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EMPLOYMENT, POVERTY AND DISPARITIES AMONG SOCIALLY DISADVATAGED GROUPS IN RURAL WEST BENGAL

EMPLOYMENT, POVERTY AND DISPARITIES AMONG SOCIALLY DISADVATAGED GROUPS IN RURAL WEST BENGAL. Dr. Arun Kumar Nandi Assistant Professor of Economics Chakdaha College, W.B Dr. Dipika Basu Assistant Professor of Economics West Bengal State University, W.B E-mail: anu_dipa@yahoo.com.

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EMPLOYMENT, POVERTY AND DISPARITIES AMONG SOCIALLY DISADVATAGED GROUPS IN RURAL WEST BENGAL

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  1. EMPLOYMENT, POVERTY AND DISPARITIES AMONG SOCIALLY DISADVATAGED GROUPS IN RURAL WEST BENGAL Dr. Arun Kumar Nandi Assistant Professor of Economics Chakdaha College, W.B Dr. Dipika Basu Assistant Professor of Economics West Bengal State University, W.B E-mail: anu_dipa@yahoo.com This paper is presented in the National Seminar organised by the Deptt. of Economics & Politics, VISVA-BHARATI, SANTINIKETAN, 11-13 March, 2011.

  2. The significance of the study • Theoretical Approaches (economic logic of caste system) i) Neo-classical, ii) Marxian, & iii) Ambedkar’s Approach [Akerlof (1976), Lal (1984), Hann (1997), Sen (2000)] B. Empirical Studies Lakshmanasamy & Maddheswaran (1995)- emphasized on caste discrimination in the labour market. Thorat & Mahamallik (2007)- emphasized on chronic poverty among socially disadvantaged groups at the aggregate level.

  3. FOCUS AREAS EMPLOYMENT-UNEMPLOYMENT & PUBLIC WORKS POVERTY & ILLITERACY By social category (SC & ST) in Rural W.B (Bankura & Nadia)

  4. Objectives of the study • To discuss employment-unemployment situations by social groups and regions in Rural W.B. • To analyse poverty among SC & ST and explore the role of caste factor in the probability of getting rid of poverty. • To examine the impact of public works like MGNREGA on these socially disadvantaged groups in backward areas. • To identify some factors and suggest some policies in this regard.

  5. Data Base and Methodology Study area (Rural): Bankura & Nadia Secondary Data: NSSO 61st Round (July 2004-June 2005) unit level (employment & unemployment) Sample Size: BANKURA: No. of HH = 279 (ST-15, SC-105, Non-SC/ST-159) NADIA: No. of HH = 320 (ST-7, SC-77, Non-SC/ST-236) Primary Data: No. of HH = 209 (ST-64, SC-132, Non-SC/ST-13) Spread over two adjacent villages – Purulkhan and Salboni under Dhanara G.P. of Raipur block, Bankura.

  6. *STUDY VILLAGES

  7. Data Base and Methodology Form of Dummy variable regressions: (where Y= Poverty/Employment related indicator) Within SC/ST: Yi = α + βD1i +…+ ui, where dummy D1i= 0 for ST =1 for SC Between SC/ST and Non-SC/ST: Yi = α + βD2i +…+ ui, where dummy D2i= 0 for SC/ST =1 for Non-SC/ST. Between Bankura and Nadia: Yi = α + βD3i +…+ ui, where dummy D3i= 0 for Bankura =1 for Nadia.

  8. Logit Model Li = Log (Pi/1-Pi) = α + β1X1i + β2X2i + β3Di + ui where Pi = probability that the household is non-poor (that is Yi = 1), (1-Pi) = probability that the household is poor (that is Yi = 0), and Pi = E (Yi = 1 | Xi, Di) = 1/(1+e-Yi) = eYi/(1+eYi) X1i = Household Size, X2i = Land Owned (0.000 hectare) Di = 1 if the household Non-SC/ST = 0 if the household SC/ST Thus, eβ3isthe contribution of the caste factor in favour of the probability of a household of being non-poor, other things remaining the same.

