Forecasting when model stability is uncertain

宏观经济和金融变量的预测在政府和金融机构进行的前瞻性规划中起着至关重要的作用，但这些序列的可预测性往往与背景和时间有关，这使得标准的预测技术不可靠。该项目旨在开发新的建模和预测技术，以便能够在模型发生结构变化后不久适应这些变化。它的目的是推导相关的计量经济学理论，使用模拟来研究所提出的技术的特性，以及将这些新技术应用于观测数据。

Forecasts of macroeconomic and financial variables play a crucial role in forward planning undertaken by government and financial institutions, but the predictability of these series is often context and time specific, making standard forecasting techniques unreliable. This project aims to develop new modelling and forecasting techniques that can adapt to structural changes in the model soon after they occur. It aims to derive relevant econometric theory, use simulations to study the properties of the proposed techniques, as well as apply these new techniques to observed data.