Model uncertainty, state uncertainty, and state-space models
This technical paper considers ways to capture uncertainty in the context of so-called "state-space" models. ; State-space models are powerful tools commonly used in macroeconomics, international economics, and finance. State-space models can generate estimates of an underlying, ultimately unobserved variable—such as the natural rate of unemployment—based on the movements of other variables that are observed and have some relationship to the unobserved variable. The paper shows how several macroeconomic models can be mapped to the state-space framework, thus helping quantify uncertainty about the true model (model uncertainty) or about the amount of information available when decisions are made (state uncertainty).
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