Abstract
Input-output models used for macroeconomic impact and policy analysis are often characterised by large data sets and resource-heavy computing. However, the types of results they provide are sensitive to uncertainty in their core assumptions. Various approaches have been proposed to account for the uncertainty in one or more parts of the analysis assumptions. Although it is standard practice to include varied cases in policy analysis, the notion of stochasticity of parameters across periods of time is less widespread. Costly numerical computing and difficulty in interpreting the results complicate this approach. In this work, we adapt an environmentally-extended dynamic econometric input-output model to account for uncertainty of various kinds. We demonstrate the methodology in the case of building renovation. The results provide insight into situations where explicitly considering uncertainty as part of the analysis is useful, as well as others in which no additional information was gained from such treatment.