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Prof. B. P. Sharma
(Editor in Chief)
Prof. Mahima Birla
(Group Editor)
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(Editor)
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Dr. Devendra Shrimali
Dr. Dharmesh Motwani
Mr. Jinendra Vyas
 

Socio - Economic Determinants of Unskilled Workers of MGNREGAS: A Study with Reference to Villianur Block of Puducherry Region


By


GOPINATHAN RADHIKA

Ph.D Research Scholar

Kanchi Mamunivar Centre for Postgraduate Studies (Autonomous)

Government of Puducherry, Lawspet, Puducherry

Mobile: + (91) – 9442032032

E. Mail: radhi_kub24@yahoo.com

and

 

 

 

 

Dr. RAMACHANDRAN AZHAGAIAH

Associate Professor and Head

Avvaiyar Government College for Women

Karaikal - Puducherry (U.T.)

Phone:  + (91) -9952474095

Fax: +91(413) - 2251613

  1. Mail: drrazhagaia@yahoo.co.in

 


 


 

 

 

 

 

 

Abstract

            MGNREGA has become a powerful instrument for inclusive growth in rural India through its impact on social protection, livelihood security and democratic governance. MGNREGA is the first ever law internationally that guarantees wage employment at an unprecedented scale.The Act provides a list of works that can be undertaken to generate employment related to water conservation, drought proofing, land development, and flood control and protection works.  The present study analyses the difference in gender, age and educational level towards socio - economic determinants of unskilled workers of MGNREGS. Primary data were collected from 1300 beneficiaries of MGNREGS of all the villages in Villianur Panchayat of Puducherry Region using interview schedule. The ultimate sample respondents were selected using Systematic Random Sampling Technique. The study revealed that the females havethe highest mean rank in socio economic determinants like family size, wait days, monthly expenditure, distance, other expenditure, land and mobile holding of the workers under MGNREGS. The workers who belong to age group of 40-60 years have higher participation in MGNREGS than the other age categories and the workers belong to educational level others category have higher participation in MGNREGS than the other category of educational level.

 

Key Words

CAG- Comptroller and Auditor General, MGNREGA – Mahatma Gandhi National Rural Employment Guarantee Act, MIP - Minor Irrigation Project, MWA - Minimum Wage Act,NREGP - National Rural Employment Guarantee Programme, PDS - Public Distribution System, PEO - Panchayat Executive Officer, PO - Programme Officer.

 

JEL classification   I38, O12, R28, Z18

Socio - Economic Determinants of Unskilled Workers of MGNREGS: A Study with Reference to Villianur Block of Puducherry Region

 

Introduction

            Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) aims at enhancing livelihood security of households in rural areas of the country by providing at least one hundred days of guaranteed wage employment in a financial year to every household whose adult members volunteer to do unskilled manual work. The MGNREGA has become a powerful instrument for inclusive growth in rural India through its impact on social protection, livelihood security and democratic governance. The MGNREGA is the first ever law internationally that guarantees wage employment at an unprecedented scale.

Salient Features of MGNREGA

            Planning, execution, monitoring and up-keeping/use of assets under the MGNREGA Scheme are distinctivelydifferent from the previous wage employment schemes. Salient features of the Act and the schemesunder it are:

