Can the Rural Employment Guarantee Scheme Reduce Rural Out-migration: Evidence from West Bengal, India

Abstract

Using survey data from the Cooch Behar district of West Bengal, the paper documents the impact of the rural employment guarantee scheme in reducing rural out-migration. Using regression framework and case studies, it finds no significant impact of household participation in the programme on migration decision. However, extent of participation in terms of number of days of work and earnings has a significant negative impact on short-term migration but not on longer duration ones. The findings lay emphasis on effective implementation in terms of asset creation, reduction in rationing of works and tackling delayed payments to enjoy its potential benefits.

Acknowledgements

The paper is based on the author’s doctoral dissertation at the Indira Gandhi Institute of Development Research (IGIDR), Mumbai, India. The author would like to thank two anonymous referees along with Dr. Srijit Mishra, Dr. Sudha Narayanan, Dr. Reetika Khera, Dr. Kent Zhao, Dr. Haiyuan Wang, Ritika Palit, Naraparaju Karthikeya and Andaleeb Rahman for their comments and suggestions. The author also thanks the conference participants of the 2013 International Symposium of Labour Economics, Xiamen, the 55^th Annual Conference of the Indian Society for Labour Economics, New Delhi and the Conference on The MGNREGA in India: ‘Taking Stock, Looking Ahead at IGIDR, Mumbai’ for the valuable comments. The code used in the paper as well as the data can be provided on request. Usual disclaimers apply.

Notes

1. A GP is the primary unit of the three-tier structure of the local self-government in the rural parts of India. Each panchayat consists of a few villages.

2. For more information on the programme, please refer to Dey, Dreze, and Khera (2006)

3. Please refer to http://nrega.nic.in/netnrega/home.aspx

4. It may be noted that the SCs and STs along with the OBCs have suffered from severe social exclusion and discrimination from historical times and lag behind the upper castes in different indicators of welfare (Deshpande, 2011).

5. Hindu is the majority religious group of the Indian population (taken as the reference category) and Muslims is the largest group among the religious minorities.

6. Please refer to Khandekar, Koolwal, and Samad (2010) for an excellent overview of most of the methodologies available.

7. Bivariate probit for impact evaluation has been used by Evans and Schwab (1995) and Chen, Yen, and Eastwood (2005).

8. Please refer to Staiger, Douglas and Stock (1997) for details.

9. These tests are done using the ivreg2 command in STATA, which assumes a linear structure of the endogenous variable as well as the outcome variable.

10. For more on the methodology, please refer to Fan and Gijbels (1996).

11. The results of the other regression can be provided on request.

Additional information

Funding

This research has been supported by a grant for research scholars by IGIDR.