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This study aims to evaluate the link between climate/weather change and farmer migration in Bihar, India. The influence of cognitive conditions and climate-related stress on farmer migration decisions and the socioeconomic characteristics of migrating and non-migrating farm households are analysed. The focus is the role of migration in access to climate and agricultural extension services and the contribution of migration to enhanced farmer coping capacity.

A primary survey was conducted of farm households in seven districts of Bihar, India. Farmer perceptions of climate change were analysed using the mental map technique. The role of socioeconomic characteristics in farm household migration was evaluated using binary logistic regression, and the influence of migration on access to climate and agricultural extension services and the adaptive capacity of migrating households was investigated using descriptive statistics.

Climate-induced livelihood risk factors are one of the major drivers of farmer’s migration. The farmers’ perception on climate change influences migration along with the socioeconomic characteristics. There is a significant difference between migrating and non-migrating farm households in the utilization of instructions, knowledge and technology based climate and agriculture extension services. Benefits from receipt of remittance, knowledge and social networks from the host region enhances migrating households’ adaptive capacity.

This study provides micro-evidence of the contribution of migration to farmer adaptive capacity and access to climate and agricultural extension services, which will benefit analyses of climate-induced migration in other developing countries with higher agricultural dependence. In addition, valuable insights are delivered on policy requirements to reduce farmer vulnerability to climate change.

The purpose of this paper is to provide a quantitative approach to measure industry clusters competitiveness.

An attempt has been made to construct a composite indicator backed up by a conceptually grounded framework, by means of Analytical Hierarchical Process technique. Four industry clusters from auto sector in India are chosen for manifestation of the methodology.

The proposed methodology sufficiently emphasises on the order of significance of the factors/indicators that make a cluster competitive. The study demonstrates the comparative competitiveness performance of four select industry clusters from India.

The methodology only focusses on auto clusters from India, application of the model/methodology needs to be extended to other set of industries that follows tier structure, or belong to other developing nations to corroborate the findings.

The proposed approach is a useful tool to provide guidance to policy-makers and in monitoring industry clusters progress.

The paper offers an empirical approach for measuring competitiveness of industry clusters. So far there has been only a minuscule research on cluster competitiveness using empirical methods specifically in case of developing countries like India. Because of the heterogeneity of actors in industry clusters and absence of cluster relevant databases, its performance has been mostly captured via means of case studies. This study is one of its kind that renders comparison of competitiveness across industry clusters by combining secondary data with the perception of cluster actors.

The Sundarbans is a unique ecosystem, the most expansive mangrove system in the world covering the Ganga–Brahmaputra–Meghna delta system and spread over 10,000 sq.km across India and Bangladesh. The Indian Sundarbans have been witnessed to large-scale conversion of mangroves to settled agriculture and steady growth of population over the decades. With time, while population growth has taken place, there has been no significant change in the development scenario, as the agriculture and fishing dependent communities have remained trapped in the vicious cycle of poverty. Its deltaic location and its position in the path of cyclones, tidal surges and seasonal floods have made the people and landscape of Sundarbans more vulnerable than ever before. Cyclones affecting this region have grown both in frequency and intensity over the years and have caused devastation to the land, homes, lives and livelihoods. The problem of salinity has also affected the region relentlessly. Given this scenario, scenario of progressing vulnerabilities, livelihood losses have led to a gradual increase in out-migration of the adult male population. This disaster-led outmigration from Sundarban region as a whole has affected the social fabric of displaced communities to a great extent. This chapter makes an attempt to discuss results of sample surveys across six villages in three CD Blocks of Sagar, Gosaba and Kultali to trace the nature and dimension of the migration patterns of the region.

The purpose of the study is to understand the relative impacts of structural characteristics of house, its locational attributes and neighbourhood characteristics on the choice of house and the rent paid by the individual tenants. The micro level study helps in understanding the issues of urban housing and help in policy formulation.

This paper tried to identify the socio-economic, locational and neighbourhood factors that influence tenant households in determining their residential choices in an urban area of North-east India. Also, the extent of impacts of those characteristics on the monthly rent for housing is analysed. The analysis is based on the primary data collected from the sample residents of Dimapur Town in Nagaland. The sample units are selected by cluster sampling technique from all the wards. Regression technique is used under hedonic pricing technique to examine the impacts of various potential factors on the rent.

The analysis reveals that family size, income, education of the head of family, water availability, security, convenience to access workplace, road conditions, etc. have significant positive impacts on the monthly rent. However, the impacts of some locational and neighbourhood variables vary across social and economic groups.

Time series data on the growth of house price are not available, so that the authors could examine the escalation of house price and rising scarcity of houses in the selected town.

Rental housing accounts for a significant percentage of housing in many urban centres. It is particularly important for the migrants and urban poor for whom it is the only source of accommodation. Location choice depending on capability, availability, requirement and neighbourhood conditions are integral parts of selection of accommodation in a city. Hence the present study has its relevant practical implications.

Housing choice in a hilly urban area like Dimapur assumes a special significance for the presence of heterogeneous ethnic, social and cultural groups with majority of Tribal inhabitants with varied requirements and lifestyle.

No study on housing choice or pricing of residential accommodation has been done in North-East India. Here along with the socio-economic characteristics of the individuals, structural characteristics of house, neighbourhood and locational characteristics are used simultaneously to find out the impact of various factors on the total prices through hedonic pricing method.