MAHATMA GANDHI NATIONAL RURAL EMPLOYMENT GUARANTEE ACT (MGNREGA): A TOOL FOR EMPLOYMENT GENERATION

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DOI: 10.3126/ijssm.v3i4.15974 Research Article MAHATMA GANDHI NATIONAL RURAL EMPLOYMENT GUARANTEE ACT (MGNREGA): A TOOL FOR EMPLOYMENT GENERATION Lamaan Sami* and Anas Khan Department of Commerce, Aligarh Muslim University, Aligarh-202002 *Corresponding author s email: lamaansami@yahoo.com Abstract This study is an empirical study which aims to examine the impact of MGNREGA in generating employment to poor in selected districts in India. Data have been collected through personal interview and analyzed with the application of linear regression. The analysis of the data revealed that MGNREGA played a significant role in generating employment, increase in income and consumption of respondents in selected Keywords: MGNREGA; employment; income; consumption. Introduction Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) is considered as a Magic Bullet in eradicating rural poverty and unemployment by way of generating demand for productive labour force in villages. Rural poverty and unemployment in India have grown in an unprecedented manner since independence. There is a growing incidence of illiteracy, hungry people, malnourished children, farmer suicides, starvation deaths, resulting from inadequate employment and poverty and the failure of subsistence production during droughts (Datta & Singh, 2012). In this backdrop, Government of India (GOI) enacted the National Rural Employment Guarantee Act (NREGA) in the year 2005. It is the biggest poverty alleviation programme in the world which is started with an initial outlay of Rs. 11,300 crores in year 2006-07. This Act is now called as Mahatma Gandhi National Rural Employment Guarantee Act. It provides a legal guarantee for 100 days of employment in every financial year to adult members of any rural household to do public work related unskilled manual work at the statutory minimum wage. The Act covered 200 districts in its first phase implemented on February 2, 2006 and have been extended to 130 additional districts in 2007-2008 (Roy & Samanta, 2010). All the remaining rural areas have been notified with effect from April 1, 2008.This minimum wage varies from state to state. It is Rs. 80 in some states whereas in other it is Rs 125 or Rs 120. According to the Act, the minimum wage cannot be less than Rs. 60. The 100 days of work figure was estimated because the agricultural season is only supposed to last roughly around 250 days and unskilled workers have no alternative source of income in the remaining parts of the year. Table 1 shows a brief profile of MGNREGA (http://www.nrega.net). Table 1: Profile of MGNREGA Year Particulars August 2005 Parliament passed an act called as NREGA February 2006 Came into force in 200 districts April 2007 130 more districts included April 2008 Universalization of the scheme October 2008 Wage transaction through banks/post offices February 2009 MOU with the postal department 2 nd October 2009 Name changed to MGNREGA Source: http://www.nrega.net Objectives of MGNREGA Providing 100 days of wage employment in rural areas during a financial year to every registered household. Creating productive assets Reducing urban migration Empowering rural women and the poor through the provision of a right-based law. To create strong social safety net for the vulnerable groups by providing employment source, when other alternative are inadequate.