  • It provides a legal guarantee of minimum 100 days of wage employment to the most vulnerable families in a financial year.
  • All households residing permanently in a hamlet / village are entitled to register for job cards.
  • Job cards should be issued to the eligible families after scrutiny containing photographs of all entitled applicants within 15 days of application.
  • Members of the families holding job card are entitled to demand / apply for wage employment either individually or in group, either verbally or in written form.
  • Job card holders demanding / applying for job should be acknowledged and they should be allotted jobs within the radius of five kms within 15 days of demand / application.
  • If employment is not provided within 15 days, a daily unemployment allowance in cash has to be paid.
  • If employment is not provided within five kms, the workers are entitled to travel expenses up to 10% of the wage.
  • At least one - third of the jobs under the MGNREGA scheme should be allotted for women.
  • Panchayati Raj Institutions at the district block and Gram Panchayat (GP) levels are the authorities responsible for planning and implementation of MGNREGA scheme.
  • Gram Sabha is responsible for selection of projects / schemes in the respective villages.
  • The shelf of projects for a village selected / recommended by the Gram Sabha is sent to GP and the GP forwards those projects / schemes for approval by the ‘Zilla Panchayat’.
  • Labour and material components of the works done under MGNREGA schemes should be in the proportion of 60:40 in principle revised labour to material ratio as 51:49.
  • Fifty percent of the MGNREGA works should be implemented through GPs and rest by Blocks and District Panchayats.
  • Entire work under MGNREGA scheme should be done manually and no contractor and machinery should be used.
  • Wage payment to the workers should be made within 15 days through nationalized banks or Post Offices.
  • Social audit is an essential feature of MGNREGA that helps maintaining transparency and accountability of all the stakeholders involved in implementation of the scheme.
  • A Report on the outcome of MGNREGA is presented annually by the Government of India to the Indian Parliament and by the State governments to the State Legislatures.
  • The Act has codified the following types of work for creation of durable assets.
  • Soil and water conservation and water harvesting.
  • Activities related to draught proofing like afforestation and social forestry.
  • Macro and minor irrigation work for irrigation purposes.
  • Land and irrigation development particularly the land owned by Scheduled Castes and Scheduled Tribes and the beneficiaries of land reforms / Indira Aawas Yojana.
  • Renovation of traditional water bodies including de-silting of tanks.
  • Flood control and protection works including construction of drainage system in the waterlogged areas.
  • Rural connectivity to provide all - weather road communication.
  • Any other works which may be notified by the central government in consultation with the state governments (presently employment generating rural development works by all the Government departments have been converged with MGNREGA scheme).

Review of Literature

Siddhartha and Vanaik (2008),in a research paper titled “Comptroller and Auditor General(CAG) Report on NREGA: Fact and Fiction” criticised the way that the CAG has done the audit. The CAG does not explore the impact of MGNREGA on lives of workers, quality of assets created, impact on poverty, women empowerment, or agricultural productivity. They also observed that the CAG has not taken into consideration of the state specific NREGS circulars and orders. The authors viewed that the CAG averages reflected from extremely different regions with uneven performance of MGNREGS and hence, these averages should not be treated as benchmarks for judging the performance and viability of programme in a specific state. They appreciated the CAG’s valuable and novel recommendations for effective implementation of NREGS in various states.

Kheraand Nandini (2009),in a research paper titled “Women workers and perceptions of the National Rural Employment Guarantee Act in India” reported the survey results and indicated the female labour workforce participation rate is significant in Rajasthan and Madhya Pradesh and it is the least in Uttar Pradesh which was broadly in line with the official data. They wrote that employment opportunities for women in the private labour market are limited, irregular, poorly paid and can even be hazardous. It often involves migration which raises a whole range of issues of its own. In addition to invisible social barriers, working conditions in the private labour market are often very demanding and exploitative. Hence, the female workers’ participation was high in many states.

Roy and Singh (2010),in a research paper titled “Impact of NREGA on Empowerment of the Beneficiaries in West Bengal”conducted study in two districts, Burdwan and Dakshin Dinajpur of West Bengal to assess the impact of MGNREGA on the empowerment of the beneficiaries. Significant positive changes were found in the level of aspiration, self-confidence and self-reliance of the respondents after commencement of the scheme. All the respondents were found to be in low empowerment category before MGNREGA. After working under MGNREGA, 75.5 per cent of the respondents were found to be under low empowerment category and 24.5 per cent were found to be under medium empowerment category. So a positive impact of the programme was observed on the empowerment of its beneficiaries in the study area.

Sankaran (2011),in a research paper titled “NREGA Wages: Ensuring Decent Work”  discussed the universalisation of payment of minimum wages as an obligation on the part of government to ensure the minimum rights of sustenance of workers. The paper recommends that the crisis around the MGNREGA wagerate is an occasion to rationalise wages both under MGNREGA and the Minimum Wage Act (MWA) and to bring about a true need-based minimum wage, which is a prerequisite for the millions in the informal economy of India today. The author suggested consultative process to be adopted for fixing need-based minimum wage rate.

