"Competing Causal Interpretations: An Experimental Study", joint with Sandro Ambuehl (2024)

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Good decisions require understanding the causal impact of actions on outcomes. Yet, data is often correlational and could stem from multiple causal mechanisms with divergent implications.
Our experiments comprehensively characterize choice under competing causal interpretations.
Choice features substantial heterogeneity that primarily reflects three types: following misspecified interpretations that make attractive promises, choosing cautiously, and assessing the fit between theory and data. We characterize the properties of ill-fitting interpretations that subjects struggle to recognize. Preferences for more complex models are twice as common as preferences consistent with Occam’s razor. Implications extend to the literatures on Causal Narratives and Model Persuasion.

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"Fiscal Rules and Market Discipline", joint with Ethan Ilzetzki (2023)

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Fiscal rules have proliferated as a way to limit public debt. Rules intend to impose fiscal discipline on  governments that might be otherwise present-biased. However, lenders also discipline government borrowing through a market mechanism, with excessive debt penalized with higher interest rates. In this paper, we study the interaction between fiscal rules and market discipline in limiting government borrowing. We do so in a sovereign borrowing model with asymmetric information about governments' propensity to over-borrow and default. Governments may signal their fiscal rectitude by showing fiscal restraint and this can lead not only to over-borrowing as in traditional models, but also to under-borrowing, as governments attempt to signal their fiscal responsibility. In addition to its traditional role of restraining present-biased governments, fiscal rules also make signalling more difficult and may have the perverse effect of forcing prudent governments to save even more excessively than otherwise or alternatively hamper their ability to signal their rectitude entirely. Fiscal rules restrain impatient governments but penalize prudent governments. An optimal fiscal rule balances these trade-offs and will be binding at times, but will never be so tight as to naively push governments to ``do the right thing''.

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“Subjective Causality in Choice”, joint with Andrew Ellis (2022)

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When making a decision based on observational data, a person's choice depends on her beliefs about which correlations reflect causality and which do not. We model an agent who predicts the outcome of each available action from observational data using a subjective causal model represented by a directed acyclic graph (DAG). An analyst can identify the agent's DAG from her random choice rule. Her choices reveal the chains of causal reasoning that she undertakes and the confounding variables she adjusts for, and these objects pin down her model. When her choices determine the data available, her behavior affects her inferences, which in turn affect her choices. We provide necessary and sufficient conditions for testing whether such an agent's behavior is compatible with the model.

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"Correlation Neglect as a Commitment Device" (2018)

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We study the strategic transmission of information from two informed senders to an uninformed receiver. The senders, whose preferences are perfectly aligned can send correlated, binary, pay-off irrelevant messages. The receiver observes the messages and takes an action that affects the pay-off of all the agents. The receiver understands the informational content of the individual messages, but not their correlation. Compared to the rational benchmark the receiver’s inability to infer the correlation between messages expands the range of disagreement for which information transmission can take place. The receiver strictly prefers to suffer from correlation neglect.

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