Essays on informational frictions in macroeconomics and finance
Massachusetts Institute of Technology. Dept. of Economics.
George-Marios Angeletos and Mikhail Golosov.
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This dissertation consists of four chapters analyzing the effects of heterogeneous and asymmetric information in macroeconomic and financial settings, with an emphasis on short-run fluctuations. Within these chapters, I study the implications these informational frictions may have for the behavior of firms and financial institutions over the business cycle and during crises episodes. The first chapter examines how collateral constraints on firm-level investment introduce a powerful two-way feedback between the financial market and the real economy. On one hand, real economic activity forms the basis for asset dividends. On the other hand, asset prices affect collateral value, which in turn determines the ability of firms to invest. In this chapter I show how this two-way feedback can generate significant expectations-driven fluctuations in asset prices and macroeconomic outcomes when information is dispersed. In particular, I study the implications of this two-way feedback within a micro-founded business-cycle economy in which agents are imperfectly, and heterogeneously, informed about the underlying economic fundamentals. I then show how tighter collateral constraints mitigate the impact of productivity shocks on equilibrium output and asset prices, but amplify the impact of "noise", by which I mean common errors in expectations. Noise can thus be an important source of asset-price volatility and business-cycle fluctuations when collateral constraints are tight. The second chapter is based on joint work with George-Marios Angeletos. In this chapter we investigate a real-business-cycle economy that features dispersed information about underlying aggregate productivity shocks, taste shocks, and-potentially-shocks to monopoly power. We show how the dispersion of information can (i) contribute to significant inertia in the response of macroeconomic outcomes to such shocks; (ii) induce a negative short-run response of employment to productivity shocks; (iii) imply that productivity shocks explain only a small fraction of high-frequency fluctuations; (iv) contribute to significant noise in the business cycle; (v) formalize a certain type of demand shocks within an RBC economy; and (vi) generate cyclical variation in observed Solow residuals and labor wedges. Importantly, none of these properties requires significant uncertainty about the underlying fundamentals: they rest on the heterogeneity of information and the strength of trade linkages in the economy, not the level of uncertainty. Finally, none of these properties are symptoms of inefficiency: apart from undoing monopoly distortions or providing the agents with more information, no policy intervention can improve upon the equilibrium allocations. The third chapter is also based on joint work with George-Marios Angeletos. This chapter investigates how incomplete information affects the response of prices to nominal shocks. Our baseline model is a variant of the Calvo model in which firms observe the underlying nominal shocks with noise. In this model, the response of prices is pinned down by three parameters: the precision of available information about the nominal shock; the frequency of price adjustment; and the degree of strategic complementarity in pricing decisions. This result synthesizes the broader lessons of the pertinent literature. However, this synthesis provides only a partial view of the role of incomplete information: once one allows for more general information structures than those used in previous work, one cannot quantify the degree of price inertia without additional information about the dynamics of higher-order beliefs, or of the agents' forecasts of inflation. We highlight this with three extensions of our baseline model, all of which break the tight connection between the precision of information and higher-order beliefs featured in previous work. Finally, the fourth chapter studies how predatory trading affects the ability of banks and large trading institutions to raise capital in times of temporary financial distress in an environment in which traders are asymmetrically informed about each others' balance sheets. Predatory trading is a strategy in which a trader can profit by trading against another trader's position, driving an otherwise solvent but distressed trader into insolvency. The predator, however, must be sufficiently informed of the distressed trader's balance sheet in order to exploit this position. I find that when a distressed trader is more informed than other traders about his own balances, searching for extra capital from lenders can become a signal of financial need, thereby opening the door for predatory trading and possible insolvency. Thus, a trader who would otherwise seek to recapitalize is reluctant to search for extra capital in the presence of potential predators. Predatory trading may therefore make it exceedingly difficult for banks and financial institutions to raise credit in times of temporary financial distress.
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Economics, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 209-220).
DepartmentMassachusetts Institute of Technology. Department of Economics
Massachusetts Institute of Technology