Finite Memory Distributed Systems

A distributed system model is studied, where individual agents play repeatedly against each other and change their strategies based upon previous play. It is shown how to model this environment in terms of continuous population densities of agent types. A complication arises because the population densities of different strategies depend upon each other not only through game payoffs, but also through the strategy distributions themselves. In spite of this, it is shown that when an agent imitates the strategy of his previous opponent at a sufficiently high rate, the system of equations which governs the dynamical evolution of agent populations can be reduced to one equation for the total population. In a sense, the dynamics 'collapse' to the dynamics of the entire system taken as a whole, which describes the behavior of all types of agents. We explore the implications of this model, and present both analytical and simulation results.Fixed strategy, Prisoner's dilemma, Fokker-Plank, Distributed system

Agency Costs and Investment Behaviour. ENEPRI Working Paper, No. 47, 3 February 2007

How do differences in the credit channel affect investment behavior in the U.S. and the Euro area? To analyze this question, we calibrate an agency cost model of business cycles. We focus on two key components of the lending channel, the default premium associated with bank loans and bankruptcy rates, to identify the differences in the U.S. and European financial sectors. Our results indicate that the differences in financial structures affect quantitatively the cyclical behavior in the two areas: the magnitude of the credit channel effects is amplified by the differences in the financial structures. We further demonstrate that the effects of minor differences in the credit market translate into large, persistent and asymmetric fluctuations in price of capital, bankruptcy rate and risk premium. The effects imply that the Euro Area's supply elasticities for capital are less elastic than the U.S

Risk Shocks and Housing Markets

This paper analyzes the role of uncertainty in a multi-sector housing model with financial frictions. We include time varying uncertainty (i.e. risk shocks) in the technology shocks that affect housing production. The analysis demonstrates that risk shocks to the housing production sector are a quantitatively important impulse mechanism for the business cycle. Also, we demonstrate that bankruptcy costs act as an endogenous markup factor in housing prices; as a consequence, the volatility of housing prices is greater than that of output, as observed in the data. The model can also account for the observed countercyclical behavior of risk premia on loans to the housing sector.Agency costs, credit channel, time-varying uncertainty, residential investment, housing production, calibration