Informational Frictions and Learning in Emerging Markets

Abstract

Emerging market financial crises are abrupt and dramatic, usually occurring after a period of high output growth, massive capital flows, and a boom in asset markets. This thesis develops an equilibrium asset pricing model with informational frictions in which vulnerability and the crisis itself are consequences of the investor optimism in the period preceding the crisis. The model features two sets of investors, domestic and foreign. Both sets of investors are imperfectly informed about the true state of the emerging economy. Investors learn from noisy signals which contain information relevant for asset returns and formulate expectations, or "beliefs", about the state of productivity. Numerical analysis shows that, if preceded by a sequence of positive signals, a small, negative noise shock can trigger a sharp downward adjustment in investors' beliefs, asset prices, and consumption. The magnitude of this downward adjustment and sensitivity to negative signals increase with the level of optimism attained prior to the negative signal. The model calibrated to a typical emerging market economy, Turkey, reveals that with the introduction of incomplete information asset prices display persistent effects in response to transitory shocks, and the volatility of consumption increases by 2.1 percentage points. The maximum likelihood estimation of the model's parameters using U.S. data documents that the estimated signal-to-noise ratio for the U.S. is higher since, unlike Turkey, a significantly higher portion of fluctuations can be accounted for by changes in the persistent component rather than the noise. Feeding these two different signal-to-noise ratios to the model, we find that the booms and busts driven by misperceptions of the investors have significantly lower frequency, magnitude, and duration in the case of U.S. compared to Turkey.