Development of a Scale to Measure Socio-economic Impact of Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) on its Beneficiaries
Development of a Scale to Measure Socio-economic Impact of Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) on its Beneficiaries
Dhulgand VG1 , Kadam RP1* , Pawar GS2
1Department of Extension Education, Vasantrao Naik Marathwada Krishi Vidyapeeth (VNMKV), Parbhani. Maharashtra, India
2Department of Botany, Vasantrao Naik Marathwada Krishi Vidyapeeth (VNMKV), Parbhani. Maharashtra, India
Corresponding Author Email: rpk.mkv@gmail.com
DOI : http://dx.doi.org/10.53709/ CHE.2020.v01i01.020
Abstract
In the present study, the scale to measure the socio-economic impact of MGNREGA on its beneficiaries was constructed. For the construction of scale, seventy-six items pertaining to the socio-economic impact of MGNREGA on its beneficiaries were collected through a review of literature and discussion with academic staff at various levels. Based on their relevancy, finally, fifty-six items were included in the final scale. Thus, the proposed scale finally comprised fifty-six statements. The scale values of finally selected items were worked out by using the Normalized Rank Approach. The reliability of the scale was determined by the Test-retest method. Pearson’s Product Moment Coefficient of Correlation was worked out for correlating the two sets of scores for the test-retest method. The value correlation coefficient value two scores of Test-retest reliability was 0.524. Validity of scale was established the by content validity method. The content validity was determined by a using review of literature e and the opinion of 66 judges who were experts in the field of extension education. Norms of distribution of socio-economic impact score obtained by using the scale indicated that the distribution in ,general, normal. This was tested and confirmed by the values of central tendency.
Keywords
INTRODUCTION
Poverty and unemployment are the twin problem faced by the developing countries. According to the planning India’s planning commission, nearly is Below Poverty Line (BPL). Public Policy makers India have realized the need for generating employment opportunities on large scaling the teeming millions of population above poverty the y line (APL). What the same time the labour force in India is increasing at every [1-3].
The majority the majority of population (72.22 per cent) live, in rural areas and many of them suffer owing to seasonal under employment under employment and disguised unemployment. (Source: Planning CoPhDion).
In India, GDP and Unemployment rates are going hand in hand, causing fret for any democratic society. Unemployment and poverty are strongly related and hinder the economic growth and development of the country. In India, these two The rural areas, leaving it outside in India the growth path. Thus, Government the of India aiming balanced growth and to over cover coming the above-mentioned of past employment programmes, passed National Rural Employment Guarantee Act (NREGA) in 25 August 2005 in order to the tourers with right to get employment of 100 days per year per household during off-season. In accordance, National Rural Employment Guarantee Act has been launched in Anantapur district of Andhra Pradesh on 2nd February, 2006, with effect from 1st April 2006 in 200 drought prone and backward districts in India [4-7]. This was extended to additional 130 districts in the financial year 2007-2008. The NREGA coverage has been expanded from 330 districts to 619 districts of India beginning April, 2008. In Maharashtra the NREGA was implemented during the 2006 in 12 districts (Dhule, Nandurbar, Ahemednagar, Aurangabad, Hingoli, Nanded, Amravati, Gadchiroli, Yavatmal, Bhandara, Gondhiya and Chjandrapur) of Maharashtra state. Thus, NREGA covered that entire country except districts withpercent urban population. This programme has been formulated by merging early formulated programmes such as Sampoorna Gramin Rozgar Yojana (SGRY) of 2001 and National Food for Work Programme (NFFWP) of 2004. Again the Government of India on 2nd October, 2009 renamed its flagship rural job guarantee programme- National Rural Employment Guarantee Act (NREGA) as Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) [8-10]. Development of a scale to measure socio-economic impact of MGNREGA on its beneficiaries was attempted by using the normalized rank approach recommended by Guilford (1978). With this context in view an empirical study was conducted with specific objectives i) To development a scale for measuring the socio-economic impact of MGNREGA on its beneficiaries.
Materials and Methods
In the present study, socio-economic impact is conceptualized as dependent variable for analyzing socio-economic impact of Mahatma Gandhi National Rural Employment Guarantee Act on its beneficiaries in Marathwada region. Development of a scale to measure socio-economic impact of MGNREGA on its beneficiaries was attempted by using the normalized rank approach recommended by Guilford (1978) [11-14]. This procedure included collection of items, allocation of weightages to items, standardization of the scale, testing its reliability and validity, and norms of distribution of scores. For the construction of scale, seventy six items about socio-economic impact of MGNREGA on its beneficiaries were collected through literature review and discussion with academic staff at various levels. From the 76 statements finally 56 statements were selected for judgment [15-24].
The research study was conducted in the Aurangabad, Nanded, Beed and Jalna district of the Marathwada region of Maharashtra state during 2017-18. Two hundred forty beneficiaries were personally interviewed at their home and farm using the scale developed to measure the socio-economic impact of MGNREGA on its beneficiaries. The collected data were scored and analyzed using appropriate statistical methods.