TiwariCollins et al.(2011),in a research paper titled “MGNREGA for Environmental Service Enhancement and Vulnerability Reduction: Rapid Appraisal in Chitradurga District, Karnataka” assessed and found significant positive impact on soil fertility due to silt application, improved recharge and percolation rate due to construction of percolation tanks, financial benefits to farmers due to land development and land reclamation. The study team also estimated carbon sequester and biodiesel production due to plantation for over a period of thirty years and calculated the vulnerability reduction by using water, agriculture and livelihood indices. The authors opined that there was very limited attention towards the environmental or ecological or sustainable water and food security aspects of the programme.

            Shihabudheen (2013), in a research study titled“Potential of MGNREGA in Empowering Rural Women: Some Preliminary Evidence Based on a Field Study in Ernakulam District in Kerala, India”attempted to study women empowerment which is quite typical in Kerala,MGNREGA implementation has got tremendous potential for economic development of Kerala state, particularly through the socio - economic upliftment of the rural poor. Besides, NREGS has the potential to give a new dimension to the work culture in the state. While the workers have been hitherto controlled by contractors and their middlemen who know how to extract work. Withthe NREGS implementation the out turn has been initially very poor as the workers could not be supervised properly. However, soon the workers have themselves realized that they would be losing collectively and a new internal dynamics evolved with peerpressure forcing workers to put in their maximum effort. Besides, a kind of social responsibility has also become evident as morecapable workers have become more than willing to put in extra effort to make up for those who genuinely could not do hard work beyond a point, like the women and the elderly. In short, a new culture that promises far reaching benefits to the state in the future has begun to emerge.

Kar (2013), in a research study titled“Empowerment of Women through MGNREGS: Issues and Challenges” attempted to study whether there is inequality and vulnerability of women in all sphere of life. They need to be empowered in all walksof life. Without the active participation of women, establishment of a new social order may not be a successfulone, because women constitute half of the population. Women should realize that they have constitutionalrights to quality health care, economic security, and access to education and political power. Mahatma Gandhi firmly stated that the status of women would not change merely by bringing legislations; it must besupported by change in the women’s social circumstances and situations and also man’s sexist attitude towomen. The National Rural Employment Guarantee Act, which entitles rural households to 100 days ofcasual employment on public works at the statutory minimum wage, contains special provisions to ensurefull participation of women.

Azhagaiah and Radhika (2014), in a research paper titled “Impact of MGNREGA on the Economic Well – being of Unskilled workers: Evidence from Puducherry Region” stated that the haunting problem of unemployment is not confined to any particular class, segment or society as massive unemployment exists among educated, well-trained and skilled people as well as among semi-skilled and unskilled labourers, landless labourers, small and marginal farmers etc. The study examined the economic empowerment and well being of the rural poor in Karaiyamputhur / Panayadikuppam villages of Puducherry Union Territory. The survey was conducted by use of interview schedule and data were collected from 323 beneficiaries of MGNREGA of the selected villages. The study revealed that there is a significant increase in the welfare of the family for both male and female workers in respect of spending more for family, children’s education and enables them to save in bank / post office after working under MGNREGA. However, the economic well being will be improved still better if 100 days of employment in a year is provided to them.

Research Methodology

Objectives of the Study

  • To study the progress of number of households provided employment, average number of person days of works per household and total expenditure on MGNREGS in India from 2006 – 07 to 2012 – 13.
  • To study the socio-demographic profile i.e. gender, age and educational status of beneficiaries of MGNREGA in the chosen area.
  • To analyze the difference in the gender and socio - economic determinants ofparticipation in MGNREGA in the chosen area.
  • To analyze the difference in the age, educational status and socio - economic determinants ofparticipation in MGNREGA in the chosen area.

Hypotheses Development for the Study

  • H01 =There is no significant difference in gender in respect of the socio - economic determinants ofparticipation in MGNREGA.
  • H02 = There is no significant difference in age in respect of the socio - economic determinants ofparticipation in MGNREGA.
  • H03 = There is no significant difference in educational status in respect of the socio - economic determinants ofparticipation in MGNREGA.

Kruskal - Wallis Test: The Kruskal–Wallis one-way analysis of variance by ranks (named after William Kruskaland W. Allen Wallis) is a non-parametric method for testing whether samples originate from thesame distribution. It is used for comparing more than two samples that are independent, or notrelated.

