Rural Transformation & Implications for Agricultural & Rural Devt by Steve Wiggins
PARMOD KUMAR Agricultural Development and Rural Transformation Centre … OF...
Transcript of PARMOD KUMAR Agricultural Development and Rural Transformation Centre … OF...
IMPACT OF MGNREGA ON WAGE RATE, FOOD SECURITY AND RURAL URBAN MIGRATION: A
CONSOLIDATED REPORT
PARMOD KUMAR
Agricultural Development and Rural Transformation Centre Institute for Social and Economic Change
Bangalore- 560 072
December 2013
Project Leader: Prof. Parmod Kumar
Project Team:
1. Ms. Prema Kumari
2. Ms. Neelambari Dasgupta
3. Dr. I Maruthi
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Chapter 1
Introduction
1.1 Introduction
A majority of people in India live in villages and about 50 per cent of the villages have
very poor socio-economic conditions. Since the dawn of independence, concerted efforts
have been made to uplift the living standards of rural masses. Rural development as an
integrated concept of growth and poverty elimination has been of paramount concern in
all the consequent five year plans. The Ministry of Rural Development, Government of
India, runs a number of schemes and programmes with the principal objective of enabling
rural people to improve the quality of their lives. In the process of planned development,
it has been realized that a sustainable strategy of poverty alleviation has to be based on
increasing the productive employment opportunities in the process of growth itself. In the
Sixth Five Year Plan emphasis was laid on employment generation and poverty
alleviation. To generate additional gainful employment in rural areas, Ministry of Rural
Development, Government of India launched National Rural Employment Programme
(NREP) in October 1980. Under this programme, an outlay of 1620 crores was
provided which was to be shared equally between the Centre and the States. The creation
of durable assets was an important objective of this programme.
The total employment generated and expenditure incurred under the NREP is depicted in
Table 1.1. However, this programme was not targeted and therefore, it is not known as to
how much of out of total expenditure was directed towards those who were landless and
the poorest among the poor. To this extent, the programme apparently lacked a direct
focus on the target-group population for whom it was meant. The programme, however,
had a substantial impact in terms of stabilization of wages in the rural areas, containing
prices of foodgrains and creation of a wide variety of community assets which could be
expected to help raising the levels of living of the rural population.
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Table 1.1: Performance of NREP in the Sixth and Seventh Five Year Plans
Source: Planning commission, GOI (2001)
On 15th
August 1983, Rural Landless Employment Guarantee Programme (RLEGP), a
programme to supplement NREP was introduced by the Ministry of Rural Development,
Government of India, with the objective of improving and expanding employment
opportunities for the rural landless. The prime objective of this programme was providing
guaranteed employment to at least one member of every landless household up to 100
days in a year and creating durable assets for strengthening infrastructure so as to meet
the growing requirements of the rural economy. An outlay of 500 crores to be fully
financed by the Central Government was provided under this programme under the Sixth
Five Year Plan.
Table 1.2: Performance of RLEGP in the Seventh Five Year Plans
Year
Resource
availability
( crores)
Expenditure
( crores)
Employments
generation
(in million
man days)
Man-day
cost ( )
Wage:
Material
ratio
1985-86 580.35 453.17 247.58 18.30 57.43
1986-87 649.96 635.91 306.14 20.77 57.43
1987-88 648.41 653.53 304.11 21.49 58.42
1988-89 761.55 669.37 296.56 22.57 58.42
Source: Planning commission, GOI (2001)
Year
Resource
availability
( crores)
Expenditure
( crores)
Employments
generation (in
million man days)
Man-
day cost
( )
Wage:
Material
ratio
1980-81 346.32 219.03 413.58 5.25 -
1981-82 460.37 317.63 354.52 9.04 62:38
1982-83 540.15 394.76 351.20 11.24 69:31
1983-84 535.59 392.22 302.76 13.08 62:38
1984-85 590.68 519.14 352.31 14.74 60:40
1985-86 593.08 531.95 316.41 16.81 60:40
1986-87 765.13 717.77 395.39 18.15 60-40
1987-88 888.21 788.31 370.77 21.26 59:41
1988-89 845.68 901.84 394.96 22.83 57:43
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The implementation of the programme was entrusted to the States/Union Territories, but
they were required to prepare specific projects for approval by a Central Committee.
During (1985) the Central Committee approved 320 projects with an estimated cost of
906.59 crores. The target for employment generation in 1983-84 and 1984-85 was fixed
at 360 million mandays against which 260.18 million man-days of employment was
actually generated. Experience in the Sixth Plan in certain states indicated that if
integrated projects are developed, this stipulation would still allow substantial scope for
productive works to be planned within a decentralized framework at the district level.
Hence both the projects viz., NREP and RLEGP were merged as Jawahar Rozgar Yojana
(JRY) in the last year of 7th
Five Year Plan. JRY was launched with a total allocation of
2600 crores to generate 931 million mandays of employment. The primary objective of
the programme was generation of additional employment on productive works which
would either be of sustained benefit to the poor' or contribute to the creation of rural
infrastructure. Under this programme, Centre's contribution was 80 per cent while States’
share was 20 per cent. The JRY was implemented in all villages in the country.
It was reported that Panchayats were not above procedural violations, i.e., use of private
contractors. Under the program, projects were to be executed by the Government
Ministries and agencies without the employment of contractors so that full benefit of
wages should go to the workers. The payments to contractors constituted at least 10 per
cent of the cost of project. Clear-cut guidelines were absent regarding the criteria to be
used by the Panchayats in selecting the rural poor. It was not enough only to indicate that
the JRY was targeted at the poor. In practice, the executing agencies did not follow any
list of workers belonging to poor families needing employment (Islam, 2005).
Central assistance was provided to the states on the basis of proportion of the rural poor
in a state/UT to the total rural poor in the country. Of the total allocations at the state
level, six per cent of the total resources were earmarked for housing under the Indira
Awaas Yojana (IAY), which were allotted to the Scheduled Castes and Scheduled Tribes
and freed bonded labour. In addition, 20 per cent were earmarked for Million Wells
Scheme (MWS). In fact, this scheme was launched as a special feature both under NREP
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and RLEGP in 1988-89. The objective was to provide open wells free of cost to poor
SC/ST farmers in the category of small and marginal farmers and to free bonded
labourers. However, where such wells were not feasible, the amounts allotted was to be
utilized for other schemes of minor irrigation like irrigation tanks, water harvesting
structures and also for development of lands of SCs/STs and freed bonded labourers
including ceiling surplus and bhoodan lands. A maximum of 2 per cent of JRY funds
were to be spent as administrative costs inclusive of any additional staff.
The Employment Assurance Scheme (EAS) was launched on 2nd
October, 1993 in 1775
identified backward blocks situated in drought prone, desert and tribal and hill areas in
which the revamped public distribution system was in operation by District Rural
Development Agency (DRDA). Subsequently, the scheme was extended to additional
blocks which included the newly identified Drought Prone Area Programme (DPAP) /
Desert Development Programme (DDP), Modified Area Development Approach
(MADA) and blocks having a larger concentration of tribal and flood prone areas of Uttar
Pradesh, Bihar, Assam and Jammu & Kashmir. In addition, 722 non-EAS blocks
previously covered under second stream of Jawahar Rozgar Yojana (JRY) were also
brought under the EAS. The EAS has since been universalized to cover all the rural
blocks in the country with effect from 1.4.1997.
The main objective of the EAS was to provide about 100 days of assured casual manual
employment during the lean agricultural season at statutory minimum wages to all
persons above the age of 18 years and below 60 years who needed and sought
employment on economically productive and labour intensive social and community
works. Though, the creation of community assets had important spin offs for rural
poverty and development, the impact of these programmes on employment and income
was limited. The universalisation of the scheme severely eroded its basic objective of
providing assured employment in areas of extreme poverty and chronic unemployment.
Allocations were based on a fixed criterion that did not specifically provide for regionally
differentiated needs. This led to a very thin spread of resources across the country. As a
result, even in the poorer regions, employment was provided for only 31 days (Panning
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Commission, 2001). In many states, the works taken up were not labour-intensive. Cases
of bogus reporting and fudged muster rolls were reported. The efficacy of the programme
was also affected by faulty project selection and the absence of a coherent plan which
integrated EAS projects in a long-term development strategy.
It was however felt that a stage has come when the development of village infrastructure
needs to be taken up in a planned manner. This could best be done by the village
Panchayats who are closest to the ground realities and who can effectively determine
their local needs. Accordingly, the government had restructured the existing wage
employment programme namely Jawahar Rozgar Yojana (JRY) and Employment
Assurance Scheme (EAS). The new programme, namely Jawahar Gram Samridhi Yojana
(JGSY) was dedicated entirely to the development of rural infrastructure at the village
level and implemented by the village Panchayat. This programme came into effect from
1st April 1999. The primary objective of JGSY was creation of demand driven
community village infrastructure including durable assets at the village level and assets to
enable the rural poor to increase the opportunities for sustained employment. The
secondary objective was generation of wage employment for the unemployed poor in the
rural areas. JGSY was least understood by the target groups and was seldom in its goal-
oriented implementation. So, JGSY lasted only for a short time which was being merged
into a new scheme, the Sampoorna Grameen Rozgar Yojana (SGRY).
In practice, there was little difference between the JGSY and EAS in terms of both
objectives and implementation failures, with the only sustentative difference being
administrative. The JGSY was implemented by village level institutions (PRIs) while the
EAS relied on the State Administrative apparatus. In September 2001, EAS and JGSY
were merged into a new scheme, the Sampoorna Grameen Rozgar Yojana (SGRY). The
objectives of SGRY were to provide additional wage employment in rural areas and also
food security, alongside the creation of durable community, social and economic assets
and infrastructure development. The SGRY also encompasses all food for work programs
in the country since it includes a special component for augmenting food security through
additional wage employment in calamity affected rural areas. Several problems in
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implementation were highlighted. It was documented that wages were too high in
relatively prosperous villages, leading to the use of migrant labour and machinery, while
in poor villages the wages were much lower than prevailing rates leading to crowding-out
of the really poor. Other problems were also observed such as flagrant violation of
government guidelines, including use of contractors and intermediaries, excessive
reliance on labour displacing machinery etc., (Deshingkar and Johnson, 2003).
The Planning commission identified 150 most backward districts of the country on the
basis of prevalence of poverty indicated by SC/ST population, agricultural productivity
per worker and agricultural wage rate. Most of them happen to be tribal districts. There
was a need for substantial additional investment in these districts to convert their surplus
labour into required capital formation solving livelihood issues. The National Food for
Work Programme (NFFWP) started on January 2000-01 by Ministry of Rural
Development, Government of India, was such an attempt. Substantial resources in the
form of cash and foodgrains were being provided under the programme to generate
additional supplementary wage employment and to create productive assets in these 150
identified districts. Through the programme, an attempt was made to coordinate among
different on-going schemes which had wage employment potential, so that the focused
approach provides a solid base for the districts to take-off on their own. The major
objective was to provide additional resources apart from the resources available under the
Sampoorna Grameen Rozgar Yojana (SGRY) to 150 most backward districts of the
country so that generation of supplementary wage employment and provision of food-
security through creation of need based economic, social and community assets in these
districts was further intensified. Wages under SGRY and NFFWP Programmes were paid
partly in cash and partly in the form of foodgrains valued at BPL rates. It was assumed as
an excess flow of foodgrains for the poor through the wage employment schemes.
National Rural Employment Guarantee Act (MGNREGA), now Mahatma Gandhi
National Rural Employment Guarantee Act (MGNREGA from October 2, 2009) was
passed in the year 2005. The ongoing programmes of Sampoorn Grameen Rozgar Yojna
and National Food for Work Programme were subsumed within this programme in the
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200 of the most backward districts of the country. First, it ensured the legal right to work
for a hundred days to poor people whoever is willing to work at a minimum wage rate,
particularly in the rural areas, which in turn would reduce the flow of rural to urban
migration (Dreze et al. 2006). In addition to this, another important objective of the Act
has been to strengthen the PRIs. MGNREGA addresses mainly to rural poor and their
fundamental right to work with dignity. It is noted from the above mentioned
employment programmes that MGNREGA envisaged a paradigm shift from all precedent
Wage Employment Programmes (WEP) operating in the country since 1980. Earlier
WEP were allocation based whereas MGNREGA is demand-driven. MGNREGA has
extensive in-built transparency safeguards. The act is designed to offer employment
within 15 days of application of work, if the employment cannot be provided by the
authorities then daily unemployment allowance has to be paid.
Unique features of MGNREGA are: time bound employment guarantee and wage
payment within 15 days; Incentive-disincentive structure to the state governments for
providing employment as 90 per cent of the cost for employment provided is borne by the
Centre while payment of unemployment allowances are borne by state governments (at
their own cost); and emphasis on labour intensive works prohibiting the use of
contractors and machinery. The Act mandates 33 per cent participation for women. The
key processes in the implementation of MGNREGA are the following:
Adult members of rural households submit their name, age and address with photo to
the Gram Panchayat.
The Gram Panchayat registers households after making enquiry and issues a job card
which contains the details of adult member enrolled and his/her photo.
Registered person can submit an application for work in writing (for at least fourteen
days of continuous work) either to Panchayat or to Programme Officer.
The Panchayat/Programme Officer will accept the valid application and issue dated
receipt of application, letter providing work will be sent to the applicant and also
displayed at Panchayat Office.
The employment will be provided within a radius of 5 kilometers and if it is above 5
kilometers extra wage will be paid.
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If employment under the scheme is not provided within fifteen days of receipt of the
application daily unemployment allowance will be paid to the applicant.
The cost sharing is done as: Central Government 3/4th
and State Government 1/4th
.
MGNREGA was implemented in three phases:
I Phase - notified in 200 districts with effect from February 2nd
2006
II Phase - extended to 130 districts in the financial year 2007-08 (113 districts
from April 1st 2007 and 17 districts of Uttar Pradesh were notified with effect
from May 15th
2007)
III Phase - remaining districts in all the States/UTs were notified from April 1st
2008.
1.2 Review of Literature
The recent literature on various aspects of MGNREGA functioning is expanding vary fast
as the programme encompasses the whole of the rural India and spends a huge budget
compared to any other social welfare programme. When compared to preceding
programmes like the NFFWP, the MGNREGA has generated roughly three to four times
the number of work days. The Programme has therefore succeeded in providing the much
needed wage employment to the rural masses. Among many recent studies focusing on
the implementation and operational details of MGNREGA, the important ones are Aiyar
and Samji (2006), Bhatia and Dreze (2006), Chakraborty (2007), Comptroller and
Auditor General (2008), Ambasta et al. (2008), Jha et.al. (2009), Gopal (2009), Khera
and Nayak (2009), Adhikari and Bhatia (2010), Jha et al (2011), Shankar et al (2011),
Dutta et al (2012) and so on.
Aiyar and Samji (2006) argue for strengthening social audit in order to improve the
effectiveness of MGNREGA Programme. They argue that the earlier wage employment
programmes failed due to the common problems of ineffective targeting, leakages and
poor quality asset creation, etc. They emphasized for a clear separation of functions
across tiers of government. The Gram Panchayat (GP) along with Zila Panchayat should
be responsible for all operational activities whilst the state government should take
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overall monitoring and regulation of the process. According to them such a system
allows the GP flexibility to respond effectively to citizen needs and priorities without
depending on any external authority. It also prevents tiers of government from passing
responsibility for performance on to one another, as is common in the present system.
Secondly, the citizen must play the central role in monitoring the provision of public
services. In such a system the regular flow of information would be crucial as well as the
enhanced ability of citizens to exercise enforceability through tools such as social audits
and community score cards will have to play a major role.
The Comptroller and Auditor General (CAG) carried a review of MGNREGA scheme in
which it found many loopholes in the implementation of MGNREGA in various parts of the
country (CAG, 2008). In 26 states, 558 village panchayats were identified for the survey
spread over 68 districts and 141 blocks. The study observed that in as many as 70 per cent of
villages checked, there were no proper records available on number of households who
demanded jobs and the actual number of people who benefited from the job guarantee
scheme. In many cases it was found that jobs were allocated on "verbal basis" and no
documentation was available with the village body. As per the survey findings, in 340
villages in 24 states, no meetings were conducted for identifying the households to be
registered under MGNREGA. No door-to-door survey was conducted in these villages to
identify persons. Some households were not registered despite submitting applications on the
ground that their names did not feature in the BPL survey list.
Chakraborty (2007) presents a budgetary appraisal of MGNREGA. The study observed
that the existing institutional arrangement in poorer states was not good enough to
implement the MGNREGA in an effective manner. Only half of the total available funds
were utilised and the utilisation ratio was particularly low in poorer states. There was an
urgent need for both vertical and horizontal coordination across levels of governments
within the states. The paper suggests that the devolution of responsibilities and strict
accountability norms would accelerate capacity building at the level of the panchayat and
the scheme could effectively function as a demand-driven one. Keeping the spatial
dimension of the implementation in mind, the importance of the smooth flow of funds for
implementation of projects in accordance with the demand, capacity building at the
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village level, right to information to enable social audits effectively, accountability of
functionaries and an effective grievance redressal mechanism assume critical importance.
The paper further elaborates that better coordination by the levels of governments with
the gradual expansion of the programme covering more districts would lead to increased
outlays and one would hope that the programme effectiveness will increase with
experience, particularly in poorer states.
Dreze et al. (2008) in their evaluation study in Chhattisgarh found MGNREGA
functioning far better than the other employment programmes. They observed that there
was virtually no check on the embezzlement of NFFWP funds in Surguja district of
Chhattisgarh. The situation was so bad that it was constrained to describe NFFWP as
“Loot for Work Programme”. In the same district, it was interesting to hear from a wide
range of sources where the enactment of MGNREGA had led to a steep decline in the
incidence of corruption. This was borne out by the muster roll verification exercises. In a
random sample of nine works implemented by gram Panchayat, it was found that 95 per
cent of the wages that had been paid according to the muster rolls had actually reached
the labourers concerned. A similar exercise conducted in Koriya, the neighboring district,
led to similar estimates of “leakages” in the labour component of MGNREGA by only 5
per cent or so. In Jharkhand, detailed muster roll verification of MGNREGA works in
five randomly selected gram Panchayat of Ranchi District suggested leakages of around
33 per cent. In Jharkhand, there was evidence of a gradual retreat of corruption compared
with earlier years when it was not uncommon to find that entire muster rolls had been
manufactured from top to bottom. Another study by Bhatia and Dreze (2006) highlights
the weaknesses in the implementation of the project in Jharkhand.
In a similar study, Afridi (2008) discussed the nature and characteristics of monitoring
the MGNREGA‘s implementation with a focus on the community control mechanisms
existing in the two pioneering states of Rajasthan and Andhra Pradesh. Having a close
look on the way social audit was held he pointed out that conduct of audits in villages
without the support of NGOs and members of civil society is wishful thinking. He found
that CSOs had taken a lead role in Rajasthan in generating awareness and participation of
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rural people with a bottom up approach, while in Andhra Pradesh the Government had
taken the lead role in initiating this process and co-opted individuals from
nongovernmental institutions into the process which was more of a top-down approach.
The study suggested synthesizing both the models for more effective monitoring of
MGNREGA activities.
Jacob (2008) observed that the MGNREGA programme has immense potential to
improve the gap between urban and rural India and lead to rural development in terms of
basic infrastructure like roads, in terms of agricultural productivity from irrigation works.
It also provides a stable income for workers; their income graph would be much smoother
with the MGNREGA bolstering their earnings in the 100 days between agricultural
seasons. The efforts made by the Villupuram district (of Tamil Nadu) authorities though
efficient functioning of MGNREGA, although there still might be some irregularities in
the implementation should be used as a model in other regions to help realize the
potential of this Act.
In another study (ISWSD, 2008) observed that both in Kerala and Karnataka there were
strong demand from the workers for increasing the work days to at least 200 per
household. However, in both the states, there were few complaints regarding non-
payment of minimum wages. In gross violation of the Act, workers at many MGNREGA
worksites (e.g., in Uttar Pradesh and Jharkhand) were earning less than the minimum
wages.
Ambasta et al (2008) evaluating the performance of MGNREGA in its first two years
highlights major issues confronting its implementation. The study found that the lack of
trained professionals for time bound implementation, under staffing and delay in
administration, lack of people‘s planning, poor quality of works and assets created,
inappropriate schedules of rates, unnecessary bureaucratic interventions and mockery of
social audits were hindering the implementation process. The authors suggested for hiring
a large number of full-time and fully trained professionals at Gram Panchayat level, while
strictly enforcing their accountability to PRIs. Better use of information technology,
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mandating a role for civil society organizations (CSOs) to work as support agencies for
PRIs in MGNREGA planning, implementation and social audit were some of their major
suggestions for improving the functioning of MGNREGA.
Khera (2008) observed that the role of farmer‘s organization was very effective in
making MGNREGA perform better. Her study on the Jagrut Adivasi Dalit Sangathan, a
farmer‘s organization with a membership of 3500 families in Madhya Pradesh observed
that the level of employment in the Sangathan areas was as high as 85 days per household
per year, and nearly half of all working households had got 100 days of work. Aiyar and
Samji (2009) document the Andhra Pradesh experience of institutionalizing social audits
into the implementation of the MGNREGA and use it to analyze the social audit process.
The paper draws on empirical work aimed at measuring the effectiveness of social audits
conducted in Andhra Pradesh between March and December 2007. The paper offers
some interesting insights in to the effectiveness of regular, sustained social audits.
Emerging empirical evidence on the social audits suggest social audits in fact have a
significant and lasting effect on citizen’s awareness levels. Moreover, it demonstrates that
it has some effects on implementation processes and in this process, ability to engage
with local officials. Crucially, it highlights some important lessons on how to ensure long
term effects of the audit. According to findings of the paper social audits are most
effective when they are conducted regularly, have inbuilt feedback mechanisms and are
undertaken in partnership with the state to ensure immediate, perceivable grievance
redressal. These lessons are important for any state government or civil society
organization that wants to undertake a social audit and develop a strategy for their
conduct.
Khera and Nayak (2009) undertook a study on perceptions of women workers regarding
the importance of the MGNREGA and to find out to what extent the full potential of the
programme has been realized by taking samples from Araria and Kaimur (Bihar); Surguja
(Chhattisgarh); Palamau and Koderma (Jharkhand); Badwani and Sidhi (Madhya
Pradesh); Dungarpur and Sirohi (Rajasthan); Sitapur (Uttar Pradesh). The study found
that the participation of the sample women workers varied largely across the selected
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study areas in various states. The overall women participation rate was 32 per cent
whereas the same in Rajasthan was as high as 71 per cent. The women participation rate
in Madhya Pradesh, Chhattisgarh, Jharkhand, Bihar and Uttar Pradesh was respectively ,
44 per cent, 25 per cent, 18 per cent, 13 per cent and 5 per cent as compare to stipulated
female participation rate of 33 per cent as per the MGNREGA guideline. Of the total
sample, more than 2/3rd of the sample workers stated the MGNREGA had helped them
avoid huger, while 57 per cent stated avoid migration. A majority (79 per cent) of women
workers were found to collect and keep their own wages. Major barriers to women's
participation were tenacious social norms, illegal presence of contractors, lack of
childcare facilities, and delayed payment of wages.
Jha et al. (2009) use primary data of 900 households to examine the extent of elite
capture in MGNREGA in Andhra Pradesh and Rajasthan. They observed that area of land
owned is a negative predictor of MGNREGA participation in Rajasthan, but the situation
is reversed in Andhra Pradesh indicating poor targeting due to possibly elite capture in
that state. In an another study Jha et al (2011) analyse the nutritional impact of
MGNREGA wage, non MGNREGA income and Public Distribution System (PDS)
participation. The study concludes that MGNREGA affects nutritional status of
households with respect to two macro nutrients, namely calories and protein as well as
various micronutrients. Assessing the link between information, access and delivery of
MGNREGA in Andhra Pradesh, Maharashtra and Rajasthan, Shankar et al (2011)
observed that information increases the propensity of access by those who are not
MGNREGA’s primary target, whereas, lack of information unambiguously disadvantages
the poor.
According to a NCAER-PIF study (Sharma et al, 2009) there were two possible outcomes
of MGNREGA, viz., (i) slightly improved share of ST households in employment and (ii)
the Act outshined the earlier Programme as for as participation of women was concerned.
The range of wages realized by workers under MGNREGA varied from state to state, but
in a large majority of states the average wages were little higher compared to the
minimum wages. However, the official estimates of wages realized by workers were
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generally inflated as wages received by workers were much less than what was shown in
the official documents. The other anomalies they pointed out include no compensation
being paid to labourers in cases involving delayed payments beyond the stipulated period
of 15 days and non-payment of unemployment allowances. Cases of corruption, fudging
in muster rolls, discrepancies in work days and payments were also reported. More than
50 per cent slippage in the execution of works undertaken was reported. Works and their
implementation had also suffered due to anomalies in the selection of works, poor
execution, inflated estimates and inadequacies in measurement, cost overruns and delays
in release of funds by states.
Gaiha et al (2009) tried to construct an intuitive measure of the performance of the
MGNREGA. Their paper focused on whether excess demand responds to poverty and
whether recent hikes in MGNREGA wages were inflationary. Their analysis confirms
responsiveness of excess demand to poverty. They observed that apprehensions
expressed about the inflationary potential of hikes in MGNREGA wages were confirmed.
The higher MGNREGA wages were likely to undermine self-selection of the poor in the
programme. They suggested in order to realise the poverty reducing potential of this
scheme, a policy imperative was to ensure a speedier matching of demand and supply in
districts that were highly poverty prone, as also to avoid the trade-offs between poverty
reduction and inflation.
Kareemulla et al (2010) evaluated the scheme in four states, viz., Rajasthan, Andhra Pradesh,
Karnataka and Maharashtra with a specific focus on desirability, quality and durability of
assets created and the programme’s effects on the livelihood generation of beneficiaries. The
study found that a wide variety of works were taken up under the scheme in the study
districts including works on soil and water conservation structures and rural roads, which
matched the requirements of the people but the quality and maintenance of assets need more
attention in the coming years so that investment made would not go futile. They concluded
that scheme was achieving its primary objective of employment generation but the assets
created were generally seen as a by-product in the study areas.
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Adhikari and Bhatia (2010) argued that the direct transfer of wages into worker's bank
account was a substantial protection against embezzlement and control of corruption.
Respondents had a fairly positive attitude towards bank payments, and they showed interest
in learning how to use the banking system. However, poor record-keeping, inability to cope
with mass payment of MGNREGA wages, large distance to the nearest bank or post office
caused hardship to the MGNREGA workers. Their findings revealed positive picture of the
bank payments, but they also exposed the limited capacity of the banking and post office
system in fighting corruption.
Dey (2010) looked at the performance of the MGNREGA from three perspectives: it
examined the targeting aspect of the programme, the efficiency of the implementing PRI
bodies and the impact of the program on various outcomes at household level. The study
was based on primary data collected from 500 randomly selected households, 2249
individuals and 70 schemes located in 13 Gram Panchayats in Birbhum District of West
Bengal. The study observed that in Birbhum District, the programme was likely to be
accessed by poorer households, defined in terms of land holding, monthly per-capita
income and other household related characteristics. At the same time there was a clear
and substantial impact of left political inclination in terms of enabling access to a greater
number of days of work under the scheme. In terms of the efficiency impact, the analysis
revealed a clear violation of the formal clauses and the spirit of the MGNREG Act and
thereby undermining the potential of the programme in terms of providing a safety net.
The study found no statistically significant impact on economic outcomes at household
level but there existed a statistically significant relation between reduction of stress
related to joblessness and access to the MGNREGA. The author observed that while the
MGNREGA may not be creating any new employment and may indeed be substituting
for existing employment opportunities, the scheme was still considered valuable as it
offered better working conditions.
The study by Harish et al (2011) evaluates the impact of MGNREGA on income
generation and labour supply in agriculture in one of the districts in central dry zone of
Karnataka. The results of the study showed that for the participating families the numbers
of days worked in a year with the implementation of MGNREGA programme had
16
increased significantly to 201 days, reflecting 16 per cent increase. The authors observed
that MGNREGA contributed to increase in the consumption expenditure reducing the
debt burden of the beneficiaries. Regression analysis carried out to find out the
determinants of participation revealed that gender, education and family size of the
workers were the significant factors influencing the worker’s employment under the
Program. The increase in income was to the tune of 9.04 per cent due to additional
employment generated from MGNERGA. In the total income, the contribution of
agriculture was the highest (63%), followed by non-agricultural income (29%) and
MGNREGA income (8%). Implementation of MGNERGA works has led to labour
scarcity to the tune of 53 per cent and 30 per cent for agriculture operations like weeding
and sowing, respectively. There was a decline in area for labour intensive crops like
tomato and ragi to the extent of 30 per cent due to MGNERGA implementation.
Basu (2011) examines labor and output market responses to MGNREGA and determine
the optimal compensation to public work employees consistent with the objectives of
productive efficiency in agriculture and welfare maximization of the laborers. By
accounting for the seasonality in agricultural production and the institution of permanent
labor contracts, the paper shows that technological change and productivity increases in
MGNREGA programs tend to make laborers better-off as compared to a direct increase
in the wage paid at the relief program. Further, an optimal wage that maximizes expected
agricultural output may be in conflict with the one that maximizes the expected lifetime
utility of laborers indicating trade-offs between different policy objectives. Further, in the
event of high elasticity of MGNREGA with respect to permanent laborers, a specific
subsidy targeted towards the hiring of permanent laborers would best serve the twin
objectives of increased expected agricultural productivity and increased welfare for the
laborers. The paper concludes that MGNREGA by introducing contestability in the
agricultural labor market can yield a host of interesting implications for the wage and
employment patterns of the rural poor.
Mukherjee and Sinha (2011) using a theoretical model analyzed the impact of
MGNREGA scheme on rural labour market; income of the poor households; and overall
17
agricultural production. The paper finds that the income from MGNREGA alone can be a
substantial part of the target income of the poor. The poor may exhibit a backward
bending supply curve of labour which may lead to an aggregate reduction in agricultural
output. This adverse production effect could happen even when the MGNREGA
activities lead to a moderate improvement in agricultural productivity. A crucial
dimension of the rural labour market is the target income of the poor. This target income
is the root cause of the backward bending supply curve of labour. So the policy focus
should be to increase this target income by creating more market access and opportunities
for the poor households and improving their standard of living. To enhance the
opportunities for the poor the policy should be inclusive and multipronged. The target
income may be enhanced by creating opportunities and market access from multiple
dimensions and not just an income generating scheme like MGNREGA that can help to
improve the situation of the poor households.
Berg et al (2012) test the impact of the MGNREGA on agricultural wages using monthly
wage data from the period 2000-2011 for a panel of 249 districts across 19 Indian states.
They observed that on average MGNREGA boosts the real daily agricultural wage rates
by 5.3 per cent. It takes 6 to 11 months for an MGNREGA intensity shock to feed into
higher wages. The wage effect appears to be gender neutral and biased towards unskilled
labour. They found it was positive across different implementation stages and months and
remained significant even after controlling for rainfall; district and time fixed effects; and
phase-wise linear, quadratic, and cubic time trends. They argue that since most of the
world’s poor live in rural areas, and the poorest of the poor are agricultural wage
labourers, rural public works constitute a potentially important anti-poverty policy tool.
Dutta et al (2012) used National Sample Survey (NSS) data for 2009-10 to verify the
guarantee of employment at the stipulated wage rates to the households seeking employment
under the Act. They observed considerable un-met demand for work in all states under
MGNREGA. The authors confirm that poorer families tend to have more demand for
work expectations on the scheme and that despite the un-met demand the self-targeting
mechanism allows it to reach relatively poor families and backward castes. The extent of
18
the un-met demand is greater in the poorest states, ironically where the scheme is needed
most. Labor-market responses to the scheme are likely to be weak. The scheme is
attracting poor women into the workforce, although the local-level rationing processes
favor men. The authors although find a significant negative correlation between the extent
of rationing and the wage rate in the casual labor market relative to the wage rate on the
scheme. However, the correlation vanishes when the level of poverty was introduced as a
control factor. Poorer states tend to see both more rationing of work on the scheme and
lower casual wages, possibly due to a greater supply of labor given the extent of rural
landlessness.
Imbert and Papp (2012) estimated the impact of MGNREGA on wages and employment
using NSS employment and unemployment cross sectional data. They used quinquennial
surveys and as well as thin round surveys starting from 60 round up to 66th
round. The
authors found that MGNREGA increases public works employment by 0.3 person-days
per month. They further observed that casual wage income of the workers increased by
4.5 per cent. Liu and Barrett (2013) using 2009-10 NSS data, analysed patterns of job-
seeking, rationing, and participation in the MGNREGA. At the national level, they found
that the self-targeting design of MGNREGA leads to greater rates of self-selection into
the programme by poorer and Scheduled Tribe or Scheduled Caste households. However,
the administrative rationing of MGNREGA jobs was not pro-poor but exhibited a sort of
middle class bias. At the state level, roughly half of 27 states exhibited rationing and
participation profiles that signal effective pro-poor targeting; the other half struggled to
avoid high rates and regressive patterns of administrative rationing of jobs to which the
poor had a legal right. They argued that households near the poverty line were more
likely to receive the jobs they sought than were the poorer households, although those in
the upper reaches of the expenditure distribution were least likely to secure MGNREGA
jobs. They further observed that MGNREGA fares less well in reaching poor female-
headed households, due both to self- selection and rationing effects. Male headed
households were more likely to seek and receive MGNREGA jobs over most of the per
capita expenditure distribution. According to them there was room for improvement and
perhaps much to be learned from an in-depth comparative analysis of MGNREGA
19
programme implementation across states that had demonstrated greater or lesser success
in targeting the poor with job opportunities.
Anderson et al (2013) suggest the role of Unique Identification (UID) in the functioning
of MGNREGA and how this new system can bring better efficiency in its functioning and
they also suggest to use control group methodology for testing the efficiency of UID
system in improving MGNREGA. The new UID system will enable payments to go
through the banking system. Bank accounts for MGNREGA workers will be linked to the
unique biometric id. As a result, the actual transfer of payments will immediately reach
the hands of who it is intended for. This should drastically reduce the inherent corruption
in the current system and increase the amounts and reliability of payments to the workers.
Using an experimental approach, it would be possible to directly identify the effects of
introducing UID on the performance of MGNREGA programs. One needs to compare
outcomes in a designated “treatment” group compared to a “control” group. In the
treatment group, individuals will receive their MGNREGA payments through UID. In the
“control” group, individuals will continue to receive their MGNREGA payments as they
do now. Comparing outcomes across these two groups, will inform us directly on the
impacts of introducing UID on MGNREGA payments.
The MGNREGA Scheme has high expectations in terms of employment generation,
alleviation of poverty, food security, halting migration and overall rural development. As
the scheme has already completed seven years of its functioning, there is a need for a
study to evaluate the scheme for its impact on rural poor. Based on this background the
study is conceptualized with the following objectives:
1.3 Main Objectives of the Study
1. Measure the extent of manpower employment generated under MGNREGA, their
various socio-economic characteristics and gender variability in implementing
MGNREGA since its inception in the selected states.
2. To compare wage differentials between MGNREGA activities and other wage
employment activities.
20
3. Effect of MGNREGA on the pattern of migration from rural to urban areas.
4. To find out the nature of assets created under MGNREGA and their durability.
5. Identification of factors determining the participation of people in MGNREGA
scheme and whether MGNREGA has been successful in ensuring better food security
to the beneficiaries.
6. To assess the implementation of MGNREGA, its functioning and to suggest suitable
policy measures to further strengthen the programme.
1.4 Methodology and Data Sources
The study is based on both primary and secondary data. Primary data was collected from
the selected villages and households in 16 states as per the guidelines of the Ministry.
From the each selected state, five districts were selected, one each from the north, south,
east, west and central locations of the state. From each districts, two villages were
selected keeping into account their distance from the location of the district or the main
city/town. One village was selected from the nearby periphery of around 5 kilometers of
the district/city head- quarters and the second district was selected from a farthest
location of 20 kilometers or more than that. From each selected village, primary survey
was carried out on 20 participants in MGNREGA and 5 non-participants working as
wage employed. In this fashion, from each state, 10 villages were selected and a total
number of 250 households were surveyed in detail with the help of structured household
questionnaire. In this way around 200 participants and 50 non participants were selected
from each state and data was collected in 16 states. The total sample consists of 3166
participants and 839 non participants. The selected states were, Karnataka, Andhra
Pradesh and Kerala in the South, Himachal Pradesh, Uttar Pradesh, Haryana and Punjab
in the North, Madhya Pradesh and Chhattisgarh in the Central, Maharashtra, Gujarat and
Rajasthan in the West, Bihar, and West Bengal in the East and Sikkim and Assam in the
North-east. The details of the selected districts (falling in different phases) for the study
and the number of participants and non participants selected in each state and the name of
the AERCs carrying out the study is provided in Annexure II.
21
For the selection of participant households, a list of all beneficiaries (participants) in the
village was obtained from the Gram Panchayat in the village along with the information
about caste factor of the workers. After getting the list, Random Sampling Method was
adopted for selection of the participant households. Attention was given for the proper
representation of Scheduled Caste, Scheduled Tribe and Other Backward Castes. A due
representation was also given to the gender factor. For the selection of non participant
households no list existed and therefore the criterion followed for them was that these
households should not have participated in MGNREGA but constitute the similar
occupation characteristics (wage earners) and socio economic wise, caste and gender
characteristics as that of selected participant households to maintain the uniformity and to
avoid the selection bias.
While selecting the districts utmost care was given to the fact that how many districts
implemented MGNREGA in the first Phase and how many did in the second and third
Phase in order to give proper representation to all the three Phases of the MGNREGA
implementation. While selecting participants, care was also taken to select participants
belonging to different socio-economic groups (e.g., tribal area, hilly area, gender and
Backward and Scheduled Caste groups etc.). The data was collected through structured
questionnaires. The data pertain to the Reference Period of January to December
2009.
In addition to household questionnaire, a Village Schedule was also designed to capture
the general changes that have taken place in the village during the last one decade and to
take note of increase in labour charges for agricultural operations after the
implementation of MGNREGA. The village schedule also has qualitative questions
related to change in life style of the villagers taking place during the last one decade. One
village schedule in each village was filled up with the help of a ‘Group Discussion’ with
the Pachayat Members, Officials, educated and other well informed people available in
the village being surveyed.
22
1.5 Overview
The report has seven chapters including the present one which provides a glimpse of
employment programmes started in the past and provides an introduction to the
MGNREGA programme and review of literature on the studies carried out in the
literature on the functioning of the MGNREGA. It also outlines the main objectives, data
base and methodology followed in the study. The second chapter is based on secondary
data which outlines manpower employment generated in all the states during the entire
functioning of the MGNREGA programme. The chapter also discusses various socio-
economic characteristics of employment generated and projects completed in each state.
The next three chapters are based on primary household survey carried out in 16 states.
Chapter 3 presents household characteristics and income and consumption pattern of the
selected participant and non participant households. To ascertain the factors that
determine participation in MGNREGA Programme, quantitative analysis has been carried
out in this chapter using logit and OLS regressions.
Chapter 4 discusses work profile, wage structure and migration issues under
MGNREGA. This chapter specifically looks into operational issues of MGNREGA
programme, like how many participant households obtained 100 days employment, how
wage rate obtained by the participants compares with the minimum wage rate in the state,
assets created and their durability etc. Chapter 5 presents some qualitative aspects of the
functioning of the MGNREGA Programme based on the household survey data. As was
mentioned above in our field survey of the villages, we held group discussion in all the
ten villages and Chapter 6 is based on the information collected through the group
discussion in the surveyed villages. The chapter summarizes the visible impact of
MGNREGA on various aspects of village economy like changes in occupation structure,
agriculture cost and wage rate in agriculture and non agricultural sector. The last chapter
7 summarizes the main findings of the report and provides policy suggestions for further
improvement in the MGNREGA Programme.
23
Chapter 2
Manpower Employment Generated Under MGNREGA
and their Socio-economic Characteristics
2.1 The implementation of MGNREGA
National Rural Employment Guarantee Act (NREGA) now Mahatma Gandhi National
Rural Employment Guarantee Act (MGNREGA from October 2, 2009) is being
implemented in India since by legislation on August 25, 2005 by the UPA coalition
government supported by the left parties. The Act is now covering all the 28 states of the
country. The basic objective of the Act is to ensure livelihood and food security by
providing unskilled work to people through creation of sustainable assets. The mandate
of the government is to implement the Scheme in the most transparent and effective way.
Under the provisions of the Act, the State has to ensure enhancement of livelihood
security to the households in rural areas by providing at least one hundred days of
guaranteed wage employment to every household whose adult members volunteer to do
unskilled work. The Programme was started as a flagship program in 2005 by the Union
Government. In-built with various transparency and accountability measures and
provisions for social audits this Act for the first time brings the role of the state as
provider of livelihood. The Act came into effect in all the districts in all 28 States as well
as 7 Union Territories (UTs) of India from April 1st 2008.
2.2 Total employment generated and their socio economic characteristics
Table 2.1 provides the overall performance of MGNREGA in terms of numbers of days
of employment created and the number of projects completed in all states during the
current year 2013-14 (up to October end 2013). A total number of 2.3 crore households
were provided employment during the current financial year till the latest estimates were
available and a total numbers of 63 crore man-days of employment was generated
through MGNREGA during this period. Looking at the socio-economic structure of
beneficiaries, around 23 and 15 per cent was the share of Scheduled Caste and Scheduled
Tribes, respectively in the total man-days generated while women had above 55 per cent
24
share in the total employment generated. Around 44 lakh works were taken up out of
which around 10 per cent works were completed and rest 90 per cent were ongoing.
The MGNREGA programme has already completed seven financial years and now
running in to eighth year. The current financial year provides data only up to October
2013 as discussed above. In order to provide snapshot of MGNREGA work since its
inception, we used the information available on the MGNREGA website which covers
seven full financial years starting from 2006-07 up to 2012-13 and data for the current
financial year up to October 2013. Table 2.2 provides state wise statistics on numbers of
days of employment created, their socio economic characteristics and the numbers of
projects completed and ongoing. At the aggregate, 81 crore households were issued job
cards during the period from 2006-07 to 2013-14 up to October. Out of which around 35
per cent demanded employment and around 97.5 per cent of them were provided
employment. At the aggregate, around 34 crore households were provided employment
during the period 2006-07 to 2013-14 averaging around 4.5 crore households working in
MGNREGA per annum that constitutes roughly around 30 per cent of the rural
households in the country as a whole.
The states that employed more than 3 crore households during the implementation of this
programme (2006-07 to 2013-14 up to October) were Andhra Pradesh, Uttar Pradesh,
Rajasthan, Tamil Nadu, West Bengal and Madhya Pradesh. The states that provided
employment between 1 to 3 crore households included Bihar, Chhattisgarh, Jharkhand,
Assam, Odisha and Karnataka (Figure 2.1). All other states provided employment to less
than one crore households. However, the more pertinent question is how many person
days of employment were generated by different states under this programme. Figure 2.2
presents the aggregate statistics of total person days of employment generated under
MGNREGA during the period of 2006-07 to 2013-14 (up to October). A total number of
1.5 thousand crore man days of employment was generated under MGNREGA during the
above mentioned time period. Out of the total person days generated, the share of
Scheduled Castes and Scheduled Tribes was 26.9 and 22.0 per cent, respectively while
share of women in the total employment was 48 per cent (Figure 2.2 and Table 2.2).
