Econometrica, Volume 87, Issue 6 (November 2019) has been published
ECONOMETRICA
Journal of the Econometric Society
Volume 87, Issue 6 (November 2019) has been published. The full content of the journal is accessible at
https://www.econometricsociety.org/publications/econometrica/browse
Articles
Frontmatter of Econometrica Vol. 87 Iss. 6
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The Aggregate Implications of Regional Business Cycles
Martin Beraja, Erik Hurst, Juan Ospina
Making inferences about aggregate business cycles from regional variation alone is difficult because of economic channels and shocks that differ between regional and aggregate economies. However, we argue that regional business cycles contain valuable information that can help discipline models of aggregate fluctuations. We begin by documenting a strong relationship across U.S. states between local employment and wage growth during the Great Recession. This relationship is much weaker in U.S. aggregates. Then, we present a methodology that combines such regional and aggregate data in order to estimate a medium‐scale New Keynesian DSGE model. We find that aggregate demand shocks were important drivers of aggregate employment during the Great Recession, but the wage stickiness necessary for them to account for the slow employment recovery and the modest fall in aggregate wages is inconsistent with the flexibility of wages we observe across U.S. states. Finally, we show that our methodology yields different conclusions about the causes of aggregate employment and wage dynamics between 2007 and 2014 than either estimating our model with aggregate data alone or performing back‐of‐the‐envelope calculations that directly extrapolate from well‐identified regional elasticities.
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Bargaining Under Strategic Uncertainty: The Role of Second-Order Optimism
Amanda Friedenberg
This paper shows that bargainers may reach delayed agreements even in environments where there is no uncertainty about payoffs or feasible actions. Under such conditions, delay may arise when bargainers face direct forms of strategic uncertainty—that is, uncertainty about the opponent's play. The paper restricts the nature of this uncertainty in two important ways. First, it assumes on‐path strategic certainty: Bargainers face uncertainty only after surprise moves. Second, it assumes Battigalli and Siniscalchi's (2002) rationality and common strong belief of rationality (RCSBR)—a requirement that bargainers are “strategically sophisticated.” The main result characterizes the set of outcomes consistent with on‐path strategic certainty and RCSBR. It shows that these assumptions allow for delayed agreement, despite the fact that the bargaining environment is one of complete information. The source of delay is second‐order optimism: Bargainers do not put forward “good” offers early in the negotiation process because they fear that doing so will cause the other party to become more optimistic about her future prospects.
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Strategic Communication with Minimal Verification
Gabriel Carroll, Georgy Egorov
A receiver wants to learn multidimensional information from a sender, and she has the capacity to verify just one dimension. The sender's payoff depends on the belief he induces, via an exogenously given monotone function. We show that by using a randomized verification strategy, the receiver can learn the sender's information fully in many cases. We characterize exactly when it is possible to do so. In particular, when the exogenous payoff function is submodular, we can explicitly describe a full‐learning mechanism; when it is (strictly) supermodular, full learning is not possible. In leading cases where full learning is possible, it can be attained using an indirect mechanism in which the sender chooses the probability of verifying each dimension.
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Dynamic Quantile Models of Rational Behavior
Luciano de Castro, Antonio F. Galvao
This paper develops a dynamic model of rational behavior under uncertainty, in which the agent maximizes the stream of future τ‐quantile utilities, for τ ∈ (0,1). That is, the agent has a quantile utility preference instead of the standard expected utility. Quantile preferences have useful advantages, including the ability to capture heterogeneity and allowing the separation between risk aversion and elasticity of intertemporal substitution. Although quantiles do not share some of the helpful properties of expectations, such as linearity and the law of iterated expectations, we are able to establish all the standard results in dynamic models. Namely, we show that the quantile preferences are dynamically consistent, the corresponding dynamic problem yields a value function, via a fixed point argument, this value function is concave and differentiable, and the principle of optimality holds. Additionally, we derive the corresponding Euler equation, which is well suited for using well‐known quantile regression methods for estimating and testing the economic model. In this way, the parameters of the model can be interpreted as structural objects. Therefore, the proposed methods provide microeconomic foundations for quantile regression methods. To illustrate the developments, we construct an intertemporal consumption model and estimate the discount factor and elasticity of intertemporal substitution parameters across the quantiles. The results provide evidence of heterogeneity in these parameters.