Variables

Description

Predictor Variables

Size of the family (FAMSIZE)

Family size

Monthly Expenditure (MONEXP)

Monthly Expenditure of the Household

Wait days (WAITDAYS)

Maximum No. of days waited by the household for payment

Other Expenditure (OTHEREXP)

No. of Days of Employment in a year other than MGNREGA

Distance

Distance (in Kms from village to the work place)

Land

Land holding of the household

Mobile

Whether the household owns mobile set

 

MGNREGA: Key indicators - At a Glance from 2006 - 07 to 2012 - 13

The MGNREGA has been implemented in phases, commencing from February 2006, and at present it covers all districts of the country with the exception of those that have a 100% urban population.  The Act provides a list of works that can be undertaken to generate employment related to water conservation, drought proofing, land development, and flood control and protection works.  

Table 1shows the annual growth rate (AGR) and compound annual growth rate (CAGR) for number of households provided employment, average number of person days of work per household and total expenditure, under MGNREGA from 2006 – 07 to 2012 – 2013. It shows that the AGR for number of households provided employment in the year 2007 – 08 was 61.43%; gradually it was decreasing over the years and recorded negatively in the year 2012 – 13 i.e., -14.83%. The CAGR over the years for number of households provided employment is positive (0.11), indicating that the number of households provided employment goes on increasing at a normal rate without any fluctuation. The AGR for average number of person days per households in the year 2007 – 08 was -2.33 and has been fluctuating over the years and goes negatively for the last three years, finally in the year 2012 – 13 it was -16.28, recording a great fluctuation, the CAGR is negative (-0.03) over the period of study. The AGR for total expenditure in the year 2007 – 08 was 79.71%; gradually it was decreasing over the years and goes negatively in the year 2012 – 13 i.e. -26.19. The CAGR is positive (0.18) for total expenditure incurred over the study period.The total expenditure incurred per household during the year 2007 – 2008 was `8823.35 lakh, it has been increasing over the years and has been decreasing in the last two years, recording ` 38034.69 lakh and ` 28073.51 lakh respectively.

Table 1    MGNREGA: Key indicators - At a Glance from 2006 - 07 to 2012 - 13

Year

Number of households provided employment

(in Rcrore)

AGR

Average number of person days of work per household

AGR

Total Expenditure (in R lakh)

AGR

2006-07

2.10

-

43

-

8823.35

-

2007-08

3.39

61.43

42

-2.33

15856.88

79.71

2008-09

4.51

33.04

48

14.29

27250.10

71.85

2009-10

5.25

16.41

54

12.50

37905.23

39.10

2010-11

5.49

4.57

47

-12.96

39377.27

3.88

2011-12

4.99

-9.11

43

-8.51

38034.69

-3.41

2012-13

4.25

-14.83

36

-16.28

28073.51

-26.19

CAGR

0.11

-0.03

0.18

Sampling Technique

Systematic Random Sampling Technique

Systematic sampling technique is a statistical method involving the selection of elements from an ordered sampling frame. The most common form of systematic sampling is an equal-probability method, in which every kth element in the frame is selected.

The formula for calculating the sample interval is:

Where k is the sampling interval (SI), N is the population size, and n is the sample size. In this case N is 29,928 and n is 1,300, when calculated the sample internal is (approximately) ≈ 23. Using this procedure, each element in the population has a known and equal probability of selection. This makes systematic sampling functionally similar to simple random sampling.

This is random sampling with a system. The ultimate sample respondents are to be selected by adopting Systematic Random Sampling Technique where the sample interval (SI) = 29928 / 1300 = 23.02 = (approximately) ≈ 23.  The first sample respondent is selected by simple random sampling technique, i.e. by lottery method, and the every other sample respondents are selected by adopting the systematic random sampling technique, keeping the SI as 23, i. e., the first sample respondent being 3rd in the population list, the second sample respondent is (3+23) = 26h in the list and so on.

