Within a costly state verification setting, we derive the optimal financial contract between an entrepreneur, a (potentially financing) supervisor and a pure investor when there is non-verifiable and non-contractible monitoring and limited liability. We show that diversion of cash flows to the...

Assuming that firms' suppliers are better able to extract value from the liquidation of assets in default and have an information advantage over other creditors, the paper derives six predictions on the use of trade credit. (1) Financially unconstrained firms (with unused bank credit lines) take...

This paper studies a contract between an optimistic agent and a realistic principal, both risk-neutral. Even with complete contracts and ex-ante symmetric information, it may be impossible to achieve the first-best unless the weight on emotions is sufficiently low.

We study an employment contract between an (endogenously) optimistic manager and realistic investors. The manager faces a trade-off between ensuring that effort reflects accurate news and savoring emotionally beneficial good news. Investors and manager agree on optimal recollection when the...

This paper uses a variant of the Lotka-Volterra system explaining the dynamic interaction between populations of infected and healthy individuals in which the demographic and epidemiological parameters (the net healthy birth rate, the death rate of the infected and the infection rate) are...

We consider the links between the health structure of the population and The productive system of an economy which is subject to infectious disease, in particular tuberculosis. Reviewing the models of tuberculosis suggests that a Lotka-Volterra system can capture the dynamics of epidemics. We...

We use a simple Lotka-Volterra model of the disease transmission process to analyse the dynamic population structure when a vaccine is available at a constant price through time which gives partial immunity to the disease. In contrast to earlier results for the full immunity case, we find that...