Research Finding
Development of scale to measure the socio-economic impact of MGNREGA on its beneficiaries
1) Identification of the items
In order to identify the basic constituents of socio-economic impact of MGNREGA on its beneficiaries, seventy six (76) items pertaining to socio-economic impact of MGNREGA on its beneficiaries were collected through review of literature and discussion with academic staff at various levels. These items/statements were sent to eighty (80) judges, the academic and administrative extension personnel and experts from extension education department working in various agriculture universities and institutions in India. The judges were requested to indicate whether each of the main items sent to them was relevant and suitable for inclusion in scale. The judges were also asked to rank the relevant main items according to their relative importance in measurement of socio-economic impact of MGNREGA on its beneficiaries and to add items if they desired to do so. Sixty six (66) judges responded out of 80. The responses received from the judges supported the relevancy of all the seventy six items. Those items which received more than 75 per cent relevancy were considered as relevant for inclusion in the scale. Thus on the basis of their relevancy, finally fifty six items were included in the final scale. These fifty six statements were categorized into eight subcategories viz, educational impact, occupational impact, annual income impact, saving pattern impact, expenditure change impact, material possession impact, socio-political participation impact and employment generation impact. Thus, proposed scale finally comprised of fifty six statements.
2) Determination of scale values
Using the Normalized Ranking Method as suggested by Guilford J.P. (1954), the scale values of all the items were calculated. The detail of calculation of scale value was given in methodology.
3) The reliability and validity of the developed scale
a) Reliability of the scale: In order to calculate reliability of the scale, Test-retest reliability test was used.
i) Retesting from the judges
These final statements then again retested from the judges for reliability and also obtained ranks for the selected items for inclusion in the final scale. Ten judges were chosen, who were expert in the field of extension education/sociology department working in Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani. After their judgments the statements were finalized and included in the final scale.
ii) Reliability of the scale
Test-retest reliability of the scale was calculated on the basis of the responses of sample of 40 beneficiaries of MGNREGA who were not included in the final sample. The scale was administered twice to these MGNREGA beneficiaries. The second administration was done approximately three weeks after the first one. Pearson’s product moment coefficient of correlation was used for the two sets of scores in order to obtain the test-retest reliability coefficient. The reliability coefficient obtained (0.524) was quite high, indicating that the developed scale was reliable. The coefficient of correlation was also statistically highly significant at 1 per cent level.
b) Validity of the scale
The validity of the developed scale was measured by content validity test.
i) Content validity
The content validity of the scale was established in two ways, firstly the various main and sub items for inclusion in the scale were based on extensive literature review from Indian and foreign studies. Secondly, the opinion of the panel of 66 judges who were expert in the field of extension education/sociology was obtained to find whether the items suggested were relevant for inclusion in the scale.
4) Norms of distribution of the scores by using the constructed scale
The norms of distribution of scores are very essential for any of the constructed scales. Therefore, in the present study, the following norms of distribution of scores were worked out. Frequency distribution and measures of central tendency. For this purpose, the data obtained from two hundred forty MGNREGA beneficiaries were considered.
a) Frequency distribution
The procedure recommended by Garrett (1967) was used to tabulate the frequency distribution and also to work out other graphical presentation. The data regarding socio-economic impact of MGNREGA scheme on its beneficiaries scale was grouped into ten classes with class interval of 3 units. The frequency distribution has been given in Table 1.
Table 1. Frequency distribution of overall impact of 240 MGNREGA beneficiaries
b) Graphical presentation of the frequency distribution
The graphical presentation of the frequency distribution helps to translate numerical facts into more concrete and understandable form. The data in Table 1 have been presented in histogram (Fig. 1) shows the histogram based on observed and smoothed frequency in column number 4 and 5 of Table 1. Further, theoretical normal curve superimposed on smoothed frequencies in the figure asymmetrically and closed resembled to normal probability curve. This indicates that the scores of two hundred forty beneficiaries were normally distributed.
c) Smoothed frequency
In smoothing, a series of ‘moving’ or ‘running’ averages were taken from which new adjusted frequencies were determined. This method is illustrated to find an adjusted or ‘smoothed’ frequencies, we add the frequency on the given interval and the frequencies on the two adjacent intervals (the interval just below and the interval just above) and divide the sum by 3.
d) Cumulative percentage curve and ‘ogive’
Cumulative percentage curve is another graphical method of representing frequency distribution. To compute cumulative percentage, cumulative frequencies were required to be found out. Table 2 indicates necessary conversion of cumulative frequencies into percentage of the total number of beneficiaries (N).
The cumulative percentage curve was later on drawn with interval limits laid on the x-axis and cumulative percentage on y-axis. Data are presented in Fig. 2. The figure drawn was quite regular, thereby indicating that scores obtained by the instrument developed followed normal distribution.
Table 2. Percentage cumulative frequency of overall impact of 240 MGNREGA beneficiaries
e) Measures of central tendency
The different values of central tendency were worked out for 240 beneficiaries were as follows.