Demographic Profile of the Workers

Figure – C Gender and Age of the Workers Employed under MGNREGA

in Villianur Block

Figure - C shows the demographic profile of the respondents viz., gender and age. Out of 1300 workers, 268 (20.62%) are male and 1032 (79.38%) are female. Out of 268 male respondents, 60 (22.38%) fall under the age group of upto 40 years, 56 (20.90%) fall in the age category of 40-60 years and 152 (56.72%) fall in the age category of >60 years. Out of 1032 female respondents, 368 (35.66%) fall under the age group of upto 40 years, 476 (46.12%) fall under 40-60 years category and 188 (18.22%) of them fall in >60 years category.

Figure - D shows the demographic profile of the workers viz gender and educational status. Out of 1300 respondents, 44 (17.32%) male and 210 (82.68%) female workers know to read and write, 47 (82.46%) male and 10 (17.54%) female workers have education up to primary level, 14 (51.85%) male and 13 (48.15%) female workers have education upto SSLC, 10 (47.62%) male and 11 (52.38%) female workers have education upto HSC respectively, and 153 (16.26%) male and 788 (83.74%) female workers fall under the education category of ‘others’.

Figure – D Gender and Educational level of the Workers Employed under MGNREGA in Villianur Block

Table 3indicates the gender with the highest mean rank is considered as having the higher participation in MGNREGS. In this case, the female has the highest mean rank in socio - economic determinants like family size, wait days, monthly expenditure, distance from the work place, other expenditure, owning of land and mobile phone by the respondents. It shows that female workers have higher participation in MGNREGS than the male workers.

Table 3 Ranks for Gender and Socio Economic Determinants of Participation in MGNREGS

Variables

Gender

N

Mean Rank

Sum of Ranks

FamSize

Male

268

296.16

79370.50

Female

1032

742.52

766279.50

Wait Days

Male

268

298.09

79888.00

Female

1032

742.02

765762.00

MonExp

Male

268

204.91

54916.00

Female

1032

766.22

790734.00

Distance

Male

268

650.50

174334.00

Female

1032

650.50

671316.00

OtherExp

Male

268

385.25

103246.00

Female

1032

719.38

742404.00

Land

Male

268

385.22

103238.00

Female

1032

719.39

742412.00

Mobile Phone

Male

268

546.50

146462.00

Female

1032

677.51

699188.00

         

Source: Computed data collected from primary source.

Table 4 provides test statistic, U statistic, as well as the asymptotic significance (2-tailed). It shows that the gender towards socio - economic determinants like family size (U = 43324.50, P = .000), wait days (U = 43842, P = .000), monthly expenditure (U = 18870, P = .000) other expenditure (U = 67200, P = .000), land (U = 67192, P = .000) and mobile phone (U = 110416, P = .000)of the female respondents. Hence, H01 is rejected; there is a significant difference in the gender about the socio - economic determinants of participation in MGNREGS.

Table 4 Results of Mann Whitney U- Test for Gender and Socio - Economic Determinants of Participation in MGNREGS

Variables

Famsize

Wait Days

Mon  Exp

Distance

Other Exp

Land

Mobile

Phone

Mann-Whitney U

43324.50

43842.00

18870.00

138288.00

67200.00

67192.00

110416.00

Wilcoxon W

79370.50

79888.00

54916.00

671316.00

103246.00

103238.00

146462.00

Z

-18.359

-18.248

-23.083

.000

-16.965

-15.151

-8.016

Asymp. Sig. (2-tailed)

.000

.000

.000

1.000

.000

.000

.000

Source: Computed data collected from primary source.

Table 5 Ranks for Age and Socio Economic Determinants of Participation in MGNREGS

Variables

Age

N

Mean Rank

FamSize

20-40

428

440.34

40-60

532

808.43

>60

340

667.94

MonExp

20-40

428

454.45

40-60

532

774.07

>60

340

703.94

Wait Days

20-40

428

444.07

40-60

532

810.95

>60

340

659.31

Distance

20-40

428

650.50

40-60

532

650.50

>60

340

650.50

Other Exp

20-40

428

584.50

40-60

532

825.55

>60

340

459.68

Land

20-40

428

424.29

40-60

532

786.77

>60

340

722.03

Mobile Phone

20-40

428

546.50

40-60

532

905.94

>60

340

341.91

                                                Source: Computed data collected from primary source.

