Forecasting when model stability is uncertain

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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.