G eneralised anxiety disorder (GAD) is prevalent among college students in India; however, barriers like stigma, treatment accessibility and cost prevent engagement in treatment. Web-and mobile-based, or digital, mental health interventions have been proposed as a potential solution to increasing treatment access. With the ultimate goal of developing an engaging digital mental health intervention for university students in India, the current study sought to understand students' reactions to a culturally and digitally adapted evidence-based cognitive behavioural therapy (CBT) for GAD intervention. Specifically, through theatre testing and focus groups with a non-clinical sample of 15 college students in India, the present study examined initial usability, acceptability and feasibility of the "Mana Maali Digital Anxiety Program." Secondary objectives comprised identifying students' perceived barriers to using the program and eliciting recommendations. Results indicated high usability, with the average usability rating ranking in the top 10% of general usability scores. Participants offered actionable changes to improve usability and perceived acceptability among peers struggling with mental health issues. Findings highlight the benefits of offering digital resources that circumvent barriers associated with accessing traditional services. Results build on existing evidence that digital interventions can be a viable means of delivering mental healthcare to large, defined populations.

A wide variety of choice behavior inconsistent with preference maximization can be explained by Manzini and Mariotti's Rational Shortlist Methods. Choices are made by sequentially applying a pair of asymmetric binary relations (rationales) to eliminate inferior alternatives. Manzini and Mariotti's axiomatic treatment elegantly describes which behavior can be explained by this model. However, it leaves unanswered what can be inferred, from observed behavior, about the underlying rationales. Establishing this connection is fundamental not only for applied and empirical work but also for meaningful welfare analysis. Our results tightly characterize the surprisingly rich relationship between behavior and the underlying rationales. (JEL D11, D12, D83, M37)

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Motivated by the basic adage that man does not live by bread alone, we offer a theory of historical economic growth and population dynamics where human beings need food to survive, but enjoy other things, too. Our model imposes a Malthusian constraint on food, but introduces a second good to the analysis that affects living standards without affecting population growth. We show that technological change does a good job explaining historical consumption patterns and population dynamics, including the Neolithic Revolution, the Industrial Revolution, and the Great Divergence. Our theory stands in contrast to models that assume a single composite good and a Malthusian constraint. These models generate negligible growth prior to the Industrial Revolution. However, recent revisions to historical data show that historical living standards—though obviously much lower than today's—varied over time and space much more than previously thought. These revisions include updates to Maddison's dataset, which served as the basis for many papers taking long‐run stagnation as a point of departure. This new evidence suggests that the assumption of long‐run stagnation is problematic. Our model shows that when we give theoretical accounting of these new observations the Industrial Revolution is much less puzzling. (JEL B10, I31, J1, N1, O30)

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