We focus on the effects that jumps and nonlinearities have on the inference in and calibration of economic models. Currently, standard continuous-time dynamical models are extended to include random jumps which represent shocks to the economy as a whole or to some assets in financial markets. Statistical tools to adjust these jump models to empirical data are currently under development. Typically, these approaches lead to statistical inverse problems, which are inherently nonlinear and ill-posed, and will raise difficult mathematical and practical problems.
DFG Programme
Collaborative Research Centres