Review of Literature Roy & Singh (2010) in their study entitled, Impact of NREGA on Empowerment of the Beneficiaries in West Bengal found a positive impact of the program on the empowerment of the respondents in the state of West Bengal. The study conducted by Tiwari & Upadhyay in the year 2012 find out the constraints faced by the women beneficiaries under MGNREGA. Their study revealed that the personal and family problems were the major constraints faced by them. Das (2012) examined the impact of MGNREGA on women beneficiaries. The author takes income, consumption; inter household effect and community level effect as the variables of the study. He analyzed that MGNREGA has positive impact on employment status of women. Pankaj & Tankha (2010) reported that the women workers gained the empowerment after joining MGNREGA in Bihar, Jharkhand, Rajasthan and Himachal Pradesh. Kumar & Bhattacharya (2013) in their study titled, Participation of women in MGNREGA: How far is it successful in Morigaon, Assam examined the level of participation of women in MGNREGA activities as against their male counterpart. The authors conducted a primary survey in the district of Morigaon (Assam) and applied probit regression model and revealed that participation of women in physical activities and decision making is far from satisfactory level and hence necessary measures should be taken in this regard. Arora et.al (2013) in their study entitled, Mahatma Gandhi National Rural Employment Guarantee Scheme: A Unique Scheme for Indian Rural Women highlighted the importance of MGNREGS on women empowerment in Rohtak district of Haryana. They took a sample of 250 respondents and conducted a field survey. The study further revealed that 95 percent of the beneficiaries believe that the program enhanced their credit worthiness and they started saving money. Farooqi & Saleem (2015) in their research paper entitled, Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) and Empowerment of Women from BPL families in rural areas A case study of district Aligarh (India) found that that a provision should be made for sparing women from hard manual work and to extend MGNREGA program to skilled or semi-skilled work so that women become professionally skilled. The authors further emphasized that Government of India should take steps so that the benefit of the provision of one third female workers in MGNREGA can be achieved by rural women. There is a need for expansion of MGNREGA work suitable to the natural instinct of women from the prospective of broadening the scope of women s employment. Objectives of the Study 1. To examine the impact of MGNREGA in generating employment in selected districts in India. 2. To examine the impact of MGNREGA on income of the respondents in selected 3. To measure the impact of MGNREGA on consumption of the respondents in selected Data Collection The study is undertaken in rural areas of 30 villages of four districts namely Rampur, Moradabad, Kanpur, and Etawah. Both primary and secondary data are used. However, major emphasis is laid on Primary data which is collected from a field survey in the study region. Secondary data is collected from websites, journals, reports and other documents. The period of data collection is four months i.e. from January, 2016 to April, 2016. Sampling Method Convenient sampling is followed. The villages which are easily accessible have been chosen for the study. In this way, 20 villages have been selected from Rampur, Moradabad, Kanpur and Etawah. Table 2 shows the selected districts, villages and respondents. The sample size of the study is 150 respondents. Statistical Tool Linear regression and pearson correlation coefficient has been used to test the hypotheses. Table 2: Shows the selected districts, villages and respondents S.N. Selected Villages Total Districts Selected Respondents 1 Rampur 5 35 2 Moradabad 5 40 3 Kanpur 5 45 4 Etawah 5 30 Total 20 150 Hypotheses of the Study H 01: MGNREGA has no significant impact in generating employment in selected H a1: MGNREGA has a significant impact in generating employment in selected H 02: MGNREGA has no significant impact on income in selected H a2: MGNREGA has a significant impact on income in selected H 03: MGNREGA has no significant impact on consumption in selected H a3: MGNREGA has a significant impact on consumption in selected

Table 3: Demographic Profile of the Respondents Demographic Profile of the Respondents Age of the Respondents Family status of the Respondents Educational Status of the Respondents Condition of the House of the Respondents Source: Primary Data Demographic Profile of the Respondents Table 3 shows a brief demographic profile of the selected respondents. Majority of the respondents were belong to the age group of 30-40 years and have joint family system. As far as education of the respondents is concerned, majority were found to be illiterate. However, 123 were living in Kuchha houses whereas 27 were in semi-pucca houses. Testing of Hypothesis H01: MGNREGA has no significant impact in generating employment in selected districts in India. Ha1: MGNREGA has a significant impact in generating employment in selected districts in India. The impact of MGNREGA in generating employment in selected districts in India has been