Dynamic Vector Mode Regression

We study the semi-parametric estimation of the conditional mode of a random vector that has a continuous conditional joint density with a well-defined global mode. A novel full-system estimator is proposed and its asymptotic properties are studied allowing for possibly dependent data. We specifically consider the estimation of vector autoregressive conditional mode models and of structural systems of linear simultaneous equations definded by mode restrictions. The proposed estimator is easy to implement using standard software and the results of a small simulation study suggest that it is well behaved in finite samples.