Bio
I am a Postdoctoral Scholar at the O’Donnell Center for Behavioral Economics at UC Berkeley. I will join the IIES as an Assistant Professor in 2026.
My research examines how governments can optimally provide assistance and social protection to help the most vulnerable meet their basic needs, focusing on the role of psychological factors—such as mental health and behavioural biases—in shaping behaviour and policy effectiveness.
I have a BA in Mathematics from the University of Cambridge and a PhD in Economics from the LSE. Before my PhD, I worked as an Economist at The Behaviouralist, a behavioural science research consultancy.
📄 CV
📧 canishknaik@gmail.com
Pronouns: he/him
Working Papers
(with
Daniel Reck)
October 2025
Abstract (click to expand)
: Inconsistent choice undermines the revealed preference foundations of traditional welfare economics, leading to controversy about policymaking in the presence of behavioral frictions. We model an optimal policy problem wherein a benevolent planner is uncertain which behavioral frame reveals normative preferences. We axiomatize welfarist criteria that are similar to social welfare functions, with intrapersonal frames replacing interpersonal types. Under paternalistic ambiguity aversion or paternalistic risk aversion, the planner values policies that are robust to normative uncertainty. We apply these welfarist criteria and robustness concepts in examples, including default options, manipulation of reference points, present focus, corrective taxation for internalities, and nudging.
October 2025
Abstract (click to expand)
: People living with mental disorders are at a higher risk of needing income-support programs but face greater difficulty overcoming barriers to access. This paper investigates whether social assistance effectively reaches people with poor mental health. I measure mental health and social assistance take-up using Dutch administrative data and develop a theoretical framework to show how take-up responses can identify the marginal value of benefits (need) and the cost of barriers. These are key components for evaluating targeting effectiveness. I find that a policy increasing barriers disproportionately screens-out those with poor mental health, indicating a 64% higher cost of these barriers. Despite their higher cost, people with poor mental health have the same average take-up levels as those with good mental health, conditional on eligibility, which suggests greater need. To assess this, I show that individuals with poor mental health are more responsive to plausibly exogenous variation in benefits than those with good mental health, demonstrating that their need is twice as high. These estimates imply that people with poor mental health are inefficiently excluded from low-income welfare assistance by barriers. Consequently, reducing barriers to take-up would be twice as effective as increasing benefits.
A Welfare Analysis of Public Housing Allocation Mechanisms
(with
Neil Thakral)
November 2022 (Please email for draft)
Abstract (click to expand)
: When allocating scarce resources such as public housing units to applicants in a waiting list, welfare depends on applicants’ preferences (match values and waiting costs) as well as their choices (which may involve errors). To trade off between allowing agents to wait for better matches and prioritizing agents with high waiting costs, allocation mechanisms impose restrictions on choices. Public housing allocation mechanisms in the UK restrict the set of available options that an applicant may accept, while mechanisms in the US restrict the number of times an applicant may reject. We examine how these different ways of restricting choices influence welfare, both theoretically and empirically. Using data on preferences for public housing in the US and the UK, we show how welfare compares under rationality and explore the sensitivity of the mechanisms to choice-error.
Work in Progress
The Social Determinants of Mental Health
(with
Jon Kolstad
, Will Parker
, Johannes Spinnewijn)
Abstract (click to expand)
: What drives the stark inequalities in mental health across socio-economic groups? Using administrative data from the population of the Netherlands, this paper uncovers a striking non-linear gradient in mental health by income: mental health sharply deteriorates below an income threshold near the poverty line but shows little association with income above this level. We find that the socio-economic gradients are strongest for working-age individuals, are not driven by access to health-care and are mostly explained by work status. Major adverse events such as physical health shocks and job losses contribute little to the overall gradient. Rather, the evidence suggests social drift as the primary mechanism: those with poor mental health sort into lower incomes over the lifecycle. These results highlight the economic vulnerability of people with poor mental health and the importance of a broad social safety net.
Rebuilding Lives, not just Homes: Addressing Trauma in Disaster Recovery
(with
Amen Jalal
, Pol Simpson)
Abstract (click to expand)
: Disaster recovery often focuses on rebuilding physical infrastructure, overlooking the mental health impact of traumatic events like floods. In Pakistan, where flooding in 2022 submerged a third of the country and lasted up to 8 months, women exposed to a more intense flood shock were 11 pp more likely to have severe psychological distress 2 years later. Ignoring mental health in reconstruction may prolong the socio-economic impact of disasters by limiting individuals’ ability to work, plan, and recover. This project explores complementarities between mental health support and the standard infrastructure-focused approach by randomizing a trauma-based mental health intervention and leveraging natural variation in access to a housing reconstruction program in a 2x2 design. Our findings aim to measure the non-economic losses and damages of climate catastrophes, and inform more holistic disaster recovery policies that address both physical and psychological needs.
Teaching
LSE
School of Public Policy (Graduate)
Public Economics for Public Policy (2022 – 2024)
Teaching evaluations: 2022 (4.8/5)| 2023 (5/5)| 2024 (4.7/5)
Class Teacher Award: 2023, 2024 (highly commended)
Excellence in Education Award: 2022, 2023, 2024
Economics Department (Undergraduate)
First-year Micro- and Macroeconomics (2021 – 2023)
Teaching evaluations: 2021 (4.5/5)| 2022 (4.7/5)| 2023 (4.6/5)
Economics Department (Graduate)
Intro Probability and Statistics (Math Camp) (2022 – 2024)
No teaching evalutions
Theme: Minimal by orderedlist
