The poll bugle has been sounded in Bihar. Come November 8 and we hope to know what has Bihar chosen: PM Narendra Modi’s development model or CM Nitish Kumar’s sushashan (good governance). Whoever wins this election, challenges and tasks before him/her would be formidable and daunting. Bihar is still struggling to break out of the vicious cycle of under-development in terms of persistent poverty, complex social stratification, unsatisfactory infrastructure and weak governance. These problems are well known, but not well understood, and the new CM can’t afford to waste any time if he is serious about fulfilling election promises.
Ostensibly, it’s not easy and wise to make plans that are workable for all regions of Bihar. The intra-state disparities reveal a stark reality of presence of regional imbalances. The widening gap in terms of per capita income of districts is almost 10 times between the richest (Patna) and the poorest (Seohar). To help policy makers in formulating right kinds of policies, we have developed a livelihood resilience index for the state at district level.
Livelihood resilience is visualized as ideal, wherein variability of bio-physical, economic and social systems operates within respective threshold limits and adaptive capabilities (Swaminathan, 1991). The Livelihood Resilience Index (LRI) developed here, includes three major components: Bio-physical resources, Economic resources, and Social resources. The resilience of bio-physical systems is influenced by factors like biodiversity, redundancies, response diversity, spatiality, and governance and management plans. The Bio-physical resilience index (BRI), is largely constructed from stock and flow resource indicators to capture the dynamics of climate change and impacts on bio-physical (re)production cycle by judiciously selecting static and dynamic indicators.
Social resilience can be increased through improvements in communications, risk awareness, and preparedness. Social resilience index (SRI) can be constructed from personal and social well-being indicators, like health, nutrition, education, employment, income-consumption, housing, and energy. Further, there is a need to examine whether the resources in a given context are over-exploited to meet the local and or global economic demand crossing the threshold limits of the resilience.
The Economic Resilience Index (ERI) is constructed from production, productivity and resource allocation indicators, for example, shifting attention to ‘more crop per drop’ and total factor productivity growth. The indicators were carefully chosen at the district level to capture the essence of the livelihood resilience as well as the practicality of available data. The standardized index, adapted from that used in the Human Development Index, computed and rescaled into a single scalar – a composite index, the LRI is scaled from 0 (least resilient) to 1 (most resilient).
The LRI estimated at the district levels reveals an interesting picture. Rohtas, Aurangabad, Kaimur, Bhojpur, Buxar, and Munger are top six LRI ranked districts, while Purnea, Darbhanga, Madhepura, Kishanganj, Sitamarhi, and Jamui are at the bottom six (Patna, being outlier, has been removed from the analysis). Another important feature of the current analysis shows that except for Buxar, all the top six districts are naxal affected! Aurangabad, Kaimur, and Buxar are surprised entry in the top six, despite having a low per capita income. They performed pretty well in terms of BRI and ERI. The low rank in terms of SRI for Kaimur and Buxar is compensated by availability of bio-physical and economic resources. However, this also warrants a special focus on urbanization and female literacy to improve the social resilience in the districts. Further the high per capita income districts, Munger, Begusarai, Muzaffarpur, Bhagalpur, and Bhojpur had performed badly on BRI, despite having a good score on SRI. This suggest the policy intervention needed in these districts are to restore the bio-physical resources, which over-exploited. The overall resilience index, therefore, had not been very good despite a good performance on socio-economic resources. The bottom six districts have no major surprises, as these districts performed badly in terms of all accounts of the three resilience indicators, namely, BRI, SRI, and ERI. One interesting case emerges from this analysis. Seohar, the district having lowest per capita income, ranked above average in LRI benchmark, i.e. 16 out of 37 districts used in the analysis. This district ranked highest in BRI ranking, despite bad performance in terms of SRI and ERI, suggesting it hardly exploited the bio-physical resources to full potential. Obviously, the district performs badly on ERI scale. This indicates that better access to resources does not necessarily mean districts have better resilience. The combination of bio-physical, economic, and social resources seems to be the determining factor in developing the livelihood resilience for the district.
LRI, developed here, can provide a powerful tool for understanding and verifying the necessary conditions for the development of the regions. Being simple and flexible, this functions as an educational and policy tool promoting a holistic perspective among planners, administrators and development workers. The index helps to focus on the conflict and the potential synergy between bio-physical and socio-economic dimension of the sustainable development. As a policy tool, LRI identify not only the districts requiring the immediate attention but also the specific thematic areas in which the efforts could be focused to attaining the livelihood resilience in case of exogenous factors, like floods, droughts, etc. Participatory identification of resilient livelihoods may be helpful in formulating and executing different programmes to reduce the vulnerability. This may assist to firmly re-establish existing livelihood or promote the diversified portfolio activities. Lastly, this would provide the guidance for implementing more sustainable practices that empower local communities to take their risks seriously, and at the same time provide guidance on the structural, economic, social, and environmental policy changes needed to enhance their own resilience.
* Prof. KV Raju is Director at Development Management Institute (DMI), Patna, Bihar, India. He previously worked as a faculty member at Institute of Rural Management, Anand (IRMA) from July 1995 – March 2014.
* Dr. Surya Bhushan is Associate Professor at Development Management Institute (DMI), Patna, Bihar. He did his PhD in Economics from Jawaharlal Nehru University (JNU) and previously worked with Accenture Advance Analytics, India for more than nine years.