Gender Vulnerability to Climate Change and Adaptation Strategy An Empirical Study in Drought prone Region of West Bengal, India

Jyotish Prakash Prakash Basu


The present paper attempts to measure gender vulnerability to climate change and to identify the gender-wise adaptation options at the household level in the drought prone region of West Bengal. The Livelihood Vulnerability Index (LVI) and combined LVI-IPCC index have been used to measure gender vulnerability. The paper is based on primary data collected from 150 households from four villages in the district of Purulia, one of the drought prone regions of West Bengal, in 2018 with the help of a structured questionnaire. The result of the paper shows that the female headed households are more vulnerable compared to the male headed households on the basis of both measures of vulnerability indices. The paper also identifies the gender-wise adaptation options like livestock rearing, formation of self-help groups (SHGs), migration, and diversification of livelihood and collection of non-timber forest products (NTFPs). The paper has an important policy implication for the reduction of vulnerability of the female headed households and strengthening livelihood opportunities.



Keywords: Livelihood vulnerability index, gender, adaptation, self-help groups, migration, livelihood opportunity.


Livelihood vulnerability index, gender, adaptation, self-help groups, migration, livelihood opportunity.

Full Text:



• Adger W.N, Brooks, N., Bentham G, Agnew M, Eriksen, S. (2004). New indicators of vulnerability and adaptive capacity. Tyndall Center for Climate Change Research, Technical Report 2004; 7: 122.

• Alhassan, S.I., Kuwornu, J.K.M and Osei-Asare, Y.B. (2018). Gender dimension of vulnerability to climate change and variability: Empirical evidence of smallholder farming households in Ghana. International Journal of Climate Change Strategies and Management. Emerald Publishing Limited, 1756-8692. DOI 10.1108/IJCCSM 10-2016-0156.

• Chaudhuri, S., Jalan, J. and Suryahadi, A. (2002). Assessing household vulnerability to poverty: A methodology and estimates for Indonesia, Department of Economics Discussion Paper No. 0102-52, New York: Columbia University.

• Christiaensen, L. and Subbarao, K. (2004). Towards an understanding of household vulnera-bility in rural Kenya. Journal of African Economies 14(4): 520-558.

• DFID (2009). Eliminating World Poverty: Building Our Common Future, London: DFID.

• Hahn, M. B., Riederer, A. M., & Foster, S. O. (2009). The livelihood vulnerability index: A pragmatic approach to assessing risks from climate variability and change—a case study in Mozambique.GlobalEnvironmentalChange,19(1),74–88. https://doi:10.1016/j.gloenvcha.2008.11.002

• Hoddinott, J., and A. R. Quisumbing ( 2003). Data sources for micro-econometric risk and vulnerability assessments. Manuscript. International Food Policy Research Institute, Washington, D.C.

• Iyengar, N.S., & P. Sudarshan.(1982). A Method of Classifying Regions from Multivariate Data. Economic and Political Weekly, Special Article. 2048-2052.

• Johnson, A. S. (2011). Virtue and vulnerability: Discourses on women, gender and climate change. Global Environmental Change 21(2):744–751.

• Lambrou Y and Nelson S. (2010). Farmers in a changing climate: Does gender matter? Food Security in Andhra Pradesh, India. Rome, Italy: Food and Agriculture Organization of the United Nations.

• Ligon,E, and L.Schecher (2003).Evaluating Different Approaches to Estimating Vulnerability. Social Protection Discussion Paper Series No. 0410, Washington DC, World Bank, 2004.

• Luers AL, Lobell DB, Sklar LS, Addams CL, Matson PA (2003). A method for quantifying vulnerability, applied to the Yaqui Valley, Mexico. Global Environmental Change, 13, 255-267.

• Ovstegard R, Kakumanu KR, Lakshmanan A and Ponnuswamy J. (2010). Gender and climate change adaptation in Tamil Nadu and Andhra Pradesh: A preliminary analysis (1), 1-12. (

• Pandey, M.K. & Jha, A. (2012). Widowhood and health of elderly in India: Examining the role of economic factors using structural equation modelling. International Review of Allied Economics 26(1), 111–124. 71.2011.587109.

• Tonmoy,F.N., El-Zein,A., Hinkle, J. et al. (2014).Assessment of vulnerability to climate change using Indicators: A meta Analysis of the literature. Willy Inter disciplinary Review of climate change, 5, 775-792, doi: 10.1002/wcc.314 University of Oxford.

• UNDP (2006). Human development report, United Nations Development Program,

• WEDO. (2007). ‘Changing the climate: Why women’s perspectives matter’. Whirled Bank Group 2008. Agriculture and the World Bank.

• World Bank (2010). Economics of Adaptation to Climate Change: Social synthesis Report, 1818 H Street NW, Washington DC.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.