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Journal Volume 16 2020 Final A DOUBLE BLIND PEER REVIEWED JOURNAL OF APG AND ISPER INDIA INDEXED IN SCOPUS VOLUME 16 ISSN- 0973–3485 OCTOBER 2020 PUNJAB GEOGRAPHER : ISSN- 0973–3485 Volume 16 October 2020 INFRASTRUCTURAL DEVELOPMENT IN BUNDELKHAND REGION: A MICRO-LEVEL ANALYSIS P. K. Sharma Abstract Infrastructure development is one of the driving forces to attain swift economic growth. It plays an important role in the reduction of poverty, improvements in standard of living and leads to sustained development of a region. This study is an attempt to analyse the micro- regional disparities in infrastructural development across 40 blocks of Bundelkhand region of Madhya Pradesh. The study is based on secondary sources of data, obtained from various government agencies for the year, 2011. In order to find out the level of infrastructural development, composite score method has been used by considering 12 variables at the block level. The study reveals widespread micro-regional infrastructural disparity, ranging from highest score of 1.34 for Nowgong block to lowest of -0.95 for Buxwaha block. On the basis of Principal Component Analysis, four dominant factors governing the level of infrastructural development in the region have been identified. These key factors may be addressed on priority basis to enhance the living condition of the people and to reduce micro regional disparities. Keywords: Infrastructure, Bundelkhand, Development, Disparities, Region, Facilities. Introduction condition for the overall development of a In the long path of planned region (Bagchi, 2017). The better infra- development in India, wide spread regional structure provides better living conditions and disparities are still one of the major concerns easy availability of services to the public. The of the national development policies. degree of road connectivity has correlation Therefore, studies on micro-regional with urbanization and agricultural prod- development are now a key issue of research uctivity in a region leading to overall in regional sciences. The development development and reduction of poverty implies progressive change in socio- (Mangat and Gill, 2015). Adequacy of economic structure of a region and the infrastructure helps toward determination of infrastructure provides the foundation for this one country's success and another's failure in transformation (Chand and Puri, 2015). diversifying production, expanding trade, Accordingly, availability of basic infra- coping with population growth, reducing structural facilities is an important pre- poverty or improving environmental 2 PUNJAB GEOGRAPHER VOLUME 16 OCTOBER 2020 conditions (WDR, 1994). Thus, infrastructure to disparities in demographic, social and plays a pivotal role in the development of economic infrastructures (Raj et al., 2019). backward region and removal of regional Infrastructural development has disparities all the way through enhancing the greater significance in backward region like level and nature of economic and social Bundelkhand due to its inherent deficiencies activities in a region. and imbalances (Purushotam and Paani, Regional disparity is a multi-dimen- 2016). The people in backward regions have sional phenomenon and the outcome of lack of economic opportunities. They are unbalanced regional development varies from deprived of the fruits of development efforts region to region depending upon economic, and often carry a deep sense of frustration socio-cultural and demographic character- (Patra, 2010). The Bundelkhand region of istics (Dinesha, 2015). A sound infrastructural Madhya Pradesh is characterized with foundation is essential for attainment of the agriculture based economy and poor overall socio-economic development of a infrastructural development. The basic region. In a modern economy, infrastructure necessities of the society aren't being met plays a pivotal role in determining the level of (Singh and Shukla, 2010). In this context, the development (Sarkar, 1994). The strong present paper attempts to study the regional positive correlation between the level of infra- disparities in infrastructural development in structure and the economic development has Bundelkhand region of Madhya Pradesh. been a well-established fact in the develop- ment economics literature (Sahoo and Objectives of the Study Saxena, 1999; Chotia and Rao, 2015). There Major objectives of the study are: have been enormous differences in individual • to analyse the disparities in infrastruc- performance among the states in terms of all tural development and the basic indicators of infrastructural develop- • to identify the most significant factors ment. Further, physical and social for infrastructural development in the infrastructural facilities have proved to be Bundelkhand