25
Figure 2.1: Cumulative number of HH provided employment
during 2006-07 to 2013-14 (numbers in crore)
Figure 2.2: Total person days generated under MGNREGA during
2006-07 to 2013-14 (days in crore)
26
Andhra Pradesh state topped in the generation of total person days (207 crore), followed
by Rajasthan 204 crore, Uttar Pradesh 166 crore, Tamil Nadu 166 crore, Madhya Pradesh
158 crore and West Bengal 93 crore during the period of 2006-07 up to 2013-14
(October). On the other hand, richer states like Haryana and Punjab generated less than 6
crore person days during the same time period. However, the participation of
economically weaker community, viz., Scheduled Castes in per cent age of person days
worked in MGNREGA was highest in richer state like Punjab (77 per cent), Haryana (52
per cent), Uttar Pradesh (48 per cent) and Tamil Nadu (42 per cent) while Scheduled
Tribes topped in north-eastern states like Mizoram (100 per cent), Nagaland (98 per
cent), Meghalaya (93 per cent), Arunachal Pradesh (87 per cent) and Manipur (65 per
cent). The percentage of women share in MGNREGA work was highest in Kerala (91 per
cent), Tamil Nadu (79 per cent), Goa (70 per cent), Rajasthan (68 per cent) and Andhra
Pradesh (58 per cent). Women share in the work was lowest in Jammu & Kashmir (only
14 per cent), Uttar Pradesh (19 per cent) and Bihar, Arunachal Pradesh and Assam (28
per cent, each).
Figure 2.3: Numbers of days per household employment generated
under MGNREGA during 2006-07 to 2013-14
27
State wise employment performance of MGNREGA is summarized in Figure 2.3 for the
period 2006-07 to 2013-14 (up to September). The figure depicts the numbers of days of
employment provided per household every year by the MGNREGA since the inception of
the programme. At the aggregate, a total number of 45 person days of employment has
been provided under MGNREGA during the implementation of this programme whereas
the target set under the programme is 100 days of employment per household. In other
words, not even half of the set target has been achieved by MGNREGA in terms of
providing employment. Only in the year 2009-10, 54 days of employment that is slightly
above 50 per cent of the target was achieved (Figure 2.4). In the beginning years of 2006-
07 and 2007-08, a total number of 43 and 42 days of employment was generated. In the
following year slightly more around 48 days of employment was generated which went
up to 54 days in 2009-10 but again came down to 47 days in 2010-11 and further slided
down to 43 days in 2011-12 and rose to 46 days in 2012-13. In the current financial year,
only 33 days of employment has been generated so far up to the month of October 2013
which is not expected to surpass the last two years range of above 43 to 46 days.
Figure 2.4: Employment generation under MGNREGA - All India
(Number of days per household)
28
Looking at the distribution of different states (Table 2.2 and Figure 2.3) the highest
numbers of days of employment (60 to 70 days) was provided by the north-eastern states
of Mizoram, Nagaland, Tripura, Sikkim and Manipur. Among the mainland states,
Rajasthan, Madhya Pradesh and Andhra Pradesh provided between 50 to 60 days of
employment. The states that lied in the middle providing 40 to 50 days of employment
included, Chhattisgarh, Himachal Pradesh, Tamil Nadu, Karnataka, Maharashtra, Uttar
Pradesh, Jharkhand and Odisha. Among the low performing states namely, Haryana,
Jammu & Kashmir, Uttrakhand, Gujarat, Kerala and Assam only 30 to 40 days of
employment was provided. The states that lied at the bottom included Bihar (31 days),
Arunachal Pradesh, West Bengal and Punjab (28 days, each) and Goa only 25 days of
employment.
How successful the MGNREGA programme in India has been in providing 100 days of
employment to those who demanded work. While at the aggregate per household
employment provided in all the states was far less than 100 days, however, there were
some households who completed 100 days of work in MGNREGA. Table 2.2 and Figure
2.5 provide statistics on the numbers of households who availed 100 days of employment
in each state during the whole period for which MGNREGA has been in operation. Out
of the total 34 crore households working in MGNREGA during its full tenure, only 2.9
crore households completed 100 days of employment. Among states, Rajasthan provided
100 days employment to 55 lakh households, followed by Andhra Pradesh, 49 lakh
households, Tamil Nadu 45 lakh households and Madhya Pradesh and Uttar Pradesh
both 25 lakh households, each. On the opposite, the richer states like Haryana provided
only 64 thousand households and Punjab only 25 thousand households hundred days of
employment under MGNREGA since the inception of the MGNREGA programme.
It is interesting to note whereas bigger states topped in the completion of hundred days of
employment like Rajasthan, Andhra Pradesh and Tamil Nadu, the percentage of
households who completed hundred days out of the households working in MGNREGA,
it was the north-eastern states which topped in the percentage term. Around 25 per cent
households completed 100 days in Mizoram, 20 per cent in Tripura, 18 per cent in
29
Sikkim and Nagaland each, 16 percent in Rajasthan and 14 per cent in Manipur. Tamil
Nadu and Andhra Pradesh were the other states where around 10 to 13 per cent
households completed hundred days of employment. Goa, Punjab and West Bengal were
at the bottom where only less than 2 per cent households completed hundred days of
employment (Figure 2.6). At the all India aggregate, only 8.4 per cent households
completed hundred days of employment during the entire period of MGNREGA in
operation up till October 2013. This indicates inefficiency of the programme in providing
hundred days work to all household who opted for working in the MGNREGA
programme.
Figure 2.5: Number of HH provided hundred days employment during
2006-07 to 2013-14 (numbers in lakh)
30
Figure 2.6: Percentage of HH completed hundred day of employment
during 2006-07 to 2013-104
2.3 Number of projects completed and total amount spent
There are around nine specific categories of works in which MGNREGA wage earners
are employed namely, rural connectivity, flood control and protection, water conservation
and water harvesting, drought proofing, micro irrigation works, provision of irrigation
facility to land owned by SCs, STs and others, renovation of traditional water bodies,
land development and other activities approved by MORD. The percentage allocation of
works completed or on-going during the entire period of MGNREGA implementation up
to October 2013 is shown in Figure 2.7 below. Looking at different activities under which
work was done, the Water conservation was the leading activity which occupied around
24 per cent projects (completed or under progress) followed by Rural connectivity
projects 17 per cent, Provision of irrigation 14 per cent, Drought proofing (13 per cent),
Land development 10 per cent, Renovation of traditional water bodies and Micro
irrigation 6 per cent, each and Flood control 3 per cent. Other works including Rajiv
Gandhi Seva Kendra occupied around 7 per cent share among the total works completed
or undergoing during the period from 2006-07 to 2013-14 up to October (Figure 2.7).
31
State wise details of works completed/under progress are given in Table 2.3 and the total
amount spent in Table 2.4 on each programme during the implementation of MGNREGA
up to December 2012. During the entire period of MGNREGA, a total number of 1 crore
projects were completed and around 2.9 crore were ongoing. Thus, out of total 4 crore
projects taken up under MGNREGA around 30 per cent were completed and rest of 70
per cent were in progress. Total amount spent on the above projects aggregated to
1,03,204 crores on the completed projects and 1,31,880 crores on the ongoing projects
during the entire period of MGNREGA. Thus a total amount of 2,35,084 crore was
spent on the MGNREGA during around 7 and a half years of functioning of the
MGNREGA with an average of slightly less than 30 thousand crore every year.
Presenting the budget for the financial year 2013-14, the Finance Minister has allocated a
sum of 33 thousand crore for MGNREGA work during the financial year 2013-14.
Working out the total expenditure incurred per project for the completed projects it
turned out around 87 thousand per project while it was 47 thousand per project for the
ongoing works giving the combined average of 59 thousand cost per project for all
MGNREGA works undertaken so far at the aggregate.
Figure 2.7: Share of different activities in MGNREGA work
during 2006-07 to 2013-14
32
Figure 2.8 presents the numbers of works completed or on-going for each of the above
nine activities during the implementation of MGNREGA. Out of the total 4 crore projects
undertaken, around 96 lakh projects were taken for water conservation, 67 lakh for rural
connectivity, 58 lakh for provision of irrigation, 52 lakh for drought proofing, 40 lakh for
land development and 23 lakh for renovation of traditional water bodies and micro
irrigation, each and around 13 lakh for the flood control and protection. Total amount
spent on completed and on-going projects during the implementation of MGNREGA is
given in Figure 2.9 and Table 2.4. During the whole period of implementation of
MGNREGA a total amount of 75 thousand crore was spent on rural connectivity, 45
thousand crore on water conservation, 27 and 25 thousand crore on renovation of
traditional water bodies and drought proofing, respectively, 17 thousand crore on
provision of irrigation, 16 thousand crore on land development, 12 thousand crore on
micro irrigation, 11 thousand crore on flood control and around 6 thousand crore on
other activities including Bharat Nirman works. Thus, at the aggregate, a sum total of
2.35 lakh crore were spent on MGNREGA works during the entire period starting from
2006-07 up to October 2013 (Table 2.4).
Figure 2.8: Numbers of works undertaken under MGNREGA
during 2006-07 to 2013-14 (lakh)
33
Looking at the state wise numbers of works completed or on-going under MGNREGA
(Figure 2.10), Andhra Pradesh topped the list with a sum of 135 lakhs works undertaken
during the entire period of MGNREGA. Uttar Pradesh was second with 48 lakh works
followed by Madhya Pradesh with 44 lakh works. Karnataka, Rajasthan, West Bengal,
Bihar, Jharkhand and Odisha lied in the middle with numbers of projects ranging between
20 to 10 lakh. The state that lied in the lower stratum included Meghalaya, Nagaland,
Punjab, Haryana and Manipur having numbers of projects between 50 and 100 thousand
while Mizoram, Sikkim, Arunachal Pradesh and Goa had less than 50 thousand projects.
Figure 2.9: Amount spent for different activities under MGNREGA
during 2006-07 to 2013-14 (Rs thousand crore)
34
Figure 2.10: State wise number of works completed/under progress
under MGNREGA during 2006-07 to 2013-14 (lakh)
Glancing through the total budget spent on the completed and on-going projects by
different states it is indicated by the statistics presented in Table 2.4 that Uttar Pradesh
topped in the total amount spent on MGNREGA works with a total budget of 26
thousand crore. Uttar Pradesh was closely followed by Madhya Pradesh, Rajasthan and
Andhra Pradesh with almost similar amount spent at the aggregate on all projects in the
duration of MGNREGA period up to October 2013. Maharashtra, Chhattisgarh, West
Bengal, Tamil Nadu and Bihar spent slightly less amount each varying between 13 to
18 thousand crore. Nagaland, Manipur, Uttrakhand, Jammu & Kashmir, Meghalaya,
Haryana and Mizoram spent only around or less than 2 thousand crore each, while
Punjab, Sikkim, Arunachal Pradesh and Goa lied at the bottom with less than 1 thousand
crore spent by each state on MGNREGA during the period 2006-07 up to October 2013
(Figure 2.11).
35
Figure 2.11: State wise expenditure incurred on MGNREGA
during 2006-07 to 2013-14 (Rs thousand crore)
The expenditure incurred on the completed and on-going projects was not exactly similar
to that of allocation of projects in different states indicating cost differences across the
projects as well as per project cost across states. It was mentioned above that at the
aggregate per project cost of MGNREGA works for its full duration up to October 2013
was around 59 thousand per project. At the aggregate, the highest amount per project
was spent on renovation of traditional water bodies 121 thousand per project that was
closely followed by 112 thousand per project on rural connectivity. Expenditure on
flood control lied on the third place with an expenditure of 79 thousand per project.
Micro irrigation had a spending of 53 thousand per project followed by drought
proofing 49 thousand per project, water conservation 47 thousand per project, land
development 40 thousand per project and provision of irrigation 29 thousand per
project (Figure 2.12). Thus, whereas water conservation topped in the total numbers of
projects undertaken but spending on per project was much less on water conservation
compared to rural connectivity that topped among all projects not only in the total amount
spent but also amount spent per project. State wise total expenditure per project
(aggregate of all categories) is depicted in Figure 2.13 below. Highest amount per project
was spent in Manipur, 297 thousand followed by Nagaland ( 245 thousand), Mizoram
36
( 269 thousand), Tamil Nadu ( 255 thousand), Assam ( 191 thousand) and
Maharashtra ( 160 thousand). The states that lied at the bottom in spending per project
were Andhra Pradesh ( 18 thousand), Gujarat ( 41 thousand), Karnataka and Goa (
48 thousand), Kerala ( 49 thousand), and Uttar Pradesh ( 54 thousand) only.
Figure 2.12: Amount spent under MGNREGA (Rs thousand per project)
during 2006-07 to 2013-14
Figure 2.13: State wise amount spent under MGNREGA during
2006-07 to 2013-14 (Rs thousand per project)
37
2.4 Performance of MGNREGA – Some qualitative indicators
Table 2.5 provides details of social auditing and inspection carried out for MGNREGA
work in different states in India. The Gram Panchayats open muster rolls to carry out
registration of workers demanding employment under MGNREGA. These muster rolls
are verified under social auditing. During 2008-09 to 2013-14 (up to October), a total
number of 10.52 crore muster rolls were opened at the aggregate (all states) out of which
around 85 per cent were verified by the authorities who carried out the auditing work.
The verification process was more than 70 per cent in all the states except West Bengal
where verification of muster roles was only 59 per cent. Social auditing of MGNREGA
work of the Gram Panchayats (GP) was held in around 87 per cent of the GPs during
2008-09 to 2013-14. The social audit was held in above 90 per cent GPs in Tamil Nadu,
Madhya Pradesh, Kerala and Nagaland whereas, it was held in less than 60 per cent GPs
in Arunachal Pradesh, around 60 to 65 per cent GPs in Jammu & Kashmir and Karnataka.
As far as inspection of the works taken up by GPs under MGNREGA, there was district
level inspection as well as at the block level inspection. The percentage of works
inspected at the district level were very low only 12 per cent whereas the works inspected
at the block level were as high as 81 per cent during the above mentioned period. Almost
half of the works were inspected at the district level in Arunachal Pradesh while
proportion of inspected works was half to 1/3rd
in Assam, Sikkim, Nagaland and Kerala.
In rest of the states, less than 1/3rd works were being inspected at the district level. On
the other hand, West Bengal, Uttar Pradesh and Maharashtra had less than half of the
works inspected at the block level. In Rajasthan, Chhattisgarh and Tamil Nadu almost all
the works taken were being inspected at the block level while rest of the states more than
half to 3/4th
works taken up was being inspected at the block level.
Complaint redressal system was adopted under MGNREGA and a total number of
215542 complaints were registered in all the states during the period of 2008-09 to 2013-
14 (up to October) out of which around 84 per cent were redressed. Complaint redressal
was 100 per cent in Goa, Arunachal Pradesh and Mizoram. It was less than 80 per cent in
38
Madhya Pradesh, Maharashtra, Odisha, West Bengal and Gujarat while in rest of the
states above 80 per cent complaints were redressed during the above mentioned period.
MGNREGA programme not only provides employment to the households but it also
brings awareness among the households. The efforts are made to bring more transparency
in the payment system. The Gram Panchayats are encouraged to make payments to the
workers through banks or post office. The numbers of active bank accounts in the year
2008-09 to 2012-13 exceeded 20 crore on individual accounts and 3 crore on joint
accounts. Similarly the active post office accounts during the same years exceeded 15
crore on individual accounts and around 1.8 crore on joint accounts. Thus a total number
of 41 crore individual and joint accounts in post offices and banks were operative through
which payments were made for MGNREGA works during the period 2008-09 to 2012-
13 (Table 2.6).
Looking at state wise performance, the highest number of bank and post office accounts
were operative in Andhra Pradesh (6.4 crore), Rajasthan (4.4 crore), Uttar Pradesh (3.7
crore), Tamil Nadu (3.6 crore) and Madhya Pradesh (3.5 crore) during the period from
2008-09 up to October 2013. The north-eastern states namely Manipur, Meghalaya,
Mizoram, Nagaland, Sikkim and Arunachal Pradesh were at the bottom having less than
10 lakh accounts in operation for MGNREGA. The more important issue is how much
amount was being paid through these operative accounts under MGNREGA. Table 2.6
also presents the amount disbursed through bank/post office for making MGNREGA
payments to the households employed. A total sum of 51 thousand crore were disbursed
through banks and 30 thousand crore through the post offices, and thus a sum of 81
thousand crore were disbursed through banks and post offices during the period of 2008-
09 to 2012-13. State wise highest amount was disbursed by Uttar Pradesh ( 12.5
thousand crore) followed by Andhra Pradesh (around 12 thousand crore), Rajasthan (
11 thousand crore), Madhya Pradesh (9 thousand crore) and Karnataka (around 5
thousand crore). The north-eastern state namely, Arunachal Pradesh was at the bottom in
disbursal of total amount through banks and post offices (Figure 2.14) during the period
2008-09 to 2012-13.
39
Figure 2.14: Amount disbursed by banks and post office
under MGNREGA during 2008-09 to 2012-13
Figure 2.15: Amount spent under MGNREGA through banks and
post offices during 2008-09 to 2012-13 (Rs lakh per project)
It is interesting to note that out of total amount paid through banks and post offices in
MGNREGA during the period 2010-11 to 2012-13, the average amount paid through
40
bank/post office per account was 1.97 lakh. State wise, the highest amount paid per
account was in Nagaland ( 24 lakh), Meghalaya ( 9.5 lakh), Mizoram ( 6 lakh),
Sikkim ( 5.8 lakh) and Tripura ( 3.8 lakh). The lowest amount was paid in Tamil Nadu
(only 3 thousand), Bihar ( 1 lakh) and Gujarat ( 1.2 lakh) as shown in Figure 2.15.
Table 2.7 shows the unemployment allowance paid to the households in lieu of not being
able to provide employment to them after having registered a household’s name for
MGNREGA work. According to the legislation on MGNREGA, if a member of a
household has not been provided employment after issuing him/her a job card after a
lapse of 15 days, the GPs are supposed to provide unemployment allowance and such
amount would be borne by the concerned state government. Following this rule, during
the period 2007-08 to 2013-14 (up to October) unemployment allowance was due for
4.83 crore person days for which employment was not provided to the job card holders.
However, there was hardly any unemployment allowance paid to the job card holders as
only in West Bengal, Nagaland, Karnataka, Tamil Nadu, Uttar Pradesh and few others
unemployment allowance was paid for few days. Even in the states where some
unemployment allowance was paid, the amount paid per day was much less than the
stipulated minimum wages set by the states, except the case of Tamil Nadu. However, it
is interesting to note that the allowance paid even in those state was only a small fraction
of the total number of days for which unemployment allowance was due. At the
aggregate, out of 4.83 crore days for which unemployment allowance was due only 2478
days of allowance was paid that makes only 0.01 per cent days of unemployment
allowance paid and it was not more than 0.04 per cent in any state.
2.5 Summary of the Chapter
In the three phases of MGNREGA implementation in India from 2006-07 to 2013-14 (up
to October) 81 crore households were issued job cards at the country as a whole out of
which around 34 crore households were provided employment averaging around 4.5
crore households working in MGNREGA per annum that constitutes roughly around 30
per cent of the rural households in the country as a whole. A total number of 1.5 thousand
crore mandays of employment was generated during the above mentioned time period.
41
Out of the total person days generated, the share of Scheduled Castes and Scheduled
Tribes was 26.9 and 22.0 per cent, respectively while share of women in the total
employment was 48.0 per cent. The Andhra Pradesh state topped in the generation of
total person days, followed by Rajasthan, Uttar Pradesh Madhya Pradesh, Tamil Nadu
and West Bengal. At the aggregate, a total number of 45 person days of employment was
provided under MGNREGA during the implementation of this programme whereas the
target set under the programme is 100 days of employment per household. The highest
numbers of days of employment was provided by the north-eastern states followed by
Rajasthan, Madhya Pradesh and Andhra Pradesh. How successful the MGNREGA
programme in India has been in providing hundred days of employment to those who
demanded work. Out of 34 crore households working in MGNREGA only 2.9 crore
households (only 8.4 per cent) completed hundred days during its full tenure. It is
interesting to note whereas bigger states topped in the completion of hundred days of
employment like Rajasthan, Andhra Pradesh and Tamil Nadu, the percentage of
households who completed hundred days, it was the north-eastern states which topped in
the percentage term.
Water conservation was the leading activity which occupied the highest numbers of
projects followed by rural connectivity, provision of irrigation, drought proofing, land
development, renovation of traditional water bodies, micro irrigation and flood control.
During the entire period of MGNREGA, out of total 2.9 crore projects taken up under
MGNREGA around 30 per cent were completed and rest of 70 per cent were in progress.
A total amount of 2,35,084 crore was spent on the MGNREGA during 7 and a half
years of functioning of the MGNREGA with an average of slightly less than 30
thousand crore every year while average expenditure per project was 59 thousand. At
the aggregate, the highest amount per project was spent on renovation of traditional water
bodies closely followed by rural connectivity, flood control, micro irrigation, drought
proofing, water conservation, and land development in the descending order.
During 2008-09 to 2013-14 (up to October), a total number of 10.52 crore muster rolls
were opened at the aggregate out of which around 85 per cent were verified. Social
42
auditing of MGNREGA work of the Gram Panchayats (GP) was held in around 87 per
cent of the GPs while the percentage of works inspected at the district level were only 12
per cent. Complaint redressal system was adopted under MGNREGA and a total number
of 215542 complaints were registered in all the states out of which around 84 per cent
were redressed. It is interesting to note that out of total amount paid through banks and
post offices under the MGNREGA during the period 2008-09 to 2012-13, the average
amount paid through bank/post office per account was 1.97 lakh. According to the
legislation on MGNREGA, if a member of a household has not been provided
employment after issuing him/her a job card after a lapse of 15 days, the GPs are
supposed to provide unemployment allowance. Following this rule, during the period
2007-08 to 2013-14 (up to October) unemployment allowance was due for 4.83 crore
person days whereas only 2478 days of allowance was paid that makes only 0.01 per cent
days of unemployment allowance paid and it was not more than 0.04 per cent in any
state.
Table 2.1: MGNREGA Statistics for the Financial Year 2013-14
(As on 6 December 2013)
Description Latest Estimates
Employment provided to Households (crore) 2.31
Total person days generated (crore) 62.57
Person days generated for SCs (crore) 14.45
(23.1)
Person days generated for STs (crore) 9.59
(15.33)
Person days generated for Women (crore) 34.91
(55.78)
Person days generated for Others (crore) 38.53
(61.57)
Total works taken up (lakh) 44.18
Work Completed (lakh) 4.22
(9.56)
Works in progress (lakhs) 39.96
(90.44)
Note: Figures in parentheses are respective percentages of total
Source: http://nrega.nic.in
43
Table 2.2: Employment Generated through MGNREGA and its Socio-Economic characteristics (2006-07 to 2013-14)
Name of
the States
Cumulati
ve No. of
HH issued
job cards
(in
crores)
No.of HH
who have
demanded
employ-
ment
(in crores)
No.of HH
provided
employ-
ment
(in crores)
Per
centage of
HH
provided
employ-
ment
No. of
days of
Employ-
ment
provided
(per HH)
Person days in crores Works
Ongoing
(in crores)
Works
Complete
d
(in crores)
Total
Works
(in crores)
Works
Completed
(%)
No. of HH
Availed
100 days
of Employ-
ment
Per centage
of HH
completed
100 days of
Employment
Total SCs
(%)
STs
(%)
Women
(%)
Others
(%)
Andhra Pradesh 8.57 4.08 4.08 100.00 50.82 207.37 25.31 14.91 57.82 59.78 0.24 1.38 1.62 85.23 4905592 12.02
Arunachal Pradesh 0.09 0.07 0.05 74.40 28.32 1.38 0.45 87.40 27.94 12.15 0.00 0.00 0.00 77.08 17985 3.70
Assam 2.54 1.19 1.14 96.34 33.47 38.26 9.22 32.44 27.93 58.34 0.01 0.02 0.03 69.88 380266 3.33
Bihar 8.51 2.39 2.32 97.40 30.92 71.85 40.95 2.29 28.42 56.77 0.04 0.12 0.16 74.91 1003496 4.32
Chhattisgarh 2.85 1.80 1.76 97.53 47.89 84.09 12.96 39.29 45.98 47.75 0.05 0.06 0.11 53.47 1093631 6.23
Goa 0.01 0.00 0.00 99.53 24.79 0.10 3.93 23.97 70.40 72.20 0.00 0.00 0.00 70.11 678 1.74
Gujarat 2.34 0.61 0.59 97.36 37.00 21.86 11.77 42.67 45.40 45.55 0.05 0.03 0.08 40.95 321998 5.45
Haryana 0.39 0.15 0.15 95.70 39.22 5.73 51.47 0.00 36.49 48.52 0.00 0.00 0.01 47.84 63756 4.36
Himachal Pradesh 0.68 0.33 0.31 95.10 47.95 14.90 31.35 8.11 49.98 60.54 0.02 0.03 0.05 54.75 202038 6.50
Jammu And
Kashmir
0.53 0.27 0.25 92.28 43.17 10.78 6.84 20.02 13.63 73.14 0.01 0.03 0.04 67.47 147968 5.92
Jharkhand 2.82 1.23 1.22 99.20 42.19 51.33 16.46 40.81 32.10 42.74 0.04 0.10 0.14 69.15 523126 4.30
Karnataka 3.26 1.20 1.13 93.85 47.22 53.22 18.26 9.93 43.17 71.81 0.05 0.19 0.24 79.54 772301 6.85
Kerala 1.52 0.78 0.73 93.19 39.79 28.97 15.93 3.72 90.98 80.36 0.06 0.03 0.09 33.95 592212 8.13
Madhya Pradesh 8.03 3.04 3.01 98.97 52.46 157.85 18.35 42.73 43.11 38.93 0.15 0.31 0.46 68.03 2515984 8.36
Maharashtra 4.30 0.67 0.66 98.06 46.65 30.80 12.53 25.27 43.99 62.21 0.02 0.10 0.12 86.42 511089 7.74
Manipur 0.28 0.25 0.25 98.47 59.45 14.73 6.96 65.14 39.59 27.90 0.00 0.00 0.01 51.84 358487 14.47
Meghalaya 0.27 0.21 0.20 95.90 46.02 9.13 0.53 93.29 46.58 6.18 0.00 0.01 0.01 68.22 125782 6.34
Mizoram 0.13 0.12 0.12 99.11 71.71 8.43 0.03 99.79 31.03 0.18 0.00 0.00 0.00 64.42 299150 25.44
Nagaland 0.23 0.22 0.22 99.87 63.68 14.04 0.34 97.51 33.27 2.14 0.00 0.00 0.01 61.26 369167 16.75
Odisha 4.26 1.18 1.13 95.67 39.96 45.13 19.77 39.20 36.91 41.03 0.03 0.10 0.14 76.52 483165 4.28
Punjab 0.49 0.15 0.15 95.95 27.37 4.06 77.65 0.02 36.46 22.33 0.00 0.01 0.01 63.27 25521 1.72
Rajasthan 6.05 3.48 3.37 96.69 60.57 204.10 23.70 27.49 67.81 48.81 0.05 0.14 0.18 73.64 5464900 16.22
Sikkim 0.05 0.04 0.03 95.75 62.76 2.11 7.46 40.73 45.04 51.81 0.00 0.00 0.00 65.33 59476 17.69
Tamil Nadu 4.94 3.38 3.37 99.65 49.37 166.27 42.26 1.71 78.98 56.03 0.02 0.04 0.06 62.17 4532597 13.46
Tripura 0.42 0.39 0.39 99.51 67.60 26.47 18.65 43.44 42.96 37.91 0.04 0.02 0.06 38.77 792636 20.24
Uttar Pradesh 9.11 4.07 3.92 96.47 42.21 165.62 47.84 1.68 19.43 50.48 0.22 0.30 0.53 57.29 2443749 6.23
Uttrakhand 0.64 0.28 0.28 99.24 38.79 10.72 23.21 3.62 41.69 73.17 0.01 0.02 0.03 60.48 93252 3.37
West Bengal 7.83 3.38 3.27 96.58 28.36 92.64 35.34 12.56 30.33 52.09 0.09 0.10 0.19 51.63 543778 1.66
Grand Total 81.15 34.96 34.09 97.51 45.24 1541.94 26.87 21.95 48.04 51.18 1.23 3.15 4.37 71.98 28643780 8.40
44
Table 2.3: State wise Works Completed/Progress under MGNREGA: 2006-07 to 2013-14 (Number of projects)
Name of
the States
Rural Connectivity Flood Control and
Protection
Water
Conservation and
Water Harvesting
Drought Proofing Micro Irrigation
Works
Provision of
Irrigation facility to
Land Owned by
Renovation of
Traditional Water
bodies
Land Development Other activity
Approved by
MRD
Total
Comp-
leted
On-
going
Comp-
leted
On-
going
Comp-
leted
On-
going
Comp-
leted
On-
going
Comp-
leted
On-
going
Comp-
leted
On-
going
Comp-
leted
On-
going
Comp-
leted
On-
going
Comp-
leted
On-
going
Comp-
leted
On-
going
Andhra
Pradesh
96072 332649 21065 123352 740931 4166080 143666 2133419 376592 798429 178432 1445415 169653 240612 480878 441458 5292 15967
04
2212581 11278118
Arunachal
Pradesh
1358 4135 478 1313 181 532 300 1007 410 1589 3 47 44 100 139 1290 214 386 3127 10399
Assam 40333 101689 7232 12810 4606 12129 12819 34698 3245 7242 8934 11325 2205 4363 8256 23621 6631 9764 94261 217641
Bihar 171453 368650 22021 30746 52580 88956 49496 483797 33588 68356 6196 17549 31225 49156 20130 60066 15082 28623 401771 1195899
Chhattisgarh 91054 163096 3134 5461 42829 67189 25962 36512 9358 18293 149507 99959 42582 50645 146154 130673 3780 10009 514360 581837
Goa 384 602 308 816 26 77 0 0 13 47 0 22 112 286 362 975 2 6 1207 2831
Gujarat 34055 50061 21610 33457 274251 55316 33699 44872 2152 4120 34166 73672 15508 15201 17328 14409 24774 19514 457543 310622
Haryana 17607 16049 1480 1368 6929 6657 2052 706 8300 4634 221 557 2925 3114 7080 5645 1072 3447 47666 42177
Himachal
Pradesh
62887 76446 24101 28775 36386 45728 4433 5527 17514 21865 18436 25661 10616 9188 30266 34032 4210 4694 208849 251916
Jammu and
Kashmir
48709 113499 36935 67761 12582 21969 1397 2426 15401 32092 1824 1475 5082 8660 16765 34168 2403 9454 141098 291504
Jharkhand 87228 170077 1380 2503 182157 400014 6350 22832 4289 10354 82383 245775 22708 38241 44653 67748 10031 29178 441179 986722
Karnataka 53274 195123 43371 143692 81071 282463 60952 233728 24480 107565 71740 217398 23588 109093 84405 278475 20258 90995 463139 1658532
Kerala 15139 8803 144198 65111 85059 51230 16704 8042 51489 26332 29605 17765 76302 36574 168587 86313 2923 2187 590006 302357
Madhya
Pradesh
159245 485482 6886 13849 286594 610645 141083 444608 16291 27902 498100 892407 32280 66484 287962 396537 12998 43320 1441439 2981234
Maharashtra 8071 97378 794 3035 73094 281498 26814 290489 1053 7399 17747 205425 10130 43678 8834 27899 3223 23162 149760 979963
Manipur 11157 15694 8632 4532 3770 4139 5524 5008 2418 3961 121 139 1099 618 3847 4723 1191 1920 37759 40734
Meghalaya 15284 34309 1236 2333 5653 11489 3115 6545 1132 2098 60 115 2119 3164 2261 5019 547 2181 31407 67253
Mizoram 9680 19943 451 1431 669 978 1247 1146 45 132 17 30 46 58 2288 3349 1334 1497 15777 28564
Nagaland 10230 31182 2116 1492 5195 4250 2422 1933 2326 3235 121 64 658 216 6014 2584 777 2229 29859 47185
Odisha 100955 300250 1703 5474 59131 203444 18819 73121 2362 13072 47063 135351 44764 166316 23558 50193 18362 81140 316717 1028361
Punjab 12141 15197 1022 1451 737 972 3592 7425 2483 2725 5 16 6378 17049 3761 7936 2274 2947 32393 55718
Rajasthan 96038 329594 4403 15908 77562 209918 15922 65295 18707 51608 172731 376559 44095 122296 25862 77916 17756 63047 473076 1312141
Sikkim 1265 3263 683 1481 714 906 1875 1307 404 844 5 16 69 105 1630 4579 265 513 6910 13014
Tamil Nadu 49546 76873 1270 1429 34490 54179 20 698 28543 45246 2347 6579 94071 164219 858 6403 166 398 211311 356024
Tripura 77346 51055 6145 2901 55988 41135 21244 22493 34691 19940 6814 1340 18781 19106 93243 53383 60708 26940 374960 238293
Uttar
Pradesh
768128 1078544 95639 130862 187423 300482 106272 148556 93070 132081 346603 293826 115361 123932 236892 254645 139757 22851
2
2089145 2691440
Uttrakhand 10449 17765 30578 49775 33419 38916 10406 15631 11216 16009 1808 2025 5206 9346 9270 20014 1053 3314 113405 172795
West
Bengal
249932 264990 50444 44475 168582 169640 161177 213229 43854 41273 44048 57322 104647 94581 85787 80329 5850 9190 914321 975029
Grand Total 2299020 4422398 539315 797593 2512609 7130931 877362 4305050 805426 1468443 1719037 4127834 882254 1396401 1817070 2174382 362933 22952
71
11815026 28118303
45
Table 2.4: State wise Works Completed/Progress under MGNREGA: 2006-07 to 2013-14 (Amount spent in Rs lakh)
Name of
the States
Rural Connectivity Flood Control
and Protection
Water
Conservation and
Water Harvesting
Drought Proofing Micro Irrigation
Works
Provision of
Irrigation facility
to Land Owned
by
Renovation of
Traditional Water
bodies
Land
Development
Any Other
activity
Approved by
MRD
Total
Comp-
leted
On
going
Comp-
leted
On
going
Comp-
leted
On
going
Comp-
leted
On
going
Comp-
leted
On
going
Comp-
leted
On
going
Comp-
leted
On
going
Comp-
leted
On
going
Comp-
leted
On
going
Comp-
leted
On
going
Andhra
Pradesh
132725 266257 17308 18954 282201 328702 58889 79896 122307 80349 120024 214876 240826 167178 149580 97842 3896 38956 1127756 1293011
Arunachal
Pradesh
1383 3237 741 1048 153 275 219 424 282 892 3 0 62 54 79 716 46 78 2969 6724
Assam 108688 188426 38185 55059 10766 63607 7783 16989 8278 13955 1603 2048 6026 9393 16037 33950 6407 9531 203773 392958
Bihar 414436 265008 29648 28787 70108 67018 24017 146007 35634 40763 7007 8901 32091 35311 21683 29415 11923 20743 646546 641953
Chhattisgarh 189845 266619 7144 11864 80890 95590 31874 443472 25463 49101 38601 27644 88391 92205 48461 41113 1379 8085 512048 1035693
Goa 384 178 290 230 24 17 0 0 18 7 0 5 73 69 413 259 2 0 1203 765
Gujarat 44619 38911 17889 20588 45145 27900 10049 14140 1869 1712 11617 21810 15241 7399 4383 4396 4480 19471 155292 156326
Haryana 28805 23321 2057 2014 13752 11771 2169 769 9819 4868 247 279 4756 5118 10580 8523 2897 7980 75082 64644
Himachal
Pradesh
43124 53692 19489 19885 22703 19937 2933 2551 14389 14935 9951 6714 5651 4797 16804 12986 2194 2098 137238 137596
Jammu &
Kashmir
39209 40364 28128 21422 7055 5477 914 875 10383 10858 1166 453 2657 2331 14603 11981 2322 6100 106438 99862
Jharkhand 92222 135953 2036 2832 122054 180601 4063 18906 5187 7947 58311 91997 15621 20100 15845 21476 3566 18536 318906 498349
Karnataka 72874 111914 70909 96820 79803 110186 31858 63520 27821 52467 21115 28382 26350 45423 50561 73015 15859 41760 397151 623488
Kerala 7193 2764 55282 17589 53313 19692 8909 2461 23383 7705 21615 8298 35249 12172 123831 36485 1643 757 330418 107924
Madhya
Pradesh
329666 526028 14158 11208 232843 363973 44279 115125 15435 26266 251448 281179 34364 44473 65988 99762 2918 5302 991099 1473316
Maharashtra 23480 135098 1471 5013 105266 372686 561301 403847 356 1979 15463 65294 48930 47750 6711 8404 1315 8234 764294 1048306
Manipur 52343 51823 14394 7630 10172 8995 9178 8011 12551 16832 146 450 3909 1000 15029 11385 5298 4079 123020 110205
Meghalaya 35180 39596 3372 3721 6649 7094 4198 4048 1996 1701 62 88 1750 1748 4595 5419 2149 5292 59952 68707
Mizoram 43902 50391 832 504 2040 1428 3223 785 152 129 328 433 71 71 5603 3087 4370 1817 60519 58646
Nagaland 83294 78581 7887 2669 6703 3401 5347 3542 9094 3642 447 12 755 204 8457 3884 5237 5263 127221 101200
Odisha 90800 229009 1571 4121 27037 117620 4340 29316 2797 9215 7342 13821 22210 72317 3636 7425 21411 66590 181143 549434
Punjab 11910 14523 1709 2434 713 882 1489 2176 1563 2155 4 2 8070 18119 4193 6224 2067 4876 31718 51392
Rajasthan 220979 693470 9844 33745 154238 391973 18943 90645 30671 83176 73072 127180 89451 256152 25410 64214 30560 61335 653169 1801890
Sikkim 1938 4903 1219 2592 213 1096 598 938 658 1073 7 10 23 105 1338 2443 69 178 6062 13339
Tamil Nadu 126183 152188 3794 4171 105413 130905 49 219 82856 98477 1503 2729 301011 432977 933 3639 585 366 622328 825671
Tripura 105375 40610 8903 1777 44592 10334 21975 10685 23755 8739 4496 518 10315 2200 62512 13467 29255 20769 311177 109099
Uttar Pradesh 636707 587497 71143 67109 187913 180279 52125 53527 43800 52641 61344 45349 164895 98327 100240 82516 44239 55867 1362405 1223110
Uttrakhand 6524 7532 27466 29465 20189 15053 7482 6635 10329 9955 733 581 3347 2563 9547 10685 588 1813 86204 84282
West Bengal 333576 242484 69105 58808 183097 102444 42802 37740 54901 32219 30332 14402 138552 73727 69451 42493 3438 5833 925255 610149
Grand Total 3277363 4250378 525972 532059 1875045 2638938 961004 1557250 575747 633759 737989 963455 1300648 1453281 856503 737205 210115 421713 10320386 13188037
46
Table 2.5: Social Auditing and Inspection of MGNREGA work (2008-09 to 2013-14) Name of the State Must Roll Verified Social Audit Inspections Conducted Gram Sabha Held Complaints
No. of
Muster Rolls
Used
% age of
muster
rolls
Verified
Total Gram
Panchayats
%age of GP
where
social Audit
held
Total Works
Taken up
%age of
Works
Inspected at
District
Level
%age of
Works
Inspected at
Block Level
Total Gram
Panchayats
No. of
Gram
Sabhas
held
No. of
VMC
meetings
held
No. of
Complaints
Received
%age of
Complaints
Disposed
Andhra Pradesh 15256472 91.33 22025 84.92 2961546 9.14 91.27 22025 21232 7112 9486 96.38
Arunachal Pradesh 19312 99.41 313 58.93 2437 45.38 90.07 313 189 124 5 100.00
Assam 2215732 82.28 1886 88.13 111733 35.71 101.51 1904 5742 3121 1687 90.16
Bihar 6848974 84.91 5307 91.83 548555 9.00 60.85 5137 16948 16902 13720 61.81
Chhattisgarh 7364510 82.78 8089 92.44 684369 19.20 87.53 9544 12046 5110 11625 85.28
Goa 7370 94.67 142 73.54 1806 8.75 89.04 172 411 22 4 100.00
Gujarat 2264472 97.37 13777 93.28 612509 9.86 95.13 14744 20008 17301 4708 79.25
Haryana 446733 98.66 5979 60.27 80898 9.21 73.07 5535 6683 3299 661 88.05
Himachal Pradesh 950859 86.54 4430 80.45 301485 13.38 85.44 2903 7576 13166 2633 85.83
Jammu and Kashmir 607317 85.80 2548 65.55 170958 17.08 76.87 2563 3087 2834 1893 96.20
Jharkhand 6210689 92.21 4445 122.64 899744 16.14 71.40 5073 23270 19340 6447 90.65
Karnataka 1429346 88.71 4041 60.02 822657 11.89 76.04 4094 4398 1897 3264 87.38
Kerala 2470199 88.82 2242 77.26 331141 31.07 90.47 2583 16105 19947 1536 91.02
Madhya Pradesh 8694851 87.32 21544 91.39 2834452 13.11 93.46 20784 52174 34859 28621 73.58
Maharashtra 925445 88.05 18179 79.97 194925 11.17 52.03 18752 23614 9713 468 73.93
Manipur 808504 88.05 2029 94.68 27634 27.46 74.17 2402 3590 3006 1184 89.95
Meghalaya 763359 86.82 1602 71.28 43016 14.33 83.83 1681 3392 3160 1050 86.00
Mizoram 230216 103.95 585 71.26 12817 30.77 99.42 570 600 990 138 98.55
Nagaland 100110 93.63 1109 99.44 37598 33.88 82.44 1160 1776 1661 48 68.75
Odisha 5445318 86.54 7373 95.68 1050512 15.03 74.17 6178 8104 13201 8646 79.26
Punjab 295491 91.33 9439 95.71 54264 20.11 83.85 9591 11209 5024 630 81.43
Rajasthan 14962913 97.64 7337 90.11 841546 19.90 148.12 7083 7435 9531 45460 85.44
Sikkim 38747 97.90 161 69.16 9046 33.00 96.29 164 431 34 5 80.00
Tamil Nadu 2287101 100.01 13293 107.47 267117 14.36 99.70 14272 29826 2513 2332 97.73
Tripura 2008475 88.54 1039 89.15 254039 11.56 49.87 1039 1019 3538 190 86.32
Uttar Pradesh 13824894 71.40 45966 82.56 2325857 10.46 53.90 38098 36637 33994 61460 90.21
Uttrakhand 1250775 73.07 5869 88.17 157424 11.42 64.96 5869 5767 6418 1540 87.34
West Bengal 7454365 59.25 6322 71.73 803781 3.59 37.17 3276 4908 2852 6101 78.45
Total 105182549 85.46 204191 87.06 16443866 12.75 81.06 194419 312577 231023 215542 84.13
47
Table 2.6: The MGNREGA payment processed through Banks / Post office (2008-09 to 2012-13)
State No. of Active Bank Account
During the Financial Year
2008-2012
Amount of wages
Disbursed
through bank
Accounts
(in lakhs.)
