Price-level targeting (PLT) is optimal under the fully-informed rational expectations (FIRE) benchmark but lacks empirical support. Given the hurdles to the implementation of macroeconomic field experiments, we utilize a laboratory group experiment – where expectations are elicited from human...

We introduce learning based on genetic algorithms in a principal-agent model of optimal contracting under moral hazard. Applications of this setting abound in finance (credit under moral hazard), public finance (optimal taxation, information-constrained insurance), development (sharecropping),...

We introduce learning in a principal-agent model of stochastic output sharing under moral hazard. Without knowing the agents' preferences and technology the principal tries to learn the optimal agency contract. We implement two learning paradigms - social (learning from others) and individual...

Price-level targeting (PLT) is optimal under the fully-informed rational expectations (FIRE) benchmark but lacks empirical support. Given the hurdles to the implementation of macroeconomic field experiments, we utilize a laboratory group experiment - where expectations are elicited from human...