Publications:
Journal of Finance, forthcoming.
Journal of Financial Economics, February 2016, Vol. 119 (2), pp. 249–283.
Working papers:
Risk Reallocation in OTC Derivatives Networks (paper available upon request)
Over-the-counter (OTC) derivatives markets are the key venue for quickly reallocating exposures to key risk factors such as interest rates, exchange rates, and credit amongst market participants. These markets are very large, and are characterized by a complex trading network with disperse prices. In this paper, we ask how the structure of the OTC derivatives trading network, the preferences and technologies of the participants, and the distribution of endowed exposures to the underlying risk factor, jointly determine the observed patterns of trade, post-trade exposures, and prices. Finally, we estimate the key parameters of our model, and we use the model to study comparative statics related to risk management and regulation.
We study how networks of informational flows are formed when agents acquire information through peers. We develop an endogenous network formation model, in which agents care not only about accuracy of their decision making but also about the actions other agents will take. We show that any strict equilibrium information structure is a hierarchical network. In addition, if the marginal cost of forming links is weakly increasing, the equilibrium network is core-periphery. Even if agents are ex-ante identical, the equilibrium information structure generates ex-post heterogeneity in payoffs and actions. In any equilibrium, agents are sorted into layers of influence.  Some individuals endogenously become opinion makers and have pervasive influence over the society, although they may not have superior information. Finally, we study how individual characteristics determine agents’ role in the network.

Firm volatilities co-move strongly over time, and their common factor is the dispersion of the economy-wide firm size distribution. In the cross section, smaller firms and firms with a more concentrated customer base display higher volatility. Network effects are essential to explaining the joint evolution of the empirical firm size and firm volatility distributions. We propose and estimate a simple network model of firm volatility in which shocks to customers influence their suppliers. Larger suppliers have more customers and the strength of a customer-supplier link depends on the size of the customer. The model produces distributions of firm volatility, size, and customer concentration that are consistent with the data.
We introduce a model of the economy as a social network. Two agents are linked to the extent that they transact with each other. This generates well-defined topological notions of location, neighborhood and closeness. We investigate the implications of our model for monetary economics. When a central bank increases the money supply, it must inject the money \emph{somewhere} in the economy. The agent closest to the location where money is injected is better off, and the one furthest is worse off. Symmetrically, any decrease in the money supply redistributes purchasing power in the other direction. This redistribution channel is independent from other previously studied channels. Our model’s theoretical predictions are supported by the data.
This paper investigates the implications of affirmative action in college admissions for welfare, aggregate output, educational investment decisions and intergenerational persistence of earnings. We construct an overlapping-generations model in which parents choose how much to invest in their child’s education, thereby increasing both human capital and likelihood of college admission. Motivated by a recent policy implemented in Brazil, we calibrate the model to quantify affirmative action long-run effects. We find that affirmative action targeting the bottom quintile of the income distribution is a powerful policy to reduce intergenerational persistence of earnings and improve welfare and aggregate output.
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