No. of Active Post Office
Account for Financial
Year
2008-2012
Amount of
Wages disbursed
through post office
Accounts (in
lakhs.)
Total Accounts Use During the
Financial Year 2008-2012
Total
Amount
Disbursed
(in lakhs.)
Individual Joint Individual Joint Individual Joint Total
Andhra Pradesh 22125456 0 394046.94 42043964 0 808835.74 64169420 0 64169420 1202882.7
Arunachal Pradesh
21494 24469 677.54 11695 8630 299.45 33189 33099 66288 977
Assam 5703034 197343 95646.95 5010532 119764 62480.54 10713566 317107 11030673 158127
Bihar 6479061 333180 45795.39 23157465 660261 280992.25 29636526 993441 30629967 326788
Chhattisgarh 11407540 73186 187901.99 16491178 211570 201899.95 27898718 284756 28183474 389802
Goa 34475 77 1165.9 0 0 0 34475 77 34552 1166
Gujarat 1932740 2610942 59221.44 4940075 4575279 114429.75 6872815 7186221 14059036 173651
Haryana 857602 732424 61864.24 62872 58554 3581.33 920474 790978 1711452 65446
Himachal Pradesh 3439016 194048 122274.09 285601 15419 9980.15 3724617 209467 3934084 132254
Jammu & Kashmir
1584941 59762 61997.69 11646 3466 533.01 1596587 63228 1659815 62531
Jharkhand 4098462 626363 81722.79 9735868 1321331 243991.71 13834330 1947694 15782024 325715
Karnataka 11897536 3528235 442482.38 2031841 3030668 73287.31 13929377 6558903 20488280 515770
Kerala 5218247 1894 176256.46 290630 382 7471.65 5508877 2276 5511153 183728
Madhya Pradesh 22075781 8598461 747073.59 3368858 1416761 125028.63 25444639 10015222 35459861 872102
Maharashtra 3083926 217317 64163.93 4246868 139114 106456.36 7330794 356431 7687225 170620
Manipur 359537 5909 37000.36 574904 0 19801.65 934441 5909 940350 56802
Meghalaya 151475 37389 32651.95 188854 18465 5044.47 340329 55854 396183 37696
Mizoram 82809 62108 14139.42 138069 159825 18904.43 220878 221933 442811 33044
Nagaland 0 4591 110752.64 0 0 0 0 4591 4591 110753
Odisha 7748786 706114 124108.73 4112687 1291956 93912.53 11861473 1998070 13859543 218021
Punjab 1408591 283549 25740.76 418789 47440 7120.67 1827380 330989 2158369 32861
Rajasthan 16310043 3749423 622331.03 22460108 1292003 493892.13 38770151 5041426 43811577 1116223
Sikkim 156091 18419 11459.04 100201 11881 5284.05 256292 30300 286592 16743
Tamil Nadu 35021217 523462 11566.79 8875 2408 0 35030092 525870 35555962 11567
Tripura 271203 1212990 59151.96 202405 372610 20073.81 473608 1585600 2059208 79226
Uttar Pradesh 33039242 2780426 1221270.1 761804 48979 28893.86 33801046 2829405 36630451 1250164
Uttrakhand 3060330 325669 63417.57 654146 57462 18522.96 3714476 383131 4097607 81941
West Bengal 11527289 3879158 247013.49 14573671 3148637 258281.34 26100960 7027795 33128755 505295
Total 209095924 30786908 5122895.1 155883606 18012865 3008999.7 364979530 48799773 413779303 8131895
48
Table 2.7: Unemployment Allowances paid in lieu of not providing Employment (2007-08 to 2013-14) Sl.
No.
State Un Employment
Allowance Due
Unemployment Allowance Paid Amount
paid Rs
per day
% days for which
unemployment
allowance paid No. of Days No. of Days Amount (in Rs.)
1 Andhra Pradesh 0 0 0 0 0.00
2 Arunachal Pradesh 1547352 0 0 0 0.00
3 Assam 37064 0 0 0 0.00
4 Bihar 1270148 0 0 0 0.00
5 Chhattisgarh 1111264 0 0 0 0.00
6 Goa 83088 19 1438.5 76 0.02
7 Gujarat 692117 19 1820 96 0.00
8 Haryana 18930 0 0 0 0.00
9 Himachal Pradesh 621270 12 1320 110 0.00
10 Jammu & Kashmir 4889440 33 1146 35 0.00
11 Jharkhand 129936 0 0 0 0.00
12 Karnataka 745276 322 10836 34 0.04
13 Kerala 775611 31 1038 33 0.00
14 Madhya Pradesh 627763 21 1214 58 0.00
15 Maharashtra 413621 0 0 0 0.00
16 Manipur 1238993 0 0 0 0.00
17 Meghalaya 276807 0 0 0 0.00
18 Mizoram 1342045 0 0 0 0.00
19 Nagaland 2080547 663 11620 18 0.03
20 Odisha 226004 0 0 0 0.00
21 Punjab 3358232 71 6238 88 0.00
22 Rajasthan 680960 15 1200 80 0.00
23 Sikkim 145014 0 0 0 0.00
24 Tamil Nadu 862564 282 99924 354 0.03
25 Tripura 74405 6 600 100 0.01
26 Uttar Pradesh 690635 218 24620 113 0.03
27 Uttrakhand 6012677 7 430 61 0.00
28 West Bengal 18409904 759 16574.5 22 0.00
Total 48361667 2478 180019 73 0.01
49
Table 2.8: Work Projection under MGNREGA for India during 2011-12 to 2012-13
Shelf of works Through Which
Employment to be Provided
Total No. of
Spill over
Works
From
Previous
year
Total No. of
New Works
Taken up in
Current
Year
No. of Works
Likely to
Spill Over
From
Current
Financial
Year to Next
financial year
No. Of
New
Works
Proposed
for next
financial
year
Benefit
Achieved
Unit
Person days
to be
Generated
Estimated Cost (In Lakhs)
On
Unskilled
Wage
On
Material
including
skilled and
semiskilled
wages
Total
Rural Connectivity 307670 856875 344466 2011738 189076226 2606487112 3831378 2592510 6423888
Flood Control and Protection 77129 299051 93551 703784 67227013 404559406 953502 663797 1617299
Water Conservation and Water Harvesting 228862 680252 293371 1484860 2709621374 8067494457 3682505 2234915 5917420
Drought Proofing 876795 536077 306661 891557 431600544 558756194 2400973 1496810 3897783
Micro Irrigation Works 86470 307757 85974 514621 106960627 10510900425 1715916 1080052 2795969
Provision of Irrigation facility to Land
Owned by
322483 884696 425794 2192011 637362744 959687614 1201329 742674 1944003
Renovation of Traditional Water bodies 141301 378155 158252 1111076 2735120114 1127740285 2098633 943888 3042521
Land Development 138096 527193 151479 1224103 11130205509 570944653 1237010 702146 1939157
Any Other activity Approved by MRD 40270 53790 21135 198988 8730369 70205053 597877 417019 1014895
Bharat Nirman Rajiv Gandhi Sewa Kendra 8235 13800 12465 39897 7235033 129024339 132737 212430 345167
Total 2227311 4537646 1893148 10372635 18023139552 25005799538 17851861 11086241 28938102
50
Chapter 3
Household Characteristics their Income and Consumption Pattern
3.1 Profile of respondents
The previous chapter presented a comprehensive analysis of functioning of the MGNREGA in
India among all states based on secondary data. In order to see the performance of MGNREGA
at the ground level and to capture qualitative information, a household survey was carried out
among a selected number of households. A sample of 250 households was selected from five
districts in each of the states covered in the study. While selecting five districts from each state, a
due representation was given to all the three phases of the implementation of MGNREGA. From
each district, two villages were selected with one village from the periphery of around 5
kilometers of the district/city head-quarters and the second district from a farthest location of 20
kilometers or more. From each selected village, primary survey was carried out on 20
participants in MGNREGA and 5 non-participants working as wage-employed. In summary,
from each state 10 villages were selected and a total number of 250 households were surveyed
with the help of a structured household questionnaire. Total sample consisted of 200 participants
and 50 non participants in each state. The detailed selection procedure for the participant and non
participant households is discussed in Chapter 1. This chapter presents a brief overview of the
selected households followed by a detailed discussion on the socio-economic characteristics,
occupation, income and consumption structures of the selected respondents in different states.
Our analysis in this chapter would be classified into participants of MGNREGA and non
participants in each state while the selected households from five districts in each state would be
clubbed together.
Tables 3.1 and 3.1.1 present demographic profile of the selected households (participants in
MGNREGA and non participants). The average household size was 4.75 with participants
having average family size of 4.7 and non participants 4.9. The number of earners in the family
was also higher for non participating households in comparison to participating households. The
average numbers of earners in the family were 2.2 members among participating families and 2.6
members among the non participating families. Similarly, the number of members in working
51
age (i.e., 16-60 years) was 74.4 per cent among participants and 73.7 per cent among non
participants. The percentage of below sixteen was less than 20 per cent among both participant
and non participant households and 6 and 7 per cent above the age of sixty years, respectively for
participants and non participants. Looking at the education status among the selected households,
the percentage of illiterate was around 1/3rd
among the participants and less than 1/3rd
among the
non participants. Those who were educated up to primary level their ratio was almost 1/3rd
among both participants and non participants and the proportion of member educated up to
secondary level was slightly above 1/4th
among both participants non participants. The
proportion of graduates and above was less than 3 per cent among the participants and less than 7
per cent among the non participants. Thus, non participants were better educated compared to
participant household members.
The demographic profile of households indicates their socio-economic characteristics. Looking
at the caste distribution among the participating households, the percentage of households
belonging to Scheduled Caste (SC), Scheduled Tribes (ST) and Other Backward Castes (OBC)
was 34, 17 and 34 per cent, respectively while General category had only 16 per cent proportion
among the selected households. In the case of non participating households, the proportion of
SC, ST, OBC and General among the selected sample was 33, 12, 35 and 20 per cent,
respectively. Looking at the proportion of number of job cards issued and number of person-days
generated as discussed in the last chapter, our socio economic structure of the selected sample
truly represents the distribution of job cards and numbers of people employed in NREGA.
Looking at the economic classification of the selected households, the people who had
Antyodaya (AAY) and Below Poverty Line (BPL) card among the participants constituted 16
and 53 per cent, respectively while Above Poverty Line (APL) card was held by 25 per cent
participating households. Among non participants, AAY card was held by 18 per cent, BPL by
39 per cent and APL by 34 per cent selected households. Six per cent households among
participants and nine per cent non participants were found not possessing any card. More than
2/3rd
proportion of the households who participated in MGNREGA had the main occupation as
wage earning. Only 23 per cent of them had main occupation as farming and another 3 per cent
as self business and 4 per cent as salaried work. Among the selected non participants, exactly
52
half were wage earners and one forth had farming as their main occupation. Other 10 per cent
each were in self business and in salaried job. The incidence of migration was not much different
among the participants and non participants.
3.2 Occupation structure
Distribution of sample family members in different occupations for participating and non
participating household is given in Tables 3.2 and 3.2.1. The age distribution in the previous
section indicated that around 2/3rd
members of the selected households were in the working age.
However, out of the working population, some members were full time students either in
college/university or doing other professional courses. A significant number of family members
belonged to housewives engaged in household activities without yielding any economic
remuneration. A few other members were unemployed or disabled persons not having any active
participation in any economic activities. Thus, the data presented in the table gives us
occupational distribution of the members who were truly active and were engaged in some
earning activities either in agriculture and related activities or in the secondary and tertiary
sectors.
The trends in occupation depict that among the participating households, the proportion of work
provided by MGNREGA was only a small proportion of their aggregate employment. Out of the
total man days employed per household including all the working members, the share of
MGNREGA varied between 12 to 32 per cent among different states. It was less than 15 per cent
in Karnataka, Kerala, Assam, Gujarat and West Bengal. Its proportion was between 15 to 25 per
cent in Uttar Pradesh, Sikkim, Madhya Pradesh, Chhattisgarh, Maharashtra, Himachal Pradesh,
Rajasthan, Haryana and Punjab. The share of MGNREGA in total employment was above 25 per
cent only in two states namely Bihar and Andhra Pradesh. At the aggregate, MGNREGA
provided 18 per cent share in the total employment among our selected households.
Glancing through the employment pattern it is evident from the statistics in the table that
participating households had their highest share in employment in casual labour in agriculture
and non agriculture sector among all the states. At the aggregate, casual labour in agriculture and
non agriculture sector constituted more than 40 per cent share in employment. Self employment
53
in agriculture and livestock constituted around 20 per cent share and self employment in business
and regular salary had around 5 and 10 per cent share, respectively in the total employment
among the selected participants. Among non participating households also majority (around 47
per cent) was engaged in casual wages in agriculture and non agriculture sector. Self
employment in agriculture and allied activities including animal husbandry contributed around
35 per cent share in the total man day’s employment. Almost 15 per cent share of man days was
contributed by regular salaried jobs. Self employment in non farming contributed around 12 per
cent. Thus, casual labour and self employment in agriculture and animal husbandry was the
prime activity that provided major employment to both participant and non participant
households. The MGNREGA programme provided only around 1/4th
to 1/5th
share of the total
employment to the participating households.
3.3 Household income
The main sources of earnings of the selected participant and non participant households were,
agriculture income also known as farm business income; Income from livestock activities
namely dairy and poultry farming; self-employment in non agricultural activities, such as small
business, shop or factory etc.; earnings through casual labour including that of NREGA; regular
salary or pension. Besides these major sources, there were also minor inflows of income in terms
of sale or renting out assets or land and remittances obtained from outside. These earnings were
mostly intermittent in nature and were sighted among very few households.
Tables 3.3 and 3.3.1 present distribution of household income by activity classifications for
participant and non participant households. All earnings from different activities are in terms of
net income obtained by subtracting material cost from the gross earnings for each activity. The
above tables also present the respective percentage share of each activity in the total household
income. The coefficient of variation is calculated for each activity across the working members.
The data on household income pertains to the calendar year 2009. A glance on the household
income statistics reveals that by and large estimated income of participant and non participant
households was on expected lines. The estimated per household income of non participant
households was higher compared to participant households. On an average, the selected non
participant households earned 70 thousand per annum compared to 59 thousand earned by the
54
participating households. Comparing the sources of income across different activities, it is
clearly evident from the tables that wage income constituted a lion’s share in the income of both
participating as well as non participating households. It was observed in the last section that
casual labour was the prominent occupation among the selected households. Looking at the share
of income obtained from different wage earning activities among the participants, it evident that
wage earnings in agriculture contributed around 17 per cent followed by wage earnings in non
agricultural activities 22 per cent, while wage earnings in MGNREGA activities contributed only
12 per cent share in the total household income of participants. In addition to wage earnings,
income from self employment in agriculture and livestock constituted around 17 per cent share
of their household income while regular salaried job contributed around 14 per cent share in the
household income of the participating households. Trends in share of various sources were
somewhat similar in the case of non participating households. Self business in agriculture and
livestock constituted 20 per cent share of their total household income while wages in agriculture
and non agriculture sectors constituted around 37 per cent share in their total income. The third
most important source of their income was regular employment in salaried job in various
activities. Income from self employment in non farming including that of business sector
constituted around 13 per cent share in their total household income.
Comparing household income per annum across the selected states for participants, the estimated
income was above 1 lakh in Kerala and Assam. It ranged between 50 thousand to 1 lakh in
Karnataka, Haryana, Madhya Pradesh, Himachal Pradesh, Gujarat and Rajasthan. The household
income per annum was found less than 50 thousand in Uttar Pradesh, Bihar, Sikkim, Andhra
Pradesh, Chhattisgarh, Punjab, Maharashtra and West Bengal. Thus, majority of the states
observed household income less than the aggregate average of 59 thousand. Ironically, the
states that observed highest household income namely Kerala and Assam, however, had much
lower percentage coming from the MGNREGA activity less than 7 per cent in Kerala and only 3
per cent in Assam in the aggregate income. Highest share contributed by MGNREGA in total
household income was observed in Maharashtra (29 per cent), followed by Haryana and Sikkim
(25 per cent, each), Andhra Pradesh and Punjab (18 per cent, each), West Bengal, Rajasthan,
Madhya Pradesh and Uttar Pradesh (each having above 13 per cent share). The lower
contribution by MGNREGA was found in Assam (3 per cent), Kerala (7 per cent), (slightly
55
above 10 per cent). In most of the states, around 50 per cent of the income share was contributed
by casual wages either in agriculture or in non agricultural sector. As MGNREGA mandates only
100 days of employment provision per household (that target is also rarely achieved) and in
many cases there are two to three members working per household, thereby MGNREGA ensures
only partial employment provision and households ought to depend on alternate employment
avenues either in agriculture sector or in other casual activities. In the case of non participants,
household income pattern was also similar to that of participant households. The highest income
in their case was observed in Himachal Pradesh, Kerala and Assam. The lowest income was
found in Sikkim, followed by Bihar.
The coefficient of variation (CV) indicates the dispersion of income across household members
for the respective economic activities (Tables 3.4 and 3.4.1). The dispersion of income across
households was highest for agriculture and livestock income for both participant and non
participant households. High variability of agricultural income across households indicates
seasonal nature of agricultural occupation, diversified cropping pattern across households and
different amount of land cultivated by different households. Dispersion was also high in casual
wage earnings in the agriculture and non agricultural activities indicating their casual nature. The
dispersion was comparatively less in MGNREGA activities indicating lesser amount of wage
rate differentials in MGNREGA as compared to casual wage rate in agriculture and non
agricultural activities. Dispersion was also high in the salaried income.
3.4 Household consumption
Food consumption expressed in Kilocalories (Kcal) per capita is used for measuring the level of
nutrition. In defining poverty, the Planning Commission uses the calorie requirement norm of
2400 Kcal per capita for the rural areas and 2100 Kcal per capita for the urban areas. It further
emphasizes that 50 per cent of calories to be derived from carbohydrate and the remaining from
the protein and fat with 25 per cent each. Fifty per cent of the required calorie means drawing
1200 calorie from cereals in rural India and 1050 in the urban India. To get the requisite 1200
calories, 10.44 kg cereals per capita per 30 days or 348 gms per capita per day are required by
56
the rural people and 9.12 kg cereals per capita per 30 days or 304 gms per capita per day are
required by the urban people to obtain 1050 calories1.
Tables 3.5 and 3.5.1 present per capita monthly consumption of food items, viz., cereals, pulses,
edible oils, sugar and milk by our selected participant and non participant households. It is
evident from the results that on average per capita cereal consumption satisfied the 1200-calorie
norm, i.e., total cereal consumption surpassed 10.5 kgs per capita per month by both the
participant and non participant households. The average cereal consumption was measured at
11.1 kg per capita per month in the case of participants and 11.6 kg per capita per month in the
case of non participants. Rice and wheat were the major cereals consumed with average amount
of 4.8 kg and 4.4 kg, respectively among the participants and 5.2 kg and 4.6 kg, respectively by
the non participants. Coarse cereals consumption was 1.8 kg among participants and 1.5 kg
among non participants.
The states that reported less than 10.5 kg cereal consumption were Bihar, Punjab, Maharashtra
and Rajasthan among both participants and non participants. Karnataka, Sikkim, Andhra
Pradesh, Chhattisgarh, Assam and West Bengal had rice as the staple cereal whereas Haryana,
Madhya Pradesh, Punjab and Rajasthan had wheat as the major cereal of consumption. The states
that had combination of wheat and rice consumption were Uttar Pradesh, Maharashtra, Himachal
Pradesh and Gujarat. Pulses consumption varied between 0.5 to 3 kg per capita per month among
different selected states and it averaged around 1 kg among both the participants and non
participants. On an average consumption basket including sugar, milk and milk products, edible
oils and fruits and vegetables were found similar among participant and non participant
households at the aggregate.
Table 3.5.2 presents household consumption of food items as revealed by the 66th
Round of
National Sample Survey (NSS) for the year 2009-10 for rural areas. The NSS data which
coincides with our survey period shows that at all India, rice consumption per capita per month
was 6 kg and wheat consumption was 4 kg per capita that compares well with our participant and
1 The above calculations are based on Planning Commission (1977) calculations that 100 gms cereal on an average
produce 345 calories.
57
non participant consumption. At the aggregate, total cereal consumption in India according to
NSS data was 11.4 kg that compared with 11.1 kg for our participant households and 11.6 kg for
the non participants. The states that had less than 10.5 kg of cereal consumption according to
NSS data were Haryana, Punjab, Gujarat, Maharashtra and Karnataka that also stand close to our
survey data. The reason, why the richer states like Punjab, Haryana, Gujarat and Maharashtra
observed less consumption of cereals, seems to be the diversification of consumption basket
taking place from the traditional cereal and pulse crops to high value commodities like milk and
meat products and fruits and vegetables. It is evident from the NSS consumption data that milk
consumption was highest in Haryana and Punjab and meat consumption topped in better off
states like Karnataka, Andhra Pradesh and West Bengal.
It is now well established that per capita consumption of cereals and total calorie intake in most
of the Indian states has started declining in the recent past. Total cereals consumption declined
from 14.9 kg to 11.8 kg in Rajasthan, 14.3 kgs to 12.2 kg in Bihar, 13.9 kgs to 12 kg in Uttar
Pradesh, 13 kg to 12.89 kg in Assam, 14.2 kg to 11.3 kg in Madhya Pradesh and 11.4 kgs to 10.2
kg in Maharashtra during almost two decades time period from 1993-94 to 2009-10. This
declining trend in cereal consumption has been caused by the diversification of food basket and
the changing income and lifestyle of the rural and urban masses. On the one hand, due to change
in work nature, the requirement of calorie intake has declined overtime and on the other, the
changes in the composition of diet have increased the cost of calories (Radhakrishna and Ravi,
1991; Murty, 1999). Convergence between rural and urban patterns of calorie consumption also
provides an explanation to this phenomenon.
The food basket of an average Indian is diversifying with her rising income and improved living
standards. Whereas, cereals and pulses were the main source of protein in both rural and urban
areas in the seventies and early eighties, the contribution of milk and milk products as source of
protein is consistently increasing in the more recent rounds of NSS and the increase is observed
much more in the urban areas. The contribution from meat, fish and eggs to protein has slightly
increased (Delgado, et. al. 1999). The diversification of consumption from cereals and pulses
towards edible oils, milk and high value products was also visible from the trends presented in
our data. Comparing the participant and non participant households, non participants were better
58
off compared to participant households as was depicted by their household income. The quantity
of high value commodities like milk and milk products, fruits and vegetables was higher for non
participant households compared to participant households. Therefore, these trends substantiate
our argument that with the rising level of income, people have a tendency to diversify their
palate towards more nutritious and high value commodities. Comparing the consumption of
other commodities like milk, sugar, edible oil etc., with NSS, generally the quantity consumed
by our participant and non participant households closely matched with the NSS 2009-10 data.
Various rounds of NSS consumption expenditure data reveals that the share of non-cereal items
in the monthly per capita expenditure (All India) has been consistently increasing in both rural
and urban areas. The share of non-food consumption expenditure increased from 27 per cent in
1972-73 to 41 per cent in 1999-00 which went up to 43 per cent in 2009-10 in rural areas, while
it increased from 36 per cent to 52 and further to 55.6 per cent in the urban areas during the same
time period. In 2009-10, about 57 per cent of the total consumption expenditure (All India) was
on food items in rural areas, while it was 44 per cent in the urban areas. As our selected sample
constitutes only rural households, expenditure on food is expected to lead that of non-food
expenditure to commensurate with the NSS trends as discussed above. Monthly consumption
expenditure per capita for participants and non participants for our selected states for food and
non-food items are given in Table 3.6 and 3.6.1. Tables present percentage distribution of each
food item in total food expenditure, each non-food item in total non-food expenditure and
percentage of total food items and total non-food items in the total expenditure.
Monthly per capita food consumption expenditure was measured as 420 for participant and
455 for non participant households (Tables 3.6 and 3.6.1). Total expenditure on cereals was
observed as 139 for participants and 143 for non participants. The corresponding amount for
the NSS 2009-10 (66th
Round) for all India was 145. In pulses, expenditure by our sample
households averaged at 44 per capita per month (that was almost same for both the categories)
which stands close to NSS average expenditure for pulses at 35. Consumption of edible oil by
our participants averaged around 34 for both the categories was also close to the national
average shown by the NSS 69th
Round of 39. Consumption of other high value commodities
like fruits, vegetables, milk and meat products were slightly higher for non participants
59
compared to participants and overall their value was comparable with that of NSS consumption
expenditure. Total monthly food expenditure among our selected sample averaged at 421 for
the participants and 455 for the non participants, whereas NSS food expenditure for all India
averaged around 600.
The difference between participants and non participants was much higher in the non food
expenditure, especially in education, clothing and other items including medical and health. The
overall non food expenditure was 237 per capita per month among the participants compared
to 271 among the non participants. Our non food expenditure was under estimated as is clear
from the much above NSS amount of 453. Almost all items of non food expenditure in the case
of our sample households were less than that of NSS. The difference could be due to under
reporting and may be few items missing in our questionnaire like conveyance, consumer
services, various entertainment goods, rent, taxes and other durable goods. Comparing food and
non-food expenditure, the proportion of food in total expenditure was 64 per cent among the
participants and 63 per cent among the non participants. In comparison, share of food
expenditure in the NSS data was 57 per cent of total expenditure that also indicate that our non
food expenditure was slightly under estimated.
3.5 Variability (CV) and Gini ratios of income and consumption
Distribution of observed income and consumption per household of the selected participants and
non participants is presented in Tables 3.7 and 3.7.1. In most of the states household income
exceeded household consumption per annum indicating household net savings. Karnataka, Bihar,
Andhra Pradesh and Rajasthan among the participants and Bihar and Rajasthan among non
participants made exception where consumption exceeded income and the selected households
had to depend either on the past savings or on borrowing from various sources. Glancing through
the coefficients of variation in the tables it is observed that variation in consumption across the
households was less than that of income. It indicates that consumption was more symmetric
compared to income. The coefficient of variation of income was higher compared to
consumption in most of the states. The only exception was Karnataka and Sikkim among the
participants while among non participants it was across the board. Looking at the concentration
ratio, the Gini coefficient of income was also mostly higher than that of consumption for both
60
participants and non participants. However, compared to coefficient of variation, Gini
coefficients of income and consumption were closer compared to coefficient of variation that
showed comparatively higher variation among the two. Thus, higher variation in income
compared to consumption shows the more vulnerability of the household in the case of an
external shock to the household income and the necessity of households to search for some
formal or informal sources of consumption smoothening (Kumar and Singh in press).
3.6 Factors determining participation in MGNREGA
Unlike other poverty removal programmes that are mostly supply based, NREGA programme is
demand driven programme, whereby every household in rural areas is given opportunity to
register any time to work under NREGA in any unskilled work at the stipulated wage rate which
is supposed to be not less than the minimum wage rate prevailing in that state. In this section, we
try to ascertain the factors that determine the participation of a particular household to register
for working under NREGA. We run two sets of equations, first at the household level and second
at the member level. In each state, at the household level, we have 250 observations pertaining to
200 observations for the participants and 50 observations for the non participants. At the member
level, numbers of observations vary from state to state depending upon the size of the household
in each state. Generally we have around more than 1000 members in each state in the category of
participating households and above 250 members in the non participating households. In the first
set, we used a logistic2 regression model regressing participation in NREGA (with households or
members who registered and worked in NREGA with value 1 and those who did not with value 0
on the explanatory variables. The explanatory variables included continuous variables as
household size, household employment and income, value of assets; and dummy variables, such
as, land ownership with value 1 for those who owned land and zero for others, dummy for AAY
and BPL card holders and dummy for various social characteristics such as households being SC,
2 In statistics, logistic regression (sometimes called the logistic model or logit model) is used for prediction of the
probability of occurrence of an event by fitting data to a logit function logistic curve. It is a generalized linear model
used for binomial regression. Like many forms of regression analysis, it makes use of several predictor variables that
may be either numerical or categorical. Logistic regression is a variation of ordinary regression which is used when
the dependent (response) variable is a dichotomous variable (i. e. it takes only two values, which usually represent
the occurrence or non-occurrence of some outcome event, usually coded as 0 or 1) and the independent (input)
variables are continuous, categorical, or both. Unlike ordinary linear regression, logistic regression does not assume
that the relationship between the independent variables and the dependent variable is a linear one. Nor does it
assume that the dependent variable or the error terms are distributed normally.
61
ST or OBC. In the second set of equations, instead of regressing dichotomous variable with
value zero or one, we tried continuous variable as response or dependent variable. We regressed,
the number of days of employment in NREGA by a household on the above mentioned
independent variables. The member level regression was done only among the participant
households. The results of the above two sets of equations are presented in Tables 3.8 to 3.10.
The logit function provides us the probabilities of the participation of a household in
MGNREGA activities. State level regression results presented in Table 3.8 show that the
households who had alternate employment opportunities and those who had higher income
contribution from other activities had less incentives to work in MGNREGA. The coefficient for
employment other than MGNREGA was negative and significant in Sikkim, Haryana, Madhya
Pradesh and Chhattisgarh. Coefficient of income other than MGNREGA was significant and
negative in Madhya Pradesh, Chhattisgarh, Punjab, Maharashtra and Himachal Pradesh. The
household size had significant and positive sign in Karnataka, Andhra Pradesh, Kerala, Haryana,
Madhya Pradesh, Chhattisgarh, Punjab, Maharashtra and West Bengal indicating with increase in
family size there was more probability of household members working in MGNREGA among
the selected households. Household size had significant but negative relationship in Uttar
Pradesh and Himachal Pradesh indicating low participation at higher family size in these two
states.
The value of assets and land ownership had negative sign in the regression indicating household
members with land ownership or better assets accumulation had less probability of participating
in MGNREGA activities although legally there was no bar on the households having land
ownership in registering for NREGA work. The coefficient was significant with a negative sign
in Karnataka, Uttar Pradesh, Sikkim, Madhya Pradesh, Assam, Punjab and West Bengal. On the
opposite, if a household owned an AAY or BPL card or if they belonged to Scheduled Caste or
Scheduled Tribe community they had higher possibility of entering into MGNREGA work. The
coefficient of dummy BPL was found positive and significant in Karnataka, Sikkim and in
Haryana. Similarly, coefficient of social characteristics (household belonging to SC, ST and
OBC) was found significant and positive in Sikkim, Andhra Pradesh, Chhattisgarh and
Maharashtra.
62
In the logit regression on member participation in MGNREGA (Table 3.9), we clubbed some
member level variables with the household variables. Some interesting relations emerged out of
this exercise. For example, among the members in a household, those who worked in
MGNREGA had a direct and significant relationship with age and negative relationship with
education. The implication is that older age and less educated people preferred to work in
MGNREGA as the latter is known providing soft wages. Similarly, the dummy on sex indicates
that the male members had higher probability of working in MGNREGA compared to female
members although female proportion in total work force constituted around 45 per cent varying
in its degree from state to state. The members with BPL and AAY cards and members belonging
to SC and ST community had better probability of working in MGNREGA. The above findings
were generally true across the states.
In the alternate regressions, continuous variable of number of days per household worked in
MGNREGA was used instead of dummy variable of participation in MGNREGA (Table 3.10).
In this household level regression, employment other than MGNREGA was significant with a
negative sign in Karnataka, Sikkim, Chhattisgarh and West Bengal indicating that those
households who had employment opportunities in other activities did not prefer to work in
MGNREGA. The other most important and significant variable was wage rate in MGNREGA
with a positive sign in almost all the states indicating that with higher wage rate households
preferred to work in MGNREGA. Once again the economic backwardness indicated by AAY
and BPL card holding and social backwardness indicating by lower castes like SC, ST and OBC
were found having positive and significant association with participation in MGNREGA in most
of the states. Household income other than MGNREGA, household size and value of land were
the other variables that were significant in some of the states.
3.7 Summary of the chapter
This chapter presents households characteristics and income and consumption details of the
selected households. The average household size was 4.75 with participants having average
family size of 4.7 and non participants 4.9. The average numbers of earners in the family were
2.2 members among participating families and 2.6 members among the non participating
families. On the overall, non participants were better educated compared to participant household
63
members. The trends in occupation depict that among the participating households, the
proportion of work provided by MGNREGA was only a small proportion of their aggregate
employment. Out of the total man days employed per household including all the working
members, the share of MGNREGA varied between 12 to 32 per cent among different states. At
the aggregate, MGNREGA provided 18 per cent share in the total employment among our
selected households. Casual labour in agriculture and non agriculture sector constituted more
than 40 per cent share in employment. Self employment in agriculture and livestock constituted
around 20 per cent share and self employment in business and regular salary had around 5 and 10
per cent share, respectively in the total employment among the selected participants.
A glance on the household income statistics reveals that the estimated per household income of
non participant households was higher compared to participant households. On an average, the
selected non participant households earned 70 thousand per annum compared to 59 thousand
earned by the participating households. Comparing the sources of income across different
activities, wage income constituted a lion’s share in the income of both participating as well as
non participating households. The dispersion of income across households was highest for
agriculture and livestock income for both participant and non participant households while it was
comparatively less in MGNREGA activities indicating lesser amount of wage rate differentials in
MGNREGA as compared to casual wage rate in agriculture and non agricultural activities. On
average, per capita cereal consumption satisfied the 1200-calorie norm, i.e., total cereal
consumption surpassed 10.5 kgs per capita per month by both the participant and non participant
households. The average cereal consumption was measured at 11.1 kg per capita per month in
the case of participants and 11.6 kg per capita per month in the case of non participants. Pulses
consumption varied between 0.5 to 3 kg per capita per month among different selected states and
it averaged around 1 kg among both the participants and non participants. The diversification of
consumption from cereals and pulses towards edible oils, milk and high value products was
visible from our data.
Total monthly food expenditure among our selected sample averaged at 421 for the participants
and 455 for the non participants whereas NSS food expenditure for all India averaged around
600. The overall non food expenditure was 237 per capita per month among the participants
64
compared to 271 among the non participants. Our non food expenditure was under estimated as
is clear from the much above NSS amount of 453. The difference could be due to under
reporting and may be few items missing in our questionnaire. The, higher variation in income
compared to consumption shows the more vulnerability of the household in the case of an
external shock to the household income and the necessity of households to search for some
formal or informal sources of consumption smoothening.
The logit function provided us the probabilities of the participation of a household in
MGNREGA activities. State level regression results showed that the households who had
alternate employment opportunities and those who had higher income contribution from other
activities had less incentive to work in MGNREGA. The value of assets and land ownership had
negative sign in the regression indicating household members with land ownership or better
assets accumulation had less probability of participating in MGNREGA activities. On the
opposite, if a household owned an AAY or BPL card or if they belonged to Scheduled Caste or
Scheduled Tribe community they had higher possibility of entering into MGNREGA work. From
the household OLS regression, the most important and significant variable emerged was wage
rate in MGNREGA with a positive sign in almost all the states indicating that with higher wage
rate households preferred to work in MGNREGA. Some interesting relations were observed in
the member level logit regression. Among the members in a household, those who worked in
MGNREGA had a direct and significant relationship with age and negative relationship with
education. The implication is that older age and less educated people preferred to work in
MGNREGA as the latter is known providing soft wages. Similarly, the dummy on sex indicates
that the male members had higher probability of working in MGNREGA compared to female
members. The members with BPL and AAY cards and members belonging to SC and ST
community had better probability of working in MGNREGA. The above findings were generally
true across the states.
