Spatial variability of agricultural development in West Bengal, India: a multivariate statistical approach

Abstract

Exploring the regional variability along with the identification of backward regions is considered as an indispensable aspect regarding a balanced regional development in agriculture. Accordingly, the aims of the study are to measure the inter-district variability of agricultural development, factors responsible for variability, identify the backward districts and estimate the potential targets of indicators for the backward districts along with the suggested model districts. For this purpose, considering 10 indicators, three important approaches like optimum combinational composite index model (OCCIM), unequal weight method (UWM) and principal component analysis (PCA) have been applied to exhibit the inter-district disparities and to identify the poorly developed districts. Finally, the potential targets of indicators and the model districts have been estimated using two statistical measures like developmental distance and critical distance. The study has established three major findings: First, the districts like Howrah, 24 Parganas (S) and Darjeeling are agriculturally backward. Second, agro-mechanization, basic indicators and agrarian structure with the contribution of 31.79%, 28.48% and 19.08% to the total variance respectively are found to be responsible for wide regional disparity. Finally, the actual achievements of indicators are lagged behind from the estimated potential targets. Results of the study thus, can be used as a reference in formulating effective policies to abridge the regional variability in agricultural development in West Bengal. Moreover, the methodological perspective adopted here may be used as a research tool in different wings of economy to address the same situations.