We examine the business model of traditional commercial banks when they compete with shadow banks. While both types of intermediaries create safe “money-like” claims, they go about this in different ways. Traditional banks create money-like claims by holding illiquid fixed-income assets to maturity, and they rely on deposit insurance and costly equity capital to support this strategy. This strategy allows bank depositors to remain “sleepy”: they do not have to pay attention to transient fluctuations in the market value of bank assets. In contrast, shadow banks create money-like claims by giving their investors an early exit option requiring the rapid liquidation of assets. Thus, traditional banks have a stable source of funding, while shadow banks are subject to runs and fire-sale losses. In equilibrium, traditional banks have a comparative advantage at holding fixed-income assets that have only modest fundamental risk but are illiquid and have substantial transitory price volatility, whereas shadow banks tend to hold relatively liquid assets.
We present a model of market competition in which consumers' attention is drawn to the products' most salient attributes. Firms compete for consumer attention via their choices of quality and price. Strategic positioning of a product affects how all other products are perceived. With this attention externality, depending on the cost of producing quality some markets exhibit “commoditized” price salient equilibria, while others exhibit “de-commoditized” quality salient equilibria. When the costs of quality change, innovation can lead to radical shifts in markets, as in the case of decommoditization of the coffee market by Starbucks. In the context of financial innovation, the model generates the phenomenon of “reaching for yield”.
We present a model of credit cycles arising from diagnostic expectations – a belief formation mechanism based on Kahneman and Tversky’s (1972) representativeness heuristic. In this formulation, when forming their beliefs agents overweight future outcomes that have become more likely in light of incoming data. The model reconciles extrapolation and neglect of risk in a unified framework. Diagnostic expectations are forward looking, and as such are immune to the Lucas critique and nest rational expectations as a special case. In our model of credit cycles, credit spreads are excessively volatile, over-react to news, and are subject to predictable reversals. These dynamics can account for several features of credit cycles and macroeconomic volatility
Using micro data from Duke University quarterly survey of Chief Financial Officers, we show that corporate investment plans as well as actual investment are well explained by CFOs’ expectations of earnings growth. The information in expectations data is not subsumed by traditional variables, such as Tobin’s Q or discount rates. We also show that errors in CFO expectations of earnings growth are predictable from past earnings and other data, pointing to extrapolative structure of expectations and suggesting that expectations may not be rational. This evidence, like earlier findings in finance, points to the usefulness of data on actual expectations for understanding economic behavior.
We present a new model of investors delegating portfolio management to professionals based on trust. Trust in the manager reduces an investor’s perception of the riskiness of a given investment, and allows managers to charge fees. Money managers compete for investor funds by setting fees, but because of trust, fees do not fall to costs. In equilibrium, fees are higher for assets with higher expected return, managers on average under perform the market net of fees, but investors nevertheless prefer to hire managers to investing on their own. When investors hold biased expectations, trust causes managers to pander to investor beliefs.