65
Table 3.1 Demographic profile of the respondents (Percentage of households) – Participants S
tate
s
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Characteristics
No of HH 201 200 200 160 200 200 200 200 200 200 200 205 200 200 200 200 3166
Household size (numbers) 5.29 4.15 6.38 4.33 4.20 3.47 5.59 5.14 3.00 4.92 3.78 5.13 4.28 5.52 5.43 4.53 4.70
Average number of earners 2.68 2.31 2.25 3.12 2.61 1.42 2.68 2.00 1.00 1.57 1.92 2.81 0.00 3.55 2.50 2.42 2.17
Age group <16 24.9 34.1 0.0 0.0 27.2 10.8 33.1 0.0 0.0 29.7 15.6 32.3 24.2 33.7 38.1 0.0 19.9
16-60 68.3 63.9 91.0 91.9 69.6 79.9 62.7 96.0 96.0 63.1 76.6 61.1 69.0 64.0 58.1 94.0 74.4
>60 6.8 2.1 9.0 8.1 3.2 9.3 4.2 4.0 4.0 7.2 7.4 5.6 6.8 2.3 3.8 6.0 5.6
Identity of
respondent
Head 54.2 99.5 72.0 79.4 95.0 66.5 65.5 85.0 84.0 90.5 35.0 82.4 90.5 43.5 73.5 96.0 75.1
Others 45.8 0.5 28.0 22.6 5.0 33.5 34.5 15.0 16.0 9.5 65.0 17.7 9.5 56.5 26.5 4.0 25.0
Education
status (Above
only)
Illiterate 35.5 43.0 31.5 21.9 47.2 2.7 38.8 46.0 43.0 18.2 52.2 39.6 18.0 37.4 44.4 46.0 35.8
Up to primary 23.2 36.7 44.5 73.1 34.5 14.8 48.1 25.0 33.0 56.2 32.3 16.4 27.8 25.4 23.9 30.5 33.8
Up to secondary 39.4 15.2 23.0 4.4 19.1 68.5 12.1 26.5 22.0 21.4 10.6 34.0 39.5 35.2 28.5 23.5 26.5
Up to graduate 1.9 3.5 1.0 0.6 3.4 11.0 0.9 2.5 2.0 3.9 0.1 9.5 2.9 1.8 2.7 0.0 2.9
Above graduate 0.0 1.7 0.0 0.0 0.4 3.0 0.1 0.0 0.0 0.4 0.1 0.1 0.4 0.1 0.5 0.0 0.4
Caste SC 34.3 49.0 38.0 5.0 27.5 12.0 61.0 35.0 17.5 34.0 86.0 20.6 33.0 24.0 25.5 37.5 34.1
ST 8.5 1.0 0.0 53.8 13.0 3.5 6.0 34.5 39.0 10.5 0.0 38.2 13.5 20.0 24.5 6.5 16.6
OBC 26.9 46.0 52.0 40.6 40.5 59.0 31.0 28.0 41.5 26.0 9.5 35.3 22.5 54.5 25.0 4.5 33.8
General 30.4 4.0 10.0 0.6 19.0 25.5 2.0 2.5 2.0 29.5 4.5 5.9 31.0 1.5 25.0 51.5 15.5
Card
holding
AAY 47.8 18.5 19.5 0.0 4.5 17.5 0.0 9.0 21.5 0.0 78.0 15.2 10.0 3.0 2.5 5.5 16.0
BPL 39.3 34.0 52.5 93.8 91.5 42.5 83.0 50.5 55.5 74.0 22.0 49.2 33.0 55.0 44.0 42.5 53.4
APL 11.9 47.0 8.5 6.3 2.5 40.0 8.5 30.5 11.5 19.0 0.0 22.6 55.0 40.0 45.0 50.0 25.1
None 1.0 8.5 19.5 0.0 1.5 0.0 8.5 10.0 11.5 7.0 0.0 13.2 2.0 2.0 8.5 2.0 6.0
Decision
maker
Male 83.6 90.0 70.0 86.3 87.5 71.0 84.5 94.5 90.5 97.0 95.0 87.8 83.5 80.0 87.5 76.5 85.3
Female 16.4 10.0 30.0 13.8 12.5 29.0 15.5 5.5 9.5 3.0 5.0 12.3 16.5 20.0 12.5 23.5 14.7
Main occupation
Farming 16.0 38.1 56.5 31.5 5.2 0.7 0.0 18.5 29.0 8.0 2.0 43.7 49.1 21.8 11.6 19.5 22.5
Self business 6.1 1.4 0.0 6.3 1.1 8.2 0.6 3.5 1.5 3.0 9.5 1.6 3.3 0.5 4.3 2.5 3.1
Salaried / pensioners 6.3 1.9 0.0 6.9 1.9 6.7 0.8 2.5 0.0 9.5 12.5 1.2 12.3 0.9 6.7 0.5 4.2
Wage earners 71.6 58.7 43.5 54.4 91.4 84.4 98.7 68.5 53.5 79.5 76.0 53.5 32.3 76.8 77.4 69.5 68.4
Others 0.0 0.0 0.0 1.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 8.0 0.6
Involved in migration during year
2009
2.73 0.00 15.00 0.00 6.91 0.00 1.00 0.00 13.50 60.50 0.00 11.65 6.66 47.00 6.00 21.50 12.18
66
Table 3.1.1 Demographic profile of the respondents (Percentage of households) - Non- Participants
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Characteristics
No of HH 54 50 50 40 50 50 50 50 50 50 100 45 50 50 50 50 839
Household size (numbers) 4.89 4.80 6.00 4.47 3.44 3.15 4.86 4.46 10.00 5.22 3.92 4.98 4.60 5.32 5.44 4.21 4.93
Average number of earners 1.94 2.26 2.32 2.03 2.74 1.60 2.36 1.00 1.00 1.62 1.70 2.56 0.00 3.30 2.10 2.12 2.60
Age group <16 42.1 0.0 0.0 23.0 6.5 28.3 0.0 0.0 31.8 15.9 33.5 30.4 39.1 33.6 0.0 0.0 18.7
16-60 54.6 76.0 90.0 69.8 76.8 65.2 98.0 94.0 60.2 80.0 62.5 62.2 59.0 62.3 88.0 88.0 73.7
>60 3.3 24.0 10.0 7.2 16.8 6.6 2.0 6.0 8.1 4.1 3.6 7.4 1.9 4.1 12.0 12.0 7.5
Identity of
respondent
Head 94.0 74.0 80.0 100.0 64.0 60.0 92.0 74.0 94.0 52.0 84.4 82.0 64.0 94.0 96.0 96.0 77.2
Others 6.0 26.0 20.0 0.0 36.0 40.0 12.0 26.0 6.0 48.0 15.6 18.0 36.0 6.0 4.0 4.0 23.0
Education
status
(Above only)
Illiterate 33.8 14.0 15.0 47.9 0.0 34.2 30.0 48.0 19.5 51.4 29.9 10.9 24.9 41.6 36.0 36.0 31.1
Up to primary 37.5 34.0 62.5 23.9 8.4 48.7 24.0 38.0 45.2 37.4 15.6 24.4 34.5 29.2 32.0 32.0 33.1
Up to secondary 18.3 34.0 22.5 21.2 53.6 15.8 36.0 14.0 30.3 11.2 37.5 45.2 39.4 27.3 22.0 22.0 28.2
Up to graduate 10.0 18.0 0.0 7.1 30.3 0.9 8.0 0.0 4.2 0.0 15.6 3.0 0.8 1.9 10.0 10.0 6.1
Above graduate 0.4 0.0 0.0 0.0 7.7 0.5 2.0 0.0 0.8 0.0 0.9 1.3 0.4 0.0 0.0 0.0 0.7
Caste SC 44.0 28.0 2.5 16.0 4.0 62.0 36.0 14.0 34.0 88.0 15.6 34.0 16.0 22.0 30.0 30.0 33.1
ST 0.0 0.0 27.5 2.0 0.0 4.0 14.0 36.0 10.0 0.0 28.9 18.0 18.0 26.0 16.0 16.0 12.0
OBC 46.0 38.0 55.0 52.0 54.0 32.0 38.0 48.0 36.0 8.0 35.6 14.0 64.0 32.0 4.0 4.0 34.8
General 10.0 34.0 15.0 30.0 42.0 2.0 12.0 2.0 20.0 4.0 20.0 34.0 2.0 20.0 50.0 50.0 20.0
Card holding AAY 24.0 2.0 27.5 4.0 6.0 2.0 6.0 16.0 0.0 73.0 15.6 6.0 8.0 0.0 4.0 4.0 17.9
BPL 22.0 20.0 52.5 92.0 16.0 72.0 38.0 64.0 44.0 25.0 35.6 34.0 36.0 24.0 40.0 40.0 39.3
APL 54.0 30.0 20.0 2.0 78.0 8.0 40.0 10.0 40.0 2.0 35.6 60.0 56.0 64.0 50.0 50.0 34.1
None 0.0 48.0 0.0 2.0 0.0 18.0 16.0 10.0 16.0 0.0 13.3 0.0 0.0 12.0 6.0 6.0 8.7
Decision
maker
Male 94.0 62.0 92.5 92.0 96.0 92.0 90.0 92.0 100.0 98.0 88.9 98.0 88.0 98.0 82.0 82.0 91.3
Female 6.0 38.0 7.5 8.0 4.0 8.0 10.0 8.0 0.0 2.0 11.1 2.0 12.0 2.0 18.0 18.0 8.7
Main occupation
Farming 46.0 52.0 45.0 23.7 0.0 0.0 26.0 22.0 22.0 2.0 48.6 46.7 21.1 17.8 20.0 20.0 26.5
Self business 5.3 20.0 25.0 20.3 11.5 0.0 16.0 10.0 4.0 10.0 8.3 6.7 0.9 12.1 8.0 8.0 9.9
Salaried/pensioners 1.8 2.0 5.0 6.1 59.0 2.5 10.0 2.0 14.0 16.0 6.4 35.0 0.9 8.4 8.0 8.0 10.3
Wage earners 46.9 26.0 10.0 49.9 29.5 97.5 42.0 52.0 60.0 72.0 36.7 10.8 77.2 61.7 52.0 52.0 50.0
Others 0.0 0.0 15.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8 0.0 0.0 12.0 12.0 1.3
Involved in migration during
year 2009
2.65 0.00 9.00 0.00 8.00 0.00 0.00 0.00 10.00 82.00 0.00 11.16 1.74 42.00 9.40 14.00 11.27
67
Table: 3.2: Main Occupation (% of total man-days per hh) – Participants
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Occupation
Agricultural casual labour 43.7 16.6 26.1 6.9 35.4 7.3 35.8 22.0 11.0 2.7 34.1 25.6 4.4 20.3 9.7 24.2 20.5
Non-agricultural casual labour 12.5 35.9 12.0 12.8 6.9 16.2 27.8 18.7 21.7 41.1 38.5 9.1 12.5 28.1 20.8 36.6 22.0
Work for PWP other than NREGA 0.1 2.3 6.0 0.0 0.0 0.0 0.2 0.2 0.9 0.0 0.0 0.1 1.3 0.6 0.3 0.0 0.8
Self employed in non-farming 4.3 6.7 0.0 6.2 1.6 11.2 0.0 13.7 6.0 12.3 5.3 1.1 3.1 0.6 4.2 4.3 5.0
Self employed in agriculture 10.0 15.3 12.0 25.0 9.3 9.2 0.0 10.3 14.8 6.5 0.0 12.7 17.1 7.7 13.7 9.8 10.7
Self employed in livestock 5.0 1.4 8.0 10.7 8.9 0.0 11.1 2.7 12.1 9.7 0.9 19.9 17.8 7.2 16.5 4.7 8.5
Regular/salary job 9.1 2.0 0.0 22.0 5.5 44.6 0.5 5.6 10.3 10.0 0.0 2.8 22.3 1.6 10.6 3.7 9.2
Worked as migrant worker 3.0 4.3 3.5 0.0 0.8 0.0 0.1 10.4 7.5 3.8 0.0 8.6 2.0 22.0 6.5 4.3 4.9
Worked under NREGA 12.2 15.5 29.0 16.4 31.5 11.5 24.6 16.3 15.8 13.9 21.2 20.3 19.7 12.0 17.7 12.3 18.1
Any other 0.0 0.0 3.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2
Total 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100
68
Table: 3.2.1 Main Occupation (% of total man-days per hh) - Non- Participants
Sta
tes
Ka
rna
tak
a
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
ha
rash
tra
HP
Gu
jara
t
Ra
jast
han
Wes
t B
eng
al
Ag
gre
ga
te
Occupation
Agricultural casual labour 16.9 26.1 20.0 4.0 18.7 7.2 34.7 11.9 14.3 7.7 26.7 22.1 0.8 16.6 10.7 16.2 16.7
Non-agricultural casual labour 18.5 38.8 13.0 10.3 23.1 22.3 53.1 16.8 32.9 36.3 61.2 8.9 9.6 44.3 28.5 34.2 30.5
Work for PWP other than NREGA 0.6 4.6 7.0 0.0 0.0 0.0 0.6 0.0 0.0 0.0 0.0 0.0 0.0 1.6 0.0 0.0 0.9
Self employed in non-farming 4.2 8.0 11.0 25.3 13.6 14.0 0.0 28.1 12.5 29.4 6.8 5.2 9.5 0.0 9.9 16.9 11.7
Self employed in agriculture 29.5 15.9 30.0 24.3 27.2 0.0 0.0 18.5 10.3 2.2 0.9 19.8 13.3 8.3 6.9 12.4 12.9
Self employed in livestock 7.8 1.0 12.0 11.1 2.3 0.0 11.6 3.4 15.0 3.7 1.8 25.8 15.9 4.7 17.6 3.1 8.0
Regular/salary job 19.9 0.0 2.0 25.1 13.3 56.5 0.0 21.4 14.9 14.8 2.6 9.0 50.9 1.1 12.1 7.2 14.8
Worked as migrant worker 2.7 5.6 3.0 0.0 1.8 0.0 0.0 0.0 0.0 5.9 0.0 9.2 0.0 23.5 14.3 10.0 4.5
Any other 0.0 0.0 2.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1
Total 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100
69
Table: 3.3: Household net income (Annual) (Rs. Per household)* - Participants
Sta
tes
Ka
rna
tak
a
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
ha
rash
tra
HP
Gu
jara
t
Ra
jast
han
Wes
t B
eng
al
Ag
gre
ga
te
Characteristics
Income from work under NREGA 6524 6128 4121 8118 6939 7409 14086 7584 5330 4154 6660 11913 9302 7084 6572 5252 7320
(11.4) (13.1) (10.1) (25.0) (18.1) (6.7) (25.0) (13.7) (11.0) (3.3) (17.8) (28.5) (10.6) (9.3) (13.1) (14.3) (12.4)
Income from wages in agriculture 22524 3593 10347 2782 12501 22318 20954 8016 7689 3118 12386 8812 2150 11183 3729 7989 10099
(39.4) (7.7) (25.3) (8.6) (32.6) (20.2) (37.3) (14.4) (15.9) (2.5) (33.1) (21.1) (2.4) (14.7) (7.4) (21.7) (17.0)
Income from wages non agriculture 9928 15693 10016 5682 5973 25551 18439 14092 12477 16826 14375 3606 7097 25029 11737 13652 13214
(17.3) (33.5) (24.5) (17.5) (15.6) (23.1) (32.8) (25.4) (25.9) (13.4) (38.4) (8.6) (8.1) (33.0) (23.4) (37.1) (22.3)
Income from wages in PWP 64 1004 3630 0 0 0 150 302 218 0 0 59 433 409 198 0 409
(0.1) (2.1) (8.9) (0.0) (0.0) (0.0) (0.3) (0.5) (0.5) (0.0) (0.0) (0.1) (0.5) (0.5) (0.4) (0.0) (0.7)
Income from wages as migrant
workers
1997 12640 3193 0 652 0 0 4798 6118 2168 0 7367 9525 19888 6893 2725 4937
(3.5) (27.0) (7.8) (0.0) (1.7) (0.0) (0.0) (8.6) (12.7) (1.7) (0.0) (17.6) (10.8) (26.2) (13.8) (7.4) (8.3)
Income from self employed in non
farming
2470 1691 0 1848 1831 21423 0 3581 2924 25888 3377 586 2415 980 2680 1096 4577
(4.3) (3.6) (0.0) (5.7) (4.8) (19.4) (0.0) (6.4) (6.1) (20.6) (9.0) (1.4) (2.7) (1.3) (5.3) (3.0) (7.7)
Income from agriculture/livestock 8723 4938 8381 6208 9591 11250 2430 13205 10588 10735 621 8664 32284 6167 12948 4961 9521
(15.2) (10.5) (20.5) (19.1) (25.0) (10.2) (4.3) (23.8) (21.9) (8.5) (1.7) (20.7) (36.7) (8.1) (25.8) (13.5) (16.1)
Income from livestock 1373 0 0 1439 0 0 0 0 0 0 0 0 0 2755 0 424 361
(2.4) (0.0) (0.0) (4.4) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (3.6) (0.0) (1.2) (0.6)
Income from regular job/
salary/pension
3621 1165 0 6350 865 22544 180 3897 2894 62859 0 755 16444 1039 3854 742 7958
(6.3) (2.5) (0.0) (19.6) (2.3) (20.4) (0.3) (7.0) (6.0) (50.0) (0.0) (1.8) (18.7) (1.4) (7.7) (2.0) (13.5)
Income from sale of assets/
rent/transfer etc.
10 0 1194 0 0 0 0 73 0 0 0 0 8218 1288 1507 0 776
(0.0) (0.0) (2.9) (0.0) (0.0) (0.0) (0.0) (0.1) (0.0) (0.0) (0.0) (0.0) (9.4) (1.7) (3.0) (0.0) (1.3)
Total 57234 46852 40882 32426 38352 110494 56239 55548 48236 125748 37418 41762 87868 75822 50117 36842 59171
(100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100)
70
Table: 3.3.1: Household net income (Annual) (Rs. Per household)* - Non- Participants
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Characteristics
Income from wages in agriculture 6188 7659 10403 1717 6698 32563 14629 7709 6766 2581 10346 8338 147 9189 3963 4766 8541
(6.6) (14.0) (25.0) (4.8) (15.4) (25.9) (34.3) (12.3) (12.2) (2.4) (24.1) (12.3) (0.1) (11.1) (6.8) (9.5) (12.3)
Income from wages non agriculture 11291 17277 6242 5567 10150 33364 25464 17791 14925 11107 24803 9193 8755 39664 17974 9890 17111
(12.1) (31.6) (15.0) (15.7) (23.4) (26.5) (59.7) (28.3) (26.9) (10.5) (57.7) (13.5) (5.1) (47.9) (30.8) (19.7) (24.5)
Income from wages in PWP 370 1650 2913 0 0 0 288 0 0 0 0 0 964 442 0 0 397
(0.4) (3.0) (7.0) (0.0) (0.0) (0.0) (0.7) (0.0) (0.0) (0.0) (0.0) (0.0) (0.6) (0.5) (0.0) (0.0) (0.6)
Income from wages as migrant
workers
1059 18250 4223 0 380 0 0 2026 15078 2402 0 9009 0 20281 16878 3324 5488
(1.1) (33.4) (10.2) (0.0) (0.9) (0.0) (0.0) (3.2) (27.2) (2.3) (0.0) (13.3) (0.0) (24.5) (29.0) (6.6) (7.9)
Income from self employed in non
farming
1763 3190 4577 8725 5831 35222 0 8818 7058 20271 5980 6971 15956 0 6150 12227 8726
(1.9) (5.8) (11.0) (24.6) (13.4) (28.0) (0.0) (14.0) (12.7) (19.2) (13.9) (10.3) (9.4) (0.0) (10.6) (24.4) (12.5)
Income from agriculture/ livestock 57944 6569 10236 7399 17370 0 2280 12090 10187 8043 588 30167 44053 9660 9540 9486 14085
(62.2) (12.0) (24.6) (20.8) (40.0) (0.0) (5.3) (19.2) (18.4) (7.6) (1.4) (44.4) (25.8) (11.7) (16.4) (18.9) (20.2)
Income from livestock 2639 0 0 2350 0 0 0 0 0 0 1260 0 0 2370 0 280 590
(2.8) (0.0) (0.0) (6.6) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (2.9) (0.0) (0.0) (2.9) (0.0) (0.6) (0.8)
Income from regular job/
salary/pension
11889 0 832 9750 3012 24632 0 14398 1440 61357 0 4196 59471 280 3348 10160 12118
(12.8) (0.0) (2.0) (27.5) (6.9) (19.6) (0.0) (22.9) (2.6) (58.0) (0.0) (6.2) (34.9) (0.3) (5.7) (20.3) (17.4)
Income from sale of assets/
rent/transfer etc.
0 0 2185 0 0 0 0 0 0 0 0 0 41093 1000 430 0 2664
(0.0) (0.0) (5.2) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (24.1) (1.2) (0.7) (0.0) (3.8)
Total 93143 54595 41610 35508 43441 125780 42661 62833 55453 105761 42976 67874 17044
0
82886 58283 50133 69721
(100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100)
71
Table: 3.4: Variability (CV) in income across households – Participants
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Occupation
Income from work under NREGA 118.0 42.9 26.1 63.2 55.7 70.0 31.8 33.2 47.6 81.4 132.7 107.1 90.0 45.6 72.0
Income from wages in agriculture 94.6 92.7 82.0 37.3 94.8 80.0 29.1 24.1 60.9 75.4 101.4 248.2 110.0 131.4 77.9
Income from wages non agriculture 204.4 58.2 78.2 91.7 43.8 153.0 52.6 62.3 52.3 105.4 305.7 197.7 168.0 67.1 94.1
Income from wages in PWP 642.6 186.4 - - 0.0 - 191.2 287.2 0.0 - 1431.8 715.9 320.0 554.1 -
Income from wages as migrant workers 437.2 330.0 - 242.6 0.0 0.0 186.7 113.4 66.2 - 287.6 305.2 196.0 255.7 370.6
Income from self employed in non farming 439.4 290.1 291.4 297.4 44.8 0.0 100.3 122.4 54.7 351.4 712.5 870.8 969.0 186.3 468.8
Income from agriculture/ livestock 283.2 85.2 80.6 97.2 15.7 41.0 90.8 67.3 87.3 705.7 156.0 93.8 229.0 - 187.2
Income from livestock 439.5 495.7 217.2 133.0 - - - - - - - - 189.0 46.5 264.1
Income from regular job/ salary/pension 433.4 0.0 198.7 42.4 0.0 204.8 221.5 80.1 160.9 663.3 275.2 691.0 158.4 561.9
Total 69.5 91.6 - 37.5 87.5 - 61.6 66.3 - 47.7 81.9 - 113.0 34.7 49.7
Table: 3.4.1: Variability (CV) in income across households - Non- Participants
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Occupation
Income from wages in agriculture 194.1 64.8 150.3 121.7 45.5 71.0 45.5 41.8 35.3 74.7 134.5 479.8 121.0 92.9 112.0
Income from wages non agriculture 342.7 53.9 112.9 78.2 55.1 67.0 59.5 51.2 43.5 82.8 326.3 193.4 144.0 55.9 124.0
Income from wages in PWP 525.3 111.1 - - 0.0 - 0.0 0.0 0.0 - 0.0 568.0 410.0 0.0 -
Income from wages as migrant workers 500.5 354.7 - 183.7 0.0 - 349.4 85.7 79.7 - 257.3 - 149.0 175.5 229.3
Income from self employed in non farming 295.2 184.6 148.4 222.0 42.4 0.0 71.4 112.9 69.2 440.0 348.4 221.7 - 159.1 327.0
Income from agriculture 472.5 109.4 60.3 78.9 0.0 41.0 106.1 70.7 67.5 703.5 194.3 71.9 223.0 74.0 186.3
Income from livestock 263.0 0.0 147.9 46.7 - - - - - - - - 187.0 - 276.3
Income from regular job/ salary/pension 275.6 0.0 147.9 - 66.7 - 129.9 266.3 20.7 185.9 327.9 120.2 707.0 192.5 455.4
Total 314.9 118.6 - 60.5 58.7 - 74.8 48.2 - 71.8 120.9 - 102.0 44.6 105.4
72
Table 3.5: Household consumption of food items (kg per capita per month) – Participants
S
tate
s
Ka
rna
tak
a
UP
Bih
ar
Sik
kim
AP
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
ha
rash
tra
HP
Gu
jara
t
Ra
jast
han
Wes
t B
eng
al
Ag
greg
ate
Rice 7.47 5.78 1.71 9.20 7.46 2.24 2.17 10.97 10.41 0.67 4.51 4.45 2.61 1.00 10.81 4.83
Wheat 1.27 7.53 5.73 1.80 0.50 8.41 7.45 1.70 1.38 8.35 2.79 5.84 5.14 7.00 1.49 4.36
Other cereals 4.12 0.29 2.00 1.70 1.34 0.65 2.33 0.87 0.00 0.43 3.00 1.00 6.73 2.20 0.17 1.84
Total cereals 12.85 13.60 9.44 12.70 11.70 11.29 11.93 13.54 11.80 9.45 9.39 11.29 14.48 10.20 12.47 11.10
Total pulses 1.14 1.32 1.45 0.40 1.00 1.42 0.70 0.81 0.53 0.63 1.15 3.47 1.64 1.10 0.44 1.12
Sugar 1.29 0.64 0.42 0.40 0.60 1.90 0.54 0.55 0.49 2.04 1.27 0.80 0.90 1.00 0.49 0.86
Edible oils 1.31 0.66 0.50 0.30 0.84 0.61 0.58 0.39 0.54 0.38 0.67 0.83 1.01 0.80 0.52 0.65
Liquid milk 2.79 1.56 3.50 1.20 2.48 3.89 0.91 0.34 1.12 - 2.56 7.80 3.11 3.90 0.93 2.43
Milk products 0.15 0.29 0.04 0.00 0.16 0.12 0.10 0.01 0.02 4.18 1.94 0.10 0.45 0.60 0.07 0.49
Meat and products 0.36 0.07 0.34 0.40 0.68 0.22 0.13 0.20 0.24 - 0.42 0.26 0.32 0.10 0.39 0.26
Fruits 0.47 0.35 - 0.10 1.00 0.26 0.23 0.10 0.33 0.23 0.20 0.84 0.42 0.40 0.12 0.32
Vegetables 2.23 6.82 4.11 2.60 5.50 0.11 5.86 6.12 6.54 2.84 1.15 2.77 3.02 3.80 6.16 3.68
73
Table 3.5.1: Household consumption of food items (kg per capita per month) - Non-Participants
S
tate
s
Ka
rna
tak
a
UP
Bih
ar
Sik
kim
AP
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
ha
rash
tra
HP
Gu
jara
t
Ra
jast
han
Wes
t B
eng
al
Ag
greg
ate
Rice 7.53 4.98 1.37 9.10
5.92 1.97 2.09 11.59 10.54 0.59 4.27 4.91 2.84 0.90 10.74 5.15
Wheat 1.29 6.87 6.70 1.70
0.20 9.00 8.58 2.19 0.91 8.97 2.70 8.87 4.50 5.80 1.52 4.60
Other cereals 3.48 0.07 1.50 1.60
1.00 0.42 1.85 0.68 0.00 0.51 3.48 1.22 4.83 4.00 0.20 1.54
Total cereals 12.31 11.92 9.57 12.50
15.88 11.39 12.52 14.46 11.45 10.07 9.59 15.00 12.13 10.70 12.46 11.62
Total pulses 1.19 1.14 1.50 0.30
0.76 0.67 1.12 0.92 0.46 0.67 1.26 3.22 1.33 1.00 0.45 1.02
Sugar 1.17 0.62 0.80 0.30
0.52 1.75 0.73 0.54 0.46 2.09 1.75 0.79 0.84 1.10 0.49 0.93
Edible oils1 0.75 0.52 0.53 0.30
0.64 0.57 0.62 0.38 0.50 0.42 0.73 0.81 0.91 0.70 0.52 0.56
Liquid milk1 3.71 1.63 5.00 1.10
2.20 4.02 1.00 0.17 0.80 3.92 8.40 3.11 4.10 1.59 2.43
Milk products 0.51 0.04 0.15 0.00
0.12 0.08 0.16 0.01 0.02 4.66 0.80 0.50 0.40 0.40 0.04 0.63
Meat and products 0.33 0.08 0.40 0.40
0.60 0.00 0.20 0.22 0.22 0.55 0.26 0.41 0.10 0.61 0.26
Fruits 0.61 1.80 0.00
1.00 0.51 0.37 0.31 0.39 0.28 0.28 1.77 0.47 0.60 0.17 0.52
Vegetables 2.30 3.90 4.00 2.60
4.00 0.64 6.09 7.93 8.67 3.07 1.12 2.26 3.11 3.60 7.92 4.13
Note: 1-Edible oil and Liquid milk is in Liters
74
Table 3.5.2: Household consumption of food items (kg per capita per month) - NSS (2009-10)
S
tate
s
Ka
rna
tak
a
UP
Bih
ar
Sik
kim
AP
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
ha
rash
tra
HP
Gu
jara
t
Ra
jast
han
Wes
t B
eng
al
All
In
dia
Rice 5.66 4.27 6.38 9.52 10.67 0.70 2.17 11.18 12.38 0.79 3.25 4.09 1.74 0.24 10.26 6.14
Wheat 1.10 7.66 5.55 0.87 0.32 8.91 8.13 0.88 0.51 8.43 4.25 6.35 4.19 8.65 1.16 4.36
Other
cereals
3.27 0.11 0.30 0.36 0.49 0.20 1.01 0.07 0.00 0.12 2.73 0.80 3.28 2.92 0.01 0.85
Total
cereals
10.03 12.04 12.23 10.76 11.48 9.81 11.30 12.13 12.89 9.35 10.24 11.24 9.21 11.82 11.43 11.35
Total pulses 0.70 0.76 0.56 0.46 0.66 0.62 0.71 0.62 0.51 0.83 0.86 1.25 0.68 0.43 0.39 0.65
Sugar 0.72 0.71 0.32 0.42 0.48 1.45 0.80 0.54 0.48 1.71 1.00 1.17 0.99 1.15 0.43 0.71
Edible oils1 0.64 0.59 0.50 0.55 0.71 0.57 0.59 0.56 0.47 0.82 0.93 0.89 0.99 0.72 0.59 0.64
Liquid
milk1
3.79 4.59 2.67 5.87 3.37 13.40 4.00 0.77 1.55 11.56 3.05 9.51 6.18 9.86 1.39 4.12
Milk
products
0.04 0.01 0.02 0.03 0.06 0.07 0.02 0.02 0.03 0.05 0.02 0.07 0.03 0.08 0.02 0.03
Eggs (no) 2.20 0.63 1.05 2.68 3.91 0.26 0.67 1.18 3.38 0.77 1.37 0.77 0.45 0.21 4.59 1.73
Meat and
products
0.50 0.19 0.14 0.47 0.67 0.08 0.20 0.34 0.99 0.07 0.33 0.20 0.12 0.07 1.10 0.49
Source: Household Consumption of Various Goods and Services in India – NSS 66th Round, Report No 541/(66/1.0/3), Ministry of Statistics and Programme Implementation, Government of India, February 2012.
Note: 1- Edible oil and Liquid milk is in Liters
75
Table 3.6: Monthly consumption expenditure of households (Rs per capita) - Participants
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Rice 101.00
(19.7)
69.62
(17.21)
42.95
(8.37)
146.9
(46.17)
99.47
(24.88)
39.32
(10.62)
28.57
(8.67)
145.55
(41.53)
167.86
(37.75)
13.18
(2.86)
39.33
(11.86)
43.76
(9.3)
47.94
(6.96)
18.60
(3.45)
149.91
(41.79)
69.12
(16.4)
Wheat 14.00
(2.7)
62.85
(15.54)
81.60
(15.9)
24.8
(7.80)
0.86
(0.22)
72.19
(19.5)
71.94
(21.84)
17.37
(4.96)
25.05
(5.63)
62.37
(13.52)
21.52
(6.49)
59.95
(12.74)
85.31
(12.38)
87.50
(16.25)
15.72
(4.38)
47.25
(11.2)
Other
cereals
52 .00
(10.2)
2.46
(0.61)
20.00
(3.9)
14.8
(4.65)
32.2
(8.05)
8.25
(2.23)
22.81
(6.92)
7.71
(2.19)
0.00 9.80
(2.12)
23.85
(7.19)
10.24
(2.18)
85.68
(12.44)
40.10
(7.45)
2.24
(0.62)
22.77
(5.4)
Total
cereals
167.00
(32.6)
134.93
(33.36)
144.55
(28.16)
186.4
(58.61)
132.53
(33.14)
119.77
(32.34)
123.32
(37.44)
170.63
(48.69)
192.21
(43.39)
85.35
(18.51)
84.71
(25.53)
113.96
(24.22)
218.93
(31.78)
146.20
(27.14)
167.87
(46.8)
139.08
(33.1)
Pulses 79 .00
(15.4)
68.67
(16.98)
69.21
(13.48)
21.3
(6.69)
41.25
(10.32)
38.44
(10.38)
32.52
(9.87)
35.2
(10.04)
24.03
(5.4)
18. 90
(4.1)
50.26
(15.15)
23.13
(4.92)
78.75
(11.43)
51.40
(9.54)
24.56
(6.85)
43.79
(10.4)
Sugar 42.00
(8.2)
11.37
(2.81)
5.06
(0.99)
10.6
(3.33)
16.83
(4.21)
59.11
(15.96)
15.64
(4.75)
14.28
(4.07)
12.99
(2.92)
78.97
(17.12)
34.87
(10.51)
15.03
(3.19)
28.85
(4.19)
36.60
(6.8)
12.49
(3.48)
25.37
(6.0)
Cooking oil 47.00
(9.2)
41.48
(10.26)
33.89
(6.6)
17.3
(5.44)
36.77
(9.2)
41.00
(11.07)
28.18
(8.55)
22.84
(6.52)
25.82
(5.81 )
32.35
(7.01)
27.91
(8.41)
27.55
(5.85)
59.60
(8.65)
43.80
(8.13)
32.46
(9.05)
33.90
(8.1)
Spices 20.00
(3.9)
12.97
(3.21)
50.13
(9.77)
6.1
(1.92)
9.56
(2.39)
14.70
(3.97)
9.21
(2.8)
14.1
(4.02)
26.40
(5.94)
50.07
(10.86)
8.44
(2.54)
14.89
(3.16)
36.08
(5.24)
26.80
(4.98)
10.69
(2.98)
20.60
(4.9)
Milk and
products
53.00
(10.38)
37.50
(9.27)
96.00
(18.70)
15.8
(4.97)
34.15
(8.54)
20.57
(5.56)
32.55
(9.88)
9.15
(2.61)
19.66
(4.42)
84.17
(18.25)
24.27
(7.32)
143.36
(30.47)
82.68
(12.0)
119.60
(22.21)
15.45
(4.31)
52.26
(12.50)
Poultry-
meat
44.00
(8.59)
7.42
(1.83)
42.50
(8.28)
35.1
(11.03)
54.47
(13.62)
15.13
(4.09)
16.54
(5.02)
16.48
(4.70)
64.35
(14.47) -
32.19
(9.7)
45.26
(9.62)
26.67
(3.87)
13.00
(2.41)
35.76
(9.97)
29.08
(6.9)
Fruits 15.00
(2.9)
5.90
(1.46) -
3.4
(1.07)
14.63
(3.66)
7.85
(2.12)
8.52
(2.59)
3.26
(0.93)
10.45
(2.35)
11.57
(2.51)
14.42
(4.35)
23.62
(5.02)
10.15
(1.47)
9.10
(1.69)
2.05
(0.57)
8.89
(2.1)
Vegetables 38 .00
(7.4)
74.65
(18.46)
71.92
(14.01)
13.6
(4.27)
50.67
(12.67)
53.70
(14.5)
59.31
(18)
61.88
(17.66)
68.02
(15.3)
89.70
(19.45)
43.61
(13.15)
52.34
(11.12)
72.40
(10.51)
70,10
(13.02)
45.70
(12.74)
55.57
(13.2)
Confectione
ry
2.00
(0.4)
9.54
(2.36)
8.5
(2.67)
8.99
(2.25)
0.00 3.62
(1.10)
2.65
(0.76)
0.00 10.12
(2.19)
11.04
(3.33)
11.40
(2.42)
6.00
(1.11)
11.65
(3.25)
5.03
(1.2)
Any other 5 .00
(0.98) - - - - - - - - - - -
74.80
(10.86)
16.0
(2.97) -
7.07
(1.7)
Total food 512.00
(47.5)
404.43
(78.33)
513.26
(73.27)
318.2
(54.4)
399.85
(68.9)
370.26
(79.6)
329.41
(51.06)
350.47
(50.76)
444.63
(75.51)
461.20
(65.17)
331.71
(54.67)
470.54
(78.05)
688.91
(62.83)
538.6
(66.45)
358.68
(69.73)
420.65
(64.0)
Education 49.00
(8.7)
13.95
(12.47)
32.06
(17.12)
22.2
(8.33)
38.08
(21.1)
0.00 22.76
(7.21)
37.9
(11.15)
17.37
(12.04)
49.01
(19.88)
39.37
(14.31)
10.29
(7.77)
55.40
(13.59)
49.80
(18.32)
25.45
(15.6)
29.61
(12.5)
Clothing 56 .00
(9.89)
18.64
(16.66)
23.50
(12.55)
34.9
(13.1)
39.39
(21.82)
26.77
(28.21)
23.81
(7.54)
61.57
(18.11)
43.96
(30.48)
72.32
(29.34)
24.28
(8.83)
54.79
(41.39)
38.59
(9.47)
23.40
(8.61)
27.01
(16.55)
34.70
(14.6)
Footwear 12.00
(2.12)
10.26
(9.17)
7.03
(3.75)
10.3
(3.87)
11.7
(6.48)
11.42
(12.03)
8.62
(2.73)
9.55
(2.81)
4.81
(3.34)
7.85
(2.85)
26.58
(20.08)
10.03
(2.46)
7.10
(2.61)
8.19
(5.02)
9.17
(3.9)
Fuel 24.00
(4.2)
16.08
(14.38)
56.06
(29.94)
34.0
(12.76)
32.29
(17.89)
0.00 61.4
(19.45)
62.49
(18.38)
58.33
(40.45)
93.17
(37.79)
26.84
(9.76)
8.13
(6.14)
43.67
(10.72)
19.60
(7.21)
27.18
(16.66)
34.85
(14.7)
Other items 425.00
(75.2)
52.93
(47.32)
68.61
(36.64)
165.0
(61.94)
59.03
(32.71)
56.71
(59.76)
199.16
(63.08)
168.53
(49.56)
19.75
(13.69)
32.03
(12.99)
176.71
(64.25)
32.56
(24.60)
259.82
(63.76)
172.00
(63.26)
75.35
(46.18)
128.70
(54.3)
Total Non
food
566 .00
(52.5)
111.86
(21.67)
187.26
(26.73)
266.4
(45.6)
180.49
(31.1)
94.90
(20.40)
315.75
(48.94)
340.04
(49.24)
144.22
(24.49)
246. 53
(34.83)
275.05
(45.33)
132.35
(21.95)
407.51
(37.17)
271.90
(33.53)
163.18
(31.27)
237.03
(36.0)
Total hh
expenditure
1078
(100.0)
516.29
(100)
700.52
(100)
584.6
(100.0)
580.34
(100)
465.16
(100.0)
645.16
(100.0)
690.51
(100.0)
588.85
(100)
707.73
(100)
606.76
(100)
602.89
(100)
1096.42
(100.0)
810.50
(100)
521.86
(100)
657.68
(100.0)
76
Table 3.6.1: Monthly consumption expenditure of households (Rs per capita) - Non-Participants
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Rice 117.00
(20.4)
57.86
(15.5)
34.41
(6.34)
142.7
(47.2)
93.74
(22.79)
34.99
(9.8)
30.45
(7.61)
160.57
(41.76)
169.97
(36.36)
11.80
(2.37)
37.53
(8.71)
43.89
(6.97)
55.16
(7.97)
20.60
(3.36)
152.47
(36.52)
75.52
(16.6)
Wheat 17.00
(3.0)
77.71
(20.85)
95.41
(17.59)
23..5
(7.78)
0.49
(0.12)
75.74
(21.22)
86.42
(21.61)
21.78
(5.66)
16.42
(3.51)
72.84
(14.64)
23.13
(5.37)
74.15
(11.78)
67.56
(9.76)
90.30
(14.71)
16.57
(3.97)
49.76
(10.9)
Other cereals 45.00
(7.8)
0.67
(0.18)
15.00
(2.77)
13.6
(4.5)
27.69
(6.73)
6.21
(1.74)
17.46
(4.37)
5.58
(1.45)
0.00 11.48
(2.3)
27.45
(6.37)
11.74
(1.87)
59.87
(8.65)
39.20
(6.39)
2.62
(0.63)
17.52
(3.8)
Total cereals 179.00
(3112)
136.26
(36.56)
144.82
(26.7)
179.8
(59.5)
121.92
(29.64)
116.95
(32.77)
134.33
(33.59)
187.93
(48.88)
186.39
(39.87)
96.12
(19.32)
88.11
(20.46)
129.78
(20.62)
182.59
(26.39)
150.20
(24.47)
171.66
(41.12)
142.81
(31.4)
Pulses 85.00
(14.8)
57.34
(15.4)
71.59
(13.20)
19.3
(6.39)
33.62
(8.17)
34.79
(9.75)
52.56
(13.14)
36.5
(9.49)
20.92
(4.48)
20.10
(4.04)
64.70
(15.02)
19.21
(3.05)
74.69
(10.8)
57.20
(9.32)
25.57
(6.12)
43.16
(9.5)
Sugar 41.00
(7.1)
11.94
(3.20)
9.64
(1.78)
10.2
(3.38)
15.58
(3.79)
56.73
(15.89)
18.61
(4.65)
13.41
(3.49)
12.04
(2.58)
80.89
(16.26)
38.43
(8.92)
13.27
(2.11)
32.88
(4.75)
45.50
(7.41)
12.66
(3.03)
28.07
(6.2)
Cooking oil 49.00
(8.5)
36.56
(9.81)
35.58
(6.56)
15.9
(5.26)
31.87
(7.75)
41.34
(11.58)
32.77
(8.19)
23.28
(6.05)
23.63
(5.05)
33.67
(6.77)
36.13
(8.39)
44.98
(7.15)
61.08
(8.83)
47.00
(7.66)
34.09
(8.17)
34.77
(7.6)
Spices 23.00
(3.9)
11.16
(2.99)
57.84
(10.66)
5.6
(1.85)
10.89
(2.65)
13.54
(3.79)
12.92
(3.23)
17.18
(4.47)
24.58
(5.26)
48.13
(9.68)
8.92
(2.07)
11.22
(1.78)
35.19
(5.09)
31.50
(5.13)
14.86
(3.56)
22.90
(5.0)
Milk and products 78.00
(13.5)
39.63
(10.63)
103.00
(18.99)
14.2
(4.7)
35.18
(8.55)
15.43
(4.32)
39.09
(9.77)
4.63
(1.20)
15.37
(3.29)
93.70
(18.84)
58.46
(13.58)
235.74
(37.45)
97.12
(14.04)
123.70
(20.15)
25.98
(6.23)
62.27
(13.7)
Poultry- meat 43.00
(7.5)
3.29
(0.88)
50.00
(9.22)
35.7
(11.81)
42.43
(10.32)
0.00 24.74
(6.19)
24.25
(6.3)
81.90
(17.52)
41.66
(9.67)
39.39
(6.26)
34.10
(4.93)
13.30
(2.17)
61.95
(14.84)
29.99
(6.6)
Fruits 21.00
(3.7)
25.24
(6.77)
0.0
(0.0)
15.0
(3.65)
14.03
(3.93)
12.86
(3.22)
4.44
(1.15)
12.48
(2.67)
14.12
(2.84)
22.14
(5.14)
47.52
(7.55)
12.35
(1.79)
17.40
(2.83)
3.81
(0.91)
13.59
(3.0)
Vegetables 49.00
(8.5)
44.68
(11.99)
70.00
(12.90)
13.2
(4.37)
40.65
(9.88)
64.12
(17.96)
67.76
(16.94)
69.09
(17.97)
90.17
(19.29)
95.35
(19.17)
48.35
(11.23)
53.17
(8.45)
78.89
(11.4)
77.70
(12.66)
51.19
(12.26)
61.96
(13.6)
Confectionery 3.00
(0.5)
6.62
(1.78) -
8.3
(2.75)
8.56
(2.08)
0.00 4.26
(1.07)
3.77
(0.98)
0.00 15.33
(3.08)
23.74
(5.51)
35.13
(5.58) -
9.00
(1.47)
15.71
(3.76)
8.06
(1.8)
Any other 4.00
(0.7) - - -
55.57
(13.51) - - - - - - -
82.96
(11.99)
41.4
(6.74) -
10.63
(2.4)
Total food 575.00
(43.07)
372.72
(79.8)
542.47
(72.28)
302.2
(53.0)
411.27
(77.28)
356.93
(71.86)
399.90
(54.43)
384.48
(50.43)
467.48
(86.74)
497.41
(61.87)
430.64
(51.19)
629.41
(77.49)
691.86
(70.64)
613.90
(69.2)
417.48
(65.87)
455.46
(62.7)
Education 87.00
(11.5)
13.16
(13.93)
36.00
(17.3)
17.1
(6.39)
35.43
(29.3)
0.00 26.38
(7.88)
41.55
(10.99)
11.85
(2.20)
52.13
(17.01)
54.00
(13.15)
19.96
(10.92)
36.75
(12.78)
24.40
(8.93)
20.31
(39.39)
32.33
(11.9)
Clothing 71.00
(9.3)
19.05
(20.16)
24.00
(11.54)
39.4
(14.7)
32.87
(27.18)
39.55
(28.29)
27.34
(8.17)
70.14
(18.56)
14.42
(2.68)
103.35
(33.72)
36.64
(8.92)
84.09
(46.0)
39.32
(13.67)
30.90
(11.3)
37.73
(17.44)
46.60
(17.2)
Footwear 14.00
(1.8)
11.51
(12.18)
6.25
(3.0)
12.6
(4.71)
10.63
(8.79)
15.84
(11.33)
13.04
(3.89)
12.12
(3.21)
3.97
(0.74)
9.60
(2.34)
34.72
(19.00)
10.29
(3.58)
9.40
(3.44)
11.41
(5.28)
10.67
(3.9)
Fuel 27.00
(3.6)
13.58
(14.37)
57.80
(27.78)
34.0
(12.7)
41.99
(34.73)
0.00 77.21
(23.06)
68.14
(18.03)
33.76
(6.26)
102.89
(33.57)
53.38
(13.00)
8.80
(4.81)
42.42
(14.75)
20.56
(7.52)
34.56
(15.98)
43.44
(16.0)
Other items 561.0
(73.9)
37.19
(39.4)
84.00
(40.37)
164.6
(61.49) -
84.40
(60.38)
190.84
(57.0)
185.91
(49.20)
7.45
(1.38)
48.12
(15.7)
256.98
(62.59)
35.22
(19.27)
158.83
(55.22)
188.00
(68.8)
112.28
(51.91)
138.19
(50.9)
Total Non food 760.00
(56.9)
94.50
(20.23)
208.05
(27.72)
267.7
(46.97)
120.92
(22.72)
139.79
(28.14)
334.81
(45.57)
377.86
(49.57
71.45
(13.26)
306.49
(38.13)
410.60
(48.81)
182.79
(22.51)
287.61
(29.36)
273.26
(30.80)
216.29
(34.13)
271.22
(37.3)
Total hh
expenditure
1335.00
(100.0)
467.22
(100)
750.52
(100)'
569.90
(100.0)
532.19
(100)
496.72
(100.0)
734.71
(100.0)
762.34
(100.0)
538.93
(100)
803.90
(100.0)
841.24
(100)
812.20
(100)
979.46
(100.0)
887.16
(100.0)
633.77
(100)
726.68
(100.0)
77
Table 3.6.2: Absolute and percentage break-up of MPCE by item group in 2009-10: all-
India, rural and urban – NSS 66th
Round (2009-10)
item group Monthly per
capita exp. (Rs.)
Percentage to total
MPCE
Rural urban rural urban
Cereals & cereal substitutes 145 162 13.8 8.2
Pulses & their products* 35 49 3.3 2.5
Milk & milk products 81 137 7.6 6.9
Edible oil 39 53 3.7 2.7
Egg, fish & meat 50 72 4.7 3.6
Vegetables 87 112 8.3 5.7
Fruits 26 63 2.4 3.2
Sugar, salt and spices 60 73 5.7 3.7
Beverages, refreshments & processed 78 159 7.4 8
Food total 600 881 57 44.4
Pan, tobacco & intoxicants 31 30 3 1.5
Fuel and light 85 138 8 6.9
Clothing & footwear$ 65 115 6.2 5.8
Education 38 161 3.6 8.1
Medical 57 99 5.4 5
Conveyance 36 112 3.5 5.6
Consumer services excl. conveyance 44 124 4.2 6.3
Misc. goods, entertainment 53 113 5 5.7
Rent 5 115 0.5 5.8
Taxes and cesses 2 16 0.2 0.8
Durable goods 36 81 3.5 4.1
Non-food total 453 1104 43 55.6
All items 1054 1984 100 100
Source: NSS Report No. 538: Level and Pattern of Consumer Expenditure, Ministry of Statistics and Programme
Implementation, Government of India, February 2012.