  9. RESULTS AND FINDINGS Analysis of secondary data • EMPLOYMENT-UNEMPLOYMENT • LEVEL OF GENERAL EDUCATION (AMONG MEMBERS OF HOUSEHOLDS BY CASTES) • HOUSEHOLD LEVEL POVERTY (AMONG SOCIALLY DSADVATAGED GROUPS) Analysis of Primary data • IMPACT OF PUBLIC WORKS (MGNREGA ON EMPLOYMENT OF SC/ST)

  10. % Distribution of sample households by household type & social groups Source: Calculated from the NSS 61st Round Unit level data

  11. Observations Agrl. Lab A significant percentage (47-48%) of rural SC/ST households are found to be agricultural labour compared with Non-SC/ST (6%) in Bankura. Nadia: ST- 57%, SC- 29% and Non-SC/ST-21%. Agr. Vs Non-Agr. The share of Non-SC/ST hh in non-agr. is observed to be more than double than that of SC/ST hh in Bankura. In contrast, % of SC hh engaged (self-emp.) in non-agr. is found to be double than that of in agr. in Nadia.

  12. Public Works

  13. OBSERVATIONS ON EMPLOYMENT -UNEMPLOYMENT: (Usual principal activity status of hh members) • The % of SC/ST household members are working in h.h. enterprise (self-employed) and also Working as regular salaried/ wage employee is observed to be lower than that of Non-SC/STs. • The percentage of unemployed persons in case of STs is observed to be higher than other castes in rural Bankura, whereas in Nadia the said figure is higher for Non-SC/ST household members. • There is not a single member of sample households who got ‘public works’ at least 60 days during a year of 2004-05 in both districts. Only about 15% members are the beneficiaries of Govt. schemes like Annapurna, ICDS, Midday meal, food for work etc. This is a matter of grave concern.

  14. FORMAL LITERACY RATE AMONG SOCIALLY DISADVANTAGED GROUPS IS FOUND TO BE LOW, VAST ILLITERACY & NO HIGHER EDUCATION AMONG THEM DISPARITY IN TERMS OF LEVEL OF GENERAL EDUCATION BETWEEN SC/ST AND NON-SC/ST IS MORE IN BANKURA THAN IN NADIA

  15. SOME OTHER INDICATORS ACROSS CASTES IN RURAL BANKURA: REGRESSION RESULTS * 2.3 times more than SC/ST, ** 1.6 times more than SC/ST Note: Regression Model: Y = α + βD + u, where Y= indicator & D= dummy variable.Here, D1 =0 for ST & D1=1 for SC, D2=0 for SC/ST & D2=1 for Non-SC/ST.

  16. SOME OTHER INDICATORS ACROSS CASTES IN RURAL NADIA: REGRESSION RESULTS * 1.7 times more than SC/ST, ** 1.2 times more than SC/ST Note: Regression Model: Y = α + βD + u, where Y= indicator & D= dummy variable.Here, D1 =0 for ST & D1=1 for SC, D2=0 for SC/ST & D2=1 for Non-SC/ST.

  17. Determinants of Monthly Cons. Exp. Per hh (MPCE): BANKURA lnMPCE = 5.182 + 0.883 lnFS + 0.209 lnLANDC - 0.048* D1 (t-value) (13.55) (6.96) (3.29) (- 0.275) R2 = 0.66, F= 31.53 lnMPCE = 5.421 + 0.675 lnFS + 0.216lnLANDC + 0.325 D2 (t-value) (27.33) (9.40) (6.35) (4.30) R2 = 0.60, F = 80.45 NADIA lnMPCE = 6.194 + 0.509 lnFS + 0.159lnLANDC + 0.118 D2 (t-value) (34.33) (6.78) (6.37) (1.71) R2 = 0.42, F = 34.65 Note: Regression models are in log-linear form. FS= family size, LANDC= Land cultivated (0.000 hectares), Dummy D1=0 for ST and D1=1 for SC and dummy D2=0 for SC/ST and D2=1 for Non-SC/ST. * indicates coefficient is not statistically significant.

  18. REGIONAL DISPARITY IN TERMS OF MPCE BY SOCIAL GROUPS SC/ST Households MPCE = 368.78 + 341.79 FS + 0.43LANDP + 411.57 D3 (t-value) (2.11) (10.95) (4.19) (2.66) R2 = 0.50, F = 65.73 Non-SC/ST Households MPCE = 1321.39 + 344.38 FS + 1.11LANDP – 428.79 D3 (t-value) (5.60) (9.01) (9.64) (-2.41) R2 = 0.46, F = 107.57 Note: FS= family size, LANDP= Land possessed (0.000 hectares), Dummy D3=0 for Bankura and D3=1 for Nadia.

