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Influence of NREGS on Agricultural Wage Determination in West Bengal: A Dynamic Panel Approach

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Abstract

It is investigated whether the expansion of the National Rural Employment Guarantee Scheme (NREGS) can influence the real agricultural wage in West Bengal. The time period studied is between 2005-06 and 2012-13 where 18 districts of the state are used as a unit. Three types of NREGS work like, (i) provision of irrigation facilities, (ii) micro irrigation work and (iii) rural connectivity are considered separately because these works are undertaken in a majority during this tenure. These works have been measured as the total number of tasks completed in different districts in the different years. They are considered separately because each type of asset creation work could influence agricultural wage but not uniformly. Both the ‘push’ and ‘pull’ factors functioning in the labour market are deemed as being able to impact agricultural wage rates. Agricultural wages of a particular district in a particular period is also very affected by the agricultural wage rates prevalent in the same district in the previous period. The dynamic panel approach used in this paper shows that all three types of NREGS work are responsible for the hike of real agricultural wage rates in West Bengal but the impact has not been very strong. It may then, be concluded that, the expansion of the NREGS has little impact when determining the real agricultural wage rate in West Bengal.

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Notes

  1. Farmers who own up to 1 hectare of land are called marginal farmers and farmers who own up to 1-2 hectares land are called small farmers.

  2. It is a common experience that agricultural labourers predominantly suffer from money illusion implying that they express their concern about nominal wage rate instead of real wage rate. But to fulfill the very academic purpose of this empirical exercise, we resorted to take account of the variation in real agricultural wage rate.

  3. SCs: Scheduled Castes; STs: Scheduled Tribes; BPL: Below Poverty Line.

  4. Here only the ‘pull’ factor is active in the agricultural labour market.

  5. Another important factor which can influence the agricultural wage rate is different private non-farm wage like wage of the construction worker. But district wise data of different private non-farm wage rate is not available. Hence this is not incorporated in Eq. (1).

  6. We cannot take natural logarithm of ‘microirr’ ‘provofirr’ or ‘ruralconn’ because at initial periods some of these types of work did not happen under NREGS.

  7. Arellano-Bond estimator is a generalised method of moment estimates is used to estimate the dynamic panel data model.

  8. Here the first difference OLS estimation is inconsistent but an Instrumental Variable estimation leads to consistent estimator.

  9. The validity of the moment conditions implied by Dynamic Panel data model is commonly tested with Sargan.

  10. Heteroskedasticity may arise if some relevant variables have been omitted which means the model is inadequately specified. Here due to lack of data, we did not include private non-farm wage as an explanatory variable but this may influence real agricultural wage rate. So rejection of Null hypothesis in Arellano-Bond’s one-step estimation is quite natural.

References

  • Arellano, M. and S. Bond (1991), “Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equation”, Review of Economic Studies, Vol. 58, pp. 277–298.

    Article  Google Scholar 

  • Basu, Arnab K., Nancy H. Chau and Ravi Kanbur (2009), “A Theory of Employment Guarantees: Contestability, Credibility and Distributional Concern”, Journal of Public Economics, Vol. 93, No. 3–4, pp. 482–87.

    Article  Google Scholar 

  • Basu, Arnab K. (2013), “Impact of Rural Employment Guarantee Programmes on Seasonal Labour Market: Optimum Compensation and Worker’s Welfare”, Journal of Economic Inequality, Vol. 11, No. 1, pp. 1–34.

    Article  Google Scholar 

  • Blundell, R. and S. Bond (1998), “Initial Conditions and Moment Restrictions in Dynamic Panel Data Model”, Journal of Econometrics, Vol. 87, No. 1, pp. 115–143.

    Article  Google Scholar 

  • Dev, Mahendra (1995), “India’s (Maharastra) Employment Guarantee Programme: Lessons from Long Experience” in Joachim von Braun (ed.), Employment for Poverty Reduction and Food Security, International Food Policy Research Institute, Washington DC., pp. 108–143.

    Google Scholar 

  • Drèze, Jean and Amartya Sen (1991), “Strategies of Entitlement Protections” in Jean Drèze and Amartya Sen (eds.), Hunger and Public Action, Clarendon Press, Gloucestershire, pp.104–121.

    Chapter  Google Scholar 

  • Haque, T. (2013), “MGNREGS and its Effects on Agriculture: Exploring Linkages” in Ashok K. Pankaj (ed.), Right to Work and Rural India, Sage Publication, New Delhi, pp. 226–245.

    Google Scholar 

  • Kundu, Amit (2006), “Wage Employment Relationship in the Agricultural Labour Market in West Bengal”, Indian Journal of Labour Economics, Vol. 49, No. 4, pp. 681–696.

    Google Scholar 

  • Kundu, Amit and Sanjib Talukdar (2014), “Impact of Mahatma Gandhi National Rural Employment Guarantee Programme on the Rural Poor - A Simple Theoretical Discourse”, Arthaniti, Vol. 13, Nos. 1–2, pp. 48–75.

  • Kundu, Amit and Sanjib Talukdar (2016), “Asset Creation through National Rural Employment Guarantee Scheme (NREGS) and its Impact on West Bengal Agriculture: A District Level Analysis”, Journal of Global Economy, Vol. 12, No. 3, pp. 151–166.

    Google Scholar 

  • Mahajan, Kanika (2015), “Farm Wages and Public Works: How Robust are the Impacts of the National Rural Employment Guarantee Scheme?”, Indian Growth and Development Review, Vol. 8, No. 1, pp. 19–72.

    Article  Google Scholar 

  • Osmani, S.R. (1991), “Wage Determination in Rural Labour Markets: The Theory of Implicit Cooperation”, Journal of Development Economics, Vol. 34, No. 1, pp. 3–23.

    Google Scholar 

  • Reddy, D. Narshimha (2013), “MGNREGS and Indian Agriculture: Opportunities and Challenges” in Ashok K. Pankaj (ed.), Right to Work and Rural India, Sage Publication, New Delhi, pp. 246–272.

    Google Scholar 

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Authors and Affiliations

  1. Department of Economics, Jadavpur University, Kolkata, West Bengal, 700032, India

    Amit Kundu

  2. Department of Economics, Sree Chaitanya Mahavidyalaya, 24 Parganas (North), Habra, West Bengal, India

    Sanjib Talukdar

Authors
  1. Amit Kundu
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  2. Sanjib Talukdar
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Correspondence to Amit Kundu.

Additional information

This is the revised version of our paper after presenting it in the 58th Annual Conference of the Indian Society of Labour Economics in Guwahati, November 26-28, 2016. We are grateful to the anonymous referee(s) whose valuable comments helped us to enrich our paper. The usual disclaimer applies.

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Kundu, A., Talukdar, S. Influence of NREGS on Agricultural Wage Determination in West Bengal: A Dynamic Panel Approach. Ind. J. Labour Econ. 59, 381–396 (2016). https://doi.org/10.1007/s41027-017-0062-7

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  • DOI: https://doi.org/10.1007/s41027-017-0062-7

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