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Dynamic Random Utility
Mira Frick, Ryota Iijima, Tomasz Strzalecki
We provide an axiomatic analysis of dynamic random utility, characterizing the stochastic choice behavior of agents who solve dynamic decision problems by maximizing some stochastic process (Ut) of utilities. We show first that even when (Ut) is arbitrary, dynamic random utility imposes new testable across‐period restrictions on behavior, over and above period‐by‐period analogs of the static random utility axioms. An important feature of dynamic random utility is that behavior may appear history‐dependent, because period‐t choices reveal information about Ut, which may be serially correlated; however, our key new axioms highlight that the model entails specific limits on the form of history dependence that can arise. Second, we show that imposing natural Bayesian rationality axioms restricts the form of randomness that (Ut) can display. By contrast, a specification of utility shocks that is widely used in empirical work violates these restrictions, leading to behavior that may display a negative option value and can produce biased parameter estimates. Finally, dynamic stochastic choice data allow us to characterize important special cases of random utility—in particular, learning and taste persistence—that on static domains are indistinguishable from the general model.
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Strategically Simple Mechanisms
Tilman Börgers, Jiangtao Li
We define and investigate a property of mechanisms that we call “strategic simplicity,” and that is meant to capture the idea that, in strategically simple mechanisms, strategic choices require limited strategic sophistication. We define a mechanism to be strategically simple if choices can be based on first‐order beliefs about the other agents' preferences and first‐order certainty about the other agents' rationality alone, and there is no need for agents to form higher‐order beliefs, because such beliefs are irrelevant to the optimal strategies. All dominant strategy mechanisms are strategically simple. But many more mechanisms are strategically simple. In particular, strategically simple mechanisms may be more flexible than dominant strategy mechanisms in the bilateral trade problem and the voting problem.
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Linear Voting Rules
Hans Peter Grüner, Thomas Tröger
How should a society choose between two social alternatives if participation in the decision process is voluntary and costly, and monetary transfers are not feasible? Assuming symmetric independent private values, we show that it is utilitarian‐optimal to use a linear voting rule: votes get alternative‐dependent weights, and a default obtains if the weighted sum of votes stays below some threshold. Any combination of weights and threshold can be optimal. A standard quorum rule can be optimal only when it yields the same outcome as a linear rule. A linear rule is called upper linear if the default is upset at every election result that meets the threshold exactly. We develop a perturbation method to characterize equilibria of voting rules in the case of small participation costs and show that leaving participation voluntary increases welfare for any two‐sided upper linear rule that is optimal under compulsory participation.
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Pricing and Liquidity in Decentralized Asset Markets
Semih Üslü
I develop a search‐and‐bargaining model of endogenous intermediation in over‐the‐counter markets. Unlike the existing work, my model allows for rich investor heterogeneity in three simultaneous dimensions: preferences, inventories, and meeting rates. By comparing trading‐volume patterns that arise in my model and are observed in practice, I argue that the heterogeneity in meeting rates is the main driver of intermediation patterns. I find that investors with higher meeting rates (i.e., fast investors) are less averse to holding inventories and more attracted to cash earnings, which makes the model corroborate a number of stylized facts that do not emerge from existing models: (i) fast investors provide intermediation by charging a speed premium, and (ii) fast investors hold more extreme inventories. Then, I use the model to study the effect of trading frictions on the supply and price of liquidity. On social welfare, I show that the interaction of meeting rate heterogeneity with optimal inventory management makes the equilibrium inefficient. I provide a financial transaction tax/subsidy scheme that corrects this inefficiency, in which fast investors cross‐subsidize slow investors.
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On the Efficiency of Social Learning
Dinah Rosenberg, Nicolas Vieille
We revisit prominent learning models in which a sequence of agents make a binary decision on the basis of both a private signal and information related to past choices. We analyze the efficiency of learning in these models, measured in terms of the expected welfare. We show that, irrespective of the distribution of private signals, learning efficiency is the same whether each agent observes the entire sequence of earlier decisions or only the previous decision. In addition, we provide a simple condition on the signal distributions that is necessary and sufficient for learning efficiency. This condition fails to hold in many cases of interest. We discuss a number of extensions and variants.
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The Econometric Society 2018 Annual Report of the President
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Backmatter of Econometrica Vol. 87 Iss. 6
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