78
Table 3.7: Variability in Consumption and Income – Participants
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Description
Average household income
during the reference year (Rs.) 57234 46851 40882 32425 43244 91578 56239 55547 48236 36079 37778 41762 87867 75821 50116 37343
Average household consumption during the reference year (Rs.) 68518 24653 42882 15001 44605 30914 32748 40601 42127 21007 33864 37352 30844 6054 53502 28766
Coefficient of variation in income
across households 69.51 91.63 - 37.3 - 59.64 75.88 61.58 66.26 80.29 47.73 81.92 47.0 113 65.5 55.04
Coefficient of variation in
consumption across households 73.76 40.02 - 38.4 - 27.98 40.35 30.36 46.11 38.29 53.02 40.97 34.0 39.0 55.7 34.78
Gini coefficient of income 0.35 0.34 - 0.19 0.28 0.32 0.32 0.10 0.71 29.19 0.25 0.37 0.43 0.47 0.34 0.50
Gini coefficient of consumption 0.36 0.22 - 0.20 0.12 0.51 0.22 0.93 0.25 16.25 0.23 0.32 0.33 0.36 0.34 0.50
Table 3.7.1: Variability in Consumption and Income (Non-Participants)
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Description
Average household income during
the reference year (Rs.) 93144 54595 41610 35508 48305 335362 42661 62832 55452 29456 42976 67873 170440 82886 58319 49963
Average household consumption during the
reference year (Rs.) 78178 25471 42804 15533 41059 88902 28376 38381 40284 20207 39216 51685 44833 5210 58725 32494
Coefficient of variation in income across households 314.9 118.6 - 40.4 - 59.49 51.68 74.77 48.15 71.78 71.82 120.9 102 102 80.7 104.6
Coefficient of variation in consumption
across households 91.8 24.4 - 32.8 - 21.62 28.04 42.57 39.71 30.71 51.94 48.76 33.0 24.0 70.6 67.41
Gini coefficient of income 0.70 0.38 - 0.21 0.34 0.33 0.29 0.11 0.74 - 0.34 0.52 0.92 0.47 0.43 0.48
Gini coefficient of consumption 0.43 0.14 - 0.18 0.05 0.50 0.15 0.96 0.22 - 0.20 0.37 0.27 0.27 0.35 0.49
79
Table 3.8: Determinants of participation in NREGA (Logit function) (Dependent variable: Dummy HH participation in NREGA)
States
Employment
other than
NREGA
HH Income
other than
NREGA
HH
Size
Land
ownership
Dummy
Value of
HH Asset
Dummy
AAY
card
holding
Dummy
BPL card
holding
Dummy
SC
Dummy
ST
Dummy
OBC
Dummy
General Constant
No of
obser-
vation
Pseudo
R²
Log
Likeli-
hood
Karnataka Coffiencient 0.0004 -0.0000 0.216** -0.596*** -0.00*** 0.687 0.80*** 0.455 - -0.037 0.422 -0.081 254 0.10 -118.8
t-value 0.39 -0.95 2.2 -1.63 -1.91 1.45 1.65 0.7 - -0.06 0.66 -0.09 - - -
Uttar
Pradesh
Coffiencient - -0.000004 -.27*** 1.056*** -0.00001* -0.75 0.115 0.456 30.7 1.137 - 3.54 - 0.383 -
t-value - -1.09 -2.07 2.09 -5.306 -1.398 0.212 0.53 0.00 1.29 - 3.41 - -
Sikkim Coffiencient -0.0026* -0.000021 0.013 0.78 -0.000005 - 2.017* 2.70 3.222* 2.414 - -1.08 200 0.308 -69.28
t-value -2.15 -1.24 0.06 1.13 -1.71 - 3.86 1.64 2.47 1.91 - -0.69
Andhra
Pradesh
Coffiencient 0.002** - 0.675* 0.298 - - 0.523 1.607** 2.476* 1.095*** - -1.409 250 0.25 179.6
t-value 2.0 - 4.17 0.72 - - 1.09 2.44 3.23 1.96 - -1.65 - - -
Kerala Coffiencient - 0.0002* 0.311 - - - - - - - - - 0.369 -
t-value - 25.2 2.1 - - - - - - - - - - -
Haryana Coffiencient -0.002*** - 0.326* 0.00 - - 1.04*** 0.228 - - - -0.853 250 0.60 234.6
Significant - - - - - -
- - - - - - -
Madhya
Pradesh
Coffiencient -0.0019** -0.00** 0.305** 0.00 -0.00** 0.4229 0.337 1.465 2.099 1.347 0.148 -0.096 245 0.179 -101.75
t-value -2.36 -2.00 3.11 0.95 -2.44 0.58 0.83 1.13 1.57 1.09 0.11 -0.07 - - -
Chhattisgarh Coffiencient -0.009*** -0.00002** 0.26***
-0.007E-
08 -1.41E-06 0.5213 0.385 20.6*** 20.5*** 19.9*** - -0.00 240 0.134 -104.03
t-value -3.74 -1.96 2.57 -0.06 -0.06 0.71 0.62 15.64 16.27 16.04 - -12.63 - - -
Assam Coffiencient 0.086 -0.00 -0.049 0.063 -0.00*** - -0.013 0.134 0.045 -0.051 - -4.62* 250 0.075 -125.1
t-value 1.23 -0.381 -0.985 0.476 -1.602 - -0.08 0.797 0.206 -0.294 - -14.07 - - -
Punjab Coffiencient - -2.56E-05* 0.27* - -1.83E-05* 0.1 - -0.49 - -0.39 - 1.77 - 0.1 -170.21
Std. Error - -6.79E-06 0.13 - -4.59E-06 0.31 - -0.83 - -0.94 - 1.02 - - -
Maharashtra Coffiencient - -0.00004* 0.272 - - - - - 1.699 - - - - 0.2049
t-value - -4.04 2.18 - - - - - 2.27 - - - - - -
Himachal
Pradesh
Coffiencient 0.002*** -7.20E-06
**
-
0.19*** 2.18E-06 -3.00E-06 0.325 -0.027 -0.074 - 0.583 -0.252 2.87* 250 0.127 216.22
t-value 1.848 -2.1 -1.72 1.56 -0.965 0.455 -0.069 -0.136 - 0.855 -0.43 3.72
West
Bengal
Coffiencient -0.00073 -0.000008 0.293* 0.423 -0.000004
* 0.393 0.155 -0.108 -1.6* -0.487 - 1.33* 250 0.168 -104.09
t-value -1.04 -0.93 2.03 1.04 -3.61 0.44 0.41 -0.26 -2.92 -0.57 - 2.09 - - -
80
Table 3.9: Determinants of participation in NREGA (Logit function)
(Dependent variable: Dummy HH Member participation in NREGA)
States
Ka
rn
ata
ka
Sik
kim
Pu
nja
b
Ma
hara
shtr
a
West
Ben
gal
Age 0.036* 0.062* 0.0019 0.043* -0.008
Education -0.193** 0.182 0.09 -0.154* -0.070*
HH Size -0.133* -0.370* - - -0.036
Dummy Sex 0.251*** 0.58* 0.90* - 0.077
Dummy AAY card holding 0.527** - - - 0.542
Dummy BPL card holding 0.348 0.208 - - 0.127
Dummy SC -0.322*** 1.18 - 0.684* 0.429*
Dummy ST 0.083 1.25 - 1.143* -1.066*
Dummy OBC -0.291 1.001 - 0.829* 0.345
Marital status - - 1.37* -
Constant -0.930** - -2.63* - 1.99
No of observation 1024 615 - - 737
Log Likelihood -584.8 307.8 -418.5 - -351.17
Pseudo R2 0.12 0.14 0.08 0.128 0.035
81
Table 3.10: Determinants of participation in NREGA (OLS) (Dependent variable: No. of days per HH worked in NREGA)
States
Ka
rn
ata
ka
Sik
kim
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Employment
other than NREGA
-0.020** -0.0004* 0.022 -0.00179 -0.095* -1.791 -0.0033 -0.0117 0.0137 0.021***
HH Income
other than
NREGA
0.0000 -0.000003 0.0000 0.0001*** -0.00014 -0.0002* 0.0000 0.000044 -0.000024 -0.0003***
HH Size 0.414 0.0114 3.815 -0.393 2.87* 2.18** 0.837 2.12*** 1.00 -0.112
Dummy AAY card holding
8.505*** -10.95*** 13.25 - 11.003* -9.092 -7.82 5.795
Dummy BPL card holding
8.887*** 0.364* 33.35* -2.057 10.69 -4.112 1.318 10.68** 2.39 1.803
Dummy SC 0.805 0.430* -60.78*** 16.45** 33.07** 4.545 2.132 20.32 -2.19 -7.356
Dummy ST 2.989 0.460* -1.175 22.67** 25.63*** 13.057* -5.080 28.31 2.21 -11.51
Dummy OBC -5.844 0.386* -62.7*** 19.53** 24.06*** 7.073*** 2.127 16.34 -6.95 -11.92
Wage rate in NREGA
0.406* - 0.131 0.056 -0.998* - 0.289* -0.027 0.884* -
Value of Land
Owned
-0.0000 0.094 -1.37E-05 -8.90E-07 3.15E-06 1.791*** -0.000014* -0.00001*** 0.000004 5.796
Constant 1.806 0.271 81.81 54.17 109.84 43.135* 128.0* 33.21 2.198 47.41
No of observation 254 200 200 195 192 200 200 250 250 199
F* 10.64* 10.71 2.537 0.077 - 2.35 3.57 2.236 24.87 3.23
R² 0.28 0.337 0.107 0.036 0.205 0.1002 0.228 0.0473 0.489 0.146
82
Chapter 4
Work Profile under MGNREGA, Wage Structure and Migration Issues
4.1 Work profile under MGNREGA
Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) is being
implemented in India since 2006. The basic objective of the Act is to ensure livelihood and food
security by providing unskilled work to people through creation of sustainable assets. Under the
provisions of the Act, the State has to ensure enhancement of livelihood security to the
households in rural areas by providing at least one hundred days of guaranteed wage
employment to every household whose adult members volunteer to do unskilled work. In-built
with various transparency and accountability measures and provisions for social audits this Act
for the first time brings the role of the state as provider of livelihood.
In Chapter 2, we presented functioning of MGNREGA in different states based on the secondary
data. We observed that on average, at the all India, a total number of 45 person days per family
employment has been provided since the inception of the MGNREGA programme. To further
probe the various aspects of functioning of the MGNREGA, a primary field survey was carried
out in five districts each in 16 states with the participation of all AERCs in this study. The details
of the selected sample and households were discussed in Chapter 3. This chapter presents various
details of working of the MGNREGA in the selected states. Table 4.1 presents the work profile
under MGNREGA in the 16 selected states. According to our survey data, on average, less than
two members (1.7) per family were employed under MGNREGA. Among the selected states, the
average exceeded 2 members per family working in MGNREGA in Sikkim, Gujarat,
Chhattisgarh and Andhra Pradesh (Figure 4.1). It was between 1.5 and 2 members in Karnataka,
Haryana, Madhya Pradesh, Maharashtra and West Bengal. The states that employed less than 1.5
members per family were Uttar Pradesh, Bihar, Kerala, Assam, Punjab, Himachal Pradesh and
Rajasthan. The highest numbers of members employed under MGNREGA among the selected
households was found 2.8 members in Sikkim and lowest, 1.07 in Kerala.
83
Out of 1.68 members employed under MGNREGA at the aggregate, 0.98 members belonged to
male households and 0.70 members belonged to female households. Only in Gujarat and
Rajasthan, the numbers of female member per household working in MGNREGA exceeded that
of male and in Sikkim and Maharashtra their percentage was same. Against the average of 1.68
aggregate members per family, the average was 1.47 for the SCs, 1.67 for STs and 1.53 for the
OBCs. The SC and ST households’ average was highest 2.63 and 2.53 members in Gujarat and
lowest 0.22 and 0.19 members in Bihar, respectively.
4.2 How successful has been MGNREGA in providing 100 days employment
Under the MGNREGA Act, every family is guaranteed for 100 days employment. In Chapter 2,
we observed that only 2.43 crore families were provided 100 days employment in the country as
a whole during the whole period of MGNREGA under operation. Table 4.1 presents number of
days of work obtained by the selected households in different states. On an average, 68 days per
household employment was generated at the aggregate during the reference period in selected
states among our selected participants. Thus, number of days of employment generated among
our selected households was above the national average of 45 days of employment since the
84
inception of the programme and 54 days of employment generated at the all India during the year
2009-10 which coincides with our survey period.
Figure 4.2 shows the numbers of days of employment generated in different states among our
selected participants. The states that topped in employment generation included Maharashtra
(100 days), Haryana (94 days), Himachal Pradesh (92 days) and Rajasthan, Sikkim and Gujarat
(slightly above 80 days). The states that were slightly above or below the national average were
Madhya Pradesh, Karnataka, Kerala and Uttar Pradesh (between 80 to 60 days). The states that
lied at the bottom were Bihar (32 days), Andhra Pradesh (43 days) and Assam (48 days).
Among all households employed in MGNREGA, those who belonged to Scheduled Caste (SC)
and Scheduled Tribes (ST), observed 60 and 68 days of respective employment at the aggregate.
Maharashtra, Karnataka, Himachal Pradesh and Gujarat had highest employment among the SCs
and STs While Assam, Bihar, Andhra Pradesh, Chhattisgarh and Sikkim had the lowest
employment among these communities. Looking at the ratio of employment among the male and
female workers, numbers of days of employment was shared by male (37 days) and female (30
days) with a per cent share of 56 for male and 44 for female. Our sample percentage of male and
85
female work days compares well with the national average of 53 per cent for male and 47 per
cent for female employed in MGNREGA as shown in Chapter 2.
The households completing 100 days employment in the selected states is shown in Table 4.1
and Figure 4.3. Out of 16 states for which analysis is done only in 10 states information about
households completing 100 days of employment was available. Among these ten states, the
percentage of households who completed 100 days, only in Himachal Pradesh their percentage
was exceptionally high (85 per cent). In Haryana and Rajasthan, 48.5 and 44.5 per cent
households completed 100 days under MGNREGA. In Karnataka and Sikkim around 1/4th
of the
participant households completed 100 days of employment. In Bihar, Assam, Gujarat and West
Bengal only less than 5 per cent households completed 100 days and in Uttar Pradesh around 10
per cent households completed 100 days. At the aggregate, only 1/4th
of the selected participants
in these 10 states completed 100 days and thus at the aggregate only 68 days of employment was
generated under MGNREGA in the selected 16 states. In other words, MGNREGA was not quite
successful in providing social security to the households as households had to depend on other
activities for earning their livelihood as MGNREGA provided only 18 per cent share of the total
employment to the selected households (see Chapter 3).
86
Looking at the wage rate on which employment was provided, average wage rate at the
aggregate was recorded at 100 and it was not particularly different among male and female
(Table 4.1 and Figure 4.4). The highest wage was recorded in Haryana ( 150), followed by
Kerala ( 125), Punjab ( 123) and Himachal ( 110). Among the selected states lowest wage
rate was paid in Rajasthan ( 80), Chhattisgarh ( 83) West Bengal ( 84) and Karnataka ( 86).
However, in most of the states actual wage rate obtained under MGNREGA was below the
stipulated minimum wage rate fixed by the states under the Minimum Wages Act 1948. The
states that were found paying equal to stipulated minimum wages were Uttar Pradesh, Kerala,
Chhattisgarh, Himachal Pradesh and West Bengal. The other states paid less than the stipulated
minimum wages. The difference between the actual payment and minimum stipulated wages was
specifically high in Karnataka ( 33), Maharashtra ( 22), Rajasthan and Assam ( 21), Madhya
Pradesh ( 19), Andhra Pradesh and Punjab ( 14), Gujarat and Haryana ( 12) and Bihar
( 10)3. The wage difference among male and female and among various other socio-economic
communities was, however, not observed as is clear from Table 4.1. Last but not the least, the
average distance of work place form the residence or village of the households was less than 2
kilometers in all the states with few exceptions. In Gujarat, Rajasthan, Maharashtra, Haryana and
Uttar Pradesh work place was slightly more than two kilometers away from the residence/village
of the selected households. In other states, distance was less than 2 kilometers.
3 Source: Ministry of Labour New Delhi.
87
4.3 Major employment activities, assets created and their durability
There were mainly 9 major activities under which work was provided in MGNREGA. These
were rural connectivity, flood control and protection, water conservation and water harvesting,
drought proofing, micro irrigation, provision of irrigation to Panchayat land, renovation of
traditional water bodies, land development and any other work approved by the Ministry of
Rural Development (MRD). Table 4.2 shows activities in which employment was provided
under MGNREGA in the selected states. Among the selected households at the aggregate, the
highest work under MGNREGA was concentrated on rural connectivity which shared around 40
per cent of the total employment followed by water conservation and water harvesting which
shared 17 per cent of employment under MGNREGA (Figure 4.5). Land development (12 per
cent), renovation of traditional water bodies (11 per cent), flood control and protection (8 per
cent) and micro irrigation (5 per cent) were the other major activities of employment under
MGNREGA. Drought proofing and other irrigation works contributed less than 2 per cent
employment. The observations at the field level match well with the information compiled from
MGNREGA website presented in Chapter 2 according to which the highest employment was
recorded for water conservation, followed by rural connectivity, provision of irrigation, land
development, drought proofing, renovation of traditional water bodies and micro irrigation in the
descending order.
Box 4.1: Work participation in MGNREGA in Karnataka
1. Work participation in MGNREGA reveals that the household belonging to scheduled
castes were invariably over represented compared to their share in total households, while
participation of upper castes was less than their share in the population in all the selected
districts.
2. Marginal and small farmers among the land holding groups were observed also working
in the MGNREGA whereas large holding size did not have any representation in
MGNREGA.
3. Job cards were not issued to several families. In some cases, applications were pending
while in other cases people did not know how to apply. Provision should be made for oral
application as well for those who are illiterate.
4. Those with job cards did not know what next is to be done to obtain employment. As a
result most people with job cards did not apply for work and did not get any employment,
neither had they got any unemployment allowance as they did not know that they had a
right to unemployment allowance if not given employment.
5. It was observed that the participation rate of women was invariably equal and sometime
higher than men across all the social groups, occupational groups, farm size groups and
economic groups.
88
Among the selected states, rural connectivity and water conservation were the main activities in
Karnataka, Uttar Pradesh, Bihar, Kerala, Madhya Pradesh, Assam, Himachal Pradesh, Gujarat
and Rajasthan. Land development was the main activity in Haryana and Andhra Pradesh while
renovation of traditional water bodies was the main activity in Chhattisgarh and Punjab. The
other major activities included flood control and protection in Sikkim, Himachal Pradesh and
Gujarat; drought proofing in Karnataka and Rajasthan; micro irrigation in Bihar, Andhra Pradesh
and Rajasthan. Thus, the projects undertaken by the Panchayats under MGNREGA were based
on the local requirements that shape up very well with the basic objective of the MGNREGA
programme.
On the question of how was the quality of the assets created through MGNREGA work, a little
less than half of the households indicated that the assets created were very good while another
half of them indicated that assets created were of the good quality. Only less than 3 per cent
households pointed out that the assets created were bad or worst in quality. A clear majority of
the households indicating good quality assets created through MGNREGA programme was
across the board in all the states without any exception. The question of quality and desirability
89
of the assets created and work undertaken will be further discussed and verified in the next
chapters.
As per the provisions under the Employment Act, after registration if a household is not provided
employment, he or she is entitled for unemployment allowance. In our above discussion we have
seen that only 25 per cent of the selected households were provided hundred days employment
under MGNREGA. We enquired the selected households whether after registration if they did
not get employment did they receive any unemployment allowance, households indicated that
they did not receive any such allowance (Table 4.2) except in Maharashtra and West Bengal
where households received only a poultry amount as unemployment allowance.
4.4 Migration issues under MGNREGA
One of the main objectives of MGNREGA Programme was to provide employment to wage
earners and landless unskilled labourers within the periphery of the village so as to prevent their
mass exodus towards cities and towns. In our primary survey we tried to find out the extent of
migration among the households after implementation of MGNREGA. Among our selected
participants how many members migrated from the village because of not getting work under
MGNREGA even after registration? Table 4.3 presents the statistics whereby it is seen that
around 0.20 members per family (with average size of 4.7 members) migrated because of not
getting work under MGNREGA. Out of the selected states, the numbers of per family members
migrated because of not getting work averaged at 0.54 in Assam, 0.44 in Rajasthan, 0.31 in
Madhya Pradesh and Maharashtra each, 0.20 in Andhra Pradesh, Chhattisgarh and Himachal
Pradesh, each and less than 0.1 members in rest of the selected states. Thus, incidences of
villagers’ migration in search of work despite having been registered for MGNREGA were still
recorded in the surveyed villages. Was there any incidence of members returning back to village
because of work now being available within the village after implementation of MGNREGA?
The statistics in the table reveals that there were some such incidences observed in the villages
surveyed. Around 0.12 members per family among the participant households returned back to
the village to work under MGNREGA at the aggregate who hitherto were working elsewhere
before the implementation of this Programme. The members retuning back to work under
MGNREGA was highest in the state of Bihar where around 0.65 members per family returned
90
back to work under MGNREGA after the implementation of the Act. The high incidence of
migrated unskilled workers returning back to work in MGNREGA in Bihar supplement the
increasing shortage of agriculture labour in Punjab and Haryana who hitherto were doing wage
work in agriculture in these two states. Among other states, the incidence was recorded in
Andhra Pradesh, Rajasthan, Madhya Pradesh and Maharashtra where, on average, 0.1 to 0.2
members per family returned back to work in MGNREGA after implementation of the Act.
Punjab, Haryana and Assam were the only states where no such reverse migration incidences
were recorded. On the overall, it is difficult to say whether the MGNREGA programme has been
successful in cutting down the incidences of labour migration from villages in search of job.
Another related question is how the MGNREGA programme has affected the labour supply for
the agricultural sector. In the next two chapters, we will further elaborate the issue of migration
based on qualitative information obtained from the households surveyed as well as the group
discussion held in the surveyed villages.
To a further question to the household members who returned back to work under MGNREGA,
where were they earlier working before returning back, majority of them replied that they were
working in the same state in the nearby town or nearby district headquarters. About the activity
in which they were earlier working, an absolute 2/3rd
majority replied that they were working in
construction, manufacturing and mining and rest 1/3rd
were working in the agricultural and other
activities. A majority of the members who migrated to work under MGNREGA came back to the
village either in the previous year of the reference period or a year before. The majority of the
households who returned back to work in MGNREGA pointed out that they were now better off
compared to earlier working as a migrant labourer.
4.5 Wage differentials in different activities
As we stated earlier, the wage rate received by the households under MGNREGA averaged
around 100 and the wage rate differences across male and female were not observed.
Comparing wages among different activities for male, wage rate averaged at 100 in agriculture
compared to 127 in non agriculture. The wage obtained by the migrant male workers averaged
at 133 while wage rate was recorded at 112 for those who were working in public work
programmes other than MGNREGA where wages were sometime paid partly in cash and partly
91
in kind. Comparing wage rates across gender, male workers obtained slightly higher wage rate
compared to female workers in all activities except the wage rate in MGNREGA where male and
female wage rate was almost similar. Among different states, wages were comparatively higher
in richer states like Kerala, Haryana, Andhra Pradesh and Punjab and lower in poor states like
Madhya Pradesh, Chhattisgarh, Uttar Pradesh and Bihar. However, wages were observed
comparatively low in well off states like Maharashtra, Gujarat, Karnataka and Assam. The least
variation in wages was found in the case of MGNREGA. Last but not the least, although
MGNREGA wage rates were less than the stipulated minimum wage rate in many states but it
was not less than the prevailing wage rate for the unskilled labour in agriculture and other
activities. The wage rate earned by the migrant workers was comparatively higher than that
obtained by the people working in MGNREGA in almost all the states. That also explains why
some migration incidences were recorded whereby some people preferred to migrate to the
nearby town or city rather than working under MGNREGA in the village. Another important
observation was that the prevalence of wage rate in MGNREGA was much more symmetric
compared to all other activities.
4.6 Summary of the chapter
This chapter presents functioning of the MGNREGA in the selected states. According to our
survey data, on average, less than two members (1.7) per family were employed under
MGNREGA. Against the average of 1.68 aggregate members per family, the average was 1.47
for the SCs, 1.67 for STs and 1.53 for the OBCs. On an average, 68 days per household
employment was generated among our selected participants. Looking at the ratio of employment
among the male and female workers, numbers of days of employment was shared by male (37
days) and female (30 days) with a per cent share of 56 for male and 44 for female. Out of 16
states for which analysis is done only in 10 states information about households completing 100
days of employment was available. At the aggregate, only 1/4th
of the selected participants in
these 10 states completed 100 days. Looking at the wage rate on which employment was
provided, average wage rate at the aggregate was recorded at 100 and it was not particularly
different among male and female. The difference between the actual payment and minimum
stipulated wages was specifically high in Karnataka ( 33), Maharashtra ( 22), Rajasthan and
Assam ( 21), Madhya Pradesh ( 19), Andhra Pradesh and Punjab ( 14), Gujarat and Haryana
92
( 12) and Bihar ( 10). Last but not the least, the average distance of work place form the
residence or village of the households was less than 2 kilometers in all the states with few
exceptions.
Among the surveyed households, the highest work under MGNREGA was concentrated on rural
connectivity which shared around 40 per cent of the total employment followed by water
conservation and water harvesting which shared 17 per cent of employment under MGNREGA.
Land development (12 per cent), renovation of traditional water bodies (11 per cent), flood
control and protection (8 per cent) and micro irrigation (5 per cent) were the other major
activities of employment under MGNREGA. Only less than 3 per cent households pointed out
that the assets created were bad or worst in quality. Households who did not get employment
after registration did not receive any unemployment allowance except in Maharashtra and West
Bengal where households received only a poultry amount as unemployment allowance. On the
issue of migration, the incidences of households migrating from village to cities were recorded
even after registration in MGNREGA and after not getting sufficient work. At the same time,
some households were retuning back to work in MGNREGA and hence it is difficult to say
whether the MGNREGA programme has been successful in cutting down the incidences of
labour migration from villages in search of jobs. The majority of the households who returned
back to work in MGNREGA pointed out that they were now better off compared to earlier
working as a migrant labourer.
93
Table 4.1: Work profile under MGNREGA (Reference period- Jan-Dec 2009)
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Characteristics Aggregate
No of members
per hh employed
during the year
Aggregate 1.81 1.42 1.26 2.80 2.01 1.07 1.73 1.80 2.21 1.25 1.10 1.88 1.12 2.31 1.41 1.74 1.68
SC 1.74 1.49 0.22 1.60 2.42 1.00 1.66 1.71 2.08 0.46 1.11 1.51 1.03 2.63 0.95 1.89 1.47
ST 2.24 1.50 0.19 3.00 1.73 1.00 - 2.02 2.31 0.08 - 2.27 1.41 2.53 1.46 1.62 1.67
OBC 1.72 1.38 - 2.60 1.84 1.07 1.74 1.72 2.10 0.38 1.00 1.75 1.17 2.11 0.95 1.44 1.53
General 1.84 1.14 - 0.50 1.97 1.30 1.75 1.20 2.75 0.33 1.00 1.50 1.06 1.33 1.43 1.65 1.38
Men 1.02 0.97 - 1.40 1.09 - 1.11 - - 0.81 0.83 0.94 - 0.99 0.60 0.98 0.98
Women 0.78 0.45 - 1.40 0.92 - 0.62 - - 0.45 0.27 0.94 - 1.32 0.81 0.76 0.70
No of days per
hh employed
during
the year
Aggregate 76.00 61.33 31.79 81.20 43.10 63.29 94.20 78.73 48.57 48.23 54.15 101.89 92.28 80.94 82.14 54.00 68.24
SC 78.00 63.37 21.61 4.70 43.62 70.63 89.70 76.73 61.81 17.56 47.62 102.71 88.13 75.29 68.58 50.00 60.00
ST 125.00 67.50 23.31 46.40 59.58 77.02 - 80.83 42.44 4.35 - 114.85 91.96 91.43 84.96 46.50 68.30
OBC 58.00 60.40 - 29.70 40.85 62.84 91.00 82.05 54.23 13.47 4.47 80.64 91.95 80.39 61.99 44.80 57.12
General 76.00 57.71 - 0.40 35.89 58.96 126.30 56.00 35.83 12.86 2.06 120.08 93.04 51.00 87.53 58.60 58.15
Men 44.00 46.19 - 44.40 23.42 - - - - 38.95 40.28 50.01 - 31.60 30.06 30.40 37.83
Women 32.00 15.14 - 37.20 19.68 - - - - 9.28 13.87 51.88 - 49.34 52.08 23.60 30.41
Wage rate
obtained
(Rs.)
Aggregate 86.00 100.00 98.98 100.00 97.56 125.00 149.60 91.10 83.23 86.12 123.00 87.82 110.47 87.53 79.14 84.42 99.37
SC 82.00 100.00 98.98 100.00 97.15 125.00 149.90 91.55 78.69 88.03 123.00 76.08 111.66 82.40 62.48 84.13 96.94
ST 93.00 100.00 98.98 100.00 63.90 125.00 147.00 90.63 83.20 87.84 - 101.07 112.43 98.43 84.33 84.18 94.50
OBC 89.00 100.00 - 100.00 100.44 125.00 149.90 91.24 82.85 83.05 123.00 78.78 104.68 85.62 63.24 82.38 97.28
General 86.00 100.00 - 100.00 84.65 125.00 147.80 91.00 88.20 86.13 123.00 77.00 105.20 57.58 81.27 84.85 95.85
Men 86.00 100.00 - 100.00 97.56 125.00 149.60 91.10 83.23 86.20 123.00 87.82 110.47 88.69 78.76 84.42 99.43
Women 85.00 100.00 - 100.00 77.00 125.00 149.60 92.05 83.12 85.76 123.00 84.08 109.74 86.85 79.99 84.47 97.79
Minimum wages for unskilled
agricultural workers fixed by
state (Source: Ministry of Labour, New Delhi) as on
30.4.2010 (Rs)
119.4 100.0 109.0 - 112.0 125.0 162.0 110.0 80.8 106.7 136.8 110.0 110.0 100.0 100.0 81.0 -
Average distance from
residence where employed (Kms)
1.77 2.18 1.0 1.10 2.00 1.53 2.23 1.11 1.37 1.11 1.98 2.53 1.48 5.00 2.54 0.80 1.86
Percentage of HH employed 100 or more days
24.88 10.5 5.31 26.90 - - 48.50 - - 1.50 - - 85.00 2.35 44.50 1.00 25.04
94
Table 4.2: The activity in which employed under MGNREGA and the quality of assets created (Reference period- Jan-Dec 2009) (% of hh)
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Characteristics Aggregate
Name of the activity
under which
employed
Rural connectivity 38.7 27.1 50.7 50.6 4.0 88.5 6.0 48.9 35.8 70.0 48.1 10.1 47.1 22.1 40.1 47.0 39.7
Flood control and protection 0.0 4.3 42.9 0.0 0.0 8.0 4.1 1.9 10.0 0.0 0.0 25.4 29.1 1.4 0.0 7.9
Water conservation and
water harvesting
20.4 24.3 10.2 0.0 22.5 5.0 0.0 30.0 2.6 10.0 0.0 74.6 13.0 30.3 20.3 14.4 17.3
Drought proofing 10.6 0.0 2.4 6.4 0.0 0.0 0.0 0.6 0.6 0.0 0.0 0.0 2.7 2.0 5.0 0.0 1.9
Micro irrigation works 2.0 8.1 13.9 0.0 27.0 0.0 0.0 1.1 0.0 0.0 0.5 8.1 2.4 0.6 5.3 9.3 4.9
Provision of irrigation facility to
land owned by (Panchayat)
3.1 2.3 0.4 0.0 5.0 1.5 0.0 0.0 1.3 0.0 0.0 0.0 7.9 3.6 0.8 0.3 1.6
Renovation of traditional water bodies
12.1 15.9 8.7 0.0 0.0 3.5 0.0 3.5 48.6 10.0 40.0 0.0 0.3 3.6 4.5 19.2 10.6
Land development 4.2 14.1 4.6 0.0 41.5 1.5 84.5 4.6 3.8 0.0 0.0 0.0 1.2 7.8 21.4 6.0 12.2
Any other activity approved by
the Min of R. Dev.
9.0 8.3 4.8 0.0 0.0 0.0 1.5 7.2 5.4 0.0 11.4 7.3 0.0 0.8 1.1 3.9 3.8
Quality of assets
created through NREGA
activities
Very good 24.3 43.0 0.0 81.3 24.5 80.5 78.5 51.4 45.5 32.5 15.5 34.2 33.5 60.5 40.0 13.0 41.13
Good 73.8 57.0 100.0 16.9 75.5 19.0 21.5 48.6 54.5 47.0 84.0 61.5 66.5 35.8 56.5 68.5 55.41
Bad 1.25 0.00 0.00 1.90 0.00 0.50 0.00 0.00 0.00 20.0 0.50 0.0 0.00 1.74 3.00 1.50 1.90
Worst 0.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0 0.0 0.00 1.95 0.50 0.0 0.19
No response 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.00 0.00 0.00 0.00 17.00 1.31
Average unemployment allowances received by the
household for not getting work under NREGA after
registration (Rs. Per hh)
0.00 0.00 0.0 0.00 0.0 0.00 0.00 0.00 0.00 0.00 0.0 27.8 0.00 0.00 0.00 2.43 1.89
95
Table 4.3: The migration incidents recorded during the Reference period - Jan-Dec 2009
Characteristics
Ka
rn
ata
ka
Bih
ar
AP
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
No of members migrated from the village because of not getting work under NREGA even after registration (per household)
0.08
0.00 0.20 0.31 0.20 0.54 0.05 0.31 0.19 0.06 0.44 0.05 0.20
No of out-migrated members returned back to village because of getting work in
NREGA (per household)
0.07 0.65 0.20 0.14 0.07 0.00 0.00 0.11 0.05 0.05 0.18 0.05 0.12
In the case some members returned back to the village to work under
NREGA where were they earlier
working (% of returned members)
Nearby village 0.00 16.70 0.00 0.00 68.18 0.00 0.00 4.55 66.67 0.00 30.00 0.00 18.61
Nearby town 33.33 11.64 70.00 71.43 31.81 0.00 0.00 45.45 22.22 0.00 20.00 17.14 32.30
Same district 6.67 11.60 20.00 14.29 0.00 0.00 0.00 18.18 11.11 0.00 20.00 14.29 11.61
Same state 60.00 15.80 10.00 14.29 0.00 0.00 0.00 22.73 0.00 100.0 10.00 8.57 24.14
Other state 0.00 44.26 0.00 0.00 0.00 0.00 0.00 9.09 0.00 0.00 20.00 60.00 13.34
Other country 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
In the case some members returned
back to the village to work under NREGA which activity earlier working
in (% of returned members)
Const/ manufacturing/mining 61.54 47.75 60.00 81.48 70.37 0.00 0.00 16.39 77.78 88.89 60.00 70.21 63.44
Trading/services and transport 0.00 8.33 40.00 0.00 0.00 0.00 0.00 0.00 0.00 11.11 0.00 8.51 6.80
Private work/self business 0.00 1.75 0.00 0.00 0.00 0.00 0.00 0.00 11.11 0.00 10.00 0.00 2.29
Other government work 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.46 0.00 0.00 0.00 2.13 0.46
Agriculture labour 23.08 36.89 0.00 3.70 18.51 0.00 0.00 8.20 11.11 0.00 30.00 19.15 15.06
Any other 15.38 5.00 0.00 14.81 11.11 0.00 0.00 72.95 0.00 0.00 0.00 0.00 11.93
Year in which shifted (% of shifted hh) Shifted last year 76.92 37.40 80.00 100.0 100.0 37.04 33.00 2.44 100.0 100.0 63.30 85.71 67.98
Shifted before last year 23.08 62.60 20.00 0.00 0.00 62.96 67.00 97.56 0.00 0.00 36.70 14.29 32.02
Is your family better off now compared to previous occupation (% of shifted hh) 63.64 37.00 100.0 - 100.0 - - 67.65 100.0 77.78 50.00 97.14 77.02
96
Table 4.4: Wage differentials among different activities – Participants
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Occupation Participants (Average)
Wage rate in agricultural casual labour (Rs.)
Male 88.00 86.90 90.90 82.32 150.60 225.35 171.00 63.14 62.37 71.25 140.50 62.22 115.50 84.11 86.20 77.49 103.62
Female 76.00 65.28 87.00 78.06 91.60 193.72 160.00 52.85 61.76 64.11 55.60 49.02 100.00 82.93 66.30 67.05 84.46
Wage rate in non
agricultural casual labour
(Rs.)
Male 134.00 104.34 102.50 91.53 177.00 277.65 161.00 95.28 76.12 98.87 148.60 83.19 145.00 123.39 123.40 91.92 127.11
Female 130.00 77.00 83.10 86.93 126.80 239.43 162.00 67.27 71.87 66.92 42.30 55.91 120.00 125.01 73.60 68.35 99.78
Wage rate in public work programmers (Rs.)
Male 55.00 106.62 92.33 - 200.00 - 200.00 88.79 84.09 78.00 - 200.00 110.00 100.91 - - 119.61
Female 64.00 108.33 89.71 - 150.00 - - 77.50 60.00 - 110.00 100.00 175.00 - 103.84
Wage rate earned
by migrant workers (Rs.)
Male 118.00 118.72 128.00 - 228.60 - - 103.38 86.69 98.57 148.60 131.61 157.00 133.82 152.90 121.25 132.86
Female 125.00 - 92.43 - 188.20 - - 60.00 - 108.87 122.20 90.00 120.00 113.34
Wage rate under
NREGA (Rs.)
Male 86.00 100.00 - 100.00 97.56 125.00 149.60 91.10 83.23 86.20 123.00 87.82 110.47 88.69 78.76 84.42 99.43
Female 85.00 100.00 - 100.00 77.00 125.00 149.60 92.05 83.12 85.76 123.00 84.08 109.74 86.85 79.99 84.47 97.79
Table 4.4.1: Wage differentials among different activities - Non-Participants
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Occupation Non-Participants (Average)
Wage rate in agricultural
casual labour (Rs.)
Male 89.00 98.05 114.00 82.50 152.40 252.78 156.00 61.81 60.75 72.05 142.80 70.74 110.00 84.44 96.50 77.19 107.56
Female 73.00 60.00 85.90 78.75 89.00 226.25 151.00 50.00 58.33 59.21 58.70 46.25 95.00 78.98 66.70 60.45 83.60
Wage rate in non agricultural casual
labour (Rs.)
Male 160.00 112.11 128.00 93.75 179.80 285.00 168.00 117.80 80.05 96.81 149.30 114.61 146.70 136.05 139.10 85.01 137.01
Female 134.00 75.30 74.00 89.06 121.20 250.00 178.00 60.00 80.00 66.03 63.50 96.33 121.50 109.17 81.00 50.50 103.10
Wage rate in public
work programmers (Rs.)
Male - 108.33 100.20 - 200.00 - - - 85.00 80.00 - - 110.00 100.00 - - 111.93
Female - 108.33 76.32 - 150.00 - - - - 60.00 - - 110.00 100.00 - - 100.78
Wage rate earned
by migrant workers (Rs.)
Male 93.00 111.42 175.12 - 228.00 - - 167.00 94.00 96.10 149.30 151.42 160.00 130.57 181.90 94.50 140.95
Female - - 81.00 - 189.00 - - - - - - 103.75 - 117.47 - - 122.81
97
Chapter 5
The Functioning of MGNREGA – Qualitative Aspects
5.1 Household assets holding
This Chapter summarizes some of the qualitative facts about the functioning of the MGNREGA.
But before looking into the qualitative factors, we briefly present the financial condition of the
selected households. Tables 5.1 and 5.1.1 presents all physical and financial assets held by the
selected households. The list of assets include agricultural land and other agricultural
implements, house property, livestock, consumer assets and belongings, business and financial
assets, household ornaments and utensils and other transport means such as two wheelers like
scooters, motor bikes and four wheelers like cars, jeeps etc. Per household land and implements
owned by the participant households averaged at slightly above 1 lakh compared to around 2
lakh by the non participant households. Similarly, house property owned by the participants was
slightly less than 1 lakh while it was slightly above that amount in the case of non participants.
The value of livestock averaged at 7.7 thousand for participants and above 10 thousand for
non participants.
Consumer assets including durables and non durables averaged slightly above 5 thousand for
the participant households and slightly above 10 thousands for the non participant category.
The participants hardly had any business or financial means while non participants recorded
more than 6000 such assets. Compared to consumer and business assets, ornaments recorded
quite high value of above 10 thousands for participants and more than double value of that for
the non participants. All the surveyed households had poor means of transportation as their
average value was almost negligible. At the aggregate, the value of assets owned by participants
were 2.2 lakh against more than double amount of 4 lakh owned by the non participants. The
above statistics indicate far better financial position of the non participants compared to
participant households. Comparing the selected states, the assets value was highest in Kerala,
followed by Maharashtra, Himachal Pradesh, Karnataka, Uttar Pradesh and Gujarat among both
participants and non participants.
98
5.2 Household status on borrowings and their financial vulnerability
Table 5.2 and 5.2.1 present borrowing by the sample households. The total loan amount by
participants was far above that of non participants. The total amount outstanding at the time of
survey among the participants was 49 thousand by participants compared to 28 thousand by
the non participants. Looking at the major sources of loan, institutional loans constituted 51 per
cent among the non participants while only 45 per cent among the participant households.
Among the non institutional sources, relatives and friends with comparatively much lower
interest rate constituted around 12 to 14 per cent share among both participant and non
participants households indicating that they highly relied on relatives and friends for providing
them the necessary insurance against the internal and external shocks and making for their
consumption smoothing4. Money lenders, commission agents, landlords and employer were the
other major sources of borrowing for both participants and non participants. Glancing at the
purpose for which loan was availed by the selected households, it is seen from the statistics that
the loan availed was mostly for consumption in both the categories. The activities like purchase
of land, purchase of machinery or vehicle constituted less than 25 per cent of the loan value
among both participant and non participant households. Construction of house was a major
investment activity which constituted around 19 per cent of loan among the participants but only
12 per cent among the non participants. Thus most of the loan taken by both these categories was
for daily or durable consumption and health treatment.
Among participants, the institutional loans constituted 100 per cent share in Uttar Pradesh,
Haryana and Himachal Pradesh while their share was above 50 per cent in Sikkim and Madhya
Pradesh. The states where non institutional loans constituted more than 2/3rd
share included
Karnataka, Bihar, Andhra Pradesh, Kerala, Chhattisgarh, Maharashtra, Rajasthan and West
Bengal. The pattern of borrowing among non participants was somewhat similar to participating
households. In the Haryana state participants used the whole loan amount for the productive
purposes like purchase of land or livestock. Among other states where participants utilized at
least 1/4th
amount for the productive uses were Uttar Pradesh, Sikkim, Chhattisgarh, Assam,
Gujarat and Rajasthan. In rest of the states almost whole amount of borrowing was used for
consumption purposes.
4 See, e.g., Kumar and Singh (in press).
99
Checking with the financial strength on borrowing (Table 5.3) around 10 per cent of
participating households indicated that they are doing wage work for those with whom they are
indebted, whereas 8 per cent of the non participating households indicated the same. Around half
of the selected households pointed out that there was a cooperative society in their village but
less than ¼th
of the households were members of such society within their village. Similarly
more than ⅔rd
majority of the household agreed that there was at least one informal credit society
or self help group in their village but only ⅓rd
of the selected households were members of such
societies. More than ¾th
of all selected households had an account in the bank or post office but
only 2 per cent of the selected households had any financial assets, like stock, bond or share of a
company. Similarly, less than 15 per cent participant households and around 20 per cent non
participant households had a life insurance policy.
Among the selected participants, around 30 per cent households in Bihar and Karnataka were
doing wage work to those whom they were indebted. In Kerala, Rajasthan and Assam, above 10
per cent households were doing wage work in lieu of borrowing. The household membership of
cooperative societies was high among participants in Kerala, Uttar Pradesh and Himachal
Pradesh (above 60 per cent of the households). Similarly, membership of informal credit
societies was found high (above 50 per cent) in Karnataka, Uttar Pradesh, Andhra Pradesh,
Kerala and Himachal Pradesh. Above 50 per cent participant households in all the selected states
indicated that they had account in a bank or post office as in most of the cases, wages under
MGNREGA were paid either through bank or post office. Among all the selected states very few
households had any financial assets but ownership of life insurance policy was found among
more than 1/4th
of the selected households in Kerala, Bihar and Uttar Pradesh.
