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<p>This paper examines whether spatial variation across states in the severity of corruption, as reported by manufacturing firms, is associated with the decisions of India’s organised manufacturing factories to adopt greener production measures by investing in pollution control equipment. We collate data from two sources: the Indian government’s principal source of industrial statistics, namely the Annual Survey of Industries 2022-23, for factory-level information, and the World Bank Enterprise Survey for India 2022, to construct a composite index that measures the state-wise variation in corruption based on indicators of firms’ experiences and perceptions of corruption as an obstacle using Principal Component Analysis. We model firms’ decision to invest in pollution control equipment as a two-step process: first, deciding whether to invest, and second, determining the extent of expenditure if they do. We correct the selection bias using the Heckman Selection model. Our results provide evidence supporting the hypothesis that factories located in states with higher levels of corruption tend to spend less on pollution control equipment in both high-polluting and less-polluting industries. Among firm-specific factors, we find that firm size, ISO 14000 series certification, and R&amp;D activity drive both the decision and intensity of pollution-control equipment expenditure. Exporting increases the likelihood of spending on pollution control equipment, while other production subsidies lead to an increased level of expenditure on such equipment in polluting industries. The paper contributes to the expanding body of research on institutional quality and the environmental sustainability of production processes, viewed through a regional perspective in a developing economy with a strong manufacturing sector.</p>

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Does corruption undermine green manufacturing? Regional evidence from India

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  • 出版模式：

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  • 发表日期：

    2026年1月23日

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  • Vaishnavi Vaishnavi,
  • Gopal Krishna Roy

摘要

This paper examines whether spatial variation across states in the severity of corruption, as reported by manufacturing firms, is associated with the decisions of India’s organised manufacturing factories to adopt greener production measures by investing in pollution control equipment. We collate data from two sources: the Indian government’s principal source of industrial statistics, namely the Annual Survey of Industries 2022-23, for factory-level information, and the World Bank Enterprise Survey for India 2022, to construct a composite index that measures the state-wise variation in corruption based on indicators of firms’ experiences and perceptions of corruption as an obstacle using Principal Component Analysis. We model firms’ decision to invest in pollution control equipment as a two-step process: first, deciding whether to invest, and second, determining the extent of expenditure if they do. We correct the selection bias using the Heckman Selection model. Our results provide evidence supporting the hypothesis that factories located in states with higher levels of corruption tend to spend less on pollution control equipment in both high-polluting and less-polluting industries. Among firm-specific factors, we find that firm size, ISO 14000 series certification, and R&D activity drive both the decision and intensity of pollution-control equipment expenditure. Exporting increases the likelihood of spending on pollution control equipment, while other production subsidies lead to an increased level of expenditure on such equipment in polluting industries. The paper contributes to the expanding body of research on institutional quality and the environmental sustainability of production processes, viewed through a regional perspective in a developing economy with a strong manufacturing sector.