Spatial Differentiation in Agricultural Development in Uttar Pradesh, India: A District-level Cluster Analysis

Abstract

Aims: The present paper attempts to explore the spatial differentiation of agricultural development across the districts of Uttar Pradesh using hierarchical cluster analysis. Five main dimensions of agricultural development are identified: agricultural performance, access to agricultural finance, unviability of agriculture, technology and land resources. Study Design: The study is based on secondary data, and district-level data were gathered from the Directorate of Economics and Statistics, Government of Uttar Pradesh. The analytical technique was used for the analysis. Place and Duration of Study: The study was conducted across the districts of Uttar Pradesh using the latest available data (2022-23). Based on data availability, 69 districts of Uttar Pradesh were selected for analysis. Methodology: For the cluster analysis, hierarchical cluster analysis using Ward’s method was applied. One-way ANOVA and Tukey’s HSD post-hoc test were subsequently used to examine differences among the identified clusters. The analysis provides an empirical basis for identifying relatively developed, intermediate and vulnerable agricultural zones within Uttar Pradesh. Results: The analysis identifies three distinct clusters of districts. Cluster 1 consists predominantly of districts in Western Uttar Pradesh, characterised by a relatively strong agricultural base, larger holdings, commercial agriculture, greater use of technology and higher productivity and returns. Cluster 2 comprises districts from Western and Central Uttar Pradesh, along with Deoria and Azamgarh from Eastern Uttar Pradesh, and occupies an intermediate position. Cluster 3 contains 36 districts, including all districts of Bundelkhand and most districts of Eastern Uttar Pradesh, and represents a relatively vulnerable agricultural zone. Conclusion: The results suggest that agricultural development in Uttar Pradesh has a significant spatial component and that consistent state-level agricultural policies may not be suitable for addressing the differing circumstances across districts. Therefore, agricultural policies need to be sensitive to individual districts and specific to each cluster.