Bio
In 2025-26, I will be a Postdoctoral Scholar at the O’Donnell Center for Behavioral Economics at UC Berkeley, before joining 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
January 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.
(with
Daniel Reck)
January 2025
Abstract (click to expand)
: We consider the optimal policy problem of a benevolent planner, who is uncertain about an individual’s true preferences because of inconsistencies in revealed preferences across behavioral frames. We adapt theories of expected utility maximization and ambiguity aversion to characterize the planner’s objective, which results in welfarist criteria similar to social welfare functions, with intrapersonal frames replacing interpersonal types. Under paternalistic risk aversion or ambiguity aversion, a policy is less desirable to the planner, holding all else fixed, when it leads to more disagreement about welfare from revealed preferences. We map some examples of behavioral models into our framework and describe how this notion of robustness plays out in applied settings.
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: Integrating Mental Health and Economic Recovery in Climate Disaster Response
(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 under water and lasted up to 8 months, over one in five flood affectees report severe psychological distress 2 years later. When asked about the long-term consequences of flooding, worsened mental and physical health is the second most commonly reported impact, following housing damage (Jalal and Simpson, 2024). Ignoring mental health in reconstruction may prolong the socio-economic impact of disasters by limiting individuals' ability to work, plan, and recover. This project studies the interaction between physical and psychological recovery in flood-affected communities, by fielding a locally developed mental health literacy initiative, cross-randomised with a housing reconstruction program. This 2x2 design allows us to compare the benefits of mental health support against the standard infrastructure-focused approach, and explore complementarities. 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