Thus, from the above analysis it is clear that participant households were more vulnerable
compared to non participant households. Whereas, participant households owned assets around
half that of non participant households, their borrowing level was more than that of non
participant households. Not only was the loan amount higher for the participant households, their
proportion of non institutional loan was also higher. The fact that more participant members did
wage work for those whom they were indebted compared to non participant households indicate
financial vulnerability of people working under MGNREGA for whatever period they were
100
provided employment. In the next section we will go through some of the qualitative aspects of
MGNREGA functioning.
5.3 Some qualitative aspects of MGNREGA
5.3.1 Job card issues and work applications
Table 5.4 presents qualitative aspects of functioning of MGNREGA programme. Regarding job
card insurance, a majority of the households responded that they did not pay any changes or
bribe for getting a job card issued. Only 7 per cent participant households in Karnataka and 11
per cent in Rajasthan pointed out that they paid some fee or bribe to get a job card. Regarding
irregularities in the job card around 15 per cent households at the aggregate indicated that either,
no entry was made in the job card about the work performed under MGNREGA or entries were
missing or fake; entries were over written or signature column was blank, while clear cut
majority observed no such irregularities. The irregularities were reported in Maharashtra, Bihar,
Assam, Karnataka, Madhya Pradesh and Chhattisgarh. On the question where the job card was
generally kept, more than 80 per cent participants indicated that the card was kept with them
while rest of the 20 per cent indicated that the card was kept either with the sarpanch or sachiv
or contractor or gram-rojgar sevak or elsewhere but not with them. The incidence of job card not
being placed at the owner was most prevalent in Karnataka, Haryana, Kerala and Punjab.
Around 80 per cent of the household were given employment in response to their application for
work. However, only half of the participants indicated that they got a written receipt when they
put up their application for work and they obtained work within the bound period of 15 days of
their application. All households with a few exception indicated that they did not get any
unemployment allowances in lieu of not getting work within the period of 15 days after putting
up their application for work under MGNREGA.
5.3.2 Payment of wages and related issues
On the system of payment of wages almost all participating households agreed that wage rate for
male and female was same. The payment system was both daily-wage basis and piece rate/task
wage basis. The participants worked mostly on daily wage basis in Uttar Pradesh, Sikkim,
Kerala, Assam, Punjab and Himachal Pradesh. The work was piece rate or task wage basis in
101
Madhya Pradesh, Chhattisgarh, Maharashtra, Rajasthan and West Bengal. The participants
worked on partly on daily wage and partly on piece meal basis in Karnataka, Bihar, Andhra
Pradesh and Gujarat. In majority of cases, work was measured on collective or team management
basis while in a thin majority it was measured on individual work basis. A majority of participant
households pointed out that wages were paid either fortnightly or monthly basis but around 12
per cent participants pointed out that they had to wait for a longer period or at least more than a
month to realize their wages from MGNREGA work.
It is interesting to note that majority of the participants (more than half of them) obtained their
wages through bank. Another 40 per cent of the participant indicated that they obtained wage
through the post office. Only 5 per cent of the interviewed household obtained their wages
through Sachiv /Contractor/others and this fact makes MGNREGA programmes different from
all other employment generation programmes under operation in different states. Further with a
few exceptions, the bank accounts were on the individuals’ name working in MGNREGA. Out
of the interviewed participant, around 85 to 90 per cent indicated that banks followed the usual
procedure in their functioning and wages were paid in front of them by making entry into their
accounts. However, those who were not paid through bank or post office, a majority of them
indicated that wages were paid in front of the labourers either on the worksite or some other
public or private place. Among the irregularities in wage payments, the participant households
indicated that there was delay in wage payments after the work was finished; the wage paid was
less than the task performed and the participants faced problem in accessing post office or bank
account and lastly they were not aware on what basis wages were determined in case of those
whom wages were not paid on daily wage basis. Delay in wage payment was reported by highest
numbers of participants in Andhra Pradesh, Chhattisgarh, Madhya Pradesh, Gujarat and
Rajasthan.
5.3.3 Worksite facilities and economic usefulness of the work
Regarding information about the work to be performed and facilities available at the worksite,
around ⅔rd
majority of participants pointed out that they were given requisite details of the work
to be performed. About the facilities available at the worksite, around ¾th
of the participants
agreed that drinking water facility was provided at the worksite. About the facilities like shade
102
for period of rest; child care facilities; first aid kit and primary medicines available at the
worksite around 40 to 50 per cent participants replied that these facilities were not available on
the work site. Lack of drinking water, child care and medicine facility at the work place was
mostly reported by participants in Karnataka, Haryana, Madhya Pradesh and Punjab.
5.3.4 Monitoring of the work
On the monitoring of the MGNREGA functioning more than 80 per cent participants indicated
that the work was being monitored through some authority but majority of them did not know
whether any auditing of the accounts take place or not. In Haryana around 80 per cent
participants indicated that there was no monitoring taking place while 16 per cent expressed their
unawareness and only 4 per cent participants indicated that there was monitoring of MGNREGA
work was being held. In all other states more than 60 per cent participants indicated that the work
was being monitored. Very few participants lodged any complaint, or in other words, very few
participants were aware how to lodge a complaint if the households were not satisfied with the
functioning of MGNREGA. Even a thin majority who indicated that they lodged a complaint
only 7 per cent of them said that their complaints were taken care of.
5.3.5 Nature of assets created and their durability
In another set of questions, we enquired about the nature of work and about the assets created.
Around 90 per cent of the participated households pointed out that the work done was useful to
the villagers. Only less than 10 per cent households pointed out that the work done was not
particularly useful for the villagers. To the question of how long the constructed structure may
last, around 30 per cent opined that it may not last more than one year while around 40 per cent
expressed hope that the structure will last up to five years. Only 30 per cent interviewed
households expressed that structure will continue five to ten years or may even last more than ten
years. More than ¾th
majority of the participant households pointed out that it was worth to
create the structure or in other words, created structure would be useful for the villagers.
Similarly, slightly above ⅔rd
majority of the households indicated that the structure created was
adequate with due attention being paid to it.
5.3.6 Labour migration and MGNREGA
103
In Chapter 4, we presented cases of migration of labourers from the village for not getting work
under MGNREGA and also those cases where labourers migrated back to village for working
under MGNREGA. In this chapter, we further elaborate some qualitative factors of labour
migration related to MGNREGA functioning. After implementation of MGNREGA in 2005-06,
was there any case whereby household members migrated out of the village in search of job?
Around 18 per cent of the respondents indicated yes to the above question and a majority of them
pointed out that only one member of the family migrated in search of job. Only in Andhra
Pradesh, Kerala and Haryana, no migration of any member was reported while all other states
some migration incidents were reported. The migrated members obtained higher wages
compared to the prevailing wage rate under MGNREGA as was also seen in chapter 4.
Regarding members migrating back to the village for working under MGNREGA or migrating
from the village not being satisfied working under MGNREGA, only a few cases (8 per cent
households in the former and 5 per cent households in the latter case) were found affirmative on
the above question. Thus, some incidents of migration out of the village as well as migration
back to the village (to work under MGNREGA) were cited, but the extent of the same was only
miniscule, not leading to the conclusion that MGNREGA had any conclusive evidence of
affecting labour migration into any particular direction. Some household members migrating out
for job after implementation of MGNREGA among the selected states was observed
comparatively higher in Bihar, Gujarat, Assam, Rajasthan and Maharashtra. However, in Bihar
and Maharashtra the incidence of family members migrating back to village to work under
MGNREGA was also found higher than the other states indicating the reverse migration
occurring along with the incidence of migration among the participant households.
5.3.7 Respondents’ awareness about MGNREGA implementation
Regarding the question of villagers’ awareness about ‘MGNREGA Act’ under implementation in
the village, around 88 per cent of the respondents pointed out that people in the village were
aware about the same. About 67 per cent respondent pointed out that they were aware about their
right to apply for work and get employed within a period of 15 days after getting registered for
the same. Around 62 per cent respondents indicated that they were aware about the work
application procedure and 69 per cent knew about the right to minimum wages. Similarly, a clear
majority of the respondents knew about the level of minimum wages in the state and how wage
104
rate was being worked out under MGNREGA. In last chapter we saw that unemployment
allowance was not being paid to those who registered for work and were not being provided
work within the stipulated period of 15 days. On our further questioning, we observed that
households were completely unaware about the provision of unemployment allowance under
MGNREGA. More than 70 per cent households were not aware or not sure about the right to
unemployment allowance. Similarly, majority of the respondents were not aware about provision
of the worksite facilities, mandatory availability of muster rolls at the worksite and list of
permissible works under the MGNREGA.
5.3.8 Potential benefits of MGNREGA
To understand how the MGNREGA programme has affected the general life of villagers we
enquired few questions related to participants’ day-to-day life. Around 67 per cent participants
were of the view that MGNREGA has enhanced food security of the villagers by providing them
employment and thus purchasing power to have better access to food. Around 60 per cent
participants pointed out that MGNREGA has given greater independence to women. Around 65
per cent agreed that MGNREGA provided protection against extreme poverty. On the migration
issues, around 49 per cent indicated that MGNREGA has helped to reduce distress migration
from the village to cities. Similarly, around 50 to 60 per cent pointed out that MGNREGA has
reduced indebtedness by generating purchasing power at the local economy.
5.3.9 MGNREGA and food security
We further probed the food security issues among the participants. To our question did your
family get full two square meals throughout the reference year, around 24 per cent households
answered in negative. If the households did not have sufficient food how did they cope up with
the situation? Around 37 per cent affected households indicated that they borrowed from some
sources to cope up with the situation. Around 13 per cent pointed out that they reduced the
numbers of meals during the crisis period while others took other measures like catching fishes
or rats etc. The states where maximum number of households indicated not having two square
meals among the selected states were the poor states of Assam and Bihar while in the states of
Haryana and Andhra Pradesh no household reported not having sufficient meal during any
month of the reference year.
105
Box 5.1: Impact of MGNREGA on the Villagers – A Case from Karnataka
The employment created through MGNREGA is expected to have an impact on the individual workers
who participate in the programme at the household level and at the village level. Prima facie
evidences collected from the households during the discussion with the villagers indicated that per
household employment gain under MGNREGA for the state during the years 2007, 2008, 2009 was
around 20 to 40 man days. It varied across the districts. At the aggregate level, the number of wage
days worked under non MGNREGA was high for participates signifying that MGNREGA has played
a complementary role and not a substitute. Self employment days were less for participating
households indicating that they had substituted MGNREGA work to their regular self employment
work, which fetched them perhaps regular and higher income as compared to income from the self
employment. Participates prefer to remain unemployed or not available for work instead of taking up
low paid or unwanted work. Wage employment from MGNREGA was found competing with non-
MGNREGA wage employment. Still MGNREGA has not been successful in substituting non
MGNREGA employment in the chosen districts. Number of days of self-employment has come down
sharply for participating households as compared to non-participants. This indicates that wage
employment (under MGNREGA) has been substituted for self-employment, in the latter there is also a
higher degree of disguised unemployment and that explain the reason for the shift towards
MGNREGA employment. The survey revealed that guarantee of employment at the minimum wage
has increased the staying power of workers and they prefer to wait rather than to accept low paid
work, and hence the number of days of unemployment has increased. This also means that
MGNREGA has not provided adequate employment to the workers and the programme has widened
the choice of employment for the participant households to some extent. Participants felt that due to
MGNREGA migration has been avoided. The participants across the selected districts were of the
view that MGNREGA has contributed to useful assets for the villagers. Both the participants and non-
participants felt that there was a rise in market wages due to MGNREGA and also labour scarcity is
happening in peak season in agriculture. Participants felt that MGNREGA has helped them in
sending their children to school. MGNREGA was also useful for the debt repayment. The improved
purchasing power through MGNREGA also contributed to coping illness among the participating
members. Average wage earned by male participants under the programme was around Rs 100 that
were found equal to the prevailing market rate in the village. On the other hand, female average wage
under MGNREGA was around Rs 90 that was much higher than the average market wage that
prevailed somewhere around Rs 50. For that reason women appear to have substituted self
employment with MGNREGA work relatively more than their male counterpart. Wage rates have
increased in agriculture as well as non agriculture for male as well as female. While talking to
farmers it was observed that in agriculture, the percentage increase in wage rate ranged up to Rs 100
and for women up to Rs 150. After MGNREGA wage rate in village tend to be equal for both male
and female. The equalization of wages across gender and space has improved labour ties in the
village.
106
5.4 Some quantification of qualitative questions
We further tried to quantify some aspects of the functioning of MGNREGA. We probed those
participants who indicated that the job card was not kept with them, what was the reason for the
same. A 3/4th
majority of those who did not have job card with them were not knowing the real
reason for not having card with themselves while rest 1/4th
of them replied that the head of the
Panchayat (Sarpanch) or contractor had kept it with themselves to make entries in the card or for
security reasons (Table 5.5). To our question who monitored the functioning of MGNREGA?
Around 11 per cent participants said it was supervisor while around the same numbers also
indicated that the person was some government official at the block or district level. However, a
clear majority (around 50 per cent) named the Gram Panchayat or Panchayat Secretary mainly
functioning for the monitoring work of MGNREGA. The rest of the participants (less than 1/3rd
)
were not knowing whether there was any monitoring being carried out or if so who carries out
the same. The matters on which complaint was lodged by the participants included, tools not
working properly, job card not returned, wage rate paid was low or wage rate not paid on time
and complaints for not following rules in the functioning of the MGNREGA. Among the
participants who lodged complaint only less than 10 per cent of them pointed out that either
action was taken or they were assured that proper care will be taken in the future. However, a
majority of those who lodged the complaints were not sure whether any action was taken or not.
5.5 The effect of MGNREGA on rural livelihood
During our field survey, we tried to capture how have the MGNREGA affected the livelihood of
the participant households. We further probed some question related to food security, poverty,
indebtedness and distress migration. We asked the participants how MGNREGA has enhanced
food security, a majority of the participants pointed out that by providing employment
MGNREGA has helped their food security during the working days, moreover by saving some
money when they are employed, they now have better food security when they are not employed
in MGNREGA as well. However, overwhelming majority indicated that MGNREGA can ensure
better food security by guaranteeing at least 100 days employment to every household and the
programme would be more useful in ensuring food security if they are also provided food at the
work place.
107
To the question how MGNREGA provided protection against extreme poverty, the respondents
were of the view that although MGNREGA provided extra purchasing power and reduced
migration but it could be more effective if it could provide full 100 days work; provide wage on
daily basis; stipulated minimum wage are ensured; and poorest people are given top priority. To
the question of migration, a significant number of respondents pointed out that to some extent
MGNREGA have been successful in reducing the distress migration but it can be more effective
in stopping unnecessary migration if 100 days work and minimum stipulated wages are ensured.
Similarly, respondents agreed that indebtedness to informal sources would also be checked if
MGNREGA provides employment to people at higher wage rate compared to prevailing wage
rate within the village.
5.6 Suggestions to raise efficacy of MGNREGA
Finally we enquired the households what problems they faced during the reference year and how
to ameliorate them. For example, those households who did not have sufficient food last year in
their opinion what was the reasons for the same. Around 30 per cent of them responded that no
opportunity for work was the reason for the same. Another 20 per cent indicated that low wage
rate, lack of access to PDS food was the reason. The other reasons pointed out by the households
were low household income, indebtedness etc. The major problems other than food during the
last year faced by the households included health, unemployment, high education expenditure,
shelter and indebtedness.
The suggestions given by households to ameliorate their problems includes providing
employment opportunities throughout the year; provision of concessional food and other
essentials through improved efficacy of government programmes; additional employment during
the off-season of agriculture among many others. Among the major suggestions to improve
MGNREGA functioning, an absolute majority of the respondents (40 per cent) pointed out that
the number of working days and wage rate should be increased under MGNREGA and work
should be available throughout the year. Respondents pointed out that the stipulated minimum
wages should be ensured in practice. A significant numbers of them pointed out that the
implementation should be improved though local bodies and job card should be given in the
hands of the workers. The other minor suggestions included quick payment after work, hundred
108
days mandatory work for all, provision of concessional loans, food facility at the work place,
preference to manual work rather than machine, proper measurement of the work, better
implementation with in-built monitoring system, transparency and accountability in
implementation, better awareness and more innovative work should be allowed under
MGNREGA. Last and the least, private farm work should be allowed to maintain continuity in
the MGNREGA works.
Box 5.2: Field observations and recommendations - Karnataka
Planning process at the Gram Sabha level was found to be far from satisfactory. The awareness level at
the village/mandal clearly points out the need for altering the administrative machinery at all levels
including district, mandal/block and village level. Applications for work deserves much higher attention
as paying unemployment allowance and provision of work were all attached to the application for work
which the households were found completely unaware because ground level procedure was not found in
proper order for putting up an application for work. Simplifying and strictly imposing these provisions
will go a long way in making the MGNREGA programme much more effective. Working conditions at
the worksite were mostly found to be satisfactory. Worksite facilities and child care facilities require
much attention. Overall, wherever the PRI officials at the village and mandal level were active, the
MGNREGA work was implemented with enthusiasm. Enough funds should be provided to Panchayats
to ensure minimum wages to the workers. Officials need to take interest frequently visiting the
worksites, enthusing gram sarpanch and other village officials to take up work actively and also assist
in conducting gram sabhas. Services of village organizations, e.g., Self Help Groups, NGOs and other
existing organizations should also be used to increase the efficacy of MGNREGA. Earlier employment
programmes like Food for Work (FFW) encountered problems in implementation like leakages and
involvement of contractors. There is a need for innovative administrative arrangements to overcome
such problems in the case of MGNREGA. The agriculture sector is undergoing structural change
whereby the large holdings are getting fragmented into small and marginal holdings and because of
increasing cost in agriculture the latter are finding it difficult to make earning in the agriculture sector.
The challenge Karnataka state is facing is to ensure higher participation of women, providing hundred
days employment to all who wish to participate in MGNREGA including the small and marginal
farmers, ensure stipulated minimum wage under MGNREGA and create productive assets under
MGNREGA at the village level that can sustain in the long run.
Suggestions to improve the programme:
A large scale, intensive awareness campaigns about MGNREGA and bringing into notice of the
people about its benefit and other legal provisions in all villages/communities.
Women need to be involved in the monitoring through their grass root organizations such as
SHGs and SHG federations which need to be empowered for the task through amendments in
the law.
Representative of women organizations should be invited to attend the quarterly review
meetings on MGNREGA at the district level.
Regular orientation and sensitization programmes for selected representatives need to be
conducted.
Panel provisions relating to the violations of MGNREGA law needs to be made rigorous in
order to deter corrupt practices and such panel provisions need to be publicized widely.
109
5.7 Summary of the Chapter
The analysis in this chapter points that participant households were much more vulnerable
compared to non participant households. Whereas, participant households owned assets less than
half that of non participant households, there borrowing level was almost double that of non
participant households. Not only was the loan amount higher for the participants, their proportion
of non institutional loan was also much higher. On the qualitative questions, a majority of the
households indicated that they did not have to pay any bribe to get a job card issued. Around 80
per cent of the household were given employment in response to their application for work. All
households who did not get work within 15 days indicated that they did not get any
unemployment allowances. On the system of payment of wages almost all participating
households agreed that wage rate for male and female was same. The payment system was both
daily-wage basis and piece rate/task wage basis. It is interesting to note that majority of the
participants obtained their wages through bank or post office. On the monitoring of the
MGNREGA functioning more than 80 per cent participants indicated that the work was being
monitored through some authority but majority of them did not know whether any auditing of the
accounts take place or not. Around 90 per cent of the participated households pointed out that the
work done was useful to the villagers. Some incidents of migration out of the village as well as
migration back to the village (to work under MGNREGA) were cited, but the extent of the same
was only miniscule, not leading to the conclusion that MGNREGA had any conclusive evidence
of affecting labour migration into any particular direction. Regarding the question of villagers’
awareness to the programme they were hardly aware about the provision of unemployment
allowance under MGNREGA. On the efficacy of MGNREGA in providing food security,
removing poverty and providing safeguards, the participants agreed that MGNREGA has been
successful in helping the poor on all these aspects, but they were of the view that MGNREGA
could have done far better if it could ensure hundred days of work to every participant and could
provide the minimum stipulated wage rate to all those who worked in MGNREGA programme.
The major suggestions given by the households to improve MGNREGA functioning included,
increased number of working days and wage rate; improved implementation through local
bodies; quick payment after work; hundred days mandatory work for all; provision of
concessional loans; and food facility at the work place.
110
Table 5.1: Assets holding (Rs per HH) – Participants
Sta
tes
Ka
rna
tak
a
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
ha
rash
tra
HP
Gu
jara
t
Ra
jast
han
Wes
t B
eng
al
Ag
greg
ate
Particulars Participants
Land and
agricultural
implements
111038 155919 83500 69996 3349 467816 47275 124979 151282 36704 1150 262166 245705 66283 55000 40909 121047
House
Property
89139 71890 85500 50200 1284 312359 30823 83038 55101 25351 36748 51121 76990 39642 95225 35645 71493
Live stock 6499 9755 8900 4324 281 3263 3728 3630 9964 1368 3385 24279 16796 9834 13866 3322 7768
Consumer
assets
5659 1198 - 4446 190 29828 4363 2715 3279 1151 4703 3886 9055 4448 5954 3067 5254
Business
assets
272 35 - 2309 273 11001 250 0 0 3209 775 0 750 1033 1228
Ornaments 10853 8943 550 5362 218 61290 196 4940 6897 10762 2067 4849 33605 10502 12961 3883 11180
Utensils 3160 635 1000 3369 20 1205 1017 573 487 1838 1524 3420 1964 2383 1168 1462
Transport
means
2984 733 2475 392
Others 154 3008 1200 2413 169 38750 1112 50 1200 231 5102 240 3007 0 23 3557
Total 229758 251383 180650 142418 5784 924306 88952 220367 228296 79263 50624 352927 386586 135680 188612 89050 223382
111
Table 5.1.1: Assets holding (Rs per HH) - Non Participants
Sta
tes
Ka
rna
tak
a
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
ha
rash
tra
HP
Gu
jara
t
Ra
jast
han
Wes
t B
eng
al
Ag
greg
ate
Particulars Non- Participants
Land and
agricultural
implements
349037 263902 109500 81407 26472 705532 30000 455584 242364 29301 12100 828921 395860 267350 77300 134394 235392
House
Property
111944 110440 120000 62375 5192 550000 27260 113500 76660 17702 53784 74512 116420 53548 100300 112810 104247
Live stock 20074 42100 15000 6823 918 4063 3380 5800 11524 3370 6360 22870 16500 9810 6130 4126 10915
Consumer
assets
7750 1403 - 8450 1015 89615 5160 5674 5560 1000 7870 13907 21260 8352 8742 8698 11911
Business
assets
4259 - 2500 14531 994 72500 0 0 0 4680 1610 800 0 1075 1700 6074
Ornaments 23750 10740 1050 14656 1990 118000 126 17462 11159 3659 5636 10122 51840 12952 24600 13370 19351
Utensils 4352 828 900 4313 168 1391 3568 980 747 1761 2643 6680 1956 4347 1863 2234
Transport
means
5178 - 7939 4274 1534
Others 537 5072 1500 988 944 35200 1028 200 0 724 33885 2420 3416 100 92 4920
Total 526881 434485 250450 193542 37694 1574910 68345 601788 348247 61183 95450 988470 611780 357384 226868 277053 396578
112
Table 5.2: Borrowing by sample households (percentage of household) – Participants
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Occupation Participants
Source
of loan
Institutional loan (banks) 32.54 100.00 34.14 73.48 27.20 28.18 100.00 58.98 22.19 23.41 100.00 43.05 38.90 32.56 44.66
Traders-cum-Money Lenders 13.61 29.15 8.26 10.37 7.72 0.00 10.09 13.99 77.43 72.34 63.46 0.00 0.00 35.70 32.95 23.44
Commission Agent 7.10 - 3.91 1.05 0.00 0.00 2.85 6.77 22.57 0.00 0.00 0.00 2.20 0.73 2.95
Landlord/Employer 4.73 10.50 3.91 5.22 20.51 0.00 0.00 33.52 17.58 1.35 0.00 10.72 3.30 3.13 7.15
Friends/Relatives 12.43 26.21 10.43 0.17 43.59 0.00 16.06 21.97 10.07 10.66 0.00 40.18 19.70 12.30 13.99
Others 29.59 - 56.00 0.00 - 12.03 1.55 1.12 0.00 6.05 0.30 18.34 7.81
Purpose of loan
Daily consumption 15.12 17.43 1.67 10.00 41.10 15.03 0.00 1.97 2.30 4.97 3.41 4.69 15.45 22.96 13.00 18.57 11.73
Social ceremony 22.09 15.62 6.63 10.43 2.03 9.06 0.00 41.27 39.07 22.57 44.14 58.48 3.09 0.00 16.50 15.53 19.16
Health treatment 9.88 1.26 24.02 4.35 7.52 9.47 0.00 10.88 2.87 9.70 12.82 8.23 0.62 1.26 13.60 10.21 7.92
Purchase of land/ livestock 0.58 23.29 13.27 33.04 7.67 12.26 100.00 0.00 35.43 29.80 9.16 2.61 15.96 26.79 30.30 14.07 22.14
Purchase of machinery/vehicle
2.33 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.15
Consumer durables 5.81 0.00 0.00 0.00 3.91 11.89 0.00 0.00 0.00 0.37 0.00 2.87 3.30 0.00 1.76
Construction of house 19.19 16.04 54.41 24.78 5.67 19.57 0.00 15.72 12.59 32.96 21.43 10.63 36.05 0.00 4.60 23.24 18.55
Purchase of livestock/land 3.49 0.00 0.00 0.00 0.00 - 0.00 0.00 0.00 0.00 0.00 0.22
Others 21.51 26.36 - 17.39 32.11 22.73 0.00 30.16 7.75 9.16 14.99 28.84 46.12 18.70 18.38 18.39
Amount
Borrowed
Total loan borrowed
(Rs. Per household)
57147 3585 4768 1438 59380 341254 250 3866 7384 2215 2730 10461 4855 2613 9221 2399 32098
Total loan outstanding at the
time of survey
(Rs. Per household)
37548 3585 3768 1438 33250 659974 250 3816 4569 2215 2730 10461 4855 2613 9221 2399 48918
Rate of interest (Per cent per annum)
9.50 13.96 17.75 24.00 10.53 13.00 25.30 10.56 10.00 36.00 16.50 8.70 10.00 27.00 36.26 16.82
113
Table 5.2.1: Borrowing by sample households (percentage of household - Non Participants
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Occupation Non-Participants
Source
of loan
Institutional loan (banks) 48.48 100.00 33.94 82.96 31.92 100.00 0.00 38.76 53.20 0.00 0.00 76.52 100.00 0.00 73.31 25.48 50.97
Traders-cum-Money Lenders 9.09 0.00 27.52 5.14 10.47 0.00 0.00 0.00 0.00 0.00 16.67 7.88 0.00 5.08 31.29 7.54
Commission Agent 9.09 0.00 0.00 6.11 0.00 0.00 0.00 54.26 0.00 59.09 0.00 0.00 0.00 0.00 8.57
Landlord/Employer 9.09 0.00 27.52 0.00 3.81 0.00 0.00 0.00 0.00 83.33 3.28 64.38 2.48 0.00 12.93
Friends/Relatives 3.03 0.00 11.01 5.79 0.00 0.00 0.00 3.88 38.57 40.91 0.49 27.04 18.82 36.19 12.38
Others 21.21 0.00 0.00 53.81 0.00 3.10 8.23 11.82 8.58 0.31 7.03 7.61
Purpose
of loan
Daily consumption 9.09 18.03 14.68 9.97 43.85 0.00 0.00 0.00 14.45 100.00 22.75 6.25 16.51 17.04
Social ceremony 21.21 17.05 24.77 5.14 0.00 0.00 0.00 15.50 18.45 26.36 83.33 3.28 72.96 15.73 0.00 20.25
Health treatment 18.18 1.25 5.50 0.00 8.69 8.06 0.00 6.98 6.47 8.64 31.20 0.00 4.33 16.82 7.74
Purchase of land/ livestock 3.03 19.84 20.18 27.01 12.16 27.42 0.00 38.76 36.89 38.86 13.79 4.29 49.54 11.21 20.20
Purchase of
machinery/vehicle
9.09 0.00 0.00 0.00 0.00 - - 0.00 0.00 0.00 0.00 0.00 0.61
Consumer durables 3.03 0.00 0.00 3.86 6.02 0.00 0.00 0.00 0.00 3.28 0.00 4.95 0.00 1.41
Construction of house 6.06 15.41 34.86 2.57 0.00 64.52 0.00 0.00 24.64 26.14 0.00 0.00 3.72 1.53 11.96
Purchase of livestock 0.00 0.00 0.00 0.00 0.00 - 0.00 0.00 0.00 0.00 0.00 0.00
Others 30.30 28.43 - 51.45 29.28 0.00 - 38.76 13.55 16.67 33.99 0.00 15.48 53.92 20.79
Amount
Borrowed
Total loan borrowed (Rs. Per household)
32426 3050 5450 3888 31530 92857 - 2580 2631.7 4400 1440 6767 2600 4660 16150 1962 14159
Total loan outstanding at the time of survey
(Rs. Per household)
30815 3050 5450 3888 17265 310000 - 2580 4066 4400 1440 6767 2600 4660 16150 1962 27673
Rate of interest
(Per cent per annum)
10.00 13.00 19.33 24.00 10.00 36.40 18.87 10.00 36.00 8.80 10.00 10.80 12.00 28.82 16.53
114
Table 5.3: Household saying yes to the following questions on strength on borrowing (Percentage of households) – Participants
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Occupation Participants
Doing wage work to those
whom they are indebted
28.64 0.00 30.00 0.00 4.00 17.50 - 7.00 8.00 13.50 5.00 9.80 0.00 2.50 10.50 4.00 10.22
Availability of co-operative credit society in village
47.24 67.50 60.00 37.50 0.00 90.00 20.00 69.00 78.50 0.00 74.00 47.55 56.50 50.00 50.00 40.00 49.24
Family member being member
of such society
26.06 64.50 30.00 31.30 7.60 64.00 5.00 0.00 0.00 0.00 0.00 11.27 60.50 13.50 13.00 10.50 21.08
Availability of informal credit
society/SHG in village
88.44 78.50 20.00 50.00 80.40 85.50 13.00 71.50 69.00 40.50 60.00 97.06 88.00 70.00 30.00 90.00 64.49
Family members being member of such society
57.73 54.00 10.00 18.10 80.40 68.00 7.00 6.50 5.50 3.50 3.50 45.59 51.00 10.00 35.00 42.00 31.11
Having account in a bank/post
office/other institution
85.07 100.00 90.00 100.00 56.00 95.00 53.00 88.00 86.50 100.00 74.00 93.63 99.50 100.00 100.00 100.00 88.79
Having any stocks/bond/
shares/other similar assets
11.17 0.00 0.00 0.00 11.40 3.50 8.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.50 2.35
Having life insurance policy 19.47 22.50 40.00 8.10 8.40 57.50 10.00 5.50 4.00 15.50 0.50 4.90 2.50 7.00 9.50 13.00 14.27
115
Table 5.3.1: Household saying yes to the following questions on strength on borrowing (Percentage of households) - Non
Participants
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Occupation Non-Participants
Doing wage work to those
whom they are indebted
10.91 8.00 16.00 2.50 2.60 0.00 - 0.00 0.00 18.00 0.00 13.33 4.00 18.00 14.00 2.00 7.96
Availability of co-operative
credit society in village
54.72 24.00 50.00 37.50 0.00 76.00 10.00 76.00 82.00 0.00 82.00 57.78 10.00 50.00 52.00 40.00 43.88
Family member being member
of such society
15.79 30.00 10.00 30.00 2.00 48.00 10.00 8.00 6.00 0.00 3.00 22.22 20.00 26.00 0.00 14.00 15.31
Availability of informal credit
society/SHG in village
87.04 62.00 10.00 50.00 80.00 62.00 8.00 82.00 76.00 38.00 65.00 91.11 50.00 70.00 26.00 90.00 59.20
Family members being member of such society
46.00 52.00 8.00 20.00 80.00 48.00 8.00 14.00 12.00 3.10 5.00 35.56 50.00 18.00 8.00 32.00 27.48
Having account in a bank/ post office/other institution
75.93 72.00 30.00 100.00 43.20 70.00 44.00 50.00 52.00 62.00 56.00 71.11 40.00 56.00 60.00 90.00 60.77
Having any stocks/bond/
shares/other similar assets
10.00 0.00 0.00 30.00 3.20 12.00 8.00 0.00 0.00 0.00 0.00 2.22 2.00 0.00 0.00 0.00 4.21
Having life insurance policy 28.85 20.00 20.00 40.00 2.20 68.00 14.00 14.00 12.00 14.00 2.00 28.89 0.00 22.00 12.00 22.00 20.00
116
Table 5.4: Qualitative questions related to functioning of MGNREGA (Percentage of HH)
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Description Yes
Job card
issuance
Paid any fees/Charges or bride to get a job
card
7 0 0 0 1 0 0 0 1 0 5 11 2
Irregularity
in the
Job card
No entries were made , even though the job
card holder(s) had worked on MGNREGA
17 0 30 10 9 3 16 16 22 4 45 0 23 20 13
Some entries were incomplete or missing or
fake information was entered
20 0 30 12 1 7 7 60 9 9 0 21 31 13
Some entries had been over-written 18 0 10 7 1 4 4 0 7 2 0 16 7 5
The signature column was blank or partly blank
27 2 15 15 5 11 30 60 9 7 1 23 18 14
Where
was the card
generally
kept
With the card holders 33 95 60 100 100 77 50 95 95 70 81 88 92 96 80 100 82
With Sarpanch or Sachiv 35 5 0 21 40 6 6 0 19 1 8 4 6 9
With Contractor 18 20 1 6 0 0 0 0 1 0 3
With the Gram Rojgar Sevak 7 20 1 0 0 0 30 0 0 1 4
Elsewhere 7 0 0 5 0 0 0 0 0 14 2
Work
application
Are you employed in response to an
application for work
77 72 60 100 90 75 67 96 18 100 94 56 100 91 93 100 80
If applied, did you get a dated receipt for the
application
48 72 50 78 80 74 65 37 35 48 55 99 88 28 19 55
If applied, did you get work within 15 days of application
55 83 100 85 100 66 77 3 0 70 7 73 100 91 75 73 66
In case of failure to provide work within 15
days, is unemployment allowance paid
6 32 0 80 0 71 0 0 0 9 0 0 0 5 13
Payment of wages
Are the wage rates same for men and women 78 100 100 100 90 100 71 100 100 100 100 99 100 97 98 84 95
Wage rates higher for men 18 0 0 10 0 22 0 0 0 0 4 3 17 4
Wage rates higher for women 1 0 0 0 8 0 0 0 0 0 0 1
Wage paid on "Daily-wage" basis 58 88 60 100 30 99 22 0 0 100 100 0 73 24 1 47
Wage paid on "Piece-rate/Task-wage" basis 42 2 40 70 2 78 100 100 0 0 100 27 76 100 100 52
Measureme
nt
of work
Work was measured by individual's work 51 98 60 10 86 24 14 0 9 5 3 11 1 10 24
Work was measured by team measurement 28 0 30 70 13 69 87 100 70 94 93 49 95 80 55
Work was measured by Collective
measurement
18 0 0 100 20 1 6 0 0 100 22 0 4 41 5 10 20
Work was not measured 3 2 10 0 0 1
117
Table 5.4: Qualitative questions related to functioning of MGNREGA (Percentage of HH) - Contd.
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Period of wage
payment
Wages were paid within a fortnight 48 53 85 73 90 65 0 16 0 70 14 47 99 61 7 50 48
Wages were paid Within a month 33 28 0 27 10 33 81 82 85 20 70 43 2 36 34 50 39
Wages were paid more than a month 19 20 15 3 19 3 16 10 17 10 4 60 12
Wages were paid after one year 0 0 0 0 0 0 0 0 0 0 0 0
Who made
the wage payment
Sarpanch or Sachiv 6 0 0 2 13 2 5 0 3 1 2 0 2
Post office 25 13 80 75 100 0 8 27 28 50 34 49 59 49 47 40
Bank 51 88 20 25 98 78 72 67 50 64 29 100 35 46 54 55
Representative of line department 5 0 0 0 1 0 0 13 6 6 2
Other Government official 2 0 0 0 0 0 8 0 0 1
Contractor 10 1
Any other 2 0
In case
wage payment
made in the
bank
Bank account was on self's name 92 100 70 100 100 100 92 100 100 100 98 90 95 82 89 100 94
Spouse's name 4 20 0 8 0 2 2 5 18 8 4
Parent's name 3 0 10 0 0 0 2 1 0 2 1
Children's name 1 0 0 0 0 0 6 0 1 0
Individual account 93 83 50 100 100 100 86 99 100 95 98 78 84 83 80 100 89
Joint account 7 17 50 1 14 2 0 5 2 22 17 17 21 11
Did bank follow usual procedure of banking 94 87 70 100 99 82 100 100 100 97 87 100 92 100 100 88
In case
wages were not
paid
through bank
Wages paid in front of all labourers 86 33 100 8 76 87 84 85 26 7 92 43
Wages paid on the worksite 9 0 59 8 8 3 0 5 3 6
Wages paid in panchayath Bhavan 5 5 30 4 3 1 2 2 4 3
Wages paid on other public/ Private place 0 96 11 0 6 25 0 92 14
Wages paid on some one's private residence 0 0 1 0 0 7 0 1 1
Other private faces 0 0 0
Complaints
regarding wage
payments
There were delays in wage payments 44 - 30 15 100 17 21 89 92 10 25 40 70 69 50 42
Wage paid less than the minimum wage 15 - - 59 8 0 0 0 19 8 59 10
Wage paid less than asked for sign/thumb impression
11 - - 7 8 0 0 0 2 8 7 3
Task was too much compared to the wages
paid
39 - 30 9 11 8 5 0 12 14 16 39 11
Faced problems in accessing post office/bank accounts
17 - 50 65 50 30 8 34 55 0 37 2 35 34 23 27
On what basis wages are calculated not clear 20 - 80 25 8 8 11 11 0 18 6 46 25 16
118
Table 5.4: Qualitative questions related to functioning of MGNREGA (Percentage of HH) – Contd.
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Details of worksite
facilities
A Board/GP member gave details of the sanctioned amount, work dimensions and
other requisite details
76 83 40 100 100 10 38 76 76 72 63 71 78 59 74 57 67
The worksite had drinking water facility 49 98 40 50 100 64 97 95 95 0 100 87 99 81 95 60 76
Worksite had shade for periods of rest 18 82 20 50 100 100 62 8 8 100 17 25 80 65 82 60 55
Worksite had child care facility 11 68 20 50 100 100 11 13 13 100 2 1 55 56 73 10 42
Worksite had first aid kit/medicines 21 88 - 50 100 100 17 7 93 100 10 89 92 53 91 80 62
Monitoring Was there any authority to monitor the
functioning of the MGNREGA administration
59 100 80 100 100 91 4 94 94 100 79 93 100 91 97 100 86
Any complaint lodged relating to worksite
etc., to the Gram Panchayat, Programme Officer or other officials
9 0 10 0 29 0 2 0 0 0 5 14 0 1 11 5
If yes, was any action taken on your
complaint
4 0 8 0 19 0 1 0 0 0 30 24 - 0 50 9
Economic usefulness
of the work
Work is very useful to the villages 61 86 60 76 100 99 88 86 85 83 74 48 85 92 40 69 77
Work is quite useful to the villagers 27 14 0 19 0 12 13 13 0 24 45 15 8 57 19 16
Work is not particularly useful to the
villagers
10 0 40 3 0 0 2 2 17 2 6 0 0 3 6 6
Work is useless for the villagers 1 0 0 0 0 0 1 0
Not sure 2 3 2 1 7 1
Nature of assets
and their
durability in
which the
interviewee involved
The structure created may last up to one year 20 4 90 25 10 95 66 32 39 50 35 5 0 7 8 30
The structure created may last up to five year 64 19 10 15 10 6 28 45 59 50 39 77 18 85 73 31 39
The structure created may last up to ten year 13 72 - 34 10 0 7 17 2 0 13 16 75 9 10 63 21
The structure created may last more than ten year
3 6 - 26 70 0 0 8 1 0 15 1 8 0 9 6 10
It is worth creating the structure 79 100 70 100 100 92 67 96 99 60 91 80 100 89 75 72 86
Was the structure created adequate 69 70 20 73 90 91 62 82 92 20 72 51 74 87 61 60 67
How has
MGNREGA
affected
labour
migration
Did any your family members migrated out
for job after implementation of MGNREGA (year 2005 onwards)
10 15 50 0 - - 10 10 43 5 27 15 47 28 24 18
Are wages higher in city or other states than
MGNREGA
73 90 100 100 - - 7 7 100 9 80 80 73 74 14 50
Any family members migrated back to village to work under MGNREGA
5 6 40 - - 0 5 0 - 27 4 9 13 23 8
Any family member migrated as wage labourer with dissatisfaction from
MGNREGA
3 0 20 - - 0 0 12 - 27 0 12 6 2 5
119
Table 5.4: Qualitative questions related to functioning of MGNREGA (Percentage of HH) – Contd.
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Respondents '
awareness
about MGNREG
A
implementation
Are respondents aware about MGNREGA implementation
68 97 50 100 100 90 80 100 100 100 100 79 96 100 92 64 88
Right to apply for work and get employed
within 15 days
35 97 30 56 100 73 77 91 91 72 69 60 96 53 68 8 67
The work application procedure 32 95 30 57 100 74 57 77 97 21 65 34 94 44 60 56 62
Right to minimum wages 37 97 80 57 100 87 38 97 100 100 66 28 95 29 59 29 69
The level of minimum wages 27 96 50 57 100 0 20 96 96 100 93 20 96 22 33 46 59
The wage calculation method 28 78 50 29 100 78 25 27 27 100 45 30 72 12 14 17 46
Right to the unemployment allowance 12 94 25 36 63 30 0 0 0 25 37 87 16 14 15 28
Minimum worksite facilities (drinking water,
first aid,)
21 90 25 47 100 70 31 11 89 22 20 71 91 45 93 39 54
Mandatory availability of muster rolls at the worksite
25 92 25 47 100 92 22 67 93 37 52 38 92 36 78 7 56
The list of permissible works under the
MGNREGA
15 76 - 60 100 73 17 71 71 0 60 13 65 33 44 6 44
Potential benefits of
MGNREG
A
MGNREGA enhanced food security 55 100 40 79 100 43 67 94 94 12 42 77 100 0 100 73 67
MGNREGA provided protection against
extreme poverty
37 100 85 83 100 48 83 85 58 15 35 51 100 0 96 68 65
MGNREGA helped to reduce distress
migration
45 100 50 0 100 18 85 39 39 7 34 37 100 0 75 59 49
MGNREGA helped to reduce indebtedness 30 100 30 82 90 8 78 31 61 12 32 25 100 0 76 60 51
MGNREGA gave greater economic
independence to women
61 100 60 75 100 44 80 34 35 12 30 51 100 0 98 49 58
MGNREGA generated purchasing power at local economy
35 100 60 71 100 36 78 51 59 27 46 28 100 93 75 60
Questions
related to
food security
Did your family get full two meals
throughout year 2009
62 96 50 70 100 95 100 74 90 26 69 78 96 69 77 71 76
How did you cope with the situation – take loan
76 - 15 33 0 - 73 73 20 100 26 0 18 10 69 37
Catch fish/rat/crab etc 5 0 30 0 0 - 0 0 10 0 0 7 2 4
Near/sometime starvation/take meal only
once
13 0 20 56 0 - 0 0 0 56 0 6 10 29 13
Begging 0 0 - 10 0 - 0 0 5 6 0 1 1 2 2
Any other 7 100 35 0 100 - 27 28 65 12 100 69 78 0 44
120
Table 5.5: Some quantification of qualitative questions (Percentage of households)
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
If the Job card is generally with the card holder, what is the reason for the same?