region. highly significant factors in determining the inter-state level of development (Ghose and Study Area Prabir, 2004). The quality of infrastructure The Bundelkhand region in India networks significantly impacts economic traverses across administrative boundaries of growth and affects inequalities in a variety of 13 districts, out of which seven districts like ways (Adhyapok and Ahmed, 2012). Econo- Jhansi, Jalaun, Lalitpur, Hamirpur, Mahoba, mists have identified various factors that have Banda, and Chitrakoot are of Uttar Pradesh, close relationship with regional development while six districts such as Datia, Tikamgarh, and infrastructure is one of the important Chhatarpur, Damoh, Panna and Sagar are factors among them (Majumder, 2005). States from Madhya Pradesh. The Bundelkhand with better infrastructural facilities are more region of Madhya Pradesh extending between attractive for domestic and foreign private latitudes of 23° 10' 48" to 26° 20' 17" north investment and perform better in terms of and longitudes of 78° 26' 31" to 81° 40' 15" economic growth (Ghosh, 2017). Disparities east is located in the northern part of the state in socio-economic development are attributed (Fig.1). The study area comprises of 6 districts INFRASTRUCTURAL DEVELOPMENT IN BUNDELKHAND REGION 3 4 PUNJAB GEOGRAPHER VOLUME 16 OCTOBER 2020 and 40 community development blocks and population (x1); number of Automatic Teller covers an area of 41330 km² comprising 13.40 Machines (ATMs) per 10,000 population (x2); per cent of the total area of the state. The number of medical institutions per 10,000 landscape is characterized with Deccan lava population (x3); per cent of villages having structure, rugged topography, low rocky mandis/regular market facilities (x4); per cent outcrops, narrow valleys and plains. The soils of villages with tap water facilities (x5); per are a mixture of black and red-yellow, which cent of villages with power supply for is not considered very fertile. The region has a agricultural use (x6); per cent of villages high percentage of barren and uncultivable having power supply for domestic uses (x7); land. per cent of villages having internet cafes/ The total population of the study area common service centre (x8); per cent of has been 86,53,492 persons in 2011 villages connected with pucca/metalled roads accounting for 11.91 per cent of the total (x9); per cent of villages connected to national population of the state. About 77.68 per cent highway and state highway (x10); per cent of of total population is residing in 7157 villages villages having public transport facilities (x11) of the study area. The decadal growth rate and per cent of villages having communi- (2001-2011) of population is 18.47 per cent, cation facilities, like telephone and mobile compared to the state average of 20.35 per phone (x12) have been taken to quantify the cent. General literacy rate in the study area is composite scores for each of the 40 blocks. 68.11 per cent, while male-female literacy To find out the block-wise spatial rate is 77.81 per cent and 57.26 per cent, patterns of infrastructural development, the respectively. The study region is predo- composite index score has been calculated on minantly an agriculture region but due to the basis of standardized values of each uneven surface and poor soil profile it has variable calculated as: only 50.10 per cent of area under agriculture, X-x Standardized Value (i) = whereas 80.77 per cent of its rural population SD is dependent on agriculture. The lack of where, i is the standardized value of an adequate infrastructure is one of the leading indicator, X is the value of variable, x is the factors to the economic backwardness of the mean of the variable and SD is the standard region. deviation of the variable. The composite index scores are computed by dividing the Database and Methodology sum of the standardized values of all the The present study is based on indicators by the total number of the variables secondary sources of data collected from and presented in Table 1. District Census Handbooks, Socio-Economic To identify the most significant factors Caste Census, Directorate of Economics and for infrastructural development in the study Statistics, Revenue Board of Madhya Pradesh area the method of Principal Component and official websites of the government of Analysis is applied. As variables with diff- Madhya Pradesh for the year 2011. To mea- erent measurement units and disproportionate sure disparities in the level of infrastructural range fail to provide an accurate result, development, 12 indicators such as number of therefore factor analysis has been carried out commercial & co-operative banks per 10,000 for each variable to get the standardized INFRASTRUCTURAL DEVELOPMENT IN BUNDELKHAND
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