Ignacio Monzón - Research

Abstract

Decision makers often rely on experts’ evaluations to decide on complex proposals. Proponents want the approval of their proposals and can work to improve their quality. The scrutiny of experts ought to push proponents to work harder, leading to high-quality proposals. Experts, however, have their own agendas: they may favor or oppose the proposals under their scrutiny. We study how the expert’s agenda affects the likelihood that proposals are approved and their quality. We show that an expert in favor of a proposal can be detrimental towards its approval. This happens when it is easy to incentivize the proponent to work and when the status quo alternative is not too attractive.

Abstract

We study bargaining with divisibility and interdependent values. A buyer and a seller trade a divisible good. The seller is privately informed about its quality, which can be high or low. Gains from trade are positive and decreasing in quantity. The buyer makes offers over time. Divisibility introduces a new channel of competition between the buyer's present and future selves. The buyer's temptation to split the purchases of the high-quality good is detrimental to him. As bargaining frictions vanish and the good becomes arbitrarily divisible, the high-quality good is traded smoothly over time and the buyer's payoff shrinks to zero.

Technical Addendum

Abstract

We present a natural environment that sustains full cooperation in one-shot social dilemmas among a finite number of self-interested agents. Players sequentially decide whether to contribute to a public good. They do not know their position in the sequence, but observe the actions of some predecessors. Since agents realize that their own action may be observed, they have an incentive to contribute in order to induce potential successors to also do so. Full contribution can then emerge in equilibrium. The same environment leads to full cooperation in the prisoners’ dilemma.

Abstract

I present a model of observational learning with payoff interdependence. Agents, ordered in a sequence, receive private signals about an uncertain state of the world and sample previous actions. Unlike in standard models of observational learning, an agent's payoff depends both on the state and on the actions of others. Agents want both to learn the state and to anticipate others' play. As the sample of previous actions provides information on both dimensions, standard informational externalities are confounded with payoff externalities. I show that in spite of these confounding factors, when signals are of unbounded strength there is learning in a strong sense: agents' actions are ex-post optimal given both the state of the world and others' actions. With bounded signals, actions approach ex-post optimality as the signal structure becomes more informative.

Online Appendix

Abstract

We propose a novel methodology to uncover the sorting pattern in labor markets. We identify the strength of sorting solely from a ranking of firms by profits. To discern the sign of sorting, we build a noisy ranking of workers from wage data. Our test for the sign of sorting is consistent even with noisy worker rankings. We apply our approach to a panel dataset that combines social security earnings records with detailed financial data for firms in the Veneto region of Italy. We find robust evidence of positive sorting. The correlation between worker and firm types is about 52%.

Online Appendix

Abstract

I present a model in which a continuum of homogeneous rational agents choose between two competing technologies. Agents observe a private signal and a sample of other agents’ previous choices. Signals have both an idiosyncratic and an aggregate component of uncertainty. Due to aggregate uncertainty, aggregate behavior does not necessarily reflect the true state of nature. Nonetheless, agents still find others’ choices a good source of information, and they base their decisions partly on the behavior of others. Consequently, bad choices can be perpetuated: aggregate uncertainty can lead to agents herding on the inferior technology with positive probability. I derive the optimal decision rule when each agent observes the decision of exactly two agents. I also present examples in which herding occurs for arbitrarily large sample sizes.

Code

Abstract

Observational learning is typically examined when agents have precise information about their position in the sequence of play. We present a model in which agents are uncertain about their positions. Agents sample the decisions of past individuals and receive a private signal about the state of the world. We show that social learning is robust to position uncertainty. Under any sampling rule satisfying a stationarity assumption, learning is complete if signal strength is unbounded. In cases with bounded signal strength, we provide a lower bound on information aggregation: individuals do at least as well as an agent with the strongest signal realizations would do in isolation. Finally, we show in a simple environment that position uncertainty slows down learning but not to a great extent.

Abstract

We present a model of delegation with moral hazard. A principal delegates a decision to an agent, who affects the distribution of the state of the world by exerting costly and unobservable effort. The principal faces a trade-off between (i) granting the agent discretion, so he can adapt the decision to the state and (ii) limiting the agent's discretion, to induce him to exert effort. Our model is flexible on how effort affects the state distribution, thus capturing several distinct economic environments. Optimal delegation takes one of four simple forms, all commonly used in practice: floors, ceilings, floor-ceilings or gaps.

Abstract

Do parents take into account their children’s ability when deciding on their education? If so, are parents’ perceptions accurate? We study this by analyzing a key educational decision. Parents choose whether their children start elementary school one year early . Do they select high-ability children to start early? We propose a novel methodology to identify the sign and strength of selection into early starting. We find robust evidence of positive selection. Had they started regularly, early starters would have obtained test scores 0.2 standard deviations higher than the average student.

We also estimate the effect of early starting on test scores and find that the effect is heterogeneous.

Abstract

We present a partnership model where heterogeneous agents bargain over the gains from trade and search on the match. Frictions allow agents to extract higher rents from more productive partners, generating an endogenous preference for high types. More productive agents upgrade their partners faster, therefore the equilibrium match distribution features positive assortative matching. Frictions are commonly understood to hamper sorting. Instead, we show how frictions generate positive sorting even with a submodular production function. Our results challenge the interpretation of positive assortative matching as evidence of complementarity.

Online Appendix and Additional Material: All Possible Equilibria with Two Types