In modern security markets information is sold and distributed to investors in a variety of ways. Brokerage (sell-side) analysts distribute reports and newsletters to a large number of clients, while buy-side employees and independent investment research firms offer investment advice to a small number of customers, often providing it only to the proprietary desk that commissions the research. Widely distributed investment advice seems to have little informational content, while the opposite is expected from more expensive personalized research.1 This heterogeneity raises a number of interesting questions: Why do such different allocations of information arise? What are the consequences for asset pricing properties such as informational efficiency and trading volume?
There is widespread concern among central banks about the influence of house prices on consumption, and much current debate on how monetary policy should react to asset price fluctuations in the context of liberalised credit markets (see Rajan (2005) and associated papers from the Jackson Hole symposium). Housing markets and their consumption interactions have, in recent years, become a very active research area. Nevertheless there is disagreement about the role of housing wealth in explaining consumption.
Unfortunately, much of the empirical literature, both macro and micro, is marred by poor controls for the common drivers both of house prices and consumption, including income, income growth expectations, interest rates, credit supply conditions, other assets and indicators of income uncertainty (such as the changes in the unemployment rate). For example, the easing of credit supply conditions is usually followed by a house price boom. Failure to control for the direct effect of such easing on consumption can result in over estimates of the effect of housing wealth or collateral on consumption. Our review of the literature in Section 2 illustrates these points; and in Sections 4 and 5, we provide specific evidence through comparisons of well-specified empirical models with those omitting relevant controls.
We present a model that simultaneously explains why uncovered interest parity holds for some pairs of countries and not for others. The flexible-price two-country monetary model is extended to include a consumption externality with habit persistence. Habit persistence is modeled using Campbell Cochrane preferences with ‘deep’ habits along the lines of the work of Ravn, Schmitt-Grohe and Uribe. By deep habits, we mean habits defined over goods rather than countries. The negative slope in the Fama regression arises when monetary instability is low and the precautionary savings motive dominates the intertemporal substitution motive. When monetary instability is high, the Fama slope is positive in line with uncovered interest parity. The model is simulated using the artificial economy methodology for 34 currencies against the US dollar. We conclude that, given the predominance of precautionary savings, the degree of monetary instability explains whether or not uncovered interest parity holds.
Eichenbaum (2008) investigates equally weighted carry trade portfolios for 20 portfolios over a thirty year period and finds consistent excess dollar returns. A ‘carry trade portfolio’ is a strategy of borrowing in the currency of the low interest currency and depositing the proceeds in the high interest currency, taking an open position to nominal exchange rate risk. He concludes that this vividly demonstrates the pervasiveness of the forward ‘bias’ puzzle. The contribution of this study is to specify and test a theory which provides for when the forward bias does and does not hold.
