Dynamic factor models have proven to be effective in nowcasting and short-term forecasting of key macroeconomic variables. We explore whether dynamic factor models can also be useful for policy and scenario analyses; for such tasks an accurate model description for the long-term features of the time series are required. In this research we propose some modifications of a dynamic factor analysis to improve the ability of the model to capture the long-term dynamics. We further show how a scenario analysis can be implemented in the context of a dynamic factor model. We present an illustration of measuring the impact on economic variables when climate change policies are implemented, such as a cap on CO2 emissions. This is joint work with Mikkel Bennedsen and Eric Hillebrand, both at CREATES, Aarhus University.
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