measured by applying linear regression. The independent variable is MGNREGA and dependent variable is employment status of the respondents. The null hypothesis is that there is no significant impact of MGNREGA in generating employment and the alternate hypothesis states that there is a significant impact of MGNREGA in generating employment in selected Table 4: Shows the Correlation between MGNREGA and Employment Status Model-1 Employment Status MGNREGA Pearson Employment Correlation Status 1.000 0.849 MGNREGA 0.849 1.000 Attributes Districts Total Rampur Moradabad Kanpur Etawah 30-40 14 18 21 13 66 41-50 16 16 18 11 61 51-60 5 6 6 6 23 Joint 31 37 41 26 135 Nuclear 4 3 4 4 15 Illiterate 26 28 37 21 112 Primary 9 12 8 9 38 Kuchha 30 33 38 22 123 Semi-Pucca 5 7 7 8 27 Table 4 shows the coefficient of correlation between the two variables. The coefficient of correlation between MGNREGA and employment status is 0.849 which indicates a very high and positive relationship between the two variables. Table 5: Regression Model of MGNREGA & Employment Status R Square 0.711 Adjusted R Square 0.711 Standard Error 1.921 Durbin Watson 1.016 ANOVA (Model Fitness) 0.000 Unstandardized Coefficients 0.667 Significant Value 0.000 a. Predictors: (Constant), MGNREGA b. Dependent Variable: Employment Status c. Source: Output of SPSS_18 Table 5 exhibits the regression model of MGNREGA and employment status. R square shows the amount of variation in one variable (employment status) that is accounted by independent variable MGNREGA. The above table shows the value of R square is 0.711. It means 71.1 percent variation in employment status is explained by MGNREGA and rest of the variation percent in employment status is an unexplained variation. Further, the value of unstandardized beta coefficients is 0.667 which shows that if MGNREGA increases by one unit, then employment status will increase by 0.667 times. Besides, this impact is strong and statistically significant as the value significant value is 0.000 which is less than 0.05 at 95 percent confidence interval. Therefore, the null hypothesis is rejected and it can be said that there is a significant impact of MGNREGA in generating employment in selected

Hypothesis 2 H02: MGNREGA has no significant impact on income of the respondents in selected Ha2: MGNREGA has a significant impact on income of the respondents in selected The impact of MGNREGA on income of the respondents in selected districts in India has been measured by applying linear regression. The independent variable is MGNREGA and dependent variable is income of the respondents. The null hypothesis is that there is no significant impact of MGNREGA on income and the alternate hypothesis states that there is a significant impact of MGNREGA on income of the respondents in selected Table 6 shows the coefficient of correlation between the two variables. The coefficient of correlation 0.769 is which indicates a positive relationship between the two variables. Table 6: Correlation between MGNREGA and Income Model-2 Income MGNREGA Pearson Correlation Income 1.000 0.769 MGNREGA 0.769 1.000 Table 7: Regression Model of MGNREGA & Income R Square 0.635 Adjusted R Square 0.635 Standard Error 1.671 Durbin Watson 1.246 ANOVA (Model Fitness) 0.009 Unstandardized Coefficients 0.521 Significant Value 0.009 d. Predictors: (Constant), MGNREGA e. Dependent Variable: Income f. Source: Output of SPSS_18 Table 7 exhibits the regression model of MGNREGA and Income. R square shows the amount of variation in one variable (Income) that is accounted by independent variable MGNREGA. The above table shows the value of R square is 0.635. It means 63.5 percent variation in income is explained by MGNREGA and rest of the variation is an unexplained variation. Moreover, the results show that the value of unstandardized beta coefficients is 0.521 which shows that if MGNREGA increases by one unit, then income will increase by times 0.521 times. Besides, this impact is strong and statistically significant as the value significant value is 0.009 which is less than 0.05 at 95 percent confidence interval. Therefore, the null hypothesis is rejected and it can be said that there is a significant impact of MGNREGA on income in selected Hypothesis 3 H03: MGNREGA has no significant impact on consumption in selected Ha3: MGNREGA has a significant impact on consumption in selected The impact of MGNREGA on consumption in selected districts in India has been measured by applying linear regression. The independent variable is MGNREGA and dependent variable is consumption of the respondents. The null hypothesis is that there is no significant impact of MGNREGA on consumption and the alternate hypothesis states that there is a significant impact of MGNREGA on consumption in selected Table 8: Correlation between MGNREGA and Consumption Pearson Correlation Model-3 Consumption MGNREGA Consumption 1.000 0.624 MGNREGA 0.624 1.000 Table 8 shows the coefficient of correlation between MGNREGA and consumption. The coefficient of correlation is 0.624 which indicates a positive relationship between the two variables. Table 9: Regression Model of MGNREGA & Consumption R Square 0.587 Adjusted R Square 0.587 Standard Error 1.443 Durbin Watson 1.086 ANOVA (Model Fitness) 0.000 Unstandardized