Table 5 indicates the age group – wise participation of workers in MGNREGS.It shows that the age group between 40-60 years has the highest mean rank in socio - economic determinants like family size, wait days, monthly expenditure, distance, other expenditure, owning of land and mobile phone by the respondents. It shows that the workers belong to age group of 40-60 years have higher participation in MGNREGS than the workers in the other  categories of age.

 

Table 6 Results of Kruskal Wallis Tests for Age and Socio Economic Determinants of Participation in MGNREGS

Variables

Famsize

MonExp

Wait Days

Distance

OtherExp

Land

Mobile

Phone

Chi-Square

256.63

203.04

253.82

.000

370.12

323.86

531.02

df

2

2

2

2

2

2

2

Asymp. Sig.

.000

.000

.000

1.000

.000

.000

.000

Source: Computed data collected from primary source.

 

Table 6 provides Chi-Square and significance (p-value). It shows that age towards socio - economic determinants like family size (c2 = 256.63, P = .000), monthly expenditure (c2 = 203.04, P = .000), wait days (c2 = 253.82, P = .000), other expenditure (c2 = 370.13, P = .000),owning of land (c2 = 323.86, P = .000) and mobile phone(c2 = 531.02, P = .000) by the respondents significantly vary. Hence, H02 is rejected, there is a significant difference in the age towards the socio - economic determinants of participation in MGNREGS.

Table 7 Ranks for Educational level and Socio Economic Determinants of Participation in MGNREGS


Variables

Educational level

N

Mean Rank

FamSize

To read & write

256

290.34

Primary

52

369.58

SSLC

24

169.54

HSC

24

345.75

Others

944

783.62

MonExp

To read & write

256

331.92

Primary

52

278.00

SSLC

24

160.00

HSC

24

323.33

Others

944

778.20

Wait Days

To read & write

256

292.00

Primary

52

373.12

SSLC

24

172.08

HSC

24

349.67

Others

944

782.81

Distance

To read & write

256

650.50

Primary

52

650.50

SSLC

24

650.50

HSC

24

650.50

Others

944

650.50

Other Exp

To read & write

256

517.97

Primary

52

584.50

SSLC

24

317.50

HSC

24

317.50

Others

944

707.01

Land

To read & write

256

410.53

Primary

52

278.50

SSLC

24

603.50

HSC

24

603.50

Others

944

738.46

Mobile Phone

To read & write

256

566.81

Primary

52

546.50

SSLC

24

546.50

HSC

24

546.50

Others

944

684.21

 

  Source: Computed data collected from primary source.

Table 7 indicates that the respondents who have high educational level with the highest mean rank are considered as having the high participation in MGNREGS. It shows that the educational category ‘others’ has the highest mean rank towards socio  - economic determinants like family size, wait days, monthly expenditure, distance, other expenditure, owning of land and mobile phone by the respondents. Therefore, the workers belong to educational category ‘others’ have higher participation in MGNREGS than the respondents who fall under other categories of educational levels.

Table 8 Results of Kruskal Wallis Tests for Age and Socio Economic Determinants of Participation in MGNREGS

Variables

Famsize

MonExp

Wait Days

Distance

OtherExp

Land

Mobile

Chi-Square

491.54

452.56

485.21

.000

158.24

283.55

69.46

df

4

4

4

4

4

4

4

Asymp. Sig.

.000

.000

.000

1.000

.000

.000

.000

Source: Computed data collected from primary source.

Table 8provides the Chi-Square and significance (p-value), which shows that socio - economic determinants like family size (c2 = 491.54, P = .000), monthly expenditure (c2 = 452.56, P = .000), wait days (c2 = 485.21, P = .000), other expenditure (c2 = 158.24, P = .000),owning of land (c2 = 283.55, P = .000) and mobile phone (c2 = 69.46, P = .000) by the respondents differ significantly in the educational level. Hence, H03 is rejected, “there is a significant difference in the educational level in respect of socio - economic determinants of participation in MGNREGS”.

