Abstract

Using a transaction costs approach, this paper attempts to understand the allocation of medical oxygen during India’s second wave. In this background, it argues for transparency in allocative decision making of health related commodities. Through process tracing methodology, it focuses on the case of the oxygen crisis in Delhi at a time when different governments within India’s federal set-up accused each other of mismanagement of this commodity. The sequence of events in the case are traced to understand the grounds of allocative decisions during this emergency. Understanding the issue of allocation of medical resources becomes important as matters of life and death are often policitized. In this case, it appears that certain questionable decisions were made by both the Central government and the state government at the peak of the country’s second wave. However, the lack of availability of good quality data even hindered the judicial committee from reaching a conclusive opinion. As a result, this paper recommends the usage of Information Communication Technology tools for sharing health related information in real time. With ICT tools, the costs of exchanges made between Central and State governments could be lowered, which could in turn result in fairer or more optimal decisions. This paper argues that within India’s federal structure, if information costs are too high, factors other than efficiency and fairness can affect allocation of resources. It concludes by recommending the creation of centralized health supply data exchange can help increase allocative efficiencies. This study uses a process tracing method to answer its research question. Process tracing refers to an in-depth empirical analysis of causal processes in a real case. Through a standardized process of data acquisition and transmission with ICT tools, transaction costs made in exchanges between central and state governments could be lowered. By automating collection and transmission processes through tamper-proof devices, the integrity of the local level data will be maintained, and transaction costs will be lowered further. As a consequence, economic efficiency and fairness would underpin the allocation of the critical medical commodity.

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