employment
TotalMaleFemale
Gender by Sector of Employment - Share
100100100
39.5744.9827.82Non-farm employment
60.4355.0272.18Farm employment
TotalMaleFemale
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Level of Education and Sector of Employment (%)
05
101520253035404550
Not literat
eLe
ss th
an Prim
ary
Primary
Middle
Second
aryHighe
r edu
catio
n
Farm Non-farm
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Distress in Farm Sector and Employment Patterns
• we divide the regions into agriculturally distressed and non-distressed regions
• GoI (2007) ‘Report of the Expert Group on Agricultural Indebtedness’, Department of Economic Affairs, Ministry of Finance, Government of India, July
• 100 distressed districts identified by the expert group is the distressed region. Non-distressed is the rest of the region
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Feminization of work in distressed region
6455.5
78.31 75.7769.74
63.06
3644.5
21.69 24.2330.26
36.94
0102030405060708090
ND D ND D ND D
Farm Non-farm Total
Male
Female
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Underemployment among UPS main workers
0
5
10
15
20
25
farm non-farm
total farm non-farm
total
Non-distressed region Distressed region
< than 1month 1 to 2 months3 to 6 months
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100100100100100100Total
28.1320.1532.8824.3920.3127.11casual labour on other works
0.380.840.10.260.590.04casual labour: in public works
9.4524.020.7912.0927.791.59regular salaried/ wage employee,
27.4714.8834.9622.9411.0330.9unpaid family worker1.390.831.721.520.941.91employer
33.1839.2929.5538.8139.3538.45self-employed
TotalNon-farmFarmTotalNon-farm
FarmDistressed RegionNon-Distress region
Share of workers by status
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Belonging to other scheduled castes and scheduled tribes
Soc_SC/ST
Belonging to other backward classesGeneral category = 0
Soc_OBC
Size of the householdHH_size
Average Land cultivated by a household/no. of persons in the household
Percap_landcult
Average Land owned by a household/no. of persons in the household
Percap_landown
Higher educationEdu_high
Secondary educationEdu_sec
Middle educationEdu_mid
Priamry educationEdu_prim
Not illiterate , but has not attended a formal school
Illiterate = 0Edu_lit
Square of ageage2
Age of the workersAge
Male =1 ,female =0sex
Variables used in the logit model
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DETERMINANTS OF RNFE
• LOGIT MODEL• Dependent variable
– Employed in farm sector = 0– Employed in non-farm sector =1The exercise is done for distressed and non-
distressed region separately for four category of workers
Casual, regular, self employed, unpaid family workers
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Effect of Gender on Prob. of RNFE(Male =1,Female =0)
0.533540.74261
0.91079
1.54736
-0.12242
-1.53367
0.420080.22733 0.25795 0.23465
-2-1.5
-1-0.5
00.5
11.5
2
NON-D Distress NON-D distress NON-D distress NON-D distress NON-D distress
Total Casual w ageemployment
Regular w ageemployment
Self employed Unpaid familylabour
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Effect of AGE on Prob. Of RNFE
-0.0027
0.03762
0.01120.02166
-0.05494
0.07408
-0.0084
-0.03786
-0.01728
-0.00405
-0.08-0.06-0.04-0.02
00.020.040.060.08
0.1N
ON
-D
Dis
tress
NO
N-D
dist
ress
NO
N-D
dist
ress
NO
N-D
dist
ress
NO
N-D
dist
ress
Total Casual Regular Self employed Unpaid family
Age
age2
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Education and RNFE -Total(illiterate=0)
0
0.5
1
1.5
2
Edu_lit
Edu_prim
Edu_mid
Edu_se
cEdu_
highNON-D
Distress
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Education and RNFS - Casual
-0.2
0
0.2
0.4
0.6
0.8
1
Edu_lit Edu_prim Edu_mid Edu_sec Edu_high
Casual NON-D Casual distress
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Education and RNFE - Regular
0
1
2
3
4
5
Edu_lit Edu_prim Edu_mid Edu_sec Edu_high
Regular NON-D Regular distress
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education and RNFE -Self employment
00.20.40.60.8
11.21.4
Edu_lit Edu_prim Edu_mid Edu_sec Edu_high
Self employed NON-D Self employed distress
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education and RNFE - unpaid family
00.10.20.30.40.50.60.7
Edu_lit
Edu_prim
Edu_mid
Edu_se
c
Edu_high
Unpaid family NON-D
Unpaid family distress
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Percap_landown and RNFE
-0.001
-0.0005
0
0.0005
0.001
0.0015
0.002N
ON
-D
Dis
tress
NO
N-D
dist
ress
NO
N-D
dist
ress
NO
N-D
dist
ress
NO
N-D
dist
ress
Total Casual Regular Self employed Unpaid family
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Percap_landcultivated and RNFE-0.008-0.007-0.006-0.005-0.004-0.003-0.002-0.001
0
NO
N-D
Dis
tress
NO
N-D
dist
ress
NO
N-D
dist
ress
NO
N-D
dist
ress
NO
N-D
dist
ress
Total Casual RegularSelf
employedUnpaidfamily
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HH_size and RNFE
-0.2
-0.15
-0.1
-0.05
0
0.05N
ON
-D
Dis
tress
NO
N-D
dist
ress
NO
N-D
dist
ress
NO
N-D
dist
ress
NO
N-D
dist
ress
Total Casual Regular Self employed Unpaid family
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social groups and RNFE(Gen cat = 0)
-0.6 -0.4 -0.2 0 0.2 0.4 0.6
NON-D
Distress NON-D
distress
NON-D
distress
NON-D
distress
NON-D
distress
Tota
lC
asua
l R
egul
arS
elf
empl
oyed
Unp
aid
fam
ily
Soc_SC/STSoc_OBC
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Conclusion
• Signs of distress related employment growth
• Employment in non-farm sector picking up probably as a residual sector
• RNFS Employment in agriculturally distressed regions is related to factors that support residual sector argument, especially in casual wage workers