Concluding Remarks and Policy Prescriptions

MGNREGS is the most significant scheme to uplift the overall quality of life of rural households from the extreme poverty.The socio - economic determinants of participation of workers in MGNREGS identify the crucial factors for the successful implementation of the programme.Women have more concentration in MGNREGS than that of the men. The female workers have the highest mean rank in socio - economic determinants like family size, wait days, monthly expenditure, distance, other expenditure, owning of land and mobile phone by the respondents. Among the beneficiaries, workers belong to age group of 40-60 years have higher participation in MGNREGS than those who belong to the other age categories; and the workers who fall under educational level ‘others’ have higher participation in MGNREGS than those who fall under other categories of educational levels.

Limitations of the Study

            The study is based on the responses of 1300 respondents only that too of the 18 villages of Villianur Panchayat of Pondicherry region,which is the most populated panchayat among the two panchayats of villianur block of the Pondicherry region as far as the MGNREGA is concerned, hence the outcome of the research may not represent the picture prevalent elsewhere, especially in the other regions of Pondicherry Union Territory.

Suggestions for ProperImplementation of MGNREGA

  • Strengthening Active Citizenship

Women’s participation in Gram Sabhas is to be increased as they become more aware of their citizenship rights and duties.

  • Social Audit Programmes

Delay in conducting periodic social audit programmes to judge the workings of the beneficiaries and to monitor the functioning of the scheme is also a pitfall of the Scheme. Hence, it is suggested that the scheme should ensure periodic social audit to assess the performance of the machineries involved in making the Scheme a vibrant and effective one.

  • Broadening the Understanding of Poverty to include needs of Women

The programme could have a greater impact on poverty reduction and on development if there were broader understanding of the nature of poverty, and especially the constraints faced by women. The programme needs to find ways and means of improving its relevance to the daily lives of people (especially women) and addressing ecological poverty, not just income poverty, through suitable modifications to programme design.

Scope for Further Studies

Further studies could be undertaken in the following aspects:

  • To study the impact of socio - economic determinants like family size, wait days, monthly expenditure, distance, other expenditure, owning land and other properties by the beneficiaries of MGNREGA.
  • To assess the implementation of NREGA, it’s functioning and to suggest suitable policy measures to further strengthening the Programme.
  • To compare wage differentials between NREGA activities and other employment activities.

References

Azhagaiah, R., and G. Radhika. (2014). Impact of MGNREGA on the economic well – being of Unskilled workers: Evidence from Puducherry Region. Pacific Business Review International, 6 (10) (April): 1-15.

http://stats.stackexchange.com/questions/77359/mann-whitney-u-test-with-very-large- sample-size

http://www.prsindia.org/theprsblog/?p=3013

http://www.slideshare.net/mhsgeography/mann-whitney-u-test-2880296

Kar, S. (2013). Empowerment of women through MGNREGS: Issues and Challenges.Odisha Review, (February – March): 76-80.

Khera, R., and N. Nandini.(2009). Women workers and perceptions of the National Rural Employment Guarantee Act in India. Gender Pathways of poverty Rural Employment Discussion Paper: 1-19.

Roy, S., and B. Singh. (2010). Impact of NREGA on Empowerment of the Beneficiaries in West Bengal. Indian Research Journal Extension Education, 10 (2): 20-3.

Sankaran, K. (2011). NREGA Wages: Ensuring Decent Work. Economic& Political Weekly, XLVI (7): 23-5.

Shihabudheen, N. (2013). Potential of MGNREGA in empowering rural women: some preliminary evidence based on a field study in Ernakulam district in Kerala, India. International Journal of Innovative Research and Development, 2 (8) (August): 272-78.

Siddhartha, and A. Vanaik. (2008). CAG Report on NREGA: Fact and Fiction.Economic& Political Weekly, 43 (25): 39-45.

 

Tiwari, R., H. I. Somashekhar, V. R. Ramakrishna Parama, Indu K. Murthy, M. S. Mohan Kumar, B. K. Mohan Kumar, H. Parate, M. Varma, S. Malaviya, A. S. Rao, A. Sengupta, R. Kattumuri, and N.H. Ravindranath. (2011). MGNREGA for environmental service enhancement and vulnerability reduction: rapid appraisal in Chitradurga District, KarnatakaEconomic& Political Weekly, XLVI (20): 39-45.

 

 
 

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