Working papers results

We exploit one of the largest data leaks to date to study whether and how firms use secret offshore vehicles. From the leaked data, we identify 338 listed firms as users of secret offshore vehicles and document that these vehicles are used to finance corruption, avoid taxes, and expropriate shareholders. Overall, the leak erased $174 billion in market capitalization among implicated firms. Following the increased transparency brought about by the leak, implicated firms experience lower sales from perceptively corrupt countries and avoid less tax. We estimate conservatively that one in seven firms have offshore secrets.

This paper formalizes an informal idea that an agent's knowledge is characterized by a collection of sets such as a -algebra within the framework of a state space model of knowledge. The formalization is based on the agent's logical and introspective abilities and on the underlying structure of the state space. The agent is logical and introspective about what she knows if and only if her knowledge is summarized by a collection of events with the property that, for any event, the collection has the maximal event included in the original event. When the underlying space is a measurable space, the collection becomes a -algebra if and only if the agent is additionally introspective about what she does not know. The paper characterizes why the agent's knowledge takes (or does not take) such a set algebra as a -algebra or a topology, depending on the agent's logical and introspective abilities and on the underlying environment.

Journal of Economic Literature Classification Numbers: C70, D83

We consider revealed preference relations over risky (or uncertain) prospects, and allow them to be nontransitive and/or fail the classical Independence Axiom. We identify the rational part of any such preference relation as its largest transitive subrelation that satisfies the Independence Axiom and that exhibits some coherence with the original relation. It is shown that this subrelation, which we call the rational core of the given revealed preference, exists in general, and under fairly mild conditions, it is continuous. We obtain various representation theorems for the rational core, and decompose it into other core concepts for preferences. These theoretical results are applied to compute the rational cores of a number of well-known preference models (such as Fishburn's SSB model, justifiable preferences, and variational and multiplier modes of rationalizable preferences). As for applications, we use the rational core operator to develop a theory of risk aversion for nontransitive nonexpected utility mod als (which may not even be complete). Finally, we show that, under a basic monotonicity hypothesis, the Preference Reversal Phenomenon cannot arise from the rational core of one's preferences.

One of the most well-known models of non-expected utility is Gul (1991)'s bmodel of Disappointment Aversion. This model, however, is defined implicitly, as the solution to a functional equation; its explicit utility representation is unknown, which may limit its applicability. We show that an explicit representation can be easily constructed, using solely the components of the implicit one. We also provide a more general result: an explicit representation for preferences in the Betweenness class that also satisfy Negative Certainty Independence (Dillenberger, 2010).

In this teaching note we discuss the relation between rational inattention and a major branch of information theory called rate distortion theory. Focusing on methods, we translate tools from rate distortion theory into the language of rational inattention. These tools provide an alternative, more primitive, approach to the study of optimal attention allocation.

We adopt the epistemic framework of Battigalli and Siniscalchi (J. Econ. Theory 88:188-230, 1999) to model the distinction between a player's behavior at each node, which is part of the external state, and his plan, which is described by his beliefs about his own behavior. This allows us to distinguish between intentional and unintentional behavior, and to explicitly model how players revise their beliefs about the intentions of others upon observing their actions. Rational players plan optimally and their behavior is consistent with their plans. We illustrate our approach with detailed examples and some results. We prove that optimal planning, belief in continuation consistency and common full belief in both imply the backward induction strategies and beliefs in games with perfect information and no relevant ties. More generally, we present within our framework relevant epistemic assumptions about backward and forward-induction reasoning, and relate them to similar ones studied in the previous literature.

We develop a general framework to study source-dependent preferences in economic contexts. We behaviorally identify two key features. First, we drop the assumption of uniform uncertainty attitudes and allow for source-dependent attitudes. Second, we introduce subjective prices to compare outcomes across different sources. Our model evaluates profiles source-wise, by computing the source-dependent certainty equivalents; the latter are converted into the unit of account of a common source and then aggregated into a unique evaluation. By viewing time and location as instances of sources, we show that subjective discount factors and subjective exchange rates are emblematic examples of subjective prices. Finally, we use the model to explore the implications on optimal portfolio allocations and home bias.

We evaluate linear stochastic discount factor models using an ex-post portfolio metric: the realized out-of-sample Sharpe ratio of mean-variance portfolios backed by alternative linear factor models. Using a sample of monthly US portfolio returns spanning the period 1968-2016, we find evidence that multifactor linear models have better empirical properties than the CAPM, not only when the cross-section of expected returns is evaluated in-sample, but also when they are used to inform one-month ahead portfolio selection. When we compare portfolios associated to multifactor models with mean-variance decisions implied by the single-factor CAPM, we document statistically significant differences in Sharpe ratios of up to 10 percent. Linear multifactor models that provide the best in-sample fit also yield the highest realized Sharpe ratios.

We propose a Markov Switching Graphical Seemingly Unrelated Regression (MS-GSUR) model to investigate time-varying systemic risk based on a range of multi-factor asset pricing models. Methodologically, we develop a Markov Chain Monte Carlo (MCMC) scheme in which latent states are identified on the basis of a novel weighted eigenvector centrality measure. An empirical application to the constituents of the S&P100 index shows that cross-firm connectivity significantly increased over the period 1999-2003 and during the financial crisis in 2008-2009. Finally, we provide evidence that firm-level centrality does not correlate with market values and it is instead positively linked to realized financial losses.

What are the effects of a housing bubble on the rest of the economy? We show that if firms and banks face collateral constraints, a housing bubble initially raises credit demand by housing firms while leaving credit supply unaffected. It therefore crowds out credit to non-housing firms. If time passes and the bubble lasts, however, housing firms eventually pay back their higher loans. This leads to an increase in banks' net worth and thus to an expansion in their supply of credit to all firms: crowding-out gives way to crowding-in. These predictions are confirmed by empirical evidence from the recent Spanish housing bubble. In the early years of the bubble, non-housing firms reduced their credit from banks that were more exposed to the bubble, and firms that were more exposed to these banks had lower credit and output growth. In its last years, these effects were reversed.