Exploring Agricultural Disparities in Western Odisha: A Comprehensive Study Based on Composite Index Scores

Suru Munda^1*, Rajendra Gartia ² and Samir Ranjan Dash³

¹School of Statistics Gangadhar Meher University, Sambalpur, Odisha, India

²Senior Statistical Officer, NSSO, Sambalpur, Odisha, India.

Corresponding Author E-mail:surumundasbp@gmail.com

DOI : http://dx.doi.org/10.12944/CARJ.11.3.27

Abstract:

The research endeavor delves into the intricate agricultural disparities prevalent in Western Odisha, focusing on crucial metrics such as land area, yield rates, and production trends spanning the years 2020 to 2022. The study encompassed an extensive scope, encompassing 50 blocks distributed across six carefully selected districts: Nuapada, Jharsuguda, Boudh, Sundargarh, Sambalpur, and Baragarh. These districts were meticulously chosen through a process of simple random sampling from a pool of ten districts in the Western Odisha region. To distill meaningful insights, the research harnessed the power of composite indices, drawn from a comprehensive set of fifteen indicators, each illuminating distinct facets of agricultural development. Through the application of Principal Component Analysis (PCA), five key indicators were expertly extracted from this data set. Drawing upon secondary data sourced from the esteemed Statistical Abstracts of Western Odisha districts, and the Directorate of Economics and Statistics (DES), Government of Odisha (2019-2020), the study validated its assumptions by subjecting the extracted components to the rigors of the Kolmogorov-Smirnov test for normal distribution. Primary data was diligently collected from a cohort of 300 households via meticulously structured questionnaires, encompassing vital parameters such as land area (measured in acres), yield rates (measured in kilograms), and production figures (measured in quintals). It was discovered that the data exhibited deviations from normality, prompting the application of non-parametric methodologies. The ensuing Kruskal-Wallis tests unearthed significant disparities among the identified groups, emphasizing substantial distinctions between the Meteoric, Progressive, Mediocre, and Laggard classifications. To gauge the extent of these disparities, the Gini Coefficient (GC) was aptly employed. The findings underscored that the Meteoric group exhibited more pronounced disparities in land area compared to the other groups, along with marked differences in yield rates. Additionally, this group displayed slightly elevated disparities in production figures. These revelatory results furnish a nuanced understanding of the diverse variances in land area, yield rates, and production levels among the distinct groups. This research endeavor, by shedding light on the dynamic agricultural landscape of Western Odisha, not only highlights the disparities but also offers valuable insights into the underlying factors influencing these agricultural outcomes. These insights, in turn, pave the way for targeted interventions aimed at augmenting agricultural productivity in the region. Addressing these identified disparities emerges as a critical step towards fostering a more equitable and sustainable agricultural sector in Western Odisha.

Keywords:

Agricultural Disparities; Composite Index; Gini Coefficient; Kruskal-Wallis Test; Non-parametric Methods; Principal Component Analysis (PCA)

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