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Articles

In situ redevelopment of slums in Indian cities: Closing a rent gap?

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Received 18 Feb 2022, Accepted 08 Feb 2023, Published online: 01 Mar 2023
 

Abstract

Cities of the Global South are often unable to invest in developing urban housing. Land value-based tools for developing low-income housing, like India’s In Situ Slum Redevelopment (ISSR, part of the Pradhan Mantri Awas Yojana—Urban scheme), seek to balance welfare and economic agendas, but have not achieved expected results. ISSR’s focus on attracting private capital to redevelop India’s slums reflects a perceived rent gap on slum lands. This paper dissects this perception using a probabilistic simulation model to assess the scheme’s feasibility and profitability, integrating data on slums, real-estate markets and policy incentives. The paper proposes a Land Shape Index, identifying slum land shape as a critical—and overlooked—determinant of rent gap. Finding little to no rent gap on slum lands across big and small cities—reflected in ISSR’s low uptake—the paper argues that land value-based capital-led slum redevelopment is unlikely to gain traction and scale. These analyses provide avenues for policy introspection, practice, and lessons for housing studies in India and beyond.

Acknowledgments

The authors thank Anant Maringanti, Angshuman Das, Gautam Bhan, Gulzar Malhotra, Meenakshi Chauhan Gupta, Nishtha Vadehra, Pankaj Kapoor, Shriya Anand and several other experts for their inputs and reviews. The authors are very grateful to the editors of Housing Studies journal and the three anonymous referees for their encouragement and critiques.

Disclosure statement

The authors have no competing interest with the topic, institutions, data, methods or results of the research.

Accessing data and code

The simulation was implemented in the statistical programming language R and is easily reproducible. The data and the R Markdown report and all the associated code can be accessed from this repository: https://github.com/soorajmr/issr-simulation.

The supplementary material with this paper includes a pdf document that explores the model data, data preparation, simulation scenarios, as well as its results in greater detail.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1 TDR is an indirect instrument that allows developers to shift development rights from one site to another, or sell them to other developers, if they are not usable on the original site.

2 For an in-depth, political reading of the Baan Mankong program, see Shelby (Citation2022).

3 The Afzulpurkar (Citation1995) committee report on the ‘Programme for Rehabilitation of Slum and Hutment Dwellers in Brihan Mumbai’, that proposed the SRS model to the Government of Maharashtra in 1995 does mention that some micro (slum-level) and macro (cluster of slums) financial analyses was conducted. However, the report itself is sketchy on the details of such analyses, whether they were spatial in nature, the empirical basis for arriving at the incentives, and as it admits itself, suffered from a lack of reliable data on real-estate markets. It is also pertinent to note that the committee was attempting to come with a solution to a massive and complex problem with several variables, and yet had to be implemented using fairly simple and rigid rules in order to enable scalability and prevent large amounts of local discretion (Afzulpurkar, Citation1995).

4 State governments and cities are free to pursue slum improvement or upgrading. However, low-income urban housing interventions in India typically depend on fiscal transfers from the Central government, to which states and cities add localized support.

5 For a detailed and wonderfully crafted analysis of Haila’s development of land rent theory, see Obeng-Odoom, Franklin (Citation2021).

7 Buildable rights are called Floor Area Ratio or FAR in India, and are defined as the ratio between the total built-up area and the plot area.

Additional information

Funding

This work was conducted under the Tacit Urban Research Network (TURN) project supported by the Ford Foundation (grant number 0160-1622).

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