Abstract
This chapter looks at the contribution of the growth of towns, particularly small and medium towns, towards the urbanisation process of India. However, instead of just looking at the broad Indian macro picture, we undertake a disaggregated analysis of urbanisation of the Indian states. Our analysis delivers a more accurate approach of the relation between the demographic change happening in small and medium towns and the economic growth at the scale of the Indian states. For the purpose of our analysis, we have considered the 15 largest states in India which represent around 90 % of India’s population and we have further classified those states into rich, middle and poor groups or clubs of states, based on their per capita income level. In our study we examine the disaggregated urbanisation process in India using the Indiapolis and Census databases. Our analysis shows that the extent (number) and speed (growth) of urbanisation is higher in the richer states, which also have a higher per capita National State Domestic Product (NSDP) growth over the analysed period as compared to the states from the middle and poor groups. However, there is a fair amount of variation in the growth of towns across all categories of states. This is underlined in a second part using the UA data set. It enables a better understanding of the link between the larger agglomerations’ dynamics and the growth of smaller towns. Then, in a third part, a preliminary analysis of the sectoral growth rates of income, employment, and productivity by city-size classes and states, notably for the industrial sector, indicates that small and medium towns can play an important role in the growth of manufacturing activities.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
See Chaudhuri et al. (2012) Club Convergence Analysis: Unlike the Solow growth model which predicts that countries with low levels of income will grow faster than countries with higher income levels and will eventually catch up; the club convergence analysis claims that countries may converge in groups to different steady-state levels depending on the initial levels of income with which they start off. Thus the distribution of income of countries may be bimodal or multimodal instead of unimodal, each depicting a cluster of countries with different steady-state levels of income. In our study, we have used a non-parametric approach of GUIDE to classify the Indian states into various income clubs.
- 2.
Even though the Census of India and the Planning Commission carry out this exercise, we have done it for 15 major states with ‘unchanged frontiers’ after the break-up of some of them into smaller states to preserve the elements of comparability that we are interested in. All differences between Planning Commission and Census figures and ours are because of these boundary differences. We believe this exercise enables us to highlight long terms trends for the major states.
- 3.
Figures for the different categories of towns are not reported in this chapter.
- 4.
Large UA: 100,000 and above, medium UA: 20,000–100,000, small UA: 10,000–20,000.
- 5.
Note on Tables 4.3 and 4.4 (see also note on the Geopolis database at the end of this chapter): We use Geopolis-Indiapolis data where we get population data for UAs for each state. We classify UAs as large, medium and small based upon the population number (similar to what we did in case of towns). Large UA: 100,000 and above, medium UA: 20,000–99,999, small UA: 10,000–19,999. In Table 4.2 we classified towns as large town: 100,000 and above, medium town: 20,000–99,999 and small town: less than 5000 to 19,999. The above data set has population figures for UAs. So we can classify UAs based on UA population data (large, medium and small). This data set also has population data on towns under each UA. Thus this data set enables us to identify towns under UAs along with the town’s population and, based on our classification of towns, Table 4.4 can be created.
- 6.
All the comments here are subject to the caveat that there are some exceptions in each group of states. We use the Geopolis data to calculate the numbers. Geopolis provides population data for towns and villages under Urban Agglomeration across states. Using the population data, we classify Urban Agglomerations and towns into large, medium and small and then count the number of large, medium, small towns and villages across large, medium and small Urban Agglomerations. We use those counts to compute the growth between 1991 and 2001. This exercise would give us an idea of towns across categories and would give a sense on the speed of transition. Moreover, we wanted to see whether the growth of medium and small towns is dependent on whether such towns are situated in large, medium or small UAs.
- 7.
Again, this has to be linked with the limited number of local units (villages) reclassified as towns (mainly as Census Towns) from Census to Census.
- 8.
Whether the firm is urban or rural is indicated in the ASI data.
- 9.
Eric Denis pointed out to us that this increase in the number of new towns can be very much a state-driven factor rather than an indicator of social or economic changes.
- 10.
Employment here includes all employment except agricultural laborers and household industry workers. This correlation uses Census data.
References
Chaudhuri, B., Majumdar, M., Marimoutou, V., Teachout, M. (2012). A convergence club analysis of income and productivity disparities in Indian states, 1965–2007 (NOPOOR FP7). Paper presented at the 2012 Boston Conference on Income and Wealth.
Calì, M. (2009). Urbanization, inequality and economic growth: Evidence from Indian states. Washington, DC: World Bank. © World Bank. https://openknowledge.worldbank.org/handle/10986/9248.
Lall, S., Shalizi, Z., & Deichmann, U. (2004). Agglomeration economies and productivity in Indian industry. Journal of Development Economics, 73, 643–673.
Mitra, A. (2011). Urbanization in India: Evidence on agglomeration economies (No. id: 4394).
Mitra, A., & Mehta, B. (2011). Cities as the engine of growth: Evidence from India. Journal of Urban Planning and Development, 137(2), 171–183.
Mills, E. S., & Becker, C. M. (1986). Studies in Indian urban development. Oxford: Oxford University Press, World Bank Research Publication.
Nijman, J. (2012). India’s urban challenge. Eurasian Geography and Economics, 53(1), 720.
Planning Commission. (2011). Mid term appraisal of the eleventh five-year plan. New Delhi: Oxford University Press.
Pradhan, K. C. (2017). Unacknowledged urbanisation: The new census towns in India. In E. Denis & M.-H. Zérah (Eds.), Subaltern urbanisation in India (pp. 39–66). New Delhi: Springer.
Swerts, E. (2017). The substantial share of small towns in India’s system of cities. In E. Denis & M.-H. Zérah (Eds.), Subaltern urbanisation in India (pp. 67–89). New Delhi: Springer.
Tripathi, S. (2013). Do large agglomerations lead to economic growth? Evidence from urban India. Review of Urban & Regional Development Studies, 25(3), 176–200.
Tolley, G. S. (1987). Urbanization and economic development. The economics of urbanization and urban policies in developing countries. Washington, DC: The World Bank.
Acknowledgments
In different phases, the research for this project has been partially funded by the Centre de Sciences Humaines (UMR CNRS 3330-UMIFRE 20, New Delhi), the ANR Suburbin project and the European Union NOPOOR project with grant agreement number 290752. We are grateful to Eric Denis and Marie-Hélène Zérah for their encouraging, rigorous and extremely patient editing, and to Partha Mukhopadhyay, Kanhu Pradhan, and S. Chandrashekhar for advice at various stages of the chapter. We remain solely responsible for any errors.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer India
About this chapter
Cite this chapter
Chaudhuri, B., Chatterjee, B., Mazumdar, M., Karim, S. (2017). Income Ranking of Indian States and Their Pattern of Urbanisation. In: Denis, E., Zérah, MH. (eds) Subaltern Urbanisation in India. Exploring Urban Change in South Asia. Springer, New Delhi. https://doi.org/10.1007/978-81-322-3616-0_4
Download citation
DOI: https://doi.org/10.1007/978-81-322-3616-0_4
Published:
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-3614-6
Online ISBN: 978-81-322-3616-0
eBook Packages: Social SciencesSocial Sciences (R0)