Sarpanch or Sachiv kept with themselves either for
security purpose or to make entries or attendance
30 0 0 0 0 22 0 92 95 70 19 0 8 6 19 0 23
Not applicable, no response or reasons not known 70 100 100 100 100 78 100 8 5 30 81 100 92 94 81 100 77
Is there any authority that monitors the functioning of the NREGA administration?
Contractor/Supervisor/Manager/Engineer 26 6 16 21 100 11
GP member/Panchyath secretary/RD Department 14 70 100 100 40 100 100 72 86 40 55 49
Name not specified 11 100 7
Do not know whether editing is done 49 11 100 21 7 12
Some Govt. Officer 13 60 5 14 60 24 11
Any Other or no reply 100 79 11
What complaint lodged to the GP, Programme officer or other officials?
For the provision of drinking water 5 0
Complaint for returning job card 5 0
Complaints for less wage payment or late payment 53 62 10 0 0 0 0 0 0 0 0 66 0 0 0 0 12
Complaint against contractors/secretary for not functioning properly
11 1
Complaint lodged but not able to specify properly or
verbal complaint lodged
26 29 2 15 10 100 5 1 11 12
Complaint was not lodged 38 90 100 71 100 98 85 90 95 34 100 100 89 100 74
Any action being taken on the complaint lodged?
They took action quickly 3 43 19 1 30 37 8
They assured that proper care will be taken next time and will not give any opportunity for complaint next
time
1 8 1
Either no action being taken or not sure whether any
action was taken on the complaint
96 2 100 100 100 25
No response 57 90 100 81 100 99 70 63 100 100 100 100 66
121
Table 5.5: Some quantification of qualitative questions (Percentage of households) – Contd.
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
IF you did not have sufficient food last year what do you think are the reasons?
No opportunity for work, especially in the summer
season
57 55 70 50 5 50 56 5 16 20 80 29
Low household income and low purchasing power 7 50 50 41 23 20 12
Earning members having bad habits like drinking 2 0
Low wage rate 15 30 6 16 4
Rainy season caused fallen of kaccha house 4 27 28 4
Others like no access to PDS food, indebtedness,
health problem and so on
15 19 2 100 100 16 0 38 42 21
Sufficient food was there 100 95 98 100 95 31
What problems other than food did you face during the last year?
Health problem 31 11 25 66 65 44 17 5 11 17
Poor economic condition, lack of purchasing power for other necessities
29 30 50 30 73 28 7 20 20 18
Unemployment 14 10 8 16 35 5
Education expenditure too high 6 11 34 5 36 3 12 6 7
Other problem including shelter, water, cloth and so on 18 36 25 30 20 27 25 11 23 80 18
No response 3 2 19 50 6 5
No Deprivation 100 70 100 100 100 29
Your suggestions to improve NREGA functioning?
Should increase wage rate and number of working days and work should be available throughout the year
50 51 35 90 100 12 10 20 100 57 10 5 40 36
Payment should be made within a week at the time of
work
5 8 30 26 5 10 25 7
Hundred days guarantee work and stipulated minimum wages should be ensured in practice
20 15 6 22 4
Any other 25 20 18 7 20 25 100 6 59 17
New types of work should be added 6 24 4 20 6 4
Better monitoring and proper measurement with
suitable timing of the work
32 7 38 28 20 2 25 21 20 12
Transparency and accountability in implementation 30 33 12 15 6
Better arrangement / worksite facilities 35 20 22 15 6
Compulsory work allocation for exclusively landless 100 6
Awareness towards Government schemes/ Rural development programmes/ legal rights in MGNREGA
20 15 2
122
Chapter 6
MGNREGA Impact on Village Economy
This Chapter is based on group discussion held among the ten villages that were surveyed in
each state. Our study carried out group discussion at the village level among the Panchayat
members and other learned people in the village at the time of field survey during the reference
year 2009. Our selected sample was 5 districts in each state and 2 villages from each district. In
this way we had group discussion in 10 villages in each state where study was carried out. The
results are present for 16 states and 160 villages. The issues discussed in the group discussion
were especially focused on the infrastructure available within the selected villages; the
implementation issues of MGNREGA; how MGNREGA has affected the village economy;
MGNREGA’s effect on agricultural wages and cost of production etc.
6.1 Infrastructure available within the village
Among the villages surveyed, most of the villages were connected with the city or nearby town
by a pucca/metal road (Table 6.1), except the case of Bihar where 3 out of the 10 villages were
not connected by pucca road. The villages that were not connected with pucca road their average
distance of un-metal road was around 3 kilometers. About the railway connectivity, only 9 per
cent of the selected villages or less than one out of the ten villages had railway connectivity.
Only in Kerala, 5 out of 10 villages had railway connectivity. The average distance of selected
villages to the nearest railway connectivity was around 31 kilometers (Table 6.1.3). The distance
for the railway connectivity was higher among the hilly terrain states like Himachal Pradesh and
Sikkim and it was higher for Chhattisgarh among the other selected states. More than 90 per cent
of the villages had telephone access while only 50 per cent of them had access to post office
within the village. The average distance to the post office in those selected villages where the
facility was not available within the village, it was available at an average distance of 4
kilometers. Only in Kerala, all the villages where group discussion was held had post office
facility within the village.
123
About access to institutional credit, around one half of the villages surveyed had cooperative
credit society within the village and another 15 per cent had commercial or regional rural banks
(RRB) within the village. Others who did not have bank access within the village had to travel 5
to 8 kilometers for the same. Only Sikkim and Kerala were the two states where all the selected
villages had cooperative society within the village. In Madhya Pradesh, there was no village
having the post office facility while only 20 per cent of the villages in Bihar, Andhra Pradesh,
Madhya Pradesh and West Bengal had cooperative society existing within the village periphery.
The APMC or agricultural produce market was available within an average distance of 11
kilometers at the aggregate while in Himachal Pradesh its distance was found up 36 kilometers
and in Sikkim it was available within a distance of 22 kilometers. Majority of the villages had
some self help group (SHG) within the village. Similarly, almost all the villages had access to
primary or secondary school within the village or in the nearby periphery. Primary health centre
was accessible either within the village or within the range of 4 kilometers while proper hospital
was available within 8 kilometers. Gram Panchayat Office (GPO) and Fair Price Shop (FPS)
were mostly available within the village or in the nearby periphery. In all the above infrastructure
indicators, Kerala was at the top, while Bihar, Madhya Pradesh and Chhattisgarh were at the
bottom.
Thus surveyed villages had mixed picture with some villages having perfect infrastructure like
road, post office, bank, SHG, school, primary health centre, FPS etc., while others had to travel
some distance to approach the same.
6.2 Changes in the occupation structure in the selected villages
We tried to capture the structure of occupation in the selected villages and change that has
occurred during the last one decade. At the aggregate, around 40 per cent of the households in
the villages were cultivators and another 33 per cent were working as agricultural labourers
during the reference period and thus adding up the dependency of all households on the
agriculture sector up to 73 per cent (Table 6.2). Around 5 per cent were working in
manufacturing or mining and rest of the 20 per cent were working in service sector like
construction, trade, business, transport and other services. A slight change in the occupation has
been observed during the last ten years period. Agriculture occupied around 80 per cent of the
124
workforce in the selected villages during the year 2001, while manufacturing had no change
having 5 per cent share around that time as well while trade and services occupied only 15 per
cent share in 2001 compared to 20 per cent seen during the reference period. These results from
our primary survey are in consonance with the occupation structure revealed by the secondary
sources, e.g., Agriculture Census data and Agricultural Statistics at a Glance.
Comparing the occupational structure among different states, the data reveals interesting trends.
The highest percentage of households as cultivators were found in Haryana, followed by
Maharashtra, Karnataka, Punjab and Uttar Pradesh while their percentage was lowest in West
Bengal, Assam, Kerala, Bihar and Gujarat during the reference period. The highest percentage of
households working as agricultural labourers were found in Chhattisgarh followed by Andhra
Pradesh and West Bengal while Himachal Pradesh, Assam and Gujarat observed lowest
percentage of households working as agricultural labourers during the reference period. The
overall households working in agriculture topped in Haryana, Andhra Pradesh, Maharashtra and
Madhya Pradesh while lowest percentage was seen in Assam, Bihar and Gujarat. During the
period of a decade from 2001 to 2009, the percentage of households working in agriculture
declined by 2 to 6 per cent in different states. The proportion of households working in non
agriculture sector at the aggregate averaged around 26 per cent during the reference period while
it was only 20 per cent in 2001. The highest percentage of households working in non agriculture
was found in Assam, Bihar, Himachal Pradesh, Kerala, Rajasthan and West Bengal. The lowest
percentage of households working in non agriculture was worked out in Haryana, Andhra
Pradesh, Maharashtra, Madhya Pradesh and Chhattisgarh.
6.3 Changes in cost and wage rate in agriculture and non agricultural sector
The observations collected through village group discussion further substantiate our findings of
household survey data. The prevailing wage rates in agriculture were fluctuating widely both
across the states as well as across gender. The prevailing average wage rate in agriculture
according to our group discussion data was around 121 for male and around 94 for female at
the aggregate (Table 6.3). The corresponding figures according to our household survey data for
male and female, respectively were 104 and 84 for the participants and 107 and 84 for the
non participants. In our group discussion, the wage rate for agriculture labour topped in Kerala
125
(above 200) followed by Haryana (between 150-200), Andhra Pradesh, Punjab, Rajasthan,
Gujarat, Himachal Pradesh, Karnataka and Bihar ( 100-150) and the states having lowest wage
rates were Uttar Pradesh, Madhya Pradesh, Chhattisgarh, Maharashtra, West Bengal, Assam and
Sikkim ( 50-100).
In comparison, prevailing wage rate in non agricultural sector were much higher and the level of
skilled wages was almost double that of unskilled wages (e.g. electrician, plumber, construction,
mining). The average wage rate for male at the aggregate was 142 for non agriculture unskilled
labour, 183 for construction work, 167 for mining work, 224 for the trained electrician,
239 for the plumber and 284 for the pump-set boring. Comparing the wage rate over the last
five years, i.e. since the time MGNREGA has come into implementation, the wage rate in
agriculture sector has increased by slightly less than 50 per cent for male and slightly above 50
per cent for the female (Table 6.3.1). By the same estimates, wage rate for unskilled as well as
skilled labour in the non agricultural sector increased by slightly less amount compared to
agriculture labour except the wage rate in mining during the same time period. The wage rate for
unskilled labour in non agriculture and construction work increased slightly less than the wage
rate increase in agriculture while wage rate for skilled labour in mining increased slightly more
than agriculture. The wage rate for technical work like electrician, plumber and pump set boring
increased by less than that of agriculture (between 35 to 47 per cent). Thus, increase in wage rate
in agriculture more than most of the other activities within the village indicate the enhanced
demand for wage labourers due to employment works in MGNREGA that goes parallel with the
agriculture sector thereby causing a competition in the labour market for the agriculture sector.
Comparison of wage rate increase in agriculture versus non agriculture sector in different states
as revealed by our group discussion shown in Tables 6.3 and 6.3.1 presents interest trends. The
states that observed increase in wage rate in agriculture more than non agriculture sector
especially for the skilled wages, e.g., electrician, plumber etc., were Bihar, Sikkim, Andhra
Pradesh, Kerala, Madhya Pradesh, Chhattisgarh, Punjab, Himachal Pradesh and Rajasthan. On
the other hand, agriculture wages increased less than that of skilled labour force in non
agriculture sector in the states of Karnataka, Uttar Pradesh, Haryana, Maharashtra, Gujarat and
West Bengal. At the overall agriculture wages (male) increased by 49 per cent compared to
126
combined skilled wages that increased by 41 per cent during the period before to after
MGNREGA.
Similar to the change in wage rate there was around 40 to 50 per cent hike in the cost of
agricultural operations also (Tables 6.4 and 6.4.1). Machine charges like tractor or charges for
manual operations like ploughing, leveling, weeding and transplantation per acre increased from
45 to 55 per cent during the period before to after MGNREGA. Charges for ploughing increased
from 620 in 2005 to 920 in 2009. Similarly, weeding charges increased from 594 to 862
and threshing of paddy charges increased from 1084 to 1459 during the same time period.
Overall, increases in charges for agricultural operations per acre on an average were almost
similar to increase in agricultural wages as overall wages observed an increase of around 49 per
cent compared to around 46 per cent increase in cost of per acre agricultural operations as per
our group discussion data.
6.4 Various changes in village economy after implementation of MGNREGA
Table 6.5 presents some aspects of MGNREGA implementations. There has been a lot of hue
and cry on shortage of labour force in the agricultural sector because of the implementation of
MGNREGA programme. In the group discussion, we especially discussed this point with the
villagers. Out of the 160 villages where group discussion was held in more than 90 villages
(around 57 per cent of the villages) we found that there was truly shortage of labour in
agriculture during few months of the reference year. The shortage has further increased after the
implementation of MGNREGA as around more than 100 villages constituting around 63 per cent
of all the villages where group discussion was held indicated shortage of agricultural labour has
increased after the implementation of MGNREGA. In majority of the villages the shortage of
labour was observed during the sowing and harvesting months of kharif and rabi seasons
especially in the months of July, August and September and March and April. This was more so
after the implementation of MGNREGA. The shortage of labour was expressed in all the states
while out of ten villages where group discussion was held in each state shortage of agriculture
labour was found in more than five villages, in the states of Karnataka, Uttar Pradesh, Sikkim,
Andhra Pradesh, Kerala, Madhya Pradesh, Chhattisgarh, Punjab, Maharashtra, Himachal
Pradesh, Gujarat and West Bengal in the post MGNREGA period. Out of 16 states where group
127
discussion was held, shortage of labour was found less severe only in Bihar, Assam, Haryana and
Rajasthan where less than 5 villages expressed shortage of labour after the implementation of
MGNREGA.
The majority of villagers were of the view that after MGNREGA implementation cost of
production in agriculture has increased by 10 to 20 per cent because of scarcity of labour.
Around 63 per cent villages expressed increase in cost in the agriculture sector by 10 to 20 per
cent in the post implementation of MGNREGA Programme. The villages where participants in
the discussion expressed cost increase by 20 to 50 per cent constituted only 20 per cent of the all
villages where group discussion was held while cost increase by more than 50 per cent was
expressed by 8 per cent of the villages. Among the selected states, only in Rajasthan, Kerala and
Uttar Pradesh more than 20 per cent of the villages participating in discussion indicated increase
in agricultural wages by more than 50 per cent after the implementation of MGNREGA. To our
question on how the wage rate of casual labour has changed during the last five years after
implementation of MGNREGA, around 84 per cent of the discussants pointed out that rate of
change in wages have increased and another 13 per cent indicated that rate of change in wages
after implementation of MGNREGA have remained constant while only 3 per cent were of the
view that the rate of change in wages have come down.
Discussion was held on labour migration issues. On the question, whether workers who earlier
migrated out of the village to work in city are now coming back to work in MGNREGA, only 24
per cent discussant agreed that it was true while same percentage of participants expressed the
opposite view that in the post MGNREGA period the exodus of labour to the cities is continuing
or the trend has increased because the wage rate in the city is much higher than that existing
under MGNREGA. The trend of villagers returning back to the village to work in MGNREGA
was found more prevalent in Andhra Pradesh, Himachal Pradesh, West Bengal, Bihar and
Karnataka while reverse was the case in Gujarat and Kerala. Around 20 per cent of the villages
indicated that the migration is happening both the ways, some people are retuning back to the
village to work under MGNREGA but some others are migrating to the cities or town because of
wage difference in MGNREGA and manual work in the city/town. Against all the above trends
around 41 per cent of the participating villages in the discussion indicated that MGNREGA has
128
not made any significant changes in the migration pattern in the village. The states in which no
change in migration trends came up predominantly were Madhya Pradesh, Chhattisgarh, Punjab,
Gujarat and Sikkim.
Another point of debate was how the MGNREGA has affected living standards of villagers, a
clear majority indicated that MGNREGA has not been successful in raising their living standards
or their consumption level and the reasons was quoted that the programme has not provided
enough numbers of days of work to make a significant dent on the poverty level, although a
minority of them were of the view that MGNREGA has been successful in doing so, to some
extent. The latter ones indicated that MGNREGA has improved living standards by providing
work within the village and by ensuring same wage rate to female as equal to that of male.
To another question, whether school enrollment or attendance has increased with MGNREGA,
54 per cent indicated no while 46 per cent expressed yes. Those who said yes pointed out that as
they were now getting better payment so they could afford to send their children to school now.
Whether MGNREGA has changed the trend of attached labour in agriculture, a significant
majority (44 per cent) said yes as people were getting better payments within the village
compared to agricultural work so the trends of attached labour for the agricultural work were
declining.
Has MGNREGA increased people awareness towards Government schemes, around 80 per cent
of the discussants were of the view that it has done so through increase in the showcasing by
television, newspaper, Gram Panchayat and Gram Sabhas and by other means like posters,
banners etc. Among the steps needed to ensure better implementation of MGNREGA, the major
ones suggested by the discussants included: increasing working days and wage rate; providing
food within the programme; allowing private land development through MGNREGA work for
longevity of the programme; and by providing proper information on various aspects of the
programme. Among the selected states, in Sikkim, Andhra Pradesh, Kerala, Rajasthan, West
Bengal, Uttar Pradesh, Maharashtra and Gujarat, a clear majority of the discussants expressed
that the household consumption as well as enrollment of children in the school have increased
after implementation of MGNREGA that has provided extra purchasing power in the hands of
129
the villagers. On the question of awareness almost all states observed increased awareness of the
households towards existing government schemes because of their participation in the gram
sabha and also because of joint working opportunities in MGNREGA.
6.5 Summary of the Chapter
The surveyed villages had mixed picture with some villages having perfect infrastructure like
road, post office, bank, SHG, school, primary health centre, FPS etc., while others had to travel
some distance to approach the same. During the last ten years there has been slight change in the
occupation structure in the selected villages. The prevailing wage rates in agriculture were
fluctuating widely. Prevailing wage rate in non agricultural sector were much higher compared to
the agricultural sector and the level of skilled wages were almost double that of unskilled wages.
Comparing the wage rate after implementation of MGNREGA, the wage rate in agriculture
sector has increased by around 50 per cent. By the same estimates, wage rate for unskilled as
well as skilled labour in the non agricultural sector increased by slightly less amount compared
to agriculture labour except the wage rate in mining during the same time period. The wage rate
for technical work like electrician, plumber and pump set boring increased by less than that of
agriculture. Thus, increase in wage rate in agriculture more than most of the other activities
within the village indicate the enhanced demand for wage labourers due to employment works in
MGNREGA that goes parallel with the agriculture sector thereby causing a competition in the
labour market for the agriculture sector. A majority of the villages indicated shortage of
agricultural labour has increased after the implementation of MGNREGA.
On labour migration, there were opinions on both sides expressing that after MGNREGA people
are not migrating to the cities as work is available within the village but also stating that people
who migrated are not coming back to work in MGNREGA. Another point of debate was how the
MGNREGA has affected living standards of villagers, a clear majority indicated that
MGNREGA has not been successful in raising their living standards or their consumption level
and the reasons was quoted that the programme has not provided enough numbers of days of
work to make a significant dent on the poverty level. However, MGNREGA has certainly
increased people awareness towards Government schemes.
130
Table 6.1: Infrastructure available within the village (percentage of villages)
Sta
tes
Ka
rna
tak
a
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
ha
rash
tra
HP
Gu
jara
t
Ra
jast
han
Wes
t B
eng
al
Ag
gre
ga
te
Item Within the Village
Road connectivity 100 100 70 87.5 100 100 90 100 100 100 100 100 100 90 100 100 96
Railway connectivity 10 20 10 0 0 50 0 0 0 0 0 0 10 20 20 10 9
Landline or mobile connectivity 100 100 40 87.5 90 100 100 100 100 100 100 70 100 100 100 100 93
Post Office 80 30 10 75 80 100 60 0 20 70 40 60 70 70 80 50 56
Co-operative credit society 60 30 20 100 20 100 40 20 40 30 50 70 40 60 60 20 48
Regional Rural Bank 20 20 0 0 0 80 0 10 10 20 0 20 10 20 0 10 14
Commercial Bank 30 10 10 0 0 70 0 0 0 0 0 30 20 30 20 20 15
Agricultural Produce Market 0 100 0 62.5 0 50 0 0 0 10 0 0 0 0 0 10 15
Self Help Group Centre 100 100 30 62.5 80 80 70 40 50 100 30 100 100 100 40 70 72
School Primary 100 100 80 87.5 100 100 100 100 100 100 100 100 100 90 100 100 97
School Secondary 90 60 40 75 50 100 80 60 60 20 30 70 80 20 90 30 60
School Higher Secondary 70 30 10 37.5 0 90 50 20 10 20 0 30 40 0 20 10 27
Primary Health Centre 50 20 30 62.5 30 80 60 30 30 30 20 30 20 40 80 50 41
Hospital/Dispensary 10 10 10 50 0 90 40 0 0 20 20 30 40 10 20 10 23
Gram Panchayat Office 70 100 40 50 100 90 100 80 100 20 0 100 100 100 80 30 73
Fair Price Shop 90 50 50 87.5 70 70 40 0 10 90 0 100 80 80 90 50 60
Any other 0 0 0 0 100 0 0 0 0 0 0 20 0 0 100 0 14
131
Table 6.1.1: Infrastructure available nearest village (percentage of villages)
Sta
tes
Ka
rna
tak
a
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
ha
rash
tra
HP
Gu
jara
t
Ra
jast
han
Wes
t B
eng
al
Ag
gre
ga
te
Item Nearest Village
Road connectivity 0 0 30 12.5 0 0 10 0 0 0 0 0 0 10 0 0 4
Railway connectivity 90 80 90 100 100 50 100 100 100 100 100 100 90 80 80 90 91
Landline or mobile connectivity 0 0 60 12.5 10 0 0 0 0 0 0 30 0 0 0 0 7
Post Office 20 70 90 25 20 0 40 100 80 30 60 40 30 30 20 50 44
Co-operative credit society 40 70 80 0 80 0 60 80 60 70 50 30 60 40 40 80 53
Regional Rural Bank 80 80 100 100 100 20 100 90 90 80 100 80 90 80 100 90 86
Commercial Bank 70 90 90 100 100 30 100 100 100 100 100 70 80 70 80 80 85
Agricultural Produce Market 100 0 100 37.5 100 50 100 100 100 90 100 100 100 100 100 90 85
Self Help Group Centre 0 0 70 37.5 20 20 30 60 50 0 70 0 0 0 60 30 28
School Primary 0 0 20 12.5 0 0 0 0 0 0 0 0 0 10 0 0 3
School Secondary 10 40 60 25 50 0 20 40 40 80 70 30 20 80 10 70 40
School Higher Secondary 30 70 90 62.5 100 10 50 80 90 80 100 70 60 100 80 90 73
Primary Health Centre 50 80 70 37.5 70 20 40 70 70 70 80 70 80 60 20 50 59
Hospital/Dispensary 90 90 90 50 100 10 60 100 100 80 80 70 60 90 80 90 78
Gram Panchayat Office 30 0 60 50 0 10 0 20 0 80 100 0 0 0 20 70 28
Fair Price Shop 10 50 50 12.5 30 30 60 100 90 10 100 0 20 20 10 50 40
Any other 100 100 100 100 0 100 100 100 100 100 100 80 100 100 0 100 86
132
Table 6.1.2: Infrastructure available nearest village, average distance (percentage of villages)
Sta
tes
Ka
rna
tak
a
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
ha
rash
tra
HP
Gu
jara
t
Ra
jast
han
Wes
t B
eng
al
Ag
gre
ga
te
Item If Nearest Village, Average Distance (kms.)
Road connectivity 0 0 6 45 0 0 2 0 0 0 0 0 0 2 0 0 3
Railway connectivity 14 12 13 112 19 9 22 33 59 - 5 23 102 19 16 14 31
Landline or mobile
connectivity
0 0 3 30 4 0 0 0 0 0 0 4 0 0 0 0 3
Post Office 4 4 2 16 6 0 7 5 4 3 2 4 2 2 5 2 4
Co-operative credit society 13 4 2 0 7 0 4 4 5 2 6 4 4 12 9 4 5
Regional Rural Bank 13 8 7 13 10 6 5 4 7 4 5 6 8 12 12 6 8
Commercial Bank 5 9 6 14 12 5 6 6 5 4 5 8 10 12 12 6 8
Agricultural Produce Market 14 0 4 22 15 7 12 6 7 1 5 13 36 17 15 3 11
Self Help Group Centre 0 0 3 19 10 10 4 4 4 1 5 0 0 0 6 3 4
School Primary 0 0 3 1 0 0 0 0 0 0 0 0 0 3 0 0 0
School Secondary 3 2 3 17 4 0 5 1 2 1 5 6 1 12 2 4 4
School Higher Secondary 3 5 6 15 6 3 4 4 4 1 4 5 5 12 9 5 6
Primary Health Centre 5 7 2 18 6 3 4 3 2 2 2 5 6 6 3 5 5
Hospital/Dispensary 13 14 4 16 10 3 7 9 5 2 5 4 12 14 9 8 8
Gram Panchayat Office 9 0 2 10 0 7 0 0 0 2 0 0 0 0 3 4 2
Fair Price Shop 18 3 1 30 9 6 14 4 1 1 3 0 1 2 3 2 6
Any other 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
133
Table 6.2: Occupational structure (% of households in the village)
Sta
tes
Ka
rna
tak
a
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
ha
rash
tra
HP
Gu
jara
t
Ra
jast
han
Wes
t B
eng
al
Ag
gre
ga
te
Occupation Reference
period
Cultivators 2009 54 50 22 49 44 21 65 43 27 21 51 59 43 24 41 20 40
2001 56 53 31 51 46 28 65 48 31 26 55 61 - 25 30 20 42
Agricultural Labour 2009 31 34 27 36 49 37 31 45 56 12 32 31 10 29 21 46 33
2001 31 37 31 36 49 60 33 35 62 11 35 31 - 26 30 46 37
Household Small
Industry 2009 0 1 3 2 2 7 1 0 1 3 1 1 5 6 1 2 2
2001 0 1 2 2 2 3 1 4 1 4 1 1 - 4 2 2 2
Other
Manufacturing./mining 2009 6 2 3 1 2 8 0 0 0 0 2 0 0 5 7 8 3
2001 5 1 5 0 2 0 0 7 0 0 2 0 - 4 7 8 3
Construction 2009 3 10 17 3 1 12 1 7 4 35 10 4 14 4 14 11 9
2001 2 6 12 2 0 5 1 6 4 34 5 4 - 4 16 11 7
Trade, Commerce and
Business 2009 3 2 7 5 0 5 1 2 2 19 2 2 5 2 3 6 4
2001 3 1 5 5 0 5 1 0 1 17 1 1 - 1 3 6 3
Transport and
Communication 2009 1 1 11 3 2 4 1 0 5 5 1 1 5 2 2 2 3
2001 1 0 9 3 1 0 0 0 0 3 1 1 - 2 2 2 2
Other Services 2009 2 1 10 2 0 5 3 3 3 5 1 2 18 9 12 6 5
2001 1 1 6 2 0 0 2 0 2 4 1 1 - 9 11 5 3
Total 2009 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100
2001 100 100 100 100 100 100 100 100 100 100 100 100 - 100 100 100 100
134
Table 6.3: Wage rates for different activities (average of all villages) ( )
Sta
tes
Ka
rna
tak
a
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
r
h
Ass
am
Pu
nja
b
Ma
ha
rash
t
ra
HP
Gu
jara
t
Ra
jast
han
Wes
t
Ben
ga
l
Ag
gre
ga
te
Activity Reference period (2009)
Prevailing
Agricultural Wages
Male 122 60 122 85 150 269 187 80 80 88 150 70 129 127 140 84 121
Female 69 40 98 80 94 204 165 70 70 78 70 48 121 112 111 73 94
Prevailing Non
Agricultural Wages
Male 157 98 130 203 125 331 206 80 80 96 150 103 130 150 149 85 142
Female 84 75 123 145 64 216 188 70 70 84 70 71 122 110 115 72 105
Construction Male 226 120 148 216 155 358 248 250 200 120 160 146 129 185 154 114 183
Female 114 100 106 161 106 253 200 90 74 125 125 131 85 128
Mining Male 200 140 125 100 325 200 85 150 76 230 238 130 167
Female 120 100 75 325 150 75 100 76 150 133 100 128
Other
skilled
work
Electrician Male 175 100 250 231 231 356 174 300 250 150 300 270 130 224
Female 146 213 179
Plumber Male 214 150 400 219 195 350 195 250 250 150 350 192 245 246 272 141 239
Female 188 175 162 175
Pump-set
boring
Male 321 120 400 94 120 317 240 150 913 125 350 400 146 284
Female
135
Table 6.3.1: Wage rates for different activities (average of all villages) ( )
Sta
tes
Ka
rna
tak
a
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
r
h
Ass
am
Pu
nja
b
Ma
ha
rash
tr
a
HP
Gu
jara
t
Ra
jast
han
Wes
t B
eng
al
Ag
gre
ga
te
Per
cen
t
cha
ng
e fr
om
bef
ore
to
aft
er
MG
NR
EG
A
Activity Before MGNREGA 2005
Prevailing Agricultural
Wages
Male 78 38 67 55 94 193 144 60 60 70 80 49 88 81 81 62 81 49.5
Female 40 29 54 55 52 134 115 60 50 60 50 31 79 64 60 51 61 52.6
Prevailing Non
Agricultural Wages
Male 98 70 87 133 72 238 147 60 60 75 100 74 88 80 78 63 95 49.2
Female 55 50 40 110 39 156 126 60 50 65 60 50 79 65 59 52 70 50.5
Construction Male 153 100 80 156 128 256 182 200 150 100 105 105 88 120 87 86 131 39.7
Female 75 80 50 130 69 150 140 80 58 79 80 66 60 86 49.7
Mining Male 100 80 50 75 200 133 75 100 54 185 144 100 108 54.2
Female 60 80 50 150 100 65 75 48 120 73 75 81 56.7
Other
skilled
work
Electrician Male 100 65 200 154 158 238 118 250 200 120 200 220 93 163 37.9
Female
Plumber Male 143 80 200 168 142 238 134 250 200 120 250 93 200 150 162 104 165 45.0
Female
Pump-set
boring
Male 179 70 200 70 85 300 188 120 695 105 225 261 105 200 42.0
Female
136
Table 6.4: Prevailing labour charges for agricultural operations (average of all villages) ( /day)
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
(R
s/acre
)
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
(Rs/
acr
e)
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
(Rs.
/day
)
Ag
greg
ate
(Rs
per
acr
e)
Per c
en
t
ch
an
ge f
rom
befo
re t
o a
fter
(Rs
per
acr
e)
Activity Reference period 2009
Ploughing 222 900 115 93 870 320 250 90 80 80 990 381 350* 339* 531** 181 920 48.9
Leveling 230 300 225 93 625 340 250 80 70 80 3455 348 340* 325* 44** 191 1460 54.5
Weeding 87 720 115 93 1690 220 215 70 70 80 113 925 298 116 120 81 139 862 45.1
Paddy transplanting 108 800 125 93 1525 221 2000** 90 90 75 1420 1408 128 110 88 116 1288 54.1
Harvesting of wheat 87 1000 150 93 2000** 80 70 75 1130 540 128 125 155 81 97 890 48.8
Harvesting of paddy 143 650 150 93 1260 257 2200** 80 80 75 1100 1021 128 120 138 88 126 1008 53.9
Harvesting of grams 97 960 150 93 675 70 70 75 425 128 150 81 97 687 44.9
Harvesting of pigeon pea 150 93 80 75 104 150 81 100 -
Harvesting of ragi 138 170 75 1500 104 150 105 835 103.7
Harvesting of jowar 108 80 75 700 116 115 152 95 700 27.3
Harvesting of maize 110 140 93 750 70 75 673 128 115 145 81 102 712 34.6
Cane-cutting 100 93 2250 192 75 3217 128 150 88 117 2733 11.3
Harvesting other crops 100 93 200 192 80 2050 128 158 88 132 2050 53.2
Digging of potatoes 100 120 93 80 90 128 150 88 102 -
Threshing of paddy 123 100 93 1940 200 70 70 979 128 120 325* 88 112 1459 34.6
Threshing of wheat 133 100 93 250 180 70 70 90 724 128 350* 352* 88 124 724 22.7
Winnowing of
wheat/paddy
100 100 93 595 300 60 60 90 350 128 325* 346* 88 116 473 51.6
Note: * Rs per hour of machinery operation like tractor etc.
** Rs per acre
137
Table 6.4.1: Prevailing labour charges for agricultural operations (average of all villages) ( /day)
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
(R
s/acre
)
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
Ass
am
Pu
nja
b
Ma
hara
shtr
a
(Rs/
acr
e)
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
(Rs.
/day
)
Ag
greg
ate
(Rs
per
acr
e)
Activity Before MGNREGA
Ploughing 2005 119 600 90 58 570 200 120 60 65 65 685 315 200* 217* 318** 121 618
2001 83 65 46 415 150 70 50 50 45 480 273 150* 132* 234** 92 448
Leveling 2005 156 200 94 58 365 225 120 45 42 65 2270 300 195 215 91 123 945
2001 131 70 46 245 175 70 40 34 45 1450 266 166 137 60 97 848
Weeding 2005 49 540 58 1090 127 100 50 50 65 82 663 274 67 83 58 97 594
2001 33 46 700 78 55 40 40 45 475 241 55 52 41 72 588
Paddy
transplanting 2005 68 580 110 58 1075 141 1200** 70 70 60 800 890 89 70 64 83 836
2001 41 80 46 788 97 800** 60 60 40 572 79 55 47 63 680
Harvesting of
wheat 2005 47 700 110 58 1200** 50 50 60 725 370 89 78 103 58 66 598
2001 34 80 46 800** 40 40 40 280 79 55 76 41 51 280
Harvesting of
paddy 2005 77 400 110 58 795 168 1400** 60 60 60 750 675 89 70 80 64 85 655
2001 63 80 46 595 114 1000** 50 50 40 475 79 50 55 47 65 535
Harvesting of
grams 2005 51 700 110 58 410 50 50 60 313 89 93 58 67 474
2001 41 50 46 350 40 40 40 225 79 70 41 48 288
Harvesting of
pigeon pea 2005 58 50 60 72 100 58 60 -
2001 46 40 40 64 75 41 48 -
Harvesting of
ragi 2005 128 120 60 700 72 100 87 410
2001 88 65 40 400 64 70 64 233
Harvesting of
jowar 2005 66 70 60 550 80 65 104 69 550
2001 49 60 40 400 71 50 66 55 400
Harvesting of
maize 2005 74 120 58 575 60 60 483 89 76 86 58 77 529
2001 55 75 46 425 50 40 333 79 60 60 41 57 379
Cane-cutting 2005 80 58 1810 100 60 3100 89 100 64 77 2455
2001 60 46 1295 80 40 2200 79 75 47 61 1748
Harvesting
other crops 2005 80 58 125 100 70 1338 89 95 64 87 1338
2001 60 46 75 80 50 825 79 65 47 65 825
Digging of
potatoes 2005 80 100 58 60 70 89 100 64 76 -
2001 60 80 46 40 50 79 60 47 59 -
Threshing of
paddy
2005 87 60 58 1500 150 60 60 668 89 85 190* 64 81 1084
2001 59 40 46 895 100 50 40 471 79 65 125* 47 59 683
Threshing of
wheat 2005 96 60 58 200 80 60 60 70 590 89 180* 229* 64 86 590
2001 66 40 46 125 50 50 40 50 475 79 100* 163* 47 61 475
Winnowing of
wheat/paddy 2005 60 60 58 390 200 50 50 70 233 89 180* 225* 64 80 312
2001 30 40 46 240 150 40 40 50 177 79 120* 156* 47 59 208
Note: * Rs per hour of machinery operation like tractor etc.
** Rs per acre
138
Table 6.5: Qualitative questions on changes in the villages during last one year (% of villages)
Sta
tes
Ka
rn
ata
ka
UP
Bih
ar
Sik
kim
AP
Ker
ala
Ha
rya
na
MP
Ch
ha
ttis
ga
rh
i
Ass
am
Pu
nja
b
Ma
hara
shtr
a
HP
Gu
jara
t
Ra
jast
ha
n
West
Ben
gal
Ag
greg
ate
Description Yes
Was there shortage of agricultural wage labour at some point during last year 80 100 30 75 70 35 70 35 30 38 20 80 30 60 70 91 57
After implementation of MGNREGA has there been a shortage of agriculture labour 70 80 30 75 70 70 40 70 70 36 60 70 60 70 50 94 63
After implementation of MGNREGA the cost of production in agriculture increased by 10 per cent because of scarcity of labour
30 10 35 13 70 15 80 80 80 68 60 50 30 50 30 28 46
Cost increased by 20 per cent 50 40 20 25 20 0 10 0 0 24 30 30 60 50 0 66 27
Cost increased by 20 to 50 per cent 20 30 40 63 0 50 10 20 20 8 10 20 10 0 20 6 20
Cost increased by 50 to 75 per cent 0 0 5 0 10 35 0 0 0 0 0 0 0 0 40 0 6
Cost increased by 100 per cent 0 20 0 0 0 0 0 0 0 0 0 0 0 0 10 0 2
Cost increased by more than 100 per cent 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
After implementation of MGNREGA labour who migrated earlier to town/city are coming back to work in the village
40 20 40 0 60 30 0 10 75 20 30 57 24
More labour is migrating from the village as wage rate in the town is higher than
wage rate under MGNREGA or other activities in the village
10 20 30 0 50 55 25 20 43 10 10 0 80 10 5 23
Some labour has come back to work in MGNREGA but others are moving to the
town/city because of wage differential
20 20 40 10 0 10 30 30 25 60 30 26 19
There is no change in labour migration by MGNREGA activities 0 30 20 100 10 15 85 80 58 90 40 20 70 30 0 41
After MGNREGA change in wages of casual labourers has increased 70 100 60 100 80 100 20 90 90 80 70 100 90 100 100 100 84
After MGNREGA change in wages of casual labourers has decreased 10 0 20 0 10 0 0 0 0 0 0 0 0 0 0 0 3
After MGNREGA change in wages of casual labourers remained same 20 0 20 0 10 1 80 10 10 20 30 0 10 0 0 0 13
The trend of people living in village and going to work outside daily has increased 30 40 40 0 40 80 20 15 20 35 30 30 50 70 20 0 33
The trend of people living in village and going to work outside for longer period has
increased
20 20 40 0 40 5 30 20 20 0 20 10 0 60 10 6 19
Has living standard improved in your village since the introduction of MGNREGA 40 70 20 100 100 80 50 15 15 54 20 70 10 50 80 100 55
After MGNREGA have you witnessed increase in household consumption in village 40 100 20 100 100 93 30 20 20 35 20 90 10 50 80 100 57
After MGNREGA have you witnessed more children are now going to the school 30 40 30 100 90 40 70 0 0 45 0 40 10 60 80 100 46
After MGNREGA, have you witnessed change in trend of attached labour in agriculture
40 30 15 13 100 75 0 60 60 54 50 30 10 70 0 94 44
After MGNREGA, have villagers’ awareness towards Government Schemes
increased
70 100 30 100 100 90 20 100 100 81 100 100 10 80 100 100 80
139
Chapter 7
Concluding Remarks and Policy Suggestions
7.1 Introduction
National Rural Employment Guarantee Act, now Mahatma Gandhi National Rural Employment
Guarantee Act (MGNREGA from October 2, 2009) was passed in the year 2005. The basic
objective of the Act is to ensure livelihood and food security by providing unskilled work to
people through creation of sustainable assets. The Ministry of Rural Development strives to
implement the Scheme in the most transparent and effective way. Under the provisions of the
Act, the state has to ensure enhancement of livelihood security to the households in rural areas
by providing at least one hundred days of guaranteed wage employment to every household
whose adult members volunteer to do unskilled work. In-built with various transparency and
accountability measures and provisions for social audits this Act for the first time brings the role
of the State as provider of livelihood. The programme was implemented in 100 most backward
districts in the country in the first phase during the financial year 2006-07. The second phase
started from the beginning of the next financial year (1st April 2007) whereby another 100
backward districts were added into the list of district where MGNREGA was under
implementation. From the beginning of the next financial year, i.e., 1st April 2008, the whole
country including the Union Territories were brought under the umbrella of MGNREGA Act.
Thus from the financial year 2008-09, MGNREGA has been implemented in the whole country.
The MGNREGA Scheme has high expectations in terms of employment generation, alleviation
of poverty, food security, halting migration and overall rural development. As the scheme has
already completed 6 years of its functioning, there is a need for a study to evaluate the scheme
for its impact on rural poor. Based on this background the study is conceptualized with the
following objectives:
1. Measure the extent of manpower employment generated under MGNREGA, their
various socio-economic characteristics and gender variability in implementing
MGNREGA since its inception in the selected states.
140
2. To compare wage differentials between MGNREGA activities and other wage
employment activities.
3. Effect of MGNREGA on the pattern of migration from rural to urban areas.
4. To find out the nature of assets created under MGNREGA and their durability.
5. Identification of factors determining the participation of people in MGNREGA
scheme and whether MGNREGA has been successful in ensuring better food security
to the beneficiaries.
6. To assess the implementation of MGNREGA, its functioning and to suggest suitable
policy measures to further strengthen the programme.
The study is based on both primary and secondary data. Primary data was collected from the
selected villages and households in 16 states as per the guidelines of the Ministry. From the each
selected state, five districts were selected, one each from the north, south, east, west and central
locations of the state. From each districts, two villages were selected keeping into account their
distance from the location of the district or the main city/town. From each selected village,
primary survey was carried out on 20 participants in MGNREGA and 5 non-participants working
as wage employed. In this fashion, from each state, 10 villages were selected and a total number
of 250 households were surveyed in detail with the help of structured household questionnaire.
