We introduce experimental persuasion between Sender and Receiver. Sender chooses an experiment to perform from a feasible set of experiments. Receiver observes the realization of this experiment and chooses an action. We characterize optimal persuasion in this baseline regime and in an alternative regime in which Sender can commit to garble the outcome of the experiment. Our model includes Bayesian persuasion as the special case in which every experiment is feasible; however, our analysis does not require concavification. Since we focus on experiments rather than beliefs, we can accommodate general preferences including costly experiments and non-Bayesian inference.
This paper examines the welfare effects of informational intermediation. A (short-lived) seller sets the price of a product that is sold through a (long-lived) informational intermediary. The intermediary can disclose information about the product to consumers, earns a fixed percentage of the sales revenue in each period, and has concerns about its prominence—the market size it faces in the future, which in turn is increasing in past consumer surplus. We characterize the Markov perfect equilibria and the set of subgame perfect equilibrium payoffs of this game and show that when the market feedback (i.e., how much past consumer surplus affects future market sizes) increases, welfare may decrease in the Pareto sense.
The paper develops a modeling framework to study how sustainability interventions impact consumer adoption of durable goods innovation, firm profit and environmental outcomes in equilibrium. Our two period model with forward looking consumers and a monopoly firm introducing an innovation in the second period accommodates three key features: (1) it builds on the psychology literature linking reactive and anticipatory guilt to consumers’ environmental sensitivity on initial purchase and upgrade decisions; (2) it disentangles environmental harm over the product life into that arising from product use and dumping at replacement; and (3) it clarifies how a taxonomy of innovations (function, fashion and use-efficiency) differ in how they provide value and cause environmental harm during use and dumping. Given how guilt impacts environmental sensitivity, the model allows for owners upgrading a product to be more environmentally sensitive than first time buyers; this makes dumping harm and in-use harm from products not fungible. We find that with fashion and function innovations, increasing consumer sensitivity to environmental harm can surprisingly result in increased environmental harm. Further, when consumers are very sensitive to environmental harm, firms will not inform (pre-announce to) consumers about the impending arrival of use-efficiency innovation; to minimize environmental harm, a sustainability advocate needs to inform consumers. Thus, contrary to conventional wisdom, consumer environmental sensitivity does not always substitute for the role of sustainability advocates. Our results clarify how to design win-win policies for firms and the environment; and when advocates have complementary/adversarial roles relative to firms to achieve sustainability goals.
As large amounts of data become available and can be communicated more easily and processed more effectively, information has come to play a central role for economic activity and welfare in our age. This essay overviews contributions to the industrial organization of information markets and nonmarkets, while attempting to maintain a balance between foundational frameworks and more recent developments. We start by reviewing mechanism-design approaches to modeling the trade of information. We then cover ratings, predictions, and recommender systems. We turn to forecasting contests, prediction markets, and other institutions designed for collecting and aggregating information from decentralized participants. Finally, we discuss science as a prototypical information nonmarket with participants who interact in a non-anonymous way to produce and disseminate information. We aim to familiarize the reader with the central notions and insights in this burgeoning literature and also point to some critical open questions that future research will have to address.
Artificial Neural Networks (ANNs) can be viewed as nonlinear sieves that can approximate complex functions of high dimensional variables more effectively than linear sieves. We investigate the computational performance of various ANNs in nonparametric instrumental variables (NPIV) models of moderately high dimensional covariates that are relevant to empirical economics. We present two efficient procedures for estimation and inference on a weighted average derivative (WAD): an orthogonalized plug-in with optimally-weighted sieve minimum distance (OP-OSMD) procedure and a sieve efficient score (ES) procedure. Both estimators for WAD use ANN sieves to approximate the unknown NPIV function and are root-n asymptotically normal and first-order equivalent. We provide a detailed practitioner’s recipe for implementing both efficient procedures. This involves the choice of tuning parameters for the unknown NPIV, the conditional expectations and the optimal weighting function that are present in both procedures but also the choice of tuning parameters for the unknown Riesz representer in the ES procedure. We compare their finite-sample performances in various simulation designs that involve smooth NPIV function of up to 13 continuous covariates, different nonlinearities and covariate correlations. Some Monte Carlo findings include: 1) tuning and optimization are more delicate in ANN estimation; 2) given proper tuning, both ANN estimators with various architectures can perform well; 3) easier to tune ANN OP-OSMD estimators than ANN ES estimators; 4) stable inferences are more difficult to achieve with ANN (than spline) estimators; 5) there are gaps between current implementations and approximation theories. Finally, we apply ANN NPIV to estimate average partial derivatives in two empirical demand examples with multivariate covariates.
We characterize the revenue-maximizing information structure in the second price auction. The seller faces a classic economic trade-o¤: providing more information improves the efficiency of the allocation but also creates higher information rents for bidders. The information disclosure policy that maximizes the revenue of the seller is to fully reveal low values (where competition will be high) but to pool high values (where competition will be low). The size of the pool is determined by a critical quantile that is independent of the distribution of values and only dependent on the number of bidders. We discuss how this policy provides a rationale for conflation in digital advertising.
Whether or not to vaccinate one’s child is a decision that a parent may approach in several ways. The vaccination game, in which parents must choose whether to vaccinate a child against a disease, is one with positive externalities (herd immunity). In some societies, not vaccinating is an increasingly prevalent behavior, due to deleterious side effects that parents believe may accompany vaccination.
The standard game-theoretic approach assumes that parents make decisions according to the Nash behavioral protocol, which is individualistic and non-cooperative. Because of the positive externality that each child’s vaccination generates for others, the Nash equilibrium suffers from a free-rider problem. However, in more solidaristic societies, parents may behave cooperatively –they may optimize according to the Kantian protocol, in which the equilibrium is efficient. We test, on a sample of six countries, whether childhood vaccination behavior conforms better to the individualistic or cooperative protocol. In order to do so, we conduct surveys of parents in these countries, to ascertain the distribution of beliefs concerning the subjective probability and severity of deleterious side effects of vaccination.
We show that in all the countries of our sample the Kant model dominates the Nash model. We conjecture that, due to the free-rider problem inherent in the Nash equilibrium, a social norm has evolved, quite generally, inducing parents to vaccinate with higher probability than they would in the non-cooperative solution. Kantian equilibrium offers one precise version of such a social norm.