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Signaling is wasteful. But how wasteful? We study the fraction of surplus dissipated in a separating equilibrium. For isoelastic environments, this waste ratio has a simple formula: β/(β + σ), where β is the benefit elasticity (reward to higher perception) and σ is the elasticity of higher types’ relative cost advantage. The ratio is constant across types and is independent of other parameters, including convexity of cost in the signal. We show that the directional effects of β and σ on waste extend to non-isoelastic environments.

AI/ML methods are increasingly used in economics to generate binary variables (or labels) via classification algorithms. When these generated variables are included as covariates in regressions, even small misclassification errors can induce large biases in OLS estimators and invalidate standard inference. We study whether the bootstrap can correct this bias and deliver valid inference. We first show that a seemingly natural fixed-label bootstrap, which generates data using estimated labels but relies on a corrupted version in estimation, is generally invalid unless a strong independence condition between the latent true labels and other covariates holds. We then propose a coupled-label bootstrap that jointly resamples the true and imputed labels, and show it is valid without this condition. Two finite-sample adjustments further improve coverage: a variance correction for uncertainty in estimated misclassification rates and a Hessian rotation for near-singular designs. We illustrate the methods in simulations and apply them to investigate the relationship between wages and remote work status.

This paper studies how new varieties enter markets and become locally available. We provide causal evidence of demand externalities that operate in two steps. First, information about new varieties diffuses directly through real-world social ties among consumers. Second, early purchases generate an indirect spillover to firms: local retailers learn from 'pioneer' consumers which new varieties are most likely to succeed and adjust their product offerings accordingly. We study this process in the context of direct-to-consumer imports. Using customs records on individuals' purchases matched to population-wide social networks, international migrant links, and retailer catchment areas, we document economically meaningful demand externalities. Product-specific demand shocks abroad transmit through migrant networks and shift which varieties consumers purchase. Leveraging these shocks as a plausibly exogenous source of local demand variation, we show strong peer effects: prior purchases by close neighbors, coworkers, or friends increase an individual’s likelihood of purchasing the same variety, especially for premium and visible goods. We leverage this result to identify an indirect spillover from consumers to firms: retailers are more likely to add a variety when it becomes popular among consumers in their catchment area. Combining the instrument with linked consumer--retailer data and a self-conducted retailer survey, we show that this response reflects learning about latent demand for varieties not yet stocked locally. Together, social diffusion and retailer learning generate demand multipliers that reshape local product availability and expand access to global variety.

Cross-country disparities in collateral technologies alone can account for large capital flows among mature economies, and allow the most advanced country to run a permanent trade deficit. When the collateral technology advantage is in creating negative beta (super safe) financial assets backed by positive beta assets, a Global Collateral Cycle emerges, with pro-cyclical gross and net flows and increased global asset price volatility. The supply of super safe assets is necessarily curtailed in downturns, providing a complementary (supply) channel to the flight to safety (demand) channel for explaining why US safe asset prices rise during crises.

We build a general equilibrium model in which firms endogenously choose whether to target prices or quantities. We characterize how these choices of organizational targets depend on firms' uncertainty about microeconomic and macroeconomic factors. In equilibrium, the transmission of both nominal and real shocks hinges on firms' organizational targets. For example, under otherwise identical microfoundations, money is neutral under quantity targets and non-neutral under price targets. We further characterize how targets shape firms' strategic interactions and prove that the macroeconomic uncertainty that arises from each choice of targets reinforces incentives to choose that target. That is, choices of organizational targets are strategic complements. For this reason, monetary policy aimed at stabilization can backfire by inducing a regime shift that renders it ineffective. A simple quantification suggests that incentives over organizational targets can vary markedly at business-cycle frequencies and help explain the state-dependent pass-through of monetary shocks to prices and output.

We document employment preferences of workers at the margin of informality using open-ended questions and discrete choice experiments in Brazil’s largest favela complex. Stated preferences emphasize pay and tangible job benefits rather than meaning or purpose, while primary complaints center on poor management, customers, and inflexible schedules. Workers exhibit high valuations for all formal sector amenities on average—unemployment insurance, parental leave, and termination notice—as well as for learning opportunities, but lower for non-formal sector amenities such as shorter commutes. Valuations vary systematically by employment sector in ways consistent with sorting: formal workers value formal amenities most, the self-employed value them least or not at all, and the informally employed exhibit mixed valuations. These patterns are also consistent with learning and endowment effects, for which we find suggestive evidence.

This paper examines the impact of early childcare on academic achievement for children in grade 5 and grade 9, based on a 2003 policy expansion that created quasi-random variation in slot availability for children aged 1–2. Starting childcare one year earlier increases math scores by 9.7% of a standard deviation (SD) in grade 9. Children whose mothers do not hold a high school diploma benefit by a significant 28% of a SD at grade 9, reducing the math achievement gap from children of higher-educated mothers by about one third. We also present evidence of strong improvements for children of immigrants.

Bilateral bargaining under incomplete information provides a controlled testbed for evaluating large language model (LLM) agent capabilities. Bilateral trade demands individual rationality, strategic surplus maximization, and cooperation to realize gains from trade. We develop a structured bargaining environment in which LLMs negotiate via tool calls within an event-driven simulator, separating binding offers from natural-language messages to enable automated evaluation. The environment serves two purposes: as a benchmark for frontier models and as a training environment for open-weight models via reinforcement learning. In benchmark experiments, a round-robin tournament among five frontier models (15,000 negotiations) reveals that effective strategies implement price discrimination through sequential offers. Aggressive anchoring, calibrated concession, and temporal patience are associated with both the highest surplus share and the highest deal rate. Accommodating strategies that concede quickly disable price discrimination in the buyer role, yielding the lowest surplus capture and deal completion. Strategically competent models scale their behavior proportionally to item value, maintaining consistent performance across price tiers; weaker models perform well only when wide zones of possible agreement compensate for suboptimal strategies. In training experiments, we fine-tune Qwen3 (8B, 14B) via supervised fine-tuning (SFT) followed by Group Relative Policy Optimization (GRPO) against a fixed frontier opponent. The two stages optimize competing objectives: SFT approximately doubles surplus share but reduces deal rates, while RL recovers deal rates but erodes surplus gains—a tension traceable to the reward structure. SFT also compresses surplus variation across price tiers, and this compression generalizes to opponents unseen during training, suggesting that behavioral cloning instills proportional strategies rather than memorized price points.