In this way around 200 participants and 50 non participants were selected from each state and
data was collected in 16 states. The total sample consists of 3166 participants and 839 non
participants. The selected states were, Karnataka, Andhra Pradesh and Kerala in the South,
Himachal Pradesh, Uttar Pradesh, Haryana and Punjab in the North, Madhya Pradesh and
Chhattisgarh in the Central, Maharashtra, Gujarat and Rajasthan in the West, Bihar, and West
Bengal in the East and Sikkim and Assam in the North-east. The data was collected through
structured questionnaires. The data pertain to the Reference Period of January to December
2009.
In addition to household questionnaire, a Village Schedule was also designed to capture the
general changes that have taken place in the village during the last one decade and to take note of
increase in labour charges for agricultural operations after the implementation of MGNREGA.
The village schedule also has qualitative questions related to change in life style of the villagers
141
taking place during the last one decade. One village schedule in each village was filled up with
the help of a ‘Group Discussion’ with the Pachayat Members, Officials, educated and other well
informed people available in the village being surveyed.
7.2 Main findings
7.2.1 Total employment generated and their socio economic characteristics
In the three phases of MGNREGA implementation in India from 2006-07 to 2013-14 (up to
October) 81 crore households were issued job cards at the country as a whole out of which
around 34 crore households were provided employment averaging around 4.5 crore households
working in MGNREGA per annum that constitutes roughly around 30 per cent of the rural
households in the country as a whole. Andhra Pradesh, Uttar Pradesh and Rajasthan each
employed more than 3 crore households during this period. A total number of 1.5 thousand crore
man days of employment was generated by MGNREGA during the above mentioned time
period. The share of Scheduled Castes and Scheduled Tribes in the total person days generated
was 26.9 and 22.0 per cent, respectively while share of women in the total employment was 48.0
per cent.
At the aggregate, a total number of 45 person days of employment was provided by MGNREGA
whereas the target set under the programme is 100 days of employment per household. Highest
number of 54 days of employment that is slightly above 50 per cent of the target was achieved
only in the year 2009-10. Among the states, highest numbers of days of employment (60 to 70
days) was provided by the north-eastern states of Mizoram, Nagaland, Tripura, Sikkim and
Manipur. Rajasthan, Madhya Pradesh and Andhra Pradesh provided between 50 to 60 days of
employment. The other states like Chhattisgarh, Himachal Pradesh, Tamil Nadu, Karnataka,
Maharashtra, Uttar Pradesh, Jharkhand and Odisha provided 40 to 50 days of employment while
Haryana, Jammu & Kashmir, Uttarakhand, Gujarat, Kerala and Assam provided 30 to 40 days of
employment. The states that lied at the bottom included Bihar (31 days), Arunachal Pradesh,
West Bengal and Punjab (28 days, each) and Goa only 25 days of employment.
Out of the total 34 crore households working in MGNREGA during its full tenure, only 2.9 crore
households completed 100 days of employment. Around 25 per cent households working in
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MGNREGA completed 100 days in Mizoram, 20 per cent in Tripura, 18 per cent in Sikkim and
Nagaland each, 16 percent in Rajasthan and 14 per cent in Manipur. Tamil Nadu and Andhra
Pradesh were the other states where around 10 to 13 per cent households completed hundred
days of employment. Goa, Punjab and West Bengal were at the bottom where only less than 2
per cent households completed hundred days of employment. At the all India aggregate, only 8.4
per cent households completed hundred days of employment during the entire period of
MGNREGA in operation up till October 2013.
7.2.2 Number of projects completed and total amount spent
Water conservation was the leading activity which occupied around 24 per cent projects under
MGNREGA followed by rural connectivity projects 17 per cent, provision of irrigation 14 per
cent, drought proofing 13 per cent, land development 10 per cent each, renovation of traditional
water bodies and Micro irrigation 6 per cent and flood control 3 per cent. During the entire
period of MGNREGA, a total number of 1 crore projects were completed and around 2.9 crore
were ongoing. Thus, out of total 4 crore projects taken up under MGNREGA around 30 per cent
were completed and rest of 70 per cent were in progress. A total amount of 2,35,084 crore was
spent on the MGNREGA with an average of slightly less than 30 thousand crore every year.
Working out the total expenditure incurred per project it turns out around 59 thousand per
project for all MGNREGA works undertaken so far at the aggregate.
During the whole period of implementation of MGNREGA a total amount of 75 thousand crore
was spent on rural connectivity, 45 thousand crore on water conservation, 27 and 25
thousand crore on renovation of traditional water bodies and drought proofing, respectively, 17
thousand crore on provision of irrigation, 16 thousand crore on land development, 12
thousand crore on micro irrigation, 11 thousand crore on flood control and around 6 thousand
crore on other activities. At the aggregate, the highest amount per project was spent on
renovation of traditional water bodies 121 thousand per project that was closely followed by
112 thousand per project on rural connectivity. Expenditure on flood control lied on the third
place with an expenditure of 79 thousand per project. Micro irrigation had a spending of 53
thousand per project, followed by drought proofing 49 thousand per project, water conservation
47 thousand per project, land development 40 thousand per project and provision of irrigation
143
29 thousand per project. Thus, whereas water conservation topped in the total numbers of
projects undertaken but spending on per project was much less on water conservation compared
to rural connectivity that topped among all projects not only in the total amount spent but also
amount spent per project. State wise highest amount per project was spent in Manipur 297
thousand followed by Nagaland ( 245 thousand), Mizoram ( 269 thousand), Tamil Nadu
( 255 thousand), Assam ( 191 thousand) and Maharashtra ( 160 thousand). The states that lied
at the bottom in spending per project were Andhra Pradesh ( 18 thousand), Gujarat ( 41
thousand), Karnataka and Goa ( 48 thousand), Kerala ( 49 thousand), and Uttar Pradesh (
54 thousand) only.
7.2.3 Qualitative indicators of MGNREGA performance
During 2008-09 to 2013-14 (up to October), a total number of 10.52 crore muster rolls were
opened in the country out of which around 85 per cent were verified by the authorities who
carried out the auditing work. Social auditing of MGNREGA work of the Gram Panchayats (GP)
was held in around 87 per cent of the GPs during the above mentioned period. The social audit
was held in above 90 per cent GPs in Tamil Nadu, Madhya Pradesh, Kerala and Nagaland
whereas, it was held in less than 60 per cent GPs in Arunachal Pradesh, around 60 to 65 per cent
GPs in Jammu & Kashmir and Karnataka. The percentage of works inspected at the district level
was very low only 12 per cent whereas the works inspected at the block level was as high as 81
per cent. Almost half of the works were inspected at the district level in Arunachal Pradesh while
proportion of inspected works was half to 1/3rd
in Assam, Sikkim, Nagaland and Kerala. In rest
of the states, less than 1/3rd works were being inspected at the district level. Complaint redressal
system was adopted under MGNREGA and a total number of 215542 complaints were registered
in all the states out of which around 84 per cent were redressed. Complaint redressal was 100 per
cent in Goa, Arunachal Pradesh and Mizoram. It was less than 80 per cent in Madhya Pradesh,
Maharashtra, Odisha, West Bengal and Gujarat while in rest of the states above 80 per cent
complaints were redressed during the above mentioned period.
The Gram Panchayats are encouraged to make payments to the workers through banks or post
office. A total number of 41 crore individual and joint accounts were operative in banks and post
offices through which payments were made for MGNREGA works during the period 2008-09 to
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2012-13. It is interesting to note that out of total amount paid through banks and post offices in
MGNREGA during the period 2008-09 to 2012-13, the average amount paid through bank/post
office per account was 1.97 lakh. State wise, the highest amount paid per account was in
Nagaland ( 24 lakh), Meghalaya ( 9.5 lakh), Mizoram ( 6 lakh), Sikkim ( 5.8 lakh) and
Tripura ( 3.8 lakh). The lowest amount was paid in Tamil Nadu (only 3 thousand), Bihar ( 1
lakh) and Gujarat ( 1.2 lakh). According to the legislation on MGNREGA, if a member of a
household has not been provided employment after issuing him/her a job card after a lapse of 15
days, the GPs are supposed to provide unemployment allowance and such amount would be
borne by the concerned state government. During the period 2007-08 to 2013-14 (up to October)
unemployment allowance was due for 4.83 crore person days for which employment was not
provided to the job card holders but only 2478 days of allowance was paid that makes only 0.01
per cent days of unemployment allowance paid and it was not more than 0.04 per cent in any
state.
7.2.4 Household characteristics their income and consumption pattern
The average household size was 4.75 with participants having average family size of 4.7 and non
participants 4.9. The average numbers of earners in the family were 2.2 members among
participating families and 2.6 members among the non participating families. Similarly, the
number of members in working age (i.e., 16-60 years) was 74.4 per cent among participants and
73.7 per cent among non participants. Looking at the education status among the selected
households, the percentage of illiterate was around 1/3rd
among the participants and less than
1/3rd
among the non participants. On the overall, non participants were better educated compared
to participant household members. Looking at the caste distribution among the participating
households, the percentage of households belonging to Scheduled Caste (SC), Scheduled Tribes
(ST) and Other Backward Castes (OBC) was 34, 17 and 34 per cent, respectively while General
category had only 16 per cent proportion among the selected households.
The trends in occupation depict that among the participating households, the proportion of work
provided by MGNREGA was only a small proportion of their aggregate employment. Out of the
total man days employed per household including all the working members, the share of
MGNREGA varied between 12 to 32 per cent among different states. It was less than 15 per cent
145
in Karnataka, Kerala, Assam, Gujarat and West Bengal. Its proportion was between 15 to 25 per
cent in Uttar Pradesh, Sikkim, Madhya Pradesh, Chhattisgarh, Maharashtra, Himachal Pradesh,
Rajasthan, Haryana and Punjab. The share of MGNREGA in total employment was above 25 per
cent only in two states namely Bihar and Andhra Pradesh. At the aggregate, MGNREGA
provided 18 per cent share in the total employment among our selected households. Casual
labour in agriculture and non agriculture sector constituted more than 40 per cent share in
employment. Self employment in agriculture and livestock constituted around 20 per cent share
and self employment in business and regular salary had around 5 and 10 per cent share,
respectively in the total employment among the selected participants.
A glance on the household income statistics reveals that the estimated per household income of
non participant households was higher compared to participant households. On an average, the
selected non participant households earned 70 thousand per annum compared to 59 thousand
earned by the participating households. Comparing the sources of income across different
activities, wage income constituted a lion’s share in the income of both participating as well as
non participating households. Earnings from agricultural wages contributed around 17 per cent
followed by wage earnings from non agricultural activities 22 per cent, while wage earnings in
MGNREGA activities contributed only 12 per cent share in the total household income of
participants. In addition to wage earnings, income from self employment in agriculture and
livestock constituted around 17 per cent share of their household income while regular salaried
job contributed around 14 per cent share in the household income of the participating
households. Trends in share of various sources were somewhat similar in the case of non
participating households.
Majority of the states observed household income less than the aggregate average of 59
thousand. Ironically, the states that observed highest household income namely Kerala and
Assam, however, had much lower percentage coming from the MGNREGA activity less than 7
per cent in Kerala and only 3 per cent in Assam in the aggregate income. Highest share
contributed by MGNREGA in total household income was observed in Maharashtra (29 per
cent), followed by Haryana and Sikkim (25 per cent, each), Andhra Pradesh and Punjab (18 per
cent, each), West Bengal, Rajasthan, Madhya Pradesh and Uttar Pradesh (each having above 13
146
per cent share). The dispersion of income across households was highest for agriculture and
livestock income for both participant and non participant households while it was comparatively
less in MGNREGA activities indicating lesser amount of wage rate differentials in MGNREGA
as compared to casual wage rate in agriculture and non agricultural activities.
On average, per capita cereal consumption satisfied the 1200-calorie norm, i.e., total cereal
consumption surpassed 10.5 kgs per capita per month by both the participant and non participant
households. The average cereal consumption was measured at 11.1 kg per capita per month in
the case of participants and 11.6 kg per capita per month in the case of non participants. The
states that reported less than 10.5 kg cereal consumption were Bihar, Punjab, Maharashtra and
Rajasthan among both participants and non participants. Pulses consumption varied between 0.5
to 3 kg per capita per month among different selected states and it averaged around 1 kg among
both the participants and non participants. The diversification of consumption from cereals and
pulses towards edible oils, milk and high value products was visible from our data. The quantity
of high value commodities like milk and milk products, fruits and vegetables was higher for non
participant households compared to participant households as non participants income was also
higher compared to participant households.
Total monthly food expenditure among our selected sample averaged at 421 for the participants
and 455 for the non participants whereas NSS food expenditure for all India averaged around
600. The difference between participants and non participants was much higher in the non food
expenditure, especially in education, clothing and other items including medical and health. The
overall non food expenditure was 237 per capita per month among the participants compared to
271 among the non participants. Our non food expenditure was under estimated as is clear
from the much above NSS amount of 453. The difference could be due to under reporting and
may be few items missing in our questionnaire like conveyance, consumer services, various
entertainment goods, rent, taxes and other durable goods. Comparing food and non-food
expenditure, the proportion of food in total expenditure was 64 per cent among the participants
and 63 per cent among the non participants. In comparison, share of food expenditure in the NSS
data was 57 per cent of total expenditure that also indicate that our non food expenditure was
slightly under estimated. Looking at the concentration ratio, the Gini coefficient of income was
147
mostly higher than that of consumption for both participants and non participants. The, higher
variation in income compared to consumption shows the more vulnerability of the household in
the case of an external shock to the household income and the necessity of households to search
for some formal or informal sources of consumption smoothening.
7.2.5 Determinants of participation in MGNREGA
The logit function provided us the probabilities of the participation of a household in
MGNREGA activities. State level regression results showed that the households who had
alternate employment opportunities and those who had higher income contribution from other
activities had less incentive to work in MGNREGA. The coefficient for employment other than
MGNREGA was negative and significant in Sikkim, Haryana, Madhya Pradesh and
Chhattisgarh. Coefficient of income other than MGNREGA was significant and negative in
Madhya Pradesh, Chhattisgarh, Punjab, Maharashtra and Himachal Pradesh. The household size
had significant and positive sign in Karnataka, Andhra Pradesh, Kerala, Haryana, Madhya
Pradesh, Chhattisgarh, Punjab, Maharashtra and West Bengal indicating with increase in family
size there was more probability of household members working in MGNREGA among the
selected households. Household size had significant but negative relationship in Uttar Pradesh
and Himachal Pradesh indicating low participation at higher family size in these two states.
The value of assets and land ownership had negative sign in the regression indicating household
members with land ownership or better assets accumulation had less probability of participating
in MGNREGA activities. The coefficient was significant with a negative sign in Karnataka,
Uttar Pradesh, Sikkim, Madhya Pradesh, Assam, Punjab and West Bengal. On the opposite, if a
household owned an AAY or BPL card or if they belonged to Scheduled Caste or Scheduled
Tribe community they had higher possibility of entering into MGNREGA work. The coefficient
of dummy BPL was found positive and significant in Karnataka, Sikkim and in Haryana.
Similarly, coefficient of social characteristics (household belonging to SC, ST and OBC) was
found significant and positive in Sikkim, Andhra Pradesh, Chhattisgarh and Maharashtra. From
the household OLS regression, the most important and significant variable emerged was wage
rate in MGNREGA with a positive sign in almost all the states indicating that with higher wage
rate households preferred to work in MGNREGA.
148
Some interesting relations were observed in the member level logit regression. Among the
members in a household, those who worked in MGNREGA had a direct and significant
relationship with age and negative relationship with education. The implication is that older age
and less educated people preferred to work in MGNREGA as the latter is known providing soft
wages. Similarly, the dummy on sex indicates that the male members had higher probability of
working in MGNREGA compared to female members although female proportion in total work
force constituted around 45 per cent varying in its degree from state to state. The members with
BPL and AAY cards and members belonging to SC and ST community had better probability of
working in MGNREGA. The above findings were generally true across the states.
7.2.6 Work profile under MGNREGA, wage structure and migration issues
According to our survey data, on average, less than two members (1.7) per family were
employed under MGNREGA. Among the selected states, the average exceeded 2 members per
family working in MGNREGA in Sikkim, Gujarat, Chhattisgarh and Andhra Pradesh. It was
between 1.5 and 2 members in Karnataka, Haryana, Madhya Pradesh, Maharashtra and West
Bengal. The states that employed less than 1.5 members per family were Uttar Pradesh, Bihar,
Kerala, Assam, Punjab, Himachal Pradesh and Rajasthan. The highest numbers of members
employed under MGNREGA among the selected households was found 2.8 members in Sikkim
and lowest, 1.07 in Kerala. Out of 1.68 members employed under MGNREGA at the aggregate,
0.98 members belonged to male households and 0.70 members belonged to female households.
Only in Gujarat and Rajasthan, the numbers of female member per household working in
MGNREGA exceeded that of male and in Sikkim and Maharashtra their percentage was same.
Against the average of 1.68 aggregate members per family, the average was 1.47 for the SCs,
1.67 for STs and 1.53 for the OBCs. The SC and ST households’ average was highest 2.63 and
2.53 members in Gujarat and lowest 0.22 and 0.19 members in Bihar, respectively.
On an average, 68 days per household employment was generated among our selected
participants. The states that topped in employment generation among our selected participants
included Maharashtra (100 days), Haryana (94 days), Himachal Pradesh (92 days) and
Rajasthan, Sikkim and Gujarat (slightly above 80 days). The states that were slightly above or
149
below the national average were Madhya Pradesh, Karnataka, Kerala and Uttar Pradesh (between
80 to 60 days). The states that lied at the bottom were Bihar (32 days), Andhra Pradesh (43 days)
and Assam (48 days). Looking at the ratio of employment among the male and female workers,
numbers of days of employment was shared by male (37 days) and female (30 days) with a per
cent share of 56 for male and 44 for female.
Out of 16 states for which analysis is done only in 10 states information about households
completing 100 days of employment was available. Among these ten states, the percentage of
households who completed 100 days, only in Himachal Pradesh their percentage was
exceptionally high (85 per cent). In Haryana and Rajasthan, 48.5 and 44.5 per cent households
completed 100 days. In Karnataka and Sikkim around 1/4th
of the participant households
completed 100 days of employment. In Bihar, Assam, Gujarat and West Bengal only less than 5
per cent households completed 100 days and in Uttar Pradesh around 10 per cent households
completed 100 days. At the aggregate, only 1/4th
of the selected participants in these 10 states
completed 100 days. In other words, MGNREGA was not quite successful in providing social
security to the households as households had to depend on other activities for earning their
livelihood as MGNREGA provided only 18 per cent share of the total employment to the
selected households.
Looking at the wage rate on which employment was provided, average wage rate at the
aggregate was recorded at 100 and it was not particularly different among male and female.
The highest wage was recorded in Haryana ( 150), followed by Kerala ( 125), Punjab ( 123)
and Himachal ( 110). Among the selected states lowest wage rate was paid in Rajasthan ( 80),
Chhattisgarh ( 83) West Bengal ( 84) and Karnataka ( 86). However, in most of the states
actual wage rate obtained under MGNREGA was below the stipulated minimum wage rate fixed
by the states under the Minimum Wages Act 1948. The difference between the actual payment
and minimum stipulated wages was specifically high in Karnataka ( 33), Maharashtra ( 22),
Rajasthan and Assam ( 21), Madhya Pradesh ( 19), Andhra Pradesh and Punjab ( 14), Gujarat
and Haryana ( 12) and Bihar ( 10). Last but not the least, the average distance of work place
form the residence or village of the households was less than 2 kilometers in all the states with
few exceptions.
150
Among the surveyed households, the highest work under MGNREGA was concentrated on rural
connectivity which shared around 40 per cent of the total employment followed by water
conservation and water harvesting which shared 17 per cent of employment under MGNREGA.
Land development (12 per cent), renovation of traditional water bodies (11 per cent), flood
control and protection (8 per cent) and micro irrigation (5 per cent) were the other major
activities of employment under MGNREGA. On the question of how was the quality of the
assets created through MGNREGA work, a little less than half of the households indicated that
the assets created were very good while another half of them indicated that assets created were of
the good quality. Only less than 3 per cent households pointed out that the assets created were
bad or worst in quality. We enquired the selected households whether after registration if they
did not get employment did they receive any unemployment allowance, households indicated
that they did not receive any such allowance except in Maharashtra and West Bengal where
households received only a poultry amount as unemployment allowance.
Our statistics on migration indicates that around 0.20 members per family (with average size of
4.7 members) migrated because of not getting work under MGNREGA. Out of the selected
states, the numbers of per family members migrated because of not getting work averaged at
0.54 in Assam, 0.44 in Rajasthan, 0.31 in Madhya Pradesh and Maharashtra each, 0.20 in Andhra
Pradesh, Chhattisgarh and Himachal Pradesh, each and less than 0.1 members in rest of the
selected states. Thus, incidences of villagers’ migration in search of work despite having been
registered for MGNREGA were still recorded in the surveyed villages. However, there were also
incidences whereby around 0.12 members per family among the participant households returned
back to the village to work under MGNREGA at the aggregate who hitherto were working
elsewhere before the implementation of this Programme. The members retuning back to work
under MGNREGA was highest in the state of Bihar where around 0.65 members per family
returned back to work under MGNREGA after the implementation of the Act. Among other
states, the incidence was recorded in Andhra Pradesh, Rajasthan, Madhya Pradesh and
Maharashtra where, on average, 0.1 to 0.2 members per family returned back to work in
MGNREGA after implementation of the Act. Punjab, Haryana and Assam were the only states
where no such reverse migration incidences were recorded. On the overall, it is difficult to say
151
whether the MGNREGA programme has been successful in cutting down the incidences of
labour migration from villages in search of job. The majority of the households who returned
back to work in MGNREGA pointed out that they were now better off compared to earlier
working as a migrant labourer.
7.2.7 The functioning of MGNREGA – Qualitative aspects – (Field Survey)
The analysis of assets and borrowing points that participant households were much more
vulnerable compared to non participant households. Whereas, participant households owned
assets less than half that of non participant households, their borrowing level was almost double
that of non participant households. Not only was the loan amount higher for the participants,
their proportion of non institutional loan was also much higher. Checking with the financial
strength on borrowing, around 10 per cent of participating households indicated that they are
doing wage work for those with whom they are indebted, whereas 8 per cent of the non
participating households indicated the same. Around half of the selected households pointed out
that there was a cooperative society in their village but less than ¼th
of the households were
members of such society within their village. Similarly more than ⅔rd
majority of the household
agreed that there was at least one informal credit society or self help group in their village but
only ⅓rd
of the selected households were members of such societies. More than ¾th
of all
selected households had an account in the bank or post office but only 2 per cent of the selected
households had any financial assets, like stock, bond or share of a company. Similarly, less than
15 per cent participant households and around 20 per cent non participant households had a life
insurance policy.
On the qualitative questions, a majority of the households indicated that they did not have to pay
any bribe to get a job card issued. Regarding irregularities in the job card around 15 per cent
households at the aggregate indicated that either, no entry was made in the job card about the
work performed under MGNREGA or entries were missing or fake; entries were over written or
signature column was blank, while clear cut majority observed no such irregularities. Around 80
per cent of the household were given employment in response to their application for work. All
households who did not get work within 15 days indicated that they did not get any
152
unemployment allowances in lieu of not getting work within the period of 15 days after putting
up their application for work under MGNREGA.
On the system of payment of wages almost all participating households agreed that wage rate for
male and female was same. The payment system was both daily-wage basis and piece rate/task
wage basis. In majority of cases, work was measured on collective or team management basis
while in a thin majority it was measured on individual work basis. A majority of participant
households pointed out that wages were paid either fortnightly or monthly basis but around 12
per cent participants pointed out that they had to wait for a longer period or at least more than a
month to realize their wages from MGNREGA work. It is interesting to note that majority of the
participants (more than half of them) obtained their wages through bank. Another 40 per cent of
the participant indicated that they obtained wage through the post office. Only 5 per cent of the
interviewed household obtained their wages through Sachiv/Contractor/Others and this fact
makes MGNREGA programmes different from all other employment generation programmes
under operation in different states. Further with a few exceptions, the bank accounts were on the
individuals’ name working in MGNREGA. Among the irregularities in wage payments, the
participant households indicated that there was delay in wage payments after the work was
finished; the wage paid was less than the task performed and the participants faced problem in
accessing post office or bank account and lastly they were not aware on what basis wages were
determined in case of those whom wages were not paid on daily wage basis. Delay in wage
payment was reported by highest numbers of participants in Andhra Pradesh, Chhattisgarh,
Madhya Pradesh, Gujarat and Rajasthan.
Regarding information about the work to be performed and facilities available at the worksite,
around ⅔rd
majority of participants pointed out that they were given requisite details of the work
to be performed. About the facilities available at the worksite, around ¾th
of the participants
agreed that drinking water facility was provided at the worksite. About the facilities like shade
for period of rest; child care facilities; first aid kit and primary medicines available at the
worksite around 40 to 50 per cent participants replied that these facilities were not available on
the work site. Lack of drinking water, child care and medicine facility at the work place was
mostly reported by participants in Karnataka, Haryana, Madhya Pradesh and Punjab.
153
On the monitoring of the MGNREGA functioning more than 80 per cent participants indicated
that the work was being monitored through some authority but majority of them did not know
whether any auditing of the accounts take place or not. In Haryana around 80 per cent
participants indicated that there was no monitoring taking place while 16 per cent expressed their
unawareness and only 4 per cent participants indicated that monitoring of MGNREGA work was
being held. In all other states more than 60 per cent participants indicated that the work was
being monitored. Very few participants lodged any complaint and even who indicated that they
lodged a complaint only 7 per cent of them said that their complaints were taken care of.
Around 90 per cent of the participated households pointed out that the work done was useful to
the villagers. Only less than 10 per cent households pointed out that the work done was not
particularly useful for the villagers. To the question of how long the constructed structure may
last, around 30 per cent opined that it may not last more than one year while around 40 per cent
expressed hope that the structure will last up to five years. More than ¾th
majority of the
participant households pointed out that it was worth to create the structure or in other words,
created structure would be useful for the villagers. Similarly, slightly above ⅔rd
majority of the
households indicated that the structure created was adequate with due attention being paid to it.
Some incidents of migration out of the village as well as migration back to the village (to work
under MGNREGA) were cited, but the extent of the same was only miniscule, not leading to the
conclusion that MGNREGA had any conclusive evidence of affecting labour migration into any
particular direction. Some household members migrating out for job after implementation of
MGNREGA among the selected states was observed comparatively higher in Bihar, Gujarat,
Assam, Rajasthan and Maharashtra. However, in Bihar and Maharashtra the incidence of family
members migrating back to village to work under MGNREGA was also found higher than the
other states indicating the reverse migration occurring along with the incidence of migration
among the participant households. Regarding the question of villagers’ awareness about
‘Mahatma Gandhi National Rural Employment Guarantee Act’ under implementation in the
village, a clear ⅔rd
majority of the respondents pointed out that people in the village were aware
about the same. However, households were hardly aware about the provision of unemployment
allowance under MGNREGA. Similarly, majority of the respondents were not aware about
154
provision of the worksite facilities, mandatory availability of muster rolls at the worksite and list
of permissible works under the MGNREGA.
To understand how the MGNREGA programme has affected the general life of villagers we
enquired few questions related to participants’ day-to-day life. Around 67 per cent participants
were of the view that MGNREGA has enhanced food security of the villagers by providing them
employment and thus purchasing power to have better access to food. Around 60 per cent
participants pointed out that MGNREGA has given greater independence to women. Around 65
per cent agreed that MGNREGA provided protection against extreme poverty. On the migration
issues, around 49 per cent indicated that MGNREGA has helped to reduce distress migration
from the village to cities. Similarly, around 50 to 60 per cent pointed out that MGNREGA has
reduced indebtedness by generating purchasing power at the local economy.
We further probed the food security issues among the participants. To our question did your
family get full two square meals throughout the reference year, around 24 per cent households
answered in negative. If the households did not have sufficient food how did they cope up with
the situation? Around 37 per cent affected households indicated that they borrowed from some
sources to cope up with the situation. Around 13 per cent pointed out that they reduced the
numbers of meals during the crisis period while others took other measures like catching fishes
or rats etc. The states where maximum number of households indicated not having two square
meals among the selected states were the poor states of Assam and Bihar while in the states of
Haryana and Andhra Pradesh no household reported not having sufficient meal during any
month of the reference year.
7.2.8 Some quantification of qualitative questions
A 3/4th
of majority of those who did not have job card with them did not know the real reason for
not having card with themselves while around 1/4th
of them replied that the head of the
Panchayat (Sarpanch) or contractor had kept it with themselves to make entries in the card or for
security reasons. To our question who monitored the functioning of MGNREGA? Around 11 per
cent participants said it was supervisor while around the same numbers also indicated that the
person was some government official at the block or district level. However, a clear majority
(around 50 per cent) named the Gram Panchayat or Panchayat Secretary mainly functioning for
155
the monitoring work of MGNREGA. The rest of the participants (less than 1/3rd
) were not
knowing whether there was any monitoring being carried out or if so who carries out the same.
On the question how MGNREGA has enhanced food security, a majority of the participants
pointed out that by providing employment MGNREGA has helped their food security during the
working days, moreover by saving some money when they are employed, they now have better
food security when they are not employed in MGNREGA as well. However, overwhelming
majority indicated that MGNREGA can ensure better food security by guaranteeing at least 100
days employment to every household and the programme would be more useful in ensuring food
security if they are also provided food at the work place.
To the question how MGNREGA provided protection against extreme poverty, the respondents
were of the view that although MGNREGA provided extra purchasing power and reduced
migration but it could be more effective if it could provide full 100 days work; provide wage on
daily basis; stipulated minimum wage are ensured; and poorest people are given top priority. To
the question of migration, a significant number of respondents pointed out that to some extent
MGNREGA has been successful in reducing the distress migration but it can be more effective
in stopping unnecessary migration if 100 days work and minimum stipulated wages are ensured.
Similarly, respondents agreed that indebtedness to informal sources would also be checked if
MGNREGA provides employment to people at higher wage rate compared to prevailing wage
rate within the village.
7.2.9 MGNREGA impact on village economy
The surveyed villages had mixed picture with some villages having perfect infrastructure like
road, post office, bank, SHG, school, primary health centre, FPS etc., while others had to travel
some distance to approach the same. During the last ten years there has been a slight change in
the occupation structure in the selected villages. The prevailing wage rates in agriculture were
fluctuating widely. Prevailing wage rate in non agricultural sector were much higher compared to
the agricultural sector and the level of skilled wages were almost double that of unskilled wages.
Comparing the wage rate over the last five years, i.e. since the time MGNREGA has come into
implementation, the wage rate in agriculture sector has increased by slightly less than 50 per cent
156
for male and slightly above 50 per cent for the female. By the same estimates, wage rate for
unskilled as well as skilled labour in the non agricultural sector increased by slightly less amount
compared to agriculture labour except the wage rate in mining during the same time period. The
wage rate for unskilled labour in non agriculture and construction work increased slightly less
than the wage rate increase in agriculture while wage rate for skilled labour in mining increased
slightly more than agriculture. The wage rate for technical work like electrician, plumber and
pump set boring increased by less than that of agriculture (between 35 to 47 per cent). Thus,
increase in wage rate in agriculture more than most of the other activities within the village
indicate the enhanced demand for wage labourers due to employment works in MGNREGA that
goes parallel with the agriculture sector thereby causing a competition in the labour market for
the agriculture sector. Increases in charges for agricultural operations per acre on an average
were almost similar to increase in agricultural wages as overall wages observed an increase of
around 49 per cent compared to around 46 per cent increase in cost of per acre agricultural
operations as per our group discussion data.
A majority of the villages indicated shortage of agricultural labour has increased after the
implementation of MGNREGA. In majority of the villages the shortage of labour was observed
during the sowing and harvesting months of kharif and rabi seasons especially in the months of
July, August and September and March and April. This was more so after the implementation of
MGNREGA. A majority of villagers were of the view that after MGNREGA implementation
cost of production in agriculture has increased by 10 to 20 per cent because of scarcity of labour.
On the question, whether workers who earlier migrated out of the village to work in city are now
coming back to work in MGNREGA, the trend of villagers returning back to the village to work
in MGNREGA was found more prevalent in Andhra Pradesh, Himachal Pradesh, West Bengal,
Bihar and Karnataka while reverse was the case in Gujarat and Kerala. But a majority of
participants in the discussion indicated that MGNREGA has not made any significant changes in
the migration pattern in the village.
Another point of debate was how the MGNREGA has affected living standards of villagers, a
clear majority indicated that MGNREGA has not been successful in raising their living standards
or their consumption level and the reasons was quoted that the programme has not provided
157
enough numbers of days of work to make a significant dent on the poverty level, although a
minority of them were of the view that MGNREGA has been successful in doing so, to some
extent. The latter ones indicated that MGNREGA has improved living standards by providing
work within the village and by ensuring same wage rate to female as equal to that of male. To
another question, whether MGNREGA has changed the trend of attached labour in agriculture, a
significant majority said yes as people were getting better payments within the village compared
to agricultural work so the trends of attached labour for the agricultural work were declining.
However, MGNREGA has certainly increased people awareness towards Government schemes
through increase in the showcasing by television, newspaper, Gram Panchayat and Gram Sabhas
and by other means. Among the selected states, in Sikkim, Andhra Pradesh, Kerala, Rajasthan,
West Bengal, Uttar Pradesh, Maharashtra and Gujarat, a clear majority of the discussants
expressed that the household consumption as well as enrollment of children in the school have
increased after implementation of MGNREGA that has provided extra purchasing power in the
hands of the villagers. On the question of awareness almost all states observed increased
awareness of the households towards existing government schemes because of their participation
in the gram sabha and also because of joint working opportunities in MGNREGA
7.2.10 Villagers’ suggestions to raise efficacy of MGNREGA
Among the steps needed to ensure better implementation of MGNREGA, the major ones
suggested by the discussants included: increasing working days and wage rate; providing food
within the programme; allowing private land development through MGNREGA work for
longevity of the programme; and by providing proper information on various aspects of the
programme; implementation should be carried out though local bodies and job card should be
given in the hands of the workers; quick payment after work.
7.3 Policy Suggestions
In the light of above discussion following policy suggestions can be made to improve the
functioning of MGNREGA.
The MGNREGA has not been successful in providing stipulated 100 days employment to
all the registered persons. The reasons expressed by the Panchayat and district officials
158
were many including lack of funds; money not being provided from the Central
authorities on time; the gap with which money reaches to the Panchayat officials; and
money being provided only for few months and not the whole year. The results of the
household survey clearly indicate that unless participants are given work for the
stipulated 100 days, MGNREGA shall not be able to make any significant dent on the
rural poverty and would fail in its basic objective. Therefore provision of 100 days
employment to all the participants should be made mandatory and strict action should be
taken against the Panchayats which fail in fulfilling this target. The issue of timely
provision of money to the Panchayats should be looked into so that MGNREGA work
does not suffer because of lack of funds with the Panchayats.
Another big anomaly was found in the wage rate paid under MGNREGA. Whereas under
the MGNREGA Act, Panchayats are ordained to pay at least equal to the minimum wage
determined for the state during a particular period. However, the actual wages paid under
MGNREGA were found much lower. Among participants in Karnataka, those who were
paid equal to or above the stipulated minimum wage, their percentage was only 1.4.
Those who were paid 100 or above constituted only 22 per cent and those who were
paid between 80 and 100 their per centage was 63, while the percentage of those paid
less than 80 was around 15. Thus, above 40 per cent of the selected participants were
paid less wages by 50 per cent or more compared to the stipulated minimum wage in the
state during the reference period. Among the corrections suggested by the households,
almost all of them wanted that the minimum stipulated wages should be ensured for all
participants irrespective to the nature of work they were involved in.
In the village analysis it was observed that there seems to be a conflicting interest
between the MGNREGA and the farming community. Farmers across the board are
feeling that they are facing labour shortage for agricultural activities because of the
diversion of labour caused by MGNREGA activities. With a meticulous planning, this
problem can be solved without affecting anyone adversely. In our secondary analysis, we
saw that MGNREGA has provided not more than 45 days of employment per household
at the all India and all states failed in providing stipulated hundred days of employment to
all households working in the programme. Even if the stipulated hundred days
employment is provided by the MGNREGA, still there is enough scope for the labour
159
force to work in the agricultural sector. There is however need to plan the MGNREGA
work at the Panchayat level in such a way that it does not clash with the sowing and
harvesting season in agriculture when the demand for agriculture labour is highest. The
projects taken up under MGNREGA should be planned in such a way that labour is
strictly employed for the project after the sowing and harvesting season of main rabi and
kharif crops is over. This planning has to be done at the Panchayat/Block and District
level depending upon the cropping pattern of the respective regions. It not only would
provide necessary labour force for agricultural operations but also would increase
employment and income opportunities for the villagers during the off-season including
that of marginal and small farmers who do not have enough work at the farm in the off-
season.
Another reason for authorities not being able to provide stipulated days of employment
to the participants, as was observed during the field survey, was that many a times
Panchayat (or other concerned authorities) ran out of ideas as in what activity labour
force should to engaged to keep them working. In many a cases labour force under
MGNREGA was used just for digging, clearing jungle, sweeping, dust-cleaning,
collecting waste and filling mud into the tractor and so forth as there was no long term
durable asset creation work available with the Gram Panchayats. In the qualitative
questions, most of the participants appeared to be worried for continuity of the
MGNREGA works and suggested for allowing the private farm work under MGNREGA.
The idea seems to be quite rational. In the villages where Pachayats fail to have any
utility work to be taken up under MGNREGA, rather than making payment for
unproductive works which make no value addition, it is better to take up development
work on the private farms. The terms and conditions of work can be planned in an
intelligent way. The farmer has to pay to the Panchayat for the work done by the
labourers at the prevailing rate in the village. The residual amount (difference of the wage
paid by the farmer and the stipulated minimum wage for MGNREGA) would be paid to
the labourers by the Panchayat. This is a win-win situation for both farmers as well as
Panchayat as the amount saved by the Panchayat from the MGNREGA fund can be used
for other development work of the village. This will also partly solve the problem of
labour shortage in agriculture as being faced at the present. Already provision of
160
irrigation facility, horticulture plantation and land development facilities to land owned
by households belonging to the Schedule Castes; Schedule Tribes; BPL families;
beneficiaries of land reforms; and beneficiaries under the Indira Awas Yojna have been
granted under the Act. Further, the benefits of works on individual lands have been
extended to small and marginal farmers vide notification dated 22.7.2009. These should
be encouraged by the Panchayat officials and permission should also be granted for land
development works for all other farmers as well, the facility to the latter one may be
granted on payment basis as explained above.
Proper punishment system should be put up in place for the unscrupulous officials who
are found guilty of indulging in corruption and other untoward activities. Similarly, those
Gram Panchayats that work efficiently in running the MGNREGA system should be
rewarded and felicitated appropriately.
The provision of food/grain at the work place and easy institutional credit can attract
more villagers, especially the poor ones towards working in MGNREGA and also
ensures better food security to the participants.
The Unique Identification (UID) should be used for the better functioning of MGNREGA
Anderson et al (2013). Bank accounts for MGNREGA workers will be linked to the
unique biometric id. As a result, the actual transfer of payments will immediately reach
the hands of who it is intended for. This would drastically reduce the alleged inherent
corruption in the current system and increase the amounts and reliability of payments to
the workers.
161
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Annexure Tables
166
ANNEXURE – I
The Details of AERCs and the Lead Person Involved in the State Report
Sl. No. States AERC who carried the
study in the state
The Lead Person Who Carried Out the Study
1. Andhra Pradesh AERC Waltare G. Gangadhara Rao and K. Adiseshu
2. Assam AERC Guwahati Jotin Bordoloi
3. Bihar AERC Bhagalpur Rajiv Kumar Sinha and Rosline K. Marandi
4. Chhattisgarh AERC Jabalpur Hari Om Sharma and Deepak Rathi
5. Gujarat AERC Vidyanagar V.D. Shah and Manish Makwana
6. Haryana AERC Delhi D.S. Bhupal
7. Himachal
Pradesh
AERC Shimla C.S. Vaidya and Ranveer Singh
8, Kerala AERC Chennai R. Arunachalam and A. Abdul Salam
9. Madhya Pradesh AERC Jabalpur Hari Om Sharma and Deepak Rathi
10. Maharashtra AERC Pune Jayanti Kajale and Sangeeta Shroff
11. Punjab AERC Ludhiana Kamal Vatta; D.K. Grover and Tinku Grover
12. Rajasthan AERC Vidyanagar Mrutyunjay Swain and Shreekant Sharma
13. Sikkim AERC Shantiniketan Jiban Kumar Ghosh and Snehasish Karmakar
14. Uttar Pradesh AERC Allahabad Ramendu Roy and Ramji Pandey
15. West Bengal AERC Shantiniketan Jiban Kumar Ghosh
16. Karnataka ADRTC Bangalore Parmod Kumar and I. Maruthi
167
ANNEXURE – II
The Details of Selected Sample State Wise
Sl. No. States Selected Districts Phases No of HHs Selected AERC who
carried out
the study in
the state
Participants Non
Participants
1. Andhra Pradesh Adilabad, Chittoor, Mahboobnagar I 200 50 Waltare
Srikakulam II
Krishna III
2. Assam Karbi Anlong, Kokrajhar I 200 50 Guwahati
Darrang, Hailakandi II
Tinsukia III
3. Bihar Kishanganj, Rohtas, Samastipur I 200 50 Bhagalpur
Banka, Gopalganj II
4. Chhattisgarh Dantewada, Kawardha I 200 50 Jabalpur
Kobra, Mahasamund II
Durg III
5. Gujarat Banas Kantha, Dahod I 200 50 Vidyanagar
Navsari II
Surendra Nagar, Jamnagar III
6. Haryana Sirsa I 200 50 Delhi
Ambala II
Bhiwani, Panipat, Faridaba III
7. Himachal Pradesh Chamba, Sirmaur I 200 50 Shimla
Mandi II
Kinnaur, Una III
8. Karnataka Bidar I 201 54 ISEC,
Bangalore Bellary, Chikmangalore II
Chamrajanagar, Dharwad III
9, Kerala Palakkad, Wayanad I 200 50 Chennai
Kasargod II
Kottayam, Thiruvananthapuram III
10. Madhya Pradesh Dhar, Sidhi I 200 50 Jabalpur
Chindawara II
Morena, Sagar III
11. Maharashtra Gondia, Nandurbar I 205 45 Pune
Thane II
Jalna, Kolhapur III
12. Punjab Hoshiarpur I 200 100 Ludhiana
Jalandhar, Amritsar II
Mansa, Firozpur III
13. Rajasthan Banswara,Karauli I 200 50 Vidyanagar
Jaisalmer II
Nagaur, Ganga Nagar III
14. Sikkim North District I 160 40 Shantiniketan
East Sikkim, South Sikkim II
West Sikkim III
15. Uttar Pradesh Bara Banki, Kushi Nagar I 200 50 Allahabad
Etah II
Allahabad, Saharanpur III
16. West Bengal Jalpaiguri, Maldah, Purulia I 200 50 Shantiniketan
Nadia II
Howrah III
Grand Total 3166 839