Coefficients 0.499 Significant Value 0.000 g. Predictors: (Constant), MGNREGA h. Dependent Variable: Consumption i. Source: Output of SPSS_18 Table 9 exhibits the regression model of MGNREGA and Consumption. R square shows the amount of variation in one variable (consumption) that is accounted by independent variable MGNREGA. The above table shows the value of R square is 0.587. It means 58.7 percent variation in consumption is explained by MGNREGA and rest of the variation is an unexplained variation. The results show that the value of unstandardized beta coefficients is 0.499 which shows that if MGNREGA increases by one unit, then consumption will increase by 0.499 times. Besides, this impact is strong and statistically significant as the value significant value is 0.000 which is less than 0.05 at 95 percent confidence interval. Therefore, the null hypothesis is rejected and it can be said that there is a significant impact of MGNREGA on consumption pattern of the respondents in selected

Table 10: Summary of Hypothesis Tested S.N. 1 2 3 Hypotheses MGNREGA has no significant impact in generating employment in selected MGNREGA has no significant impact on income in selected MGNREGA has no significant impact on consumption in selected R Square Beta Sig. Value Results 0.711 0.667 0.000 Rejected 0.635 0.521 0.009 Rejected 0.587 0.499 0.000 Rejected Table 10 shows the summary of hypothesis tested. All the three hypothesis of the study have been rejected. It means there is a significant impact of MGNREGA in generating employment, increase in income and consumption of the selected respondents in selected districts in India Major Findings 1. Majority of the surveyed respondents were belong to the age group of 30-40 years and have joint family system. As far as education of the respondents is concerned, majority were found to be illiterate. 2. The impact of MGNREGA in generating employment in selected districts in India has been measured by applying linear regression. The regression model of MGNREGA and employment status shows the value of R square is 0.711 which means 71.1 percent variation in employment status is explained by MGNREGA and rest of the variation percent in employment status is an unexplained variation. Further, the value of unstandardized beta coefficients is 0.667 which shows that if MGNREGA increases by one unit, then employment status will increase by 0.667 times. The significant value is 0.000 which is less than 0.05 at 95 percent confidence interval. Therefore, the null hypothesis is rejected and it can be said that there is a significant impact of MGNREGA in generating employment in selected 3. Linear regression has been used as the statistical tool to measure the impact of MGNREGA on income of the respondents in selected districts in India. The regression model of MGNREGA and income shows the value of R square is 0.635 which means 63.5 percent variation in income is explained by MGNREGA and rest of the variation is an unexplained variation. Moreover, the results show that the value of unstandardized beta coefficients is 0.521 which shows that if MGNREGA increases by one unit, then income will increase by times 0.521 times. The significant value is 0.009 which is less than 0.05 at 95 percent confidence interval. Therefore, the null hypothesis is rejected and it can be said that there is a significant impact of MGNREGA on income in selected 4. The researchers have applied linear regression to analyze the impact of MGNREGA on consumption of the respondents in selected The regression model of MGNREGA and consumption shows the value of R square is 0.587. It means 58.7 percent variation in consumption is explained by MGNREGA and rest of the variation is an unexplained variation. The results show that the value of unstandardized beta coefficients is 0.499 which shows that if MGNREGA increases by one unit, then consumption will increase by 0.499 times. The significant value is 0.000 which is less than 0.05 at 95 percent confidence interval. Therefore, the null hypothesis is rejected and it can be said that there is a significant impact of MGNREGA on consumption pattern of the respondents in selected Conclusion Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) is considered as a Magic Bullet in eradicating rural poverty and unemployment by way of generating demand for productive labour force in villages. In this backdrop, an effort has been made by the researchers to examine the impact of MGNREGA in generating employment, increase in income and consumption of the selected respondents in selected districts in India and linear regression has been used as the statistical tool to measure such impact. The results revealed that there is a significant impact of MGNREGA in generating employment, increase in income and consumption of the respondents in selected References Arora V, Kulshreshtha LR and Upadhyay V (2013) Mahatma Gandhi National Rural Employment Guarantee Scheme: A Unique Scheme for Indian Rural Women. International Journal of Economic Practices and Theories, 3(2): 14-18. Das (2012) Examining India s Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA): Its Impact and Women s Participation. International Journal of Research in Management. 6(2): 44-46.

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