Washed away: industrial capital, labor, and floods

Abstract This study quantifies the dynamic impacts of floods on industrial capital and labor in India using a novel dataset combining geocoded flood events with firm facility-level data from 2000 to 2021. Employing a stacked difference-in-differences approach with carefully matched controls, we uncover persistent negative effects of floods on firms’ assets and employment, with striking heterogeneity across sectors and regions. In the post-flood period, we estimate declines from mean values in total assets of 46.1% (16.68 billion INR ≈ 225 million USD), employment of 49.0% (8.20 thousand workers), and the wage bill of 74.5% (5.52 billion INR ≈ 74 million USD). The sectoral impacts are highly varied: the information technology and communication, manufacturing, and utilities sectors experience significant declines in assets, while the financial services sector exhibits growth. Mapping the spatial distribution of flood events and industrial facilities reveals pronounced regional heterogeneity in flood exposure and economic impacts. Adding nuance to the empirical investigation of the ‘creative destruction’ hypothesis, we find limited evidence of systematic capital reallocation toward better-performing sectors, suggesting instead that floods generate sector-specific impacts with varying recovery patterns. These findings challenge assumptions of rapid post-disaster equilibration and have important implications for policymakers and firm managers in developing sector-specific strategies to mitigate the adverse impacts of floods in an increasingly climate-uncertain world.

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Publication Details

Journal
Environmental Research Letters
Published
2024-12-11
DOI
https://doi.org/10.1088/1748-9326/ad9d5c
Primary Topic
Flood Risk Assessment and Management
Type
article
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article

Washed away: industrial capital, labor, and floods

Anish Sugathan, Deepak Malghan, Arpit Shah
Environmental Research Letters
Flood Risk Assessment and Management
article

Washed away: industrial capital, labor, and floods

Anish Sugathan, Deepak Malghan, Arpit Shah
article en

Abstract

Abstract This study quantifies the dynamic impacts of floods on industrial capital and labor in India using a novel dataset combining geocoded flood events with firm facility-level data from 2000 to 2021. Employing a stacked difference-in-differences approach with carefully matched controls, we uncover persistent negative effects of floods on firms’ assets and employment, with striking heterogeneity across sectors and regions. In the post-flood period, we estimate declines from mean values in total assets of 46.1% (16.68 billion INR ≈ 225 million USD), employment of 49.0% (8.20 thousand workers), and the wage bill of 74.5% (5.52 billion INR ≈ 74 million USD). The sectoral impacts are highly varied: the information technology and communication, manufacturing, and utilities sectors experience significant declines in assets, while the financial services sector exhibits growth. Mapping the spatial distribution of flood events and industrial facilities reveals pronounced regional heterogeneity in flood exposure and economic impacts. Adding nuance to the empirical investigation of the ‘creative destruction’ hypothesis, we find limited evidence of systematic capital reallocation toward better-performing sectors, suggesting instead that floods generate sector-specific impacts with varying recovery patterns. These findings challenge assumptions of rapid post-disaster equilibration and have important implications for policymakers and firm managers in developing sector-specific strategies to mitigate the adverse impacts of floods in an increasingly climate-uncertain world.

Environmental Research LettersVol. 20(2)
Indian Institute of Management Ahmedabad (IN), Stockholm Environment Institute (TH), Asia Centre (TH), Indian Institute of Management Bangalore (IN)
Openalex Percentile: Top 80%
Flood Risk Assessment and Management
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Washed away: industrial capital, labor, and floods — Anish Sugathan, Deepak Malghan, et al. · Environmental Research Letters (2024) | TGRS Research Map | TGRS