MAHA REHMAN

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Research linked at https://maharehman.github.io/research/;

Policy Writing at https://maharehman.github.io/policy/;

Select media at https://maharehman.github.io/media/;

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I study how firms adapt to economic disruptions and crises in environments shaped by weak institutions, financial frictions, and infrastructural constraints. My research investigates the mechanisms through which shocks reshape resource allocation, behaviour, and productivity in developing economies. I am currently pursuing my PhD at Cornell University. 

Across two interrelated streams, I examine: (i) how shock-induced reallocations generate persistent inefficiencies and misallocation at the firm level, and (ii) how behavioural frictions and network dynamics shape collective action during public health and environmental crises. These projects are unified by a focus on how institutional constraints condition responses that result in inefficiencies.

My recent work shows that when firms anticipate limited government support, they rationally over-adapt by substituting public goods through costly self-provisioning. This behaviour ultimately undermines long-term productivity and resilience. I formalise this mechanism in a model of adaptive misallocation, where policy uncertainty drives over-investment in short-term defensive strategies, distorting capital allocation and entrenching inefficiency.

My threshold adoption framework, first tested in Lahore’s 2021 mask RCT, models how lowering adoption costs and increasing salience at central nodes can trigger compliance cascades in dense networks. I extend this framework to vaccines and other crises. Drafts, protocols, and questionnaires are time-stamped and archived on OSF. 

Together, these frameworks anchor a unified research agenda on thresholds, adaptation, and misallocation across health, disaster, and digital systems.

Methodologically, I combine experimental and quasi-experimental designs with tools from empirical industrial organisation and applied theory to unpack adjustments, identify misaligned incentives, and test behavioural models in dense urban contexts. This empirical foundation informs structural modeling and policy design, with the aim of generating scalable reforms that improve industrial productivity, strengthen public goods provision, and enhance state capacity—particularly in South Asia.

You can explore my research, policy writing, and teaching here—or connect with me via Twitter, Linkedin, Bluesky or Google Scholar.