This paper investigates a two-agent mechanism design problem without transfers, where the principal must decide one action for each agent. In our framework, agents only care about their own adaptation, and any deterministic dominant incentive compatible decision rule is equivalent to contingent delegation: the delegation set offered to one agent depends on the other's report. By contrast, the principal cares about both adaptation and coordination. We provide sufficient conditions under which contingent interval delegation is optimal and solve the optimal contingent interval delegation under fairly general conditions. Remarkably, the optimal interval delegation is completely determined by combining and modifying the solutions to a class of simple single-agent problems, where the other agent is assumed to report truthfully and choose his most preferred action.
We present an approach to analyse learning outcomes in a broad class of misspecified environments, spanning both single-agent and social learning. We introduce a novel “prediction accuracy” order over subjective models and observe that this makes it possible to partially restore standard martingale convergence arguments that apply under correctly specified learning. Based on this, we derive general conditions to determine when beliefs in a given environment converge to some long-run belief either locally or globally (i.e. from some or all initial beliefs). We show that these conditions can be applied, first, to unify and generalize various convergence results in previously studied settings. Second, they enable us to analyse environments where learning is “slow”, such as costly information acquisition and sequential social learning. In such environments, we illustrate that even if agents learn the truth when they are correctly specified, vanishingly small amounts of misspecification can generate extreme failures of learning.
Fundraising campaigns draw support from a wide pool of contributors. Some contributors are interested in private rewards offered in exchange for contributions (buyers), whereas others are publicly-minded and value success (donors). Buyers face a coordination problem because of the positive externalities of campaign success. A leadership donor who strategically times contributions can promote coordination by dynamically signaling his valuation. The ability to signal increases the probability of success and benefits all participants relative to the donor valuation being known. We validate our modeling assumptions and theoretical predictions using Kickstarter data.
The present study examines the assumptions, modeling structure, and preliminary results of DICE-2023, the revised Dynamic Integrated Model of Climate and the Economy (DICE), updated to 2023. The revision contains major changes in the carbon and climate modules, the treatment of non-industrial greenhouse gases, discount rates, as well as updates on all the major components. The major changes are a significant reduction in the target for the optimal (cost-beneficial) temperature path, a lower cost of reaching the 2 °C target, an analysis of the impact of the Paris Accord, and a major increase in the estimated social cost of carbon.
We study the intergenerational effect of education policy on crime. We use Swedish administrative data that links outcomes across generations with crime records and we show that the comprehensive school reform, gradually implemented between 1949 and 1962, reduced conviction rates both for the generation directly affected by the reform and for their sons. The reduction in conviction rates occurred across many types of crime. Key mediators for this reduction in the child generation are an increase in education and a decline in crime amongst their fathers.
Spatial units typically vary over many of their characteristics, introducing potential unobserved heterogeneity which invalidates commonly used homoskedasticity conditions. In the presence of unobserved heteroskedasticity, methods based on the quasi-likelihood function generally produce inconsistent estimates of both the spatial parameter and the coefficients of the exogenous regressors. A robust generalized method of moments estimator as well as a modified likelihood method have been proposed in the literature to address this issue. The present paper constructs an alternative indirect inference (II) approach which relies on a simple ordinary least squares procedure as its starting point. Heteroskedasticity is accommodated by utilizing a new version of continuous updating that is applied within the II procedure to take account of the parameterization of the variance–covariance matrix of the disturbances. Finite-sample performance of the new estimator is assessed in a Monte Carlo study. The approach is implemented in an empirical application to house price data in the Boston area, where it is found that spatial effects in house price determination are much more significant under robustification to heterogeneity in the equation errors.
Addressing public health externalities often requires community-level collective action. Due to social norms, each person’s sanitation investment decisions may depend on the decisions of neighbors. We report on a cluster randomized controlled trial conducted with 19,000 households in rural Bangladesh where we grouped neighboring households and introduced (either financial or social recognition) rewards with a joint liability component for the group, or asked each group member to make a private or public pledge to maintain a hygienic latrine. The group financial reward has the strongest impact in the short term (3 months), inducing a 7.5–12.5 percentage point increase in hygienic latrine ownership, but this effect dissipates in the medium term (15 months). In contrast, the public commitment induced a 4.2–6.3 percentage point increase in hygienic latrine ownership in the short term, but this effect persists in the medium term. Non-financial social recognition or a private pledge has no detectable effect on sanitation investments.
Limit distribution theory in the econometric literature for functional coefficient cointegrating regression is incorrect in important ways, influencing rates of convergence, distributional properties, and practical work. The correct limit theory reveals that components from both bias and variance terms contribute to variability in the asymptotics. The errors in the literature arise because random variability in the bias term has been neglected in earlier research. In stationary regression this random variability is of smaller order and can be ignored in asymptotic analysis but not without consequences for finite sample performance. Implications of the findings for rate efficient estimation are discussed. Simulations in the Online Supplement provide further evidence supporting the new limit theory in nonstationary functional coefficient regressions.
We compare contrarian to conformist advice, a contrarian expert being one whose preference bias is against the decision-maker’s prior optimal decision. Optimality of an expert depends on characteristics of prior information and learning. If either the expert is fully informed or fine information can be acquired cheaply, then for symmetric distributions F (of the state), a conformist (contrarian) is superior if F is single peaked bimodal. If only coarse information can be acquired, then a contrarian acquires more on average and hence is superior. If information is verifiable, a contrarian has less incentive to hide unfavorable evidence and again is superior.
The propensity of consumers to talk after a good versus bad experience with a product can differ based on information available from other marketing channels, for example the brand image or advertising. This can result in selection of positive/negative word-of-mouth for reasons outside of product quality. We develop a unifying framework of WOM, brand image, product advertising, and pricing with a focus on the instrumentality motive of word-of-mouth: early adopters talk to inform new buyers’ purchasing decisions. The different marketing channels shape the information sharing behavior of the early adopter as well as the target consumer’s purchase decision. We show that if the brand image is strong, then in equilibrium only negative WOM can arise. In contrast, with a weak brand image, positive WOM must occur. We also show that holding product quality fixed, a positive advertising signal realization leads to a more positive WOM selection. The model can be applied to both one-one informal WOM as well as online reviews. The assumptions and main predictions of our model are consistent with those that we identified from a primary survey and observational Yelp data.