Dynamic Vector Mode Regression
提出一种半参数估计方法，用于估计随机向量的条件众数，适用于向量自回归和联立方程模型，并通过模拟和实证示例展示其有限样本表现和多步预测应用。
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 \nnovel full-system estimator is proposed and its asymptotic properties are studied. We \nspecifically consider the estimation of vector autoregressive conditional mode models and \nof systems of linear simultaneous equations defined by mode restrictions. The proposed \nestimator is easy to implement and simulations suggest that it is reasonably behaved in \nfinite samples. An empirical example illustrates the application of the proposed methods, including its use to obtain multi-step forecasts and to construct impulse response \nfunctions.