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Dynamics of Socio-Economic Development of Districts of Eastern Uttar Pradesh

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Dynamics of Socio-Economic Development of Districts of Eastern Uttar Pradesh View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Journal of Applied and Natural Science AL SC R IEN TU C A E N F D O N U A N D D Journal of Applied and Natural Science 8 (1): 5 - 9 (2016) A E I T L I O P JANS N P A ANSF 2008 Dynamics of socio-economic development of districts of eastern Uttar Pradesh Nitin Tanwar1*, Sunil Kumar1, B.V.S. Sisodia1, B.K. Hooda2 1Department of Agricultural Statistics, Narendra Deva University of Agriculture and Technology, Kumarganj, Faizabad, U.P., INDIA 2Department of Mathematics, Statistics & Physics, Chaudhary Charan Singh Haryana Agricultural University, Hisar, Haryana, INDIA *Corresponding author. E-mail: [email protected] Received: March 11, 2015; Revised received: August 17, 2015; Accepted: January 1, 2016 Abstract: Development process of any system is dynamic in nature and depends on large number of parameters. This study attempted to capture latest dynamics of development of districts of Eastern Uttar Pradesh in respect of three dimensions- Agriculture, Social and Infrastructure. Techniques adopted by Narain et al. (1991) have been used in addition to Principal component and factor analysis. Ranking seems to very close to ground reality and pro- vides useful information for further planning and corrective measures for future development of Eastern Uttar Pradesh’s Districts. The Composite Indices (C.I.) of development in respect of 18 developmental indicators for the total 28 districts of eastern Uttar Pradesh have been estimated for the year 2010-2011. The district Barabanki was showed a higher level of development (C.I. =0.10) in Agricultural development compared to Social development (C.I. =1.12) and Infrastructural development (C.I. =0.89) followed by the district Ambedkar nagar (Agricultural, C.I. =0.52), (Social, C.I. =1.12) and (Infrastructure, C.I. =0.89). District Allahabad secured first position in the Social develop- ment (C.I. =0.81) and second in Infrastructural development (C.I. =0.34) as compared to Agriculture (C.I. =0.93). District Varanasi was the most developed district in Infrastructure (C.I. =0.10) as compared to Agriculture (C.I. =0.96) and Social (C.I. =0.96). As per findings of the study, the two districts Mau and Jaunpur were down in their ranking and the districts Chandauli and Maharajganj improved their ranking. Keywords: Composite index, Developmental Indicator, Factor analysis, Principal component analysis, Socio- economic INTRODUCTION in the country in a planned way through various Five Year Plans. The Green Revolution in the agriculture Development is a dynamic concept and has different sector and commendable progress on the industrial meaning for different people. It is used in many disci- front has certainly increased the overall total produc- plines at present. The notion of development in the tion, but there is no indication that these achievements context of regional development refers to a value posi- have been able to reduce substantially the regional tive concept which aims to enhance the levels of living inequalities in the level of development (Narain et al. of the people and general conditions of human welfare 2007). Although resource transfers are being executed in a region. Socio-economic developments have be- in backward region of country, it has been observed come one of the most important glaring and growing that the regional disparities exist in terms of socio- problems not only in developing countries but also in economic development are not declining over time the most advanced countries of the World. Since some (Narain et al., 2003). regions are economically developed but backward so- Since Independence the country has implemented vari- cially, whereas some other are developed socially and ous Five Year Plans and few Annual Plans for enhanc- remained backward economically. Historically, India ing the quality of life of people by providing basic has been observing inter-state variations as far as the necessities for effective improvement in their social socio-economic, political and geographical aspects are and economic well-being. Various area development concerned (Siddiqui, 2012). programmes were launched during the fifth plan, with Socio-economic development is to improve the quality one of the aims to reduce regional disparities at micro- of life of people by creation of appropriate infrastruc- level. During the sixth, seventh and eight plans, the ture, among others, for industry, agriculture environ- previous programmes of development were carried on. ment. Economic planning of the country is aimed at Presently, development programmes covering agricul- bringing about maximum regional development and ture, employment generation, population control, liter- reduction in regional disparities in the pace of develop- acy, health, environment, provision of basic amenities ment. Programmes of development have been taken up etc. are in the process of development. As result