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ALT In many choice settings, a rise in aggregate demand for an option lowers an individual's payoff from choosing it. Driving becomes less attractive than taking a train when more commuters drive, clogging the highway. In such cases, a targeted intervention that mitigates the externality at the congested option can divert it elsewhere and also undermine preference based sorting, making overall welfare effects theoretically ambiguous. We develop an empirical framework to analyze such scenarios of endogenous congestion. We show that in these settings, equilibrium exists and is unique without restrictions on functional-form of utilities or dimension/distribution of preference heterogeneity, and even when congestion at one option affects payoffs from other choices. Under a linear-index structure, micro-data on choice enables semiparametric identification of utility contrasts and welfare effects of some, but not all, interventions. We apply the framework to Cambridge undergraduate admissions, w
ALT Can welfare effects of price change be identified when consumers' consideration sets are heterogeneous and unobserved? We establish that the welfare distribution is the same functional of structural choice probabilities under stable but limited consideration as under full consideration. The result permits unrestricted income-effects, preference heterogeneity, and dependence between preferences and consideration. Within this class, limited consideration admits a full-consideration representation preserving choice-probabilities and money-metric compensation: consideration/preferences can remain unidentified while demand and welfare are identified. When consideration sets contract as prices rise, the welfare distribution can be bounded using demand and a bound on choice-set attrition.
ALT We study shrinking tax kinks when the counterfactual density is locally Hölder continuous and may be accompanied by a known background atom at the threshold. Small policy incentives create two distinct obstacles: few behavioral bunchers and an unobserved relocation interval. For the complete observed distribution, we establish matching minimax bounds for elasticity estimation and honest confidence-set diameter. With kink size d, background mass γ, and smoothness 0<s≤1, the rate is min{1,√((γ+d)/(nd²))+dˢ}. The stochastic component has a rare-event scale when the background mass is of the kink order or smaller and a conventional weak-signal scale when it remains positive. The extrapolation component follows from observationally equivalent counterfactual densities, rather than sampling error. We derive normal and Poisson limits for a conventional bunching ratio, show a coverage failure of its Wald interval, and give finite-sample confidence sets by exact binomial inversion with a determi
ALT This paper documents that expansions of UK maternity pay in the 2000s improved children's test scores while reducing maternal employment. Extending job protection alone generated similar employment effects but no detectable impact on children. None of these effects are recoverable with a conventional regression discontinuity (RD) design because eligibility is only imperfectly captured by the available data. We explain why existing corrections for measurement error in RD are not well suited and propose a simple imputation-based solution. The approach preserves RD's main advantages, nonparametric identification and transparency, and remains valid even when measurement error has economic content.
ALT This note contains a story and a paper. The paper is about the admissibility of two-stage least squares with weak instruments, a topic we have worked on together since 2019. The story is about how we (or, rather, our LLMs) wrote the paper, and some thoughts on what this may mean for our field.
ALT We study the design of multi-arm experiments that identify local average treatment effects under imperfect compliance. With three or more arms, conventional randomization fails to identify margin-specific effects even under strong extensions of monotone compliance. A choice-theoretic analysis unifies these extensions and motivates a two-stage design: subjects report a preferred arm and are randomized conditional on it. If treatment is confined to the assigned or reported arm, one-sided noncompliance is restored conditional on the report, identifying the effect between the two for their compliers. We discuss the design's applicability and feasibility in relation to the choice model.
ALT This paper analyzes when choice probabilities reveal rankings of deterministic utility indices in semiparametric discrete choice models. It begins with binary choice, where quantile thresholds guarantee ranking recovery, and shows that such thresholds can arise either from behavioral departures from utility maximization (e.g., limited attention) under exchangeable unobservables, or from non-exchangeable unobservables under standard utility maximization. These behavioral and distributional routes are then extended to multinomial choice. Under limited attention, balance restrictions on attention probabilities yield global linear ranking partitions which are robust to the distribution of unobservables and, given sufficiently rich joint variation in the differences of utility indices, are also necessary. Absent the required attention restrictions, opposite rankings can produce overlapping probability images. Under non-exchangeable unobservables, a comparable distribution-uniform partition
ALT Representation theorems in decision theory establish that behavior satisfies certain axioms if and only if it can be rationalized by a well-defined objective. I argue that this “if and only if” structure provides a potentially useful foundation for label-free evaluation and regularization of LLMs and other AI systems. Axiom compliance can be checked from the model's own responses to synthetic choice problems, with no external labels or human feedback, and the penalties are readily computable. Because the axioms are necessary and sufficient, the resulting checks exhaust the implications of the relevant rationality standard for the elicited data: a model that passes cannot be rejected on rationality grounds by any further test of the same data. I discuss three instantiations: probabilistic coherence via a theorem of de Finetti, preference rationality via Afriat's theorem, and subjective expected utility via a theorem of Echenique and Saito (2015), each yielding a continuous penalty that
ALT Admission systems often fill seats by applying criterion-specific rankings sequentially. We derive criterion-wise comparative statics with respect to precedence order when rankings may be arbitrarily nonaligned, and each criterion evaluates the entire admitted set through a responsive preference. For a fixed applicant set, reversing the final two blocks makes each criterion weakly prefer the outcome in which its block is later. This comparison can reverse if two blocks are followed by another criterion, even under reserve-type rankings. Under student-proposing deferred acceptance, it can also reverse with two criteria because rejection chains change the focal college's applicant set; such feedback is the only possible source of failure. In regular large markets, failures vanish for almost all colleges and, under sufficient thickness, uniformly across colleges. Under the Boston mechanism, final acceptance prevents feedback; thus the comparison holds in every finite market for fixed subm