Mean : 26.75
Median: 26.00
Mode : 26.20
These values being very close, indicating that distribution followed normal curve.
Administration of the scale (Scoring technique)
For application of the scale, the researcher can collect information against each fifty six statements in three continuum viz. ‘Agree’, ‘Partially Agree’ and ‘Disagree’ with weighted score of 2, 1 and 0 and reverse to negative statements. The table 3 indicated the scale value of each items as given by the judges with relevancy percentage.
Table 3: Final statements/ items included in the scale to measure the socio-economic impact of MGNREGA beneficiaries.
CONCLUSIONS
The socio-economic impact scale developed is found to be reliable and valid; hence it can be used to measure the socio-economic impact of MGNREGA beneficiaries. From the various methods available for constructing the scale, to measure the socio-economic impact of MGNREGA beneficiaries was attempted by using the normalized rank approach. The advantage of this method was that it can be used with almost any number of variables and does not require a large number of judges for ranking the variables. Hence, this method was used in developing the present instrument.
Get the all table and images here…
REFERENCES
- Chole, R.R. (1986). Stratification, opportunity, structure and technological change in rural Marathwada. Ph.D. (Agri.) Thesis, Marathwada Agricultural University, Parbhani (Maharashtra).
- Devi, R. Uma. “An impact study of micro finance system on the enterpreneurial development of Andhra Pradesh, India.” International Journal of Innovative Research and Development 2.4 (2013): 656-689.
- Planning Commission. (2002). Tenth Five Year Plan 2002-07: Dimensions and Strategies. Vol-I.
- Prasad, P. N., & Sreedevi, V. (2007). Economic empowerment of women through information technology: A case study from an Indian state. Journal of International Women’s Studies, 8(4), 107-120.
- Edwards, M.M. (2000). Community guide to development impact analysis. UW-Madison program on agricultural technology studies, pp: 315-319.
- Garrett H.E. (1967). Statistics in psychology and education: Vakils Feffer and Simons, Pvt. Ltd., Bombay, pp: 27-65.
- Guilford J. P. (1954). Psychometric methods. Tata McGraw Hill Book Publication Company, Bombay, pp: 178-196.
- Thurstone, L. L. (1946). Comment, American J. Sociology, 52, pp: 39-50.
- Bashir, A., Bashir, U., Lone, A., & Tariq, A. Understanding the Role of Skill Development and Its Impact on Unemployment in Jammu and Kashmir. Kashmir Journal of Social Sciences, 30.
- Singh, T., & Singh, J. (2016). Direct cash benefit scheme: A review of issues in India. International Journal of Advanced Multidisciplinary Research, 3(6), 5-12.
- Mathew, V. R. (2018). The role of self help groups in rural empowerment A study with special reference to kerala.
- Behera, B. (2011). Role of micro enterprise in livelihood promotion: A perspective study in India. Annual Summit on Business and entrepreneurial studies (ASBES 2011) Proceeding.
- Datt, G., & Ravallion, M. (2002). Is India’s economic growth leaving the poor behind?. Journal of economic perspectives, 16(3), 89-108.
- Lipton, M. (1980). Migration from rural areas of poor countries: the impact on rural productivity and income distribution. World development, 8(1), 1-24.
- Henry, R. K., Yongsheng, Z., & Jun, D. (2006). Municipal solid waste management challenges in developing countries–Kenyan case study. Waste management, 26(1), 92-100.
- Buheji, M., da Costa Cunha, K., Beka, G., Mavric, B., De Souza, Y. L., da Costa Silva, S. S., … & Yein, T. C. (2020). The extent of covid-19 pandemic socio-economic impact on global poverty. a global integrative multidisciplinary review. American Journal of Economics, 10(4), 213-224.
- Tharamangalam, J. (1998). The perils of social development without economic growth: The development debacle of Kerala, India. Bulletin of Concerned Asian Scholars, 30(1), 23-34.
- Deshingkar, P. (2006). Internal migration, poverty and development in Asia. ODI Briefing Paper, 11.
- Dhulgand, V. G., & Kadam, R. P. (2019). Estimating Profile of the Beneficiaries of Mahatma Gandhi National Rural Employment Guarantee Act. Int. J. Curr. Microbiol. App. Sci, 8(12), 1800-1807.
- Aliber, M. (2003). Chronic poverty in South Africa: Incidence, causes and policies. World development, 31(3), 473-490.
- Dubey, A., Palmer-Jones, R., & Sen, K. (2006). Surplus labour, social structure and rural to urban migration: Evidence from Indian data. The European Journal of Development Research, 18(1), 86-104.
- Castles, S., & Miller, M. J. (2009). Migration in the Asia-Pacific region. Migration Information Source, 10.
- Reuveny, R. (2007). Climate change-induced migration and violent conflict. Political geography, 26(6), 656-673.
- Kumar, B. (2004). Migration, poverty and development in Nepal. Asian and Pacific migration journal, 13(2), 205-232.