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Research Article Open access CC BY 4.0

Principal Dimensions of Regional Agricultural & Socio-economic Disparities in Haryana

Ekta Hooda, B. K. Hooda, Veena Manocha, Nitin Tanwar

Advances in Research · pp. 1–11 · Published 22 Jul 2017

10.9734/AIR/2017/34767

Abstract

The present study is an attempt towards identification of principal agricultural and socio-economic dimensions in Haryana using principal component analysis (PCA) and canonical correlation analysis techniques. Principal component analysis transforms the original set of variables into a smaller set of linear combinations that account for most of the variation of the original data whereas canonical correlation analysis determines pairs of canonical variates which are orthogonal linear combinations of the variables within each set that best explain the variability both within and between sets. Canonical correlation analysis also identifies and measures the strength of relationships between two vectors of variables measured on the same individuals. The study was conducted for three periods i.e. 1991-92, 2001-02 and 2011-12. The district was considered as the unit of analysis and analysis is based on 19 indicators from the agriculture sector and 9 indicators from the socio-economic sector. The first principal component (PC) of agriculture sector represents the overall level of agriculture and livestock with 42.07, 28.71, and 28.01 per cent of the total variation in periods 1991-92, 2001-02 and 2011-12. Whereas, the first PC of socio-economic sector extracted 43.2, 42.6 and 56.6 per cent variation for the periods 1991-92, 2001-02 and 2011-12, respectively. Population density per sq km, number of vehicles on road/lakh population and number of cooperative societies/lakh population have been most important variables for the first principal component from the socio-economic sector in the periods 1991-92 and 2001-02. However, infant mortality rate, number of vehicles on road/lakh population and main workers as percentage of total population has observed to be the most important indicators during 2011-12. Canonical analysis of first two PCs from each of the agriculture and socio-economic sector indicated that the dimensions represented by the second principal component of agriculture sector and first principal component of socio-economic sector established a strong association between the agriculture and the socio-economic sectors. The significant canonical correlation between the vectors represented by first two PCs of agricultural and socio-economic sectors suggest that developments in socio-economic sectors and agricultural sectors go together. That is socio-economic development in Haryana can be achieved through development in agriculture.  

Principal component analysis canonical correlation analysis principal dimensions

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