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Theoretical Economics Letters
This paper investigates the geographic concentration of knowledge and technology-intensive (KTI) industries, covering 0.43 million establishments across various districts of rural and urban areas in India. Using the spatially weighted Ellison-Glaeser index, cartogram and choropleth map results show that few KTI industries are highly geographically concentrated in urban and rural areas, specific to certain districts and a few Indian states. Within highly employable states of India, workers are employed in only a particular location of a few districts. Also, we differentiate between urban and rural concentrated and urban and rural dispersed districts within highly employable states. In addition, results validate the extent of the geographical concentration of KTI industries in rural and urban areas of highly employable Indian states. Further, results exhibit that industries spatially concentrate in only a few locations across specific districts in India, indicating natural advantages and other economic forces are pretty strong in certain areas. Besides, results suggest that the demand-based networks and push-and-pull supply chains are well established in a specific location of a few districts, incentivizing other firms to locate their business, which creates a spatial spillover effect and benefits all economic agents. Empirical results suggest that policymakers in India could unleash the resource potential of spatially concentrated districts by implementing a location-based policy and considering multi-level governance and informal and formal institutions, which could further boost regional economic growth.
Spatial Industrial Diversification in India: An Analysis of Unorganised Manufacturing Enterprises
Assam Economic Review, Vol. 10, 2017
Industrial diversification continues to be an important policy goal in regional planning, because of its direct positive effect on economic growth and stability. A large number of studies in India, carried out at different geographical scales namely, national level, states, and districts show that the industrial structure of India and its regions and states is characterised by high degree of specialisation rather than diversification. However, these studies are related to the organised (or registered) manufacturing sector only. Despite the fact that the unorganised manufacturing sector, also known as the informal manufacturing sector, is vast and diverse, and occupies an important role in India’s industrial sector, very few studies have attempted any systematic analysis of the structure of the unorganised enterprises, both at the national and regional levels. Therefore this paper aims to examine the industrial structure and the extent of diversification of unorganised manufacturing enterprises across the Indian states. Using data from the 51st (1994–95), 62nd (2005–06), and 67th (2010–11) “quinquennial” rounds the National Sample Survey on unorganised manufacturing enterprises, we have analysed the industrial structure of the states at two-digit industry level by employing location quotient technique, whereas the diversification coefficient has been employed to examine the degree of diversification of unorganised manufacturing enterprises in different states. We have also examined the relationship between diversification of unorganised manufacturing enterprises and level of industrial development across the states.
Spatial development of organized manufacturing industries across Indian States
The paper examines the nature and pattern of development of the Indian organised manufacturing industries across Indian states using the Annual Survey of Industries (ASI) plant level data. Four different indices of industrial concentration have been used to estimate the degree of agglomeration of industries. It has been observed that states with a large industrial base are also the hub of some of the highly polluting industries. The degree of industrial agglomeration has been observed to be higher in case of polluting industries as opposed to non-polluting industries in the year 2013-14. The degree of agglomeration economies of an industry has been observed to be affected by the spill over effect from the adjacent regions. While examining the pattern of spatial concentration of industries over time, the paper concludes that during the period of the analysis 2000-01 to 2013-14, the polluting industries have shown some dispersion both across states (captured by the LQ index) as well as in terms of plant level concentration within-in the same industry.
Location Pattern of Unorganised Manufacturing Industries in India: A District-level View
Margin: The Journal of Applied Economic Research, 10(2), 2016
This paper examines the location pattern of unorganised manufacturing enterprises across districts in India. Using a unique data-set of 435 districts spread across 25 states, drawn from the Enterprise Survey data of NSS 1994-95 and 2005-06 ‘thick’ rounds, we find that unorganised manufacturing enterprises are concentrated in a few leading districts, mostly in the metropolitan areas; but their share has declined in the post-reform (post-1991) period, and some new metropolises and suburban districts have emerged as new industrial destinations. The spatial concentration in the distribution of the unorganised manufacturing enterprises across districts has marginally declined – both at the aggregated and disaggregated industry level – in the post-reform period. Our econometric analysis shows that the level of economic development, infrastructure facilities, labour productivity, capital productivity, population size, population density, availability and stock of raw materials, presence and size of organised industries, and urbanisation have significant positive effects on the location of unorganised manufacturing enterprises; while economic diversity has a strong negative impact. The specificity of our study is that we use district-level data, which allows us to provide a relatively comprehensive view of the location pattern of unorganised manufacturing enterprises in India.