  19. Observations • Within each district, there is a significant difference between SC/ST & Non-SC/ST in terms of standard of living and land owned. However, among SC/STs there is no such significant difference within the district. 2. There is a regional disparity across social groups. Nadia’s SC/ST hhs are in better position than SC/ST hhs of Bankura. But in case of Non-SC/ST hhs, the situation is just reverse.

  20. Note: PCMCE = Per capita monthly consumer expenditure. *Based on minimum of Rs. 130 PCMCE instead of Rs. 29 (an outlier). Poverty line =Rs. 445.38 PCMCE for rural West Bengal, Source: calculated from the NSS data (2004-05)

  21. Note: PCMPCE= Per capita monthly consumer expenditure. Source: Field Survey

  22. OBSERVATIONS • POVERTY AMONG THESE SOCIALLY DISADVANTAGED GROUPS IS ALARMING • VARIATION IN PCMCE IS LOWER AMONG POOR HOUSEHOLDS THAN NON-POOR IN BOTH DISTRICTS. • POVERTY AND DISPARITY AMONG SC/STs IN BANKURA IS FOUND TO BE HIGHER THAN IN NADIA.

  23. Results of Logit Model: Method: ML- Binary Logit Dependent variable = Y Note: where Y = 1 if the household non-poor = 0 if the household poor X1 = Household Size, X2 = Land Owned (0.000 hectare) D= 1 if the household Non-SC/ST = 0 if the household SC/ST

  24. REGARDING POVERTY SITUATION, CASTE FACTOR IS SIGNIFICANT IN BANKURA (BACKWARD DISTRICT) BUT NOT IN NADIA (DEVELOPED DISTRICT). THE COEFFICIENT OF CASTE DUMMY IN LOGIT MODEL (IN BANKURA) IS SIGNIFICANTLY 1.716 WHICH SUGGESTS THAT HOUSEHOLDS THOSE ARE NON- SC/ST ARE 6 TIMES (SINCE e1.716 = 5.6) MORE LIKELY TO GET RID OF POVERTY THAN SC/ST HOUSEHOLDS, HOLDING OTHER THINGS CONSTANT.

  25. ANALYSIS OF PRIMARY DATA IMPACT OF MGNAREGA ON EMPLOYMENT OF SC/ST HOUSEHOLDS IN BANKURA

  26. PUBLIC WORKS (NREGA) & AGRICULTURAL EMPLOYMENT BY CASTES Source: Field Survey

  27. Regression Results PW = 24.163+ 0.599 FS + 0.085 AGWOL -5.934 LANDO + 7.539 D1(t-value) (7.92) (2.061) (5.631) (-3.229 ) (4.639) R2 = 0.543, df = 191, F = 56.82 --------------------------------------------- Where, PW= Public works under NREGA (No. of person days per HH), FS= Household size, AGWOL= No. of days (wage) employed in agriculture other than owned land, LANDO= Land owned (in Hectare), D1= 0 for ST and 1 for SC. PUBLIC WORKS - NREGA IS APPROACHING TOWARDS THE TARGET GROUPS IN THE STUDY AREA BUT THE IMPACT OF IT ON EMPLOYMENT OF SC/ST HOUSEHOLDS IS NOT SATISFACTORY. THERE IS A LACK OF PROPER MONITORING AND SUPERVISION OF THE PROJECT AND PAYMENTS OF WAGES.

  28. CONCLUSIONS There is a significantly clear distinction between SC/ST and Non-SC/ST in respect of employment –unemployment and poverty situation, standard of level of living, general education level, land owned, and land cultivated. Within SCs & STs, there is no such significant difference between them. But there is Regional Variation in this regard. The impact of public works like NREGA on employment of SC/ST households is not satisfactory in the study villages of BANKURA. However, conditions of SCs are worse than STs and such variation is explained to some extent by their crucial factor-area of cultivated land. Social caste plays an important role in the probability of a household to get rid of poverty in the backward region.

  29. Some policies may be suggested: • Effective and adequate number of public works should be provided in a sustainable and more transparent manner so that accessibility and awareness among socially disadvantaged groups be enhanced substantially. E-monitoring including video display may be arranged for confidence building among local people. • Govt policies should be directed towards reduction of regional disparity in poverty and unemployment. • Rural infrastructures should be developed with a time bound manner through the involvement of local people. • Agriculture and allied activities should be developed and diversified. Agriculture-linked and other rural industries should be developed. • Formal literacy among these socially disadvantaged groups should be increased substantially.

  30. THANK YOU

  31. THANK YOU

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