of six ISSN : 0974-9411 (Print), 2231-5209 (Online) All Rights Reserved © Applied and Natural Science Foundation www.ansfoundation.org 6 Nitin Tanwar et al. / J. Appl. & Nat. Sci. 8 (1): 5 - 9 (2016) decades of planned development and policies, overall mercial Banks. improvement in the economic condition has taken A total of eighteen developmental indicators have been place. The structure of national and state economies included in the analysis. These indicators are the major has been changed significantly. The socio-economic interacting components of development. Out of these condition of the masses has considerably been im- eighteen indicators, seven indicators are directly con- proved. The literacy level, housing condition, quality cerned with agricultural development and the rest of life have gone up. But the level of development has eleven indicators describe the availability of social and not been uniformly at any level. Inter and intra-section infrastructural facilities in the districts. differences in the economic structure have become Method of analysis more sharp and noticeable. Consequently, certain areas Method of estimation of Composite Index of devel- went ahead leaving other lagged behind (Siddiqui, opment (Narain et al. 1991): Let [Xij] be data matrix 2012). The Green Revolution in the agriculture sector giving the values of the variables of ith district. Where i has enhanced the crop productivities and commendable = 1, 2… n (number of districts) and j = 1, 2… k progress in the industrial front has increased the quan- (number of indicators). tum of manufactured goods. The structure of the econ- For combined analysis [Xij] is transferred to [Zij] the omy has undergone certain changes. But a regional matrix of standardized indicators as follows disparity has also been aggravated here which opens Xij X j up a vista of research. [Zij] = Agriculture is the mainstay of the majority of the Sj population in the state. It employs about two-thirds of th Where, S j = Standard deviation of j indicator the workforce and contributes about one-third to the th state income. While wheat is the state’s principal crop, = mean of the j indicator sugarcane is the state’s main commercial crop, largely From [Zij], identify the best value of each indicator. concentrated in the western and central belts of the Let it be denoted as Zoj. The best value will be either state. The western region of the state is more ad- the maximum value or the minimum value of the indi- vanced in terms of agriculture. Majority of the popula- cator depending upon the direction of the impact of indicator on the level of development. For obtaining tion depends upon farming as its main occupation. th Rice, pulses, oil seeds and potatoes are other main the pattern of development Ci of i districts, first calculate Pij as follows products of the state (Narain et al. 1995). 2 The present study deals with the evaluation of the lev- Pij = (Zij –Zoj) els of agricultural, social and industrial developments Pattern of development is given by at district level in the State of Eastern Uttar Pradesh. Where, (CV)j = coefficient of variation in Xij for jth indicator. MATERIALS AND METHODS Composite index of development (C.I.) is given by C.I. = C / C for i = 1, 2, …, n Study area: The study comprised of 28 districts of i eastern Uttar Pradesh (Table 1). Each district faces C = C +3SDi situational factors of development unique to it as well as common administrative and financial factors. Fac- Where C = mean of Ci and tors common to all the districts have been taken as the SDi = Standard deviation of Ci indicators of development. Smaller value of C.I. will indicate high level of devel- Developmental indicators: The composite indices of opment and higher value of C.I. will indicate low level development for different districts were obtained by of development. using the data on the following development indica- Principal component analysis: Principal component tors: Percentage of net area irrigated, Average Produc- analysis (PCA) is a multivariate technique that ana- tivity of food grains (q/h), Per capita consumption of lyzes a data table in which observations are described electricity (kw/h), Per Capita Gross Value of Agricul- by several inter-correlated quantitative dependent vari- tural Produce (Rs.), Gross Value of Agricultural Pro- ables. Its goal is to extract the important information duce per Hec. of Net Area Sown (Rs.), Gross Value of from the table, to represent it as a set of new orthogo- Agricultural Produce Per hec. of Gross Area Sown nal variables called principal components, and to dis- (Rs.), Cropping intensity in percentage, No. of Private play the pattern of similarity of the observations and of Tube wells, Number of Registered Factories per lacs the variables as points in maps. Mathematically, PCA population, Percentage of Electrified villages, Percent- depends upon the eigen-decomposition of positive age of Literacy Rate, Number of Post offices per lacs semi-definite matrices and upon the singular value population, Number of Telephone connections per lacs decomposition (SVD) of rectangular matrices.
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