Determinants of entrepreneurship. Is it all about the individual or the region?
It is well established at whatever spatial level studied that economic actors exhibit a strong tendency to cluster. Despite this fact many explanations to entrepreneurship only considers the personal characteristics of entrepreneurs. This is certainly not a satisfactory state-of-the-art. It is obvious that the influence of spatial factors must be considered carefully. In this paper we illustrate empirically that variations in the rate of entrepreneurship are explained not only in terms of characteristics of entrepreneurs, such as education, sector of employment, occupation, experience and income but also by the characteristics of i) the localities where they worked before they became entrepreneurs, ii) the localities where they currently started their firm and iii) the regions where these localities are situated. The characteristics of localities include size, population density, firm density and type of locality (metropolitan, urban, semi-rural or rural). The estimations use a multi-level approach to decipher the how much of the variance that can be explained by the different levels (individual, locality and region). The data used in this study is micro-level data for Sweden provided by Statistics Sweden.
REGIONAL CONCENTRATION OF ENTREPRENEURIAL ACTIVITIES
Frontiers of Entrepreneurship Research, 2010
Empirical evidence indicates that entrepreneurial activities tend to concentrate geographically. Strategic complementarities, knowledge spillovers and network externalities are regarded as the principal sources of such phenomena. Although conspicuous examples point at the presence of positive feedback mechanisms, agglomerations also occur in the absence of these features and in areas of considerably homogeneous economic potential. We build an evolutionary game theoretic model to investigate the conditions under which regions may evolve different rates of entrepreneurship assuming that (i) regions are economically similar, (ii) there is migration between regions, and (iii) individuals are predisposed to imitate others who are economically more successful.
Entrepreneurship and the spatial context: evidence on the location of firm births in Greece
Review of Urban & Regional …, 2008
This paper analyses the effect of the spatial context upon entrepreneurship in Greek regions. Cross-sectional data referring to 4151 births at NUTS III level (prefecture) are used for firm births in four industries, namely manufacturing, commerce, services, and tourism. The formulated hypotheses are in regard to the effect of agglomeration economies, defined here as urbanization and localization economies, and other factors that typically affect the location of start-ups. Results indicate that strong localization economies exist (both of the Marshallian and the Jacobian type) while, in addition, the spatial context of entrepreneurship affects different industries in different ways.
South Asian Journal of Management, 21(4), 2014
The objective of this study is to examine the inter–state variation of unorganised manufacturing in India. Analysis has been carried out using unit–level data at three–digit industry level for 25 major Indian states for the period 1994–95 to 2005–06. The findings suggest that unorganised manufacturing continued to be concentrated in a few advanced states, while there is barely any improvement in the condition of the backward states. The high technology intensive industries are highly concentrated, whereas concentration is low for the resource–based low technology intensive industries. Spatial concentration has declined in the post–reform period for the overall unorganised manufacturing sector as well as for about two–third of the 55 three–digit industry groups. The findings raise a number of policy issues for regional industrial development in India. The paper emphasises the need for special policy attention to improvement of socio–economic infrastructure and investment climate in the backward states to enhance industrial development through attracting new investments.
Estimating Urban Agglomeration Economies for India: A New Economic Geography Perspective
Theoretical and Empirical Researches in Urban Management, 2012
The main objective of this paper is to provide answer to an important question: Are Indian firms or industries in urban areas operating under decreasing returns to scale or increasing returns to scale? Scale economies are one of the main assumptions of new economic geography models that posit the formation of agglomeration economies. For this purpose, we use Kanemoto et al. (1996) model for estimation of aggregate production function and to derive the nature and magnitude of agglomeration economies on firm level production in organized manufacturing sector. Using firm level data in 2004-05 from the Annual Survey of Industry, we find that urban firms in Indian industry operate under decreasing returns to scale. Therefore, in case of India, we find the evidence that urbanization is associated with negative external economies of scale that do not enhance productivity and do not drive urban growth and development. In addition, we provide explanation behind this phenomenon and policy opt...