India’s Ease of Living Index Report 2018 – A data driven approach

International Journal of Research and Scientific Innovation (IJRSI) | Volume VIII, Issue III, March 2021 | ISSN 2321–2705

Influence India’s Ease of Living Index Report 2018 – A data driven approach

Deva Dutta Dubey,
Associate Professor, RICS School of Built Environment, Amity University Maharashtra

Abstract : Government of India, Ministry of Housing and Urban Affairs released the first ever Ease of Living Index Report 2018. The report ranked 111 cities in India on the basis of multiple facets of urban living. The underlying data for each of the attributes was also provided. The ranking was based on a-priori weightages to different dimensions of the analysis. This paper attempts to refine the ranking and applies the technique of Partial Least Squares Path Modeling, a technique which may be an alternative for such analyses. The results show that the regression coefficients estimated through the analysis show some variation compared to the weights assigned in the report. Results prima facie indicate that emphasis of different facets of urban living is different. It is also different for different city sizes when the cities were considered as large and small. In addition to the PLSPM Model, additional models have been prepared including neural network models. The neural network and Random Forest models appear acceptable based on accuracy of fit of the models, as represented by Pseudo R2. The report for 2019 is yet to be released.
This paper is an academic paper having relevance for research in urban planning with its boundaries touching upon economics and land use. With passage of time and with evolution of the concept of ease of living and forming an index, we may witness different variables coming into play and having different loadings on the outcome of ranking of cities.
It could be useful for students of Real Estate Programs in the country and abroad as also for those pursuing Urban Planning and related academic disciplines. Familiarity with this concept and its variation will help them become better data science professionals as they seek gainful employment in various enterprises associated with urban planning and real estate development.

Keywords – Ease of Living Index, Governance, Cities, Urbanisation, PLS-PM, Neural Networks

I. INTRODUCTION

Government of India, Ministry of Housing and Urban Affairs (MOHUA) has released the Ease of Living Index (EOLI) Report 2018 in India. The report covers various facets of city and urban living and attempts to rank cities. The report attempts to ascertain and quantify the impact of chosen variables on the well-being of a region and its inhabitants. The index was first launched in 2017 and has been subject to refinement based on feedback from stakeholders. The measure looks at a broader view of factors encompassing several aspects of urban living.
It appears that the measure of EOLI, properly defined and measured, may be a reasonable indicator arising out of such an effort. An appropriate focus of the EOLI may be a city unit / urban agglomeration. This is particularly important considering that more and more people are shifting to cities in search of better economic and social opportunities and that poses a new set of challenges and aspirations for cities to cater to the requirements. The challenges appear in the domains of institutional, social and economic infrastructure not to mention the physical infrastructure. As per estimates of different agencies of the government, in case of India, the urban population is expected to reach high level by 2050.
Considering scarcity of resources and ever pressing need to address human needs and wants, there is an urgent need to manage the resources well for sustenance, well-being and eventual prosperity, as the administrative systems grapple with the constantly changing aspirations of the populace. So far, the EOLI 2018 has been released and the same is analysed in this paper together